EN中文

Journal of Geographical Sciences >

2019 , Vol. 29 >Issue 5: 730 - 748

DOI: https://doi.org/10.1007/s11442-019-1624-z

Quantifying the vertical distribution pattern of land-use conversion in the loess hilly region of northern Shaanxi Province 1995-2015

  • CAO Zhi , 1, 2 ,
  • LI Yurui , 1, 2, * ,
  • LIU Zhengjia 1, 2 ,
  • YANG Lingfan 3
Expand
  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. Center for Assessment and Research on Targeted Poverty Alleviation, CAS, Beijing 100101, China
  • 3. Faculty of Geographical Sciences, Beijing Normal University, Beijing 100875, China
*Corresponding author: Li Yurui, PhD and Associate Professor, specialized in rural geography and land engineering. E-mail:

Author: Cao Zhi, PhD, specialized in land science and rural development. E-mail:

Received date: 2018-07-20

  Accepted date: 2018-12-20

  Online published: 2019-04-19

Supported by

National Key Research and Development Program of China, No.2017YFC0504701

National Natural Science Foundation of China, No.41801175

Postdoctoral Science Foundation of China, No.2018M631558

Copyright

Journal of Geographical Sciences, All Rights Reserved
Fold

Abstract

The mountainous and hilly region plays an important role in ecological safety and production in China. However, recent studies have poorly characterized the parallel structure of land use in the valleys of the mountainous and hilly region using topographic factors (e.g. elevation, slope, aspect). Here, the loess hilly region of northern Shaanxi Province is used as a representative case area to analyze the vertical distribution pattern of land-use conversion using the relative elevation concept and the HAND index. The differences in the vertical structure of land-use conversion between absolute elevation and relative elevation were compared. We found that the classifications of absolute and relative elevation had similar proportions of each relative elevation grade in each absolute elevation grade. Cropland, woodland, and grassland were distributed evenly in each grade of absolute/relative elevation, while water body, built-up land and unused land were more likely to spread in low grades of relative elevation than those of absolute elevation. The land-use conversion (i.e. loss of cropland and gain in woodland and built-up land) showed an apparently stepped distribution with relative elevation classification, suitable for revealing vertical distributions of land-use conversion in the loess hilly region. Cropland transformed to woodland was mainly distributed in high grade of relative elevation, decreasing with a decrease in grades, while built-up land transformed from cropland and grassland was mainly distributed in low grade of relative elevation, decreasing with increases in grades. The grade of relative elevation where cropland transformed to woodland descended with the implementation of the Grain for Green Project. Our results suggest that it is better to analyze the vertical distribution of land-use conversion with relative elevation classification in hilly regions.

Key words： land use change; vertical distribution pattern; topographic factors; HAND (Height above the Nearest Drainage); loess hilly region; northern Shaanxi Province

Cite this article

CAO Zhi , LI Yurui , LIU Zhengjia , YANG Lingfan . Quantifying the vertical distribution pattern of land-use conversion in the loess hilly region of northern Shaanxi Province 1995-2015[J]. Journal of Geographical Sciences, 2019 , 29(5) : 730 -748 . DOI: 10.1007/s11442-019-1624-z

1 Introduction

Land use/land cover play important roles in understanding the interactions of human activity with the environment (Kumar et al., 2012; Liu et al., 2014; Liu, 2018). Furthermore, land use/land cover change (LUCC) is a popular topic in global ecological change, land-use allocation, and environment research (Liu et al., 2018a). Topics include spatial distribution and changes, causes and results, feedback mechanism with human activities, and optimal allocation of land use by policy makers (Liu and Li, 2017; Liu et al., 2017; Chang et al., 2018). In China, mountainous and hilly regions account for some 70% of national territorial area (Huang, 1986). These areas are also the production base for commercial crops, forest products, Chinese herbal medicines, green agricultural products, and grass and animal products. They also assume the responsibility for protecting gene, species, ecosystem, and landscape diversity, sheltering ecological safety, and the sustainable development of plain regions and cities across China. Therefore, research on LUCC in mountainous and hilly regions should be a priority.
Vertical zonality is a major feature of mountainous and hilly regions. Elevation, which affects precipitation, temperature, development space, and accessibility, has an important impact on the type, intensity, and density of human activities. Current infrastructure, economic activity, investments, and settlements are generally found in the low elevations of mountainous and hilly regions, while higher elevations are dominated by natural landscapes and are affected less by human activities. Classification of topographic factors is the method commonly adopted to indicate the vertical distribution and variation of land use. The topographic factors include elevation, slope, aspect and the Topographic Wetness Index (TWI), useful for revealing the vertical distribution of land use (Reis, 2008; Han and Jia, 2010; Park et al., 2011; Zhang et al., 2012; Li et al., 2016). However, we should note that in mountainous and hilly regions the development status and land use patterns in the upstream and downstream of gullies are usually similar in a given area and elevation range. The vertical distribution of land use in the upstream or downstream regions always presents some parallel structure relative to valleys, with grass and forest on the upper slope and settlements on the lower slope. Therefore, a relative elevation index, such as the Height above the Nearest Drainage (HAND) index, reflecting the height from valley, may be more useful if coupled with land use. The HAND index, reflecting the relative vertical flowpath distances to the nearest drainages, accurately expresses the concept of “relative elevation” (Renno et al., 2008; Nobre et al., 2011). This index is widely applied in hydrology, but has been rarely used in a coupled analysis with land use (de Lollo et al., 2019). Therefore, we employed this index to indicate relative elevation and as a means with which to analyze the vertical distribution of land use.
The loess hilly region of northern Shaanxi Province is a core area of the Loess Plateau in China, which is representative of mountainous and hilly regions. The arid and semi-arid continental monsoonal climate, thick and loose loess layer and unsustainable human activities have made this area the most seriously soil eroded region in China and possibly even globally, forming a fragmented landform of gullies and hummocks (Liu et al., 2015; Cao et al., 2018). To control soil erosion, a range of projects promoting different strategies and measures has been implemented since 1949, such as comprehensive management of small watersheds and the Grain for Green Project (GGP), with distinct effects on ecological restoration (Lü et al., 2012; Chen et al., 2015; Wang et al., 2015). The combination of representative topography, need for continued study of a fragile environment, and continued LUCC make the loess hilly region of northern Shaanxi an ideal study location for coupled analysis including relative elevation and LUCC. Recent studies have analyzed land-use conversion in the Loess Plateau using elevation and slope alone (Zhang et al., 2012; Li et al., 2016). On the whole, it is valuable to explore the vertical distribution pattern of land-use conversion in this area based on relative elevation.
The main objective of this study is to analyze the vertical distribution pattern of land-use conversion in the loess hilly region of northern Shaanxi based on relative elevation classification. The specific aims are to (1) compare vertical distribution patterns of absolute elevation and those of relative elevation, (2) compare vertical distribution patterns of land use with absolute elevation and those with relative elevation, (3) analyze land-use conversion without elevation, and (4) compare land-use conversion with absolute elevation and those with relative elevation to reveal the vertical distribution pattern of land-use conversion and verify the value of researching land-use conversion using relative elevation.

2 Methodology

2.1 Study area

The loess hilly region of northern Shaanxi Province covers the northern Shaanxi region, excluding the Mu Us Sandy Land (Li et al., 2017) but including all of Yan’an City and part of Yulin City. This region covers an area of some 66,000 km2 in the middle reaches of China’s Yellow River, accounting for 32.28% of Shaanxi’s land area. It is known as the core area of China’s Loess Plateau, south of the Mu Us Sandy Land and north of the Guanzhong Basin (Figure 1). The geomorphology of this area includes Loess Tableland, Loess Ridge, Loess Hill, and the transitional zones among them (Zhou et al., 2010). The area has an altitude between 374 m and 1913 m, and the terrain of the northwest and west is higher than that of the southeast and east. It belongs to the arid and semi-arid continental monsoonal climate in the temperate zone, with annual mean temperatures ranging from 7 to 12°C and annual precipitation ranging from 350 to 600 mm (Bai et al., 2014). Temperature and precipitation decrease from the southeast to the northwest, and the precipitation varies seasonally and annually, with 60%-70% of the annual total falling in the rainy season from June to September in the form of high-intensity rainstorms, with a relative variation of 20-30% (Lü et al., 2012; Li and Lü, 2015; Liu et al., 2019).
Figure 1 The digital elevation map of the loess hilly region in northern Shaanxi Province

2.2 Data source and processing

Land use datasets used in this study were China’s Land-Use/cover Datasets (CLUDs), provided by the Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC) (http://www.resdc.cn). The CLUDs were produced from interpreting Landsat TM images using the human-computer interactive interpretation method based on geographic knowledge (Liu et al., 2003; Liu et al., 2010; Ning et al., 2018). This study used the CLUDs’ raster data for the loess hilly region of northern Shaanxi in 1995, 2000, 2005, 2010, and 2015 with a spatial resolution of 30 × 30 m.
The terrain data were Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 2 products, obtained from the website of the USGS (United States Geological Survey) Earth Explorer (EE) (https://earthexplorer.usgs.gov/). The pixel size of the ASTER GDEM data is 1 arc-second (approximately 30 m at the equator). For consistency with the spatial resolution of land use datasets, the ASTER GDEM data were resampled using the Raster Processing toolset in ArcGIS 10.4. Based on the resampled DEM data, the valley lines and ridge lines were extracted using the Hydrology toolset and converted into raster using the To Raster toolset in ArcGIS 10.4 (Tang and Yang, 2015).

2.3 Research methods

This study adopted the HAND index to calculate the relative elevation of the loess hilly region using the DEM data. The HAND index reflects the relative vertical flowpath distances to the nearest drainages/valleys (Renno et al., 2008; Nobre et al., 2011). The flow path was calculated using the D-infinity flow model that defines flow direction as a vector along the direction of the steepest downward slope on eight triangular facets centered at each grid cell (Tarboton, 1997; Tesfa et al., 2011). Figure 2 shows the schematic of relative elevation calculation method. With this schematic, the relative elevation could be interpreted as the vertical flow distance from a point on the slope tracing down to a designated valley point defined by D-infinity flow model. The relative elevation of the study area was extracted using the AutoFuzSlpPos algorithm (https: // github. com/lreis2415/AutoFuzSlpPos), which was integrated with the HAND function (Qin et al., 2009; Zhu et al., 2018; Qin et al., 2018).
Figure 2 The schematic of relative elevation (RE) calculation method

3 Results and analysis

3.1 Patterns of absolute and relative elevation

In this study, the number of grids was calculated for different absolute elevations; the number of grids exhibited an approximate normal distribution with elevation (Figure 3a). The number of grids below 750 m changed slowly, increased rapidly above 750 m, and then increased slower above 1050 m than that between 750 m and 1050 m until the number of grids peaked at about 1120 m. The numbers of grids subsequently lowered, although discontinuously, with increases in absolute elevation, and showed minor peaks at 1350-1400 m and 1450-1550 m. Different from the results for absolute elevation, the number of grids dropped almost continuously with increases in relative elevation with a decline below about 25 m and increase at about 25-70 m (Figure 3b). Then, the number of grids presented a rapid decrease between 70-200 m and reached a lower level above 200 m.
Figure 3 Statistical characteristics of grid-based absolute elevation and relative elevation in the loess hilly region of northern Shaanxi Province
An important aspect of exploring the relationships between land use and elevation is dividing absolute/relative elevation into grades. To compare the results between absolute elevation and relative elevation classification, the absolute/relative elevation was divided into five grades shown on the map (Figure 4). In the figure, the Quantile Classification method in ArcGIS software was used to obtain groups with roughly an equal number/area. Areas with an absolute elevation classification presented higher in the west and lower in the east, and valleys showed nested distributions (Figure 4a). The difference between absolute elevation classification and relative elevation classification was that the latter presented higher valleys concentrated in the northwestern and eastern parts of Yan’an and lower valleys concentrated in most northern part of Yulin (Figure 4b). Different grades of relative elevation showed a parallel distribution, in much clearer detail than that revealed by absolute elevation.
Figure 4 Patterns of grid-based absolute elevation and relative elevation in the loess hilly region of northern Shaanxi Province
Table 1 provides the results of overlaying the classifications of absolute elevation and relative elevation. Each grade of absolute elevation had almost the same proportion of grades of relative elevation. In detail, the first grade of absolute elevation had a little more proportion of the first grade of relative elevation, while the fifth grade had a little more proportion of the fifth grade of relative elevation. In addition, the second and third grades of absolute elevation had a little more proportion of the second and third grades of relative elevation, while the fourth grade had a little more proportion of the fourth and fifth grades of relative elevation.
Table 1 Cross matrix between different classifications of absolute elevation (AE) and relative elevation (RE) in the loess hilly region of northern Shaanxi Province
Absolute
elevation (m)		 Relative elevation (m, %) Total
(AE)
0-23 23-55 55-84 84-120 120-554
374-1033 6.35 4.55 3.62 3.05 2.51 20.09
1033-1147 4.00 4.85 4.61 3.86 2.73 20.04
1147-1270 3.46 4.49 4.57 4.28 3.30 20.09
1270-1449 3.71 3.39 3.79 4.49 4.56 19.93
1449-1913 2.78 3.10 3.28 4.23 6.46 19.86
Total (RE) 20.30 20.37 19.87 19.90 19.56 100.00

3.2 Patterns of land use with absolute elevation and relative elevation

According to the published datasets, the dominant land use types were grassland, cropland and woodland, accounting for 43.26%, 34.07% and 15.23% of total area, respectively, in 2015. Grassland and cropland were scattered throughout the region, while woodland was concentrated in the south.
The land use structure for different classifications of absolute elevation and relative elevation for each land use type in 2015 were also evaluated (Figure 5a). First, similar proportions of cropland, woodland, and grassland were distributed in each grade of absolute/relative elevation. Cropland in the fourth (C4) and fifth (C5) grades of relative elevation was in greater proportion than that of absolute elevation, while cropland in C1 and C2 of relative elevation was a lesser proportion than that of absolute elevation. The characteristics of grassland were just the opposite. Woodland in C1, C2, and C5 was a greater proportion of relative elevation than that of absolute elevation, while woodland in C4 was clearly a lower proportion of relative elevation than that of absolute elevation. Second, the proportions of water body, built-up land, and unused land in C1 of relative elevation were significantly larger than those of absolute elevation. The proportions of built-up land and unused land in C3 of relative elevation were significantly less than those of absolute elevation. Built-up land was mainly distributed in C1, accounting for 68.83% of the absolute elevation classification and 84.72% of the relative elevation classification.
Figure 5 Structure of land use with absolute elevation and relative elevation in the loess hilly region of northern Shaanxi Province in 2015
Note: abbreviations are defined as the two letters indicating land use types and the last two letters indicating classification of absolute/relative elevation. CL, cropland; WL, woodland; GL, grassland; WB, water body; BL, built-up land; UL, unused land; AE, classification of absolute elevation; RE, classification of relative elevation. AE1, the first class of absolute elevation; RE1, the first class of relative elevation.
The land use structure for different classifications of absolute elevation and relative elevation in 2015 were also evaluated (Figure 5b). Cropland and grassland were the major land use types in five classes, accounting for more than 80% of absolute and relative elevations. The exceptions, where they were proportionally lower, were the fourth grade of absolute elevation (AE4, 70.29%) and fifth grade of relative elevation (RE5, 76.00%). The proportions of cropland in AE1 and AE2 were larger than those in RE1 and RE2, while the proportions in AE3, AE4, and AE5 were less than those in RE3, RE4, and RE5. In comparison, the characteristics of grassland were just the opposite. The proportions of woodland in AE3 and AE4 were larger than those in RE3 and RE4, which were also opposite in other grades of elevation.

3.3 Changes in land use without elevation

According to the transition matrices for 1995-2000, 2000-2005, 2005-2010, and 2010-2015, the dominant land use types fluctuated across the four periods (Tables 2-5). Cropland increased by 0.04% during 1995-2000, and decreased by 4.58%, 0.60%, and 0.29% during 2000-2005, 2005-2010, and 2010-2015, respectively. Woodland increased by 0.55%, 9.87%, and 1.37% in the first three periods, respectively, and decreased by 0.30% during 2010-2015. Grassland decreased by 0.37%, 0.04%, and 0.59% during 1995-2000, 2005-2010, and 2010-2015, respectively, and increased by 0.50% during 2000-2005. Finally, built-up land maintained an increasing trend, expanding by 5.29%, 13.49%, 2.38%, and 77.88% in the four periods, respectively.
Table 2 Transitions in percentages of total land use observed in the loess hilly region of northern Shaanxi Province during 1995-2000 (%)
Year 1995 2000 Total
(1995)		 Loss Net gain
in 2000		 Changes
in 2000
CL WL GL WB BL UL
CL 38.98 0.02 0.03 0.00 0.01 0.05 39.09 0.11 0.01 0.04
WL 0.02 15.44 0.01 0.00 0.00 0.00 15.48 0.03 0.09 0.55
GL 0.09 0.10 43.68 0.00 0.01 0.01 43.89 0.21 -0.16 -0.37
WB 0.01 0.00 0.00 0.66 0.00 0.00 0.68 0.02 -0.01 -1.80
BL 0.00 0.00 0.00 0.00 0.33 0.00 0.33 0.00 0.02 5.29
UL 0.00 0.00 0.00 0.00 0.00 0.53 0.53 0.01 0.06 10.46
Total (2000) 39.10 15.56 43.73 0.67 0.35 0.59 100.00 0.37
Gain 0.12 0.12 0.05 0.01 0.02 0.06 0.37

Note: The abbreviations “CL”, “WL”, “GL”, “WB”, “BL” and “UL” are defined in the note for Figure 5.

Table 3 Transitions in percentages of total land use observed in the loess hilly region of northern Shaanxi Province during 2000-2005 (%)
Year 2000 2005 Total
(2000)		 Loss Net gain
in 2005		 Changes
in 2005
CL WL GL WB BL UL
CL 37.23 1.06 0.77 0.00 0.04 0.00 39.10 1.87 -1.79 -4.58
WL 0.00 15.55 0.01 0.00 0.00 0.00 15.56 0.01 1.54 9.87
GL 0.06 0.49 43.15 0.00 0.01 0.02 43.73 0.58 0.22 0.50
WB 0.01 0.00 0.00 0.65 0.00 0.00 0.67 0.01 -0.01 -1.03
BL 0.00 0.00 0.00 0.00 0.35 0.00 0.35 0.00 0.05 13.49
UL 0.00 0.00 0.01 0.00 0.00 0.57 0.59 0.02 0.00 -0.15
Total (2005) 37.31 17.10 43.94 0.66 0.40 0.59 100.00 2.49
Gain 0.08 1.55 0.79 0.01 0.05 0.02 2.49

Note: The abbreviations “CL”, “WL”, “GL”, “WB”, “BL” and “UL” are defined in the note for Figure 5.

Table 4 Transitions in percentages of total land use observed in the loess hilly region of northern Shaanxi Province during 2005-2010 (%)
Year 2005 2010 Total
(2005)		 Loss Net gain
in 2010		 Changes
in 2010
CL WL GL WB BL UL
CL 37.08 0.17 0.05 0.00 0.01 0.00 37.31 0.23 -0.22 -0.60
WL 0.00 17.09 0.00 0.00 0.00 0.00 17.10 0.00 0.23 1.37
GL 0.00 0.07 43.87 0.00 0.00 0.00 43.94 0.07 -0.02 -0.04
WB 0.00 0.00 0.00 0.66 0.00 0.00 0.66 0.00 0.00 0.58
BL 0.00 0.00 0.00 0.00 0.40 0.00 0.40 0.00 0.01 2.38
UL 0.00 0.00 0.01 0.00 0.00 0.58 0.59 0.01 0.00 -0.75
Total (2010) 37.09 17.33 43.92 0.66 0.41 0.58 100.00 0.31
Gain 0.00 0.24 0.06 0.01 0.01 0.00 0.31

Note: The abbreviations “CL”, “WL”, “GL”, “WB”, “BL” and “UL” are defined in the note for Figure 5.

Table 5 Transitions in percentages of total land use observed in the loess hilly region of northern Shaanxi Province during 2010-2015 (%)
Year 2010 2015 Total
(2010)		 Loss Net gain
in 2015		 Changes
in 2015
CL WL GL WB BL UL
CL 36.93 0.00 0.00 0.01 0.11 0.03 37.09 0.15 -0.11 -0.29
WL 0.01 17.28 0.00 0.00 0.02 0.02 17.33 0.05 -0.05 -0.30
GL 0.03 0.00 43.66 0.01 0.17 0.06 43.92 0.27 -0.26 -0.59
WB 0.00 0.00 0.00 0.65 0.00 0.00 0.66 0.01 0.01 1.61
BL 0.00 0.00 0.00 0.00 0.41 0.00 0.41 0.00 0.32 77.88
UL 0.00 0.00 0.00 0.00 0.02 0.56 0.58 0.02 0.09 15.80
Total (2015) 36.98 17.28 43.66 0.67 0.73 0.68 100.00 0.51
Gain 0.04 0.00 0.01 0.02 0.32 0.11 0.51

Note: The abbreviations “CL”, “WL”, “GL”, “WB”, “BL” and “UL” are defined in the note for Figure 5.

Table 6 Transitions in percentages of total land use observed in the loess hilly region of northern Shaanxi Province during 1995-2015 (%)
Year 1995 2015 Total
(1995)		 Loss Net gain
in 2015		 Changes
in 2015
CL WL GL WB BL UL
CL 36.75 1.24 0.85 0.01 0.16 0.07 39.09 2.33 -2.11 -5.40
WL 0.03 15.39 0.02 0.00 0.02 0.02 15.48 0.09 1.80 11.65
GL 0.17 0.65 42.78 0.02 0.19 0.08 43.89 1.11 -0.22 -0.51
WB 0.02 0.00 0.01 0.64 0.01 0.00 0.68 0.04 0.00 -0.67
BL 0.00 0.00 0.00 0.00 0.33 0.00 0.33 0.00 0.39 117.62
UL 0.01 0.00 0.01 0.00 0.02 0.50 0.53 0.03 0.14 26.77
Total (2015) 36.98 17.28 43.66 0.67 0.73 0.68 100.00 3.61
Gain 0.22 1.89 0.88 0.04 0.39 0.17 3.61

Note: The abbreviations “CL”, “WL”, “GL”, “WB”, “BL” and “UL” are defined in the note for Figure 5.

From the perspective of land-use conversion, the loess hilly region was subject to significant changes from 2000 to 2005. Land-use conversion accounted for 2.49% of the total area. In this period, the main characteristics of land-use conversion were loss of cropland and gain of woodland. The net lost area of cropland accounted for 1.79% of the total area, mainly converting to woodland (42.59% of the total converted area) and grassland (30.98%). The net gain of woodland accounted for 1.54% of the total area, mainly converting from cropland (42.59%) and grassland (19.60%). Cropland transformed to woodland was primarily distributed in north Yan’an, and the converted grassland to grassland was mainly distributed in central Yan’an and northeast Yulin. Woodland converted from grassland was mainly distributed in northwest Yan’an (Figure 6b).
Figure 6 Patterns of land use change in the loess hilly region of northern Shaanxi Province during 1995-2000, 2000-2005, 2005-2010, 2010-2015, and 1995-2015
Note: The abbreviations “CL”, “WL”, “GL”, “BL” and “UL” are defined in the note for Figure 5.
Land use also clearly changed over the 2010-2015 period, with land-use conversion accounting for 0.51% of the total area. The main characteristics of land-use conversion were gains in built-up land and unused land and losses of grassland, mainly distributing in northeast Yulin and central Yan’an (Figure 6d). Built-up land increased 77.88%, and its net gain accounted for 0.32% of the total area, mainly converted from grassland (33.78%) and cropland (21.83%). Unused land increased 15.80%, mainly converting from grassland (11.14%) and cropland (6.57%). Finally, the net loss of grassland accounted for 0.26% of the total area, mainly converted to built-up land (33.78%) and cropland (21.83%).
However, land use change accounted for only 0.37% and 0.31% of the total area during 1995-2000 and 2005-2010. During 2005-2010, the changing trends of land use continued 2000-2005. Increases in woodland were scattered across the area, while increases in grassland were mainly distributed in northeast Yulin (Figure 6c). Land-use conversion during 1995-2000 was characterized by losses of grassland (0.16% of total area) and gains in woodland (0.09%). Simultaneously, cropland decreased (0.11%) and increased (0.12%) almost equally. Increases in cropland were scattered in east and south Yan’an and northeast Yulin, while increased grassland and woodland were mainly distributed in northeast and south Yulin (Figure 6a).
For the entire study period, land use change accounted for 3.61% of the total area. The main characteristics of land-use conversion were losses of cropland and gains in woodland and built-up land. First, the net loss area of cropland accounted for 2.11% of total area, mainly converting to woodland (34.39%) and grassland (23.50%). The patterns of cropland transformed to woodland and grassland were similar to that during 2000-2005. Second, the net gains in woodland accounted for 1.80% of the total area, mainly converted from cropland (34.39%) and grassland (18.02%). The patterns of woodland transformed from cropland and grassland were also similar to those during 2000-2005. Third, the built-up land increased 117.62% and its net gain accounted for 0.39% of the total area, mainly converted from grassland (5.32%). The pattern of built-up land transformed from grassland was similar to that during 2010-2015 (Figure 6e).

3.4 Changes in land use with elevation

Figure 7 shows land use change structure with absolute and relative elevation during 1995-2000, 2000-2005, 2005-2010, 2010-2015, and 1995-2015. For the entire study period, the proportions of each grade in the absolute/relative elevation classification were roughly equivalent. These were similar to those in the absolute elevation classification during 1995-2000 and 2000-2005 and to those in the relative elevation classification during 2000-2005 and 2005-2010. However, the proportions of C4 and C5 in the absolute/relative elevation classification were smaller in other periods. The proportions of C1 and C2 during 2005-2010 and that of C3 during 2010-2015 were larger in absolute elevation, while the proportion of C1 during 1995-2000 and that of C1 and C2 during 2010-2015 were larger in relative elevation.
Figure 7 Structure of land use change with absolute elevation and relative elevation in the loess hilly region of northern Shaanxi Province during 1995-2000, 2000-2005, 2005-2010, 2010-2015, and 1995-2015
Note: the abbreviations are based on the period and classification of absolute/relative elevation, e.g. 95-00AE for 1995-2000 and AE indicates classification with absolute elevation; RE indicates classification with relative elevation.
The main types of land-use conversion were also evaluated based on the classifications of absolute/relative elevation. The five top-ranked land-use conversion types for both classifications were selected, and their grades of absolute/relative elevation and percentages of total change area were extracted (Table 7). The top ranked land-use conversion types for the two classifications were generally similar across the five periods, as was the proportion of land use change. They were also consistent with the main land-use conversion types without elevation in Figure 6. However, the five top ranked land-use conversion types in the grades were different between the classifications for absolute and relative elevation, especially during 2000-2005, 2005-2010, and 2010-2015. To explore the difference, the structures of main land-use conversion types were plotted with the absolute and relative elevation classifications in these three periods (Figure 8).
Table 7 The five top ranked land-use conversion types in absolute and relative elevation in the loess hilly region of northern Shaanxi Province
Time Absolute elevation Relative elevation
Type Class % Type Class %
1995-2000 GL→WL
GL→CL
GL→WL
GL→CL
CL→UL		 C5
C1
C1
C2
C3		 9.02
7.13
6.31
6.06
5.88		 GL→WL
GL→WL
GL→CL
GL→CL
GL→WL		 C1
C2
C5
C2
C3		 7.26
6.12
5.37
5.17
4.92
2000-2005 CL→GL
CL→WL
CL→GL
CL→WL
CL→WL		 C3
C4
C2
C5
C1		 10.56
10.34
10.01
9.37
7.90		 CL→WL
CL→WL
CL→WL
CL→GL
CL→GL		 C5
C4
C3
C4
C3		 12.99
10.38
8.15
7.67
6.92
2005-2010 CL→WL
CL→WL
CL→WL
CL→WL
GL→WL		 C2
C1
C5
C3
C3		 14.79
14.05
11.02
9.94
7.77		 CL→WL
CL→WL
CL→WL
CL→WL
CL→WL		 C5
C4
C3
C2
C1		 13.25
13.05
11.63
9.60
7.37
2010-2015 GL→BL
CL→BL
CL→BL
GL→BL
GL→UL		 C3
C3
C1
C2
C1		 19.07
8.14
6.56
6.13
4.59		 GL→BL
GL→BL
CL→BL
GL→BL
CL→BL		 C1
C2
C1
C3
C2		 12.33
11.42
8.90
6.55
5.65
1995-2015 CL→GL
CL→WL
CL→WL
CL→GL
CL→WL		 C3
C4
C5
C2
C1		 7.97
7.66
7.43
7.28
6.72		 CL→WL
CL→WL
CL→WL
CL→GL
CL→WL		 C5
C4
C3
C4
C2		 10.13
8.29
6.64
5.65
5.35

Note: The abbreviations “CL”, “WL”, “GL”, “BL” and “UL” are defined in the note for Figure 5.

Figure 8 Vertical distribution of main land-use conversion types with two classifications of absolute elevation and relative elevation in the loess hilly region of northern Shaanxi Province during 2000-2005, 2005-2010 and 2010-2015
Note: The abbreviations “CL”, “WL”, “GL”, “BL” and “UL” are defined in the note for Figure 5 and abbreviations for “C1”, “C2”, “C3”,” “C4” and “C5” are defined in the note for Figure 7.
During 2000-2005, the five top ranked land-use conversion types were found in all grades of absolute elevation, but only occurred in C5, C4, and C3 of relative elevation (Table 7). Structurally, the primary land-use conversion in the absolute/relative elevation classification was cropland transformed to woodland and grassland, which were distributed in higher grades of relative elevation. The proportions of cropland transformed to woodland in C5 and C4 of relative elevation were 30.50% and 24.37%, higher than that of absolute elevation (22.00% and 24.27%), while those in C1 and C2 of relative elevation were 10.70% and 15.31%, lower than those of absolute elevation (18.56% and 17.64%). Similarly, the proportions of cropland transformed to grassland in C5 and C4 of relative elevation were 21.50% and 24.76%, higher than those of absolute elevation (4.07% and 15.52%), while those in C1 and C2 of relative elevation were 12.84% and 18.56%, lower than those of absolute elevation (14.00% and 32.32%) (Figure 8a). In addition, the area of cropland transformed to woodland decreased progressively as the grade of relative elevation decreased, similar to cropland transformed to grassland in C1-C4 of relative elevation.
The distribution of land-use conversion in grades of absolute/relative elevation was generally balanced or decreasing during 2005-2010. The proportion of cropland transformed to woodland and grassland decreased in high grades of absolute/relative elevation. The proportions of cropland transformed to woodland in C5 and C4 of absolute elevation decreased to 20.07% and 9.29%, and those of relative elevation decreased to 24.14% and 23.77%, while those in C1 and C2 of absolute elevation increased to 25.60% and 26.93% and those of relative elevation increased to 13.42% and 17.50%. Similarly, proportions of cropland transformed to grassland in C5 and C4 of absolute elevation decreased to 0.41% and 6.84%, and those of relative elevation decreased to 12.71% and 19.71%, while those in C1 and C2 of absolute elevation increased to 42.12% and 26.60%, and those of relative elevation increased to 18.84% and 22.85% (Figure 8b). However, land-use conversion occurred in higher grades of relative elevation than those of absolute elevation. This difference was due to the higher proportions of cropland transformed to woodland in C5 and C4 of relative elevation (24.14% and 23.77%) than those of absolute elevation (20.07% and 9.29%) and higher proportions of cropland transformed to grassland in C5 and C4 of relative elevation (12.71% and 19.71%) compared to absolute elevation (0.41% and 6.84%). In addition, the area of cropland transformed to woodland decreased progressively as the grade of relative elevation decreased.
During 2010-2015, the five top ranked land-use conversion types were found in once grade higher of absolute elevation than in relative elevation (Table 7). Structurally, the main land-use conversion in the absolute/relative elevation classification also indicated that the area of increased built-up land and unused land decreased progressively as the grade of relative elevation increased. The proportions of built-up land transformed from cropland decreased from 40.79% in C1 to 5.93% in C5, those of built-up land transformed from grassland decreased from 36.49% in C1 to 1.80% in C5, and those of unused land transformed from grassland decreased from 36.37% in C1 to 7.96% in C5 (Figure 8c). Structurally, increases in unused land from grassland in absolute elevation classification were similar to those in relative elevation. From the perspective of absolute elevation, the proportion of unused land transformed from grassland also decreased from 36.37% in C1 to 7.96% in C5, but excluded C4.

4 Discussion

4.1 Drivers of land use change

Using these results, this study then evaluated the characteristics of land use change in the loess hilly region of northern Shaanxi Province in the four study periods. During 1995-2010, increases in cropland were mainly scattered in eastern and southern Yan’an and northeastern Yulin; increases in grassland and woodland were mainly distributed in northeast and southern Yulin. During 2000-2005 and 2005-2010, decreases in cropland and increases in woodland were mainly distributed in central and northern Yan’an City and northeastern Yulin. During 2010-2015, increases in built-up land and decreases in grassland were mainly found in northeastern Yulin. Land use changes were in 2000-2005 and 2010-2015 and were consistent with the spatio-temporal features of ecological construction policy and urbanization, also affected by climate change, which we describe as follows.
Ecological construction policy. In 1978, the Three-North Shelterbelt System project was initiated. The Mu Us Sandy Land Shelterbelt System and Loess Plateau Shelterbelt System were two key sub-projects. Significant achievements were made in sand control in the Mu Us Sandy Land using innovations such as afforestation and water conservation with extensive social participation (Li et al., 2017). During 1995-2000, increases in woodland and grassland occurred mainly in Yulin. However, the loess hilly-gully region in the south of northern Shaanxi still showed sporadic expansion of cropland because of competition between woodland, cropland, and farmers’ livelihoods, which were not effectively guaranteed. In 1999, China began the Grain for Green Project (GGP), the largest and most effective ecological construction project implemented (Lü et al., 2012; Chen et al., 2015; Wang et al., 2015). Shaanxi Province, as a pilot location, took the lead in conducting this project. The loess hilly-gully region in northern Shaanxi was a key area for implementing the GGP (Cao et al., 2018). Driven by the GGP, reductions in cropland and increases in woodland were obvious across the whole area of northern Shaanxi in 2000-2005 and 2005-2010.
Urbanization. Northern Shaanxi Province is an important energy chemical base in China and located in the core of China’s national urban agglomeration of Hu-Bao-E-Yu. In the 12th Five-Year Plan (2011-2015), Yan’an and Yulin have formulated policies to expand the central city, strengthen the county town, expand the county scale, and actively guide the population transfer to the urban center. During 2010-2015, the urban population increased 503,400, and the urbanization rate increased 8.14%. According to major function oriented zoning, the key development-oriented zones mainly included six districts and counties in the northwest of Yulin City (Yuyang, Shenmu, Fugu, Hengshan, Jingbian, and Dingbian) and three districts and counties in the center of Yan’an City (Baota, Ganquan, and Ansai). In our study area, the increases in built-up land were mainly distributed in Fugu, Shenmu, and Baota during 2010-2015. To adapt to the urbanization process, Yan’an City also adopted a land creation project (Liu and Li, 2014), which results in the increase in unused land in Baota.
Climate change. Water resources are an important limiting factor for vegetation growth in the loess hilly region (Xin et al., 2008). Precipitation in most of the study area was more than 400 mm. By analyzing changes in NDVI during 2000-2013, Cao et al. (2018) found vegetation restoration was concentrated in areas where precipitation was greater than 400 mm. Moreover, the Loess Plateau presented a wetting trend after 2000 (Wang et al., 2012; Cao et al., 2018), partly inducing an increase in grassland and woodland. However, over the past three decades, the comprehensive effect of temperature, precipitation, and solar radiation has shown little impact on vegetation greening or browning trends (Liu et al., 2018b).

4.2 Comparing absolute and relative elevation

Elevation can affect the degree of land use difficulty, patterns, and utilization intensity by influencing climate, soil quality, and accessibility. Li et al. (2016) analyzed the relationship between land use change and absolute elevation in the Loess Plateau from 1986 to 2010. The authors found that land use change primarily occurred below 1600 m, and the reduction in cropland and unused land and increase in woodland primarily occurred at 800-1600 m. Similarly, this study found a reduction in cropland and increase in woodland mainly between 1000 m and 1400 m during 2005-2010 in northern Shaanxi.
From the national or regional scale, absolute elevation has a greater impact on land use. However, at the provincial or smaller scale, the role of absolute elevation gradually declines, especially in the loess hilly and gully regions of northern Shaanxi. There are similar patterns of land use in the upper and lower reaches of the gully. Most land use models are three-dimensional soil and water protection agricultural models according to the height of the terrain, and residential land is mainly distributed at lower elevations (Liu et al., 2006). Therefore, in our study area, regardless of location upstream or downstream, the determinant of land use is relative elevation. Classifications of absolute elevation presented continuous nested partition features, and that of relative elevation presented parallel distribution features along the valley (Figure 3). Classifications based on relative elevation could improve the accuracy of elevation grading compared to absolute elevation. Coupled analysis of relative elevation and land use showed that the reduction in cropland and increase in woodland and grassland driven by the GGP was primarily found between relative elevations of 20-130 m.
Concurrently, we note that relative elevation had a greater impact on land use distribution and change only at the small to medium scale and with relatively rugged topographic relief. Future studies should analyze coupled effects on a larger scale and explore the grading points of absolute elevation and relative elevation. The slope and position of the terrain are also important factors affecting land use. However, due to the limitation of geomorphological feature extraction and analysis methods at large scale, this study only analyzed land use change based on classification of relative elevation. Perfecting the geomorphological characteristics analysis and extraction will be a priority in future research. In addition, although hills and gullies are widely distributed, there are different landform types in northern Shaanxi. For example, the wind-sand grass shoal area with relatively rugged topographic relief is distributed in the northwest. A comparative analysis of different landform types in the future work should reveal land use distribution and change features in different landform types. Finally, the spatial resolution of the land use datasets may affect the accuracy of coupled analysis of land use change and relative elevation, even though the CLUDs are the most complete sequence, with the highest precision and best quality available.

5 Conclusions

To explore the vertical distributions of land-use conversion in the loess hilly region of northern Shaanxi Province, this study classified absolute/relative elevation using the HAND index and analyzed land use change characteristics based on these classifications. The main findings are as follows.
First, the spatial pattern of absolute elevation showed that valleys had a nested distribution, while the spatial patterns of relative elevation showed valleys with a densely parallel distribution. Higher absolute elevation was concentrated in the west, but higher relative elevation was distributed in northwestern and eastern parts of Yan’an. The classifications of absolute and relative elevation showed a distribution with a similar proportion of each relative elevation grade in each absolute elevation grade.
Second, of the six land use types, cropland, woodland, and grassland were distributed evenly in each grade of absolute/relative elevation, while water body, built-up land, and unused land were more likely to spread to a lower grade of relative elevation than that of absolute elevation. The built-up land distributed in C1 accounted for 68.83% of the absolute elevation classification and 84.72% of the relative classification.
Third, over the entire 1995-2015 study period, 3.61% of the loess hilly region of northern Shaanxi showed land-use conversion, with the most significant phenomenon occurring over 2000-2005 (2.49% of the total area) compared to the other four five-year periods. The main characteristics of land-use conversion were losses of cropland (2.11% of total area) and gains in woodland (1.80% of total area) and built-up land (0.39% of total area and 117.62% increase).
Finally, land-use conversion showed an apparently stepped distribution with relative elevation classification, suitable for revealing vertical distributions of land-use conversion in the loess hilly region. The area of cropland transformed to woodland increased progressively from 10.07% in C1 of relative elevation to 30.50% in C5 during 2000-2005. In comparison, the proportional area of built-up land transformed from cropland decreased progressively from 40.79% in C1 to 5.93% in C5 during 2010-2015. Cropland transformed to woodland was mainly distributed at high grades of relative elevation, decreasing with decreases in grades. In comparison, built-up land transformed from cropland and grassland was mainly distributed in the low grade relative elevation, decreasing with increases in grades. Cropland transformed to woodland was found at lower grades of relative elevation with the implementation of the GGP. Therefore, it is better to analyze the vertical distribution of land-use conversion using relative elevation classification in hilly regions.

The authors have declared that no competing interests exist.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
Bai Jianjun, Bai Jiangtao, Wang Lei, 2014. Spatio-temporal change of vegetation NDVI and its relations with regional climate in northern Shaanxi Province in 2000-2010.Scientia Geographica Sinica, 34(7): 882-888. (in Chinese)

[2]
Cao Zhi, Li Yurui, Liu Yansui et al., 2018. When and where did the Loess Plateau turn “green”? Analysis of the tendency and breakpoints of the normalized difference vegetation index.Land Degradation & Development, 29: 162-175.Abstract The Loess Plateau experiences the most serious soil erosion problems in China and possibly even globally. Many measures have been taken to increase the vegetation cover and to control soil erosion. Of these measures, the Grain for Green Project, launched in 1999, has been the most effective, changing the ecological and socio-economic situation of the Plateau significantly. Using time series normalized difference vegetation index (NDVI) data from 1981 to 2013, this study analysed spatial patterns of changes in vegetation cover, detected spatial patterns of the abrupt-change time of NDVI trends, and investigated factors that may contribute to these changes. The results showed that (a) vegetation restoration was obvious over the last decades, especially in the 2000s, and the increase in NDVI during 2000–2013 was more than 3-times that during 1990–2000. Approximately 54.99% of the Plateau during 2000–2013 had a statistically significant increase, mainly distributing in loess hilly and gully region and loess gully region. (b) Vegetation restoration was comprehensively affected by climate change and human activities (e.g., the Grain for Green Project, urbanization and policies), and the effects of each factor varied for different regions. (c) Vegetation in most of the Plateau began to increase around 2007–2010, and 4 discrete areas with different timings of such break points were detected. The difference in the timing of break points in NDVI may be related with precipitation, reproducing tree species, management measures, and survival rate. These results imply that integrating natural and human factors is important when making effective and suitable measures and policies.

DOI

[3]
Chang Yue, Hou Kang, Li Xuxiang et al., 2018. Review of land use and land cover change research progress.IOP Conference Series: Earth and Environmental Science, 113: 012087.Land Use and Land Cover Change (LUCC) can reflect the pattern of human land use in a region, and plays an important role in space soil and water conservation. The study on the change of land use patterns in the world is of great significance to cope with global climate change and sustainable development. This paper reviews the main research progress of LUCC at home and abroad, and suggests that land use change has been shifted from land use planning and management to land use change impact and driving factors. The development of remote sensing technology provides the basis and data for LUCC with dynamic monitoring and quantitative analysis. However, there is no uniform standard for land use classification at present, which brings a lot of inconvenience to the collection and analysis of land cover data. Globeland30 is an important milestone contribution to the study of international LUCC system. More attention should be paid to the accuracy and results contrasting test of land use classification obtained by remote sensing technology.

DOI

[4]
Chen Guojie, 2007. Some considerations on strategy of development of mountain regions of China.Bulletin of Chinese Academy of Sciences, 22(2): 126-131. (in Chinese)Mountain regions play an important strategic role in China's social and economic development,but the development is behind the other regions so serious that it becomes the core of the unbalance of the regional development.Currently,the development of mountain regions faces many challenges,such as the unfitness of mountain regions development for ecological protection,and the unfitness of rural settlements for the modernization process,the dilemma between high cost and low benefit in construction,and the traditional inertia of self-sufficiency for rural households.For mountain development of China,it needs to draw an integrated strategic plan and a detailed ecological functional regionalization,and the special industrialization way for mountain regions should be searched,and then reconstruct the rural settlement.

[5]
Chen Yiping, Wang Kaibo, Lin Yishanet al., 2015. Balancing green and grain trade.Nature Geoscience, 8: 739-741.Since 1999, China's Grain for Green project has greatly increased the vegetation cover on the Loess Plateau. Now that erosion levels have returned to historic values, vegetation should be maintained but not expanded further as planned.

DOI

[6]
de Lollo J A, Marteli A N, Lorandi R, 2019. Flooding susceptibility identification using the HAND algorithm tool supported by land use/land cover data. In: IAEG/AEG Annual Meeting Proceedings, San Francisco, California, 2018, 2: 107-112.

[7]
Han Jianping, Jia Ningfeng, 2010. Relationship between topographic factor and land use: A case study of Zhuanyaogou watershed.Chinese Journal of Eco-Agriculture, 18(5): 1071-1075. (in Chinese)GIS and SPSS were used to quantitatively analyze the relationships between land use type and topographic factors for 2003 and 2008.The succession pattern and driving factors of land use were also explored on 10 m 10 m grid-base for Zhuanyaogou watershed in the hilly region of the Loess Plateau of China.The study shows that land elevation,slope gradient and aspect significantly influence the spatial distribution of land use.The average elevation,slope gradient and aspect of the watershed are respectively 1 069 m,19.24 and 279 (west).Aspect-distribution map from average sin(aspect) and cos(aspect) of different land use types clearly shows the distribution characteristics of land use.Farmlands and barren-hills form about 80% of the study area,and their distribution change controls the topographic pattern of land use distribution in the watershed.Farmlands are mainly located in the upper slope and tops of the loess mountain ridges with low slope gradients and high elevations.While farmland area is significantly negative correlated with slope gradient,it is significantly positive correlated with elevation.Barren hills exhibit the opposite trend.The results fully reflect the topographic characteristics of land use in the study area.Implementation of eco-construction projects could induce significant changes in the spatial distribution of land use in the short-run.

DOI

[8]
Huang Shoubo, 1986. Advance in the investigation of the topographical microclimate in China (sum up).Geographical Research, 5(2): 90-101. (in Chinese)Mountainous and hilly regions cover a vast area of China. The mountainous topography is complex and various. Much differences in their landforms, altitudes, direction and slope resulted in much differences in the topographic microclimate, which would control the distribution of vegetations and soils, and thus it is not suitable to grow temperature demanded crops (such as citrus and, tea plants) in the unfavourable microclimatic conditions at the north and the middle sub-tropical areas in China, This paper summarizes the investigation on the survey of the topographic microclimate in China since mid-1950's. The primary content is as follows.(1) The influence of slope orientation (direction and slope) on the microclimate. The main character of the microclimate in the mountainous and hilly region in the changes of sunshine, radiant flux, temperature, precipitation and other meteorological elements with the slope orientation,(2) The influence of undulating country (top of a mountain, mountain slope, mountain valley) on the microclimate,(3) The influence of surrounding topography in a small scale region on the microclimate. Four types of the surrounding topography are studied according to their influences on minimum temperature and wind speed for both ra-diational and advectional weathers,( 4 ) The influence of composition among hills on the microclimate,(5) A study of the topography inversion. Some regularities of the vertical distributions of the meteorological elements in the major mountainous and hilly region in China were found out,(6) The influence of special topography (such as a horseshoe shape topography) on the microclimate.As a result, we must select different species of crops and plants to suit the various microclimate conditions respectively, and to develop the diversified agriculture and forest in the mountainous and hilly regions in China,

DOI

[9]
Kumar R S, Chinnaiah K, Kumar B V S, 2012. Detection studies of land use/land cover changes in Sandur Taluk, Bellary district, Karnataka, India, using remote sensing and GIS techniques.International Journal of Earth Sciences & Engineering, 5(1): 133-138.

[10]
Li Jingjing, Li Zhi, Lü Zhemin, 2016. Analysis of spatiotemporal variations in land use on the Loess Plateau of China during 1986-2010.Environmental Earth Sciences, 75(11): 997.

DOI

[11]
Li Wangjun, Lü Changhe, 2015. Aridity trend and response to vegetation restoration in the loess hilly region of northern Shaanxi Province.Journal of Geographical Sciences, 25(3): 289-300.Detecting variation trend in dry-wet conditions can provide information for developing strategic measures to mitigate the impacts of global warming, particularly in dry regions. Taking the hilly region of northern Shaanxi on the Loess Plateau as a case area, this study analyzed the trend of aridity variation during 1981-2012, and explored the effect of vegetation restoration promoted by the Grain-for-Green (GFG) program implemented in 1999. The results indicated that the aridity in the region was non-significantly increased by 0.88% per year during 1981-2012, showing a drying trend. This drying trend and amplitude were changed by the influence of vegetation restoration promoted by the GFG program, based on two findings. The first one was that the aridity variation tended to increase during 1981-1999 while it turned to decrease during 2000-2012, with the regional mean relative change rate changed from 2.45% to -1.06%. This distinction was more remarkable in the loess gully region, where the vegetation was improved more obviously. The second one was that the mean vegetation coverage as indicated by EVI increased by 0.90% to 4.32% per year at county level, while the aridity decreased by 0.14% to 2.32% per year during 2000-2012. The regression analysis using the mean county data indicated that the change rate of aridity was negatively related to that of EVI with the coefficient of determination (R2) of 0.56, illustrating that around half of the aridity decline was explained by the EVI change. The mechanism of this effect was complicated, but it was found that the wind speed decline induced by the vegetation improvement could be an important contributor. It is concluded that the region became drier during 1981-2012, but the eco-restoration reduced the drying speed. However, this conclusion is involved in uncertainties, and further study based on experiments is needed to confirm the effect of the GFG-promoted vegetation restoration.

DOI

[12]
Li Xiubin, 2002. Explanation of land use changes.Progress in Geography, 21(3): 195-203. (in Chinese)The most fundamental obstacle to progress in the understanding and prediction of human impacts on environmental changes lies in the lack of a comprehensive and integrative theory of human land relationships. The recent growth of research into land use and land cover change has revealed the inadequacy of current theories. On the other hand, specific land use issues have been effectively addressed by different disciplines, such as economic geography, regional and urban economics, and law. This paper reviews the land use theories and system models that indirectly or exclusively touch the dynamics of land use in time and space. A comprehensive framework for the explanation of land use changes is proposed. The author argues that a multi disciplinary approach into land use change studies, as an alternative to a new integrative theory of human land relationships, help the establishment of a holistic understanding of the process. Analyses of land user's economic behavior and land manager's institutional behavior constitute the major components of the framework. Thunen and Alonso's bid rent curve approach provides a foundation for the former analysis, while Platt's interaction loop among land use system, environment system and institution system provides theoretical base for the latter. With the bid rent curve approach, understanding of land use change lies in an analysis of conditions for change of transference margins in the micro perspective and an analysis of conditions for change of the slope of bid rent curve in the macro perspective. All these changes will break the spatial equilibrium of land use and then constitute the driving forces of land use change. With Platt's interaction loop approach, attention should be paid to strength of the signals from both the nature side and the society side. The author claims that changes on land use policies in China after the 'who will feed China' debate in the mid 1990s, the large flooding on the lower reaches of the Yangtze River and the strong dust storms in North China in early 2000, reflect the impact of strong signals. The paper also discusses the intrinsic properties of land that make unique of the dynamic mechanism of land use. Of these properties, multiple suitability, constraint in area and quality, and immovability are imperative to land use changes. Trend in land use specialization and the implicative shrinking of land's natural functions is a cue for the understanding of land use changes, and that of the overall human environment relationships as well.

DOI

[13]
Li Yurui, Cao Zhi, Long Hualou et al., 2017. Dynamic analysis of ecological environment combined with land cover and NDVI changes and implications for sustainable urban-rural development: The case of Mu Us Sandy Land, China.Journal of Cleaner Production, 142: 697-715.61Investigate dynamics of ecological environment combined with land cover and NDVI.61NDVI values in Mu Us showed an evident increase of 0.0076 year611during 2000–2014.61Ecological restoration projects laid vital foundation for ecological reconstruction.61Precipitation has been major climatic factors in NDVI growth (R02=020.687, P02≤020.01).61Ecological performance index has been built for ecological restoration classification.

DOI

[14]
Liu Jiyuan, Liu Mingliang, Zhuang Dafang et al., 2003. Study on spatial pattern of land-use change in China during 1995-2000.Science in China (Series D), 46(4): 373-384.It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spa-tial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The im-plementation of returning arable land into woodland or grassland policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, in-cluding studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.

DOI

[15]
Liu Jiyuan, Zhang Zengxiang, Xu Xinliang et al., 2010. Spatial patterns and driving forces of land use change in China during the early 21st century. Journal of Geographical Sciences, 20(4): 483-494.Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km * 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the "Grain for Green" policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of "Western Development", "Revitalization of Northeast", coupled with rapidly economic development during this period.

DOI

[16]
Liu Yansui, 2018. Introduction to land use and rural sustainability in China.Land Use Policy, 74(5): 1-4.Urban-rural transformation and rural development are issues at the forefront of research on the topic of the urban-rural relationship in the field of geography, as well as important practical problems facing China’s new urbanization and overall planning of urban and rural development. The Center for Regional Agricultural and Rural Development, part of the Institute of Geographic Sciences and... [Show full abstract]

DOI

[17]
Liu Yansui, Fang Fang, Li Yuheng, 2014. Key issues of land use in China and implications for policy making.Land Use Policy, 40(4): 6-12.The paper aims to comprehensively analyze key issues of current land use in China. It identifies the major land-use problems when China is undergoing rapid urbanization. Then, the paper interprets and assesses the related land-use policies: requisition-compensation balance of arable land, increasing vs. decreasing balance of urban-rural built land, reserved land system within land requisition, rural land consolidation and economical and intensive land use. The paper finds that current policies are targeting specific problems while being implemented in parallel. There is lacking a framework that incorporates all the policies. The paper finally indicates the current land-use challenges and proposes strategic land-use policy system to guide sustainable land use in the future.

DOI

[18]
Liu Yansui, Guo Yanjun, Li Yuruiet al., 2015. GIS-based effect assessment of soil erosion before and after gully land consolidation: A case study of Wangjiagou project region, Loess Plateau.Chinese Geographical Science, 25: 137-146.The Loess Plateau is one typical area of serious soil erosion in the world. China has implemented ′Grain for Green′(GFG) project to restore the eco-environment of the Loess Plateau since 1999. With the GFG project subsidy approaching the end, it is concerned that farmers of fewer subsidies may reclaim land again. Thus, ′Gully Land Consolidation Project′(GLCP) was initiated in 2010. The core of the GLCP was to create more land suitable for farming in gullies so as to reduce land reclamation on the slopes which are ecological vulnerable areas. This paper aims to assess the effect of the GLCP on soil erosion problems by studying Wangjiagou project region located in the central part of Anzi valley in the middle of the Loess Plateau, mainly using the revised universal soil loss equation(RUSLE) based on GIS. The findings show that the GLCP can help to reduce soil shipment by 9.87% and it creates more terraces and river-nearby land suitable for farming which account for 27.41% of the whole study area. Thus, it is feasible to implement the GLCP in places below gradient 15°, though the GLCP also intensifies soil erosion in certain places such as field ridge, village land, floodplain, natural grassland, and shrub land. In short, the GLCP develops new generation dam land and balances the short-term and long-term interests to ease the conflicts between economic development and environmental protection. Furthermore, the GLCP and the GFG could also be combined preferably. On the one hand, the GFG improves the ecological environment, which could offer certain safety to the GLCP, on the other hand, the GLCP creates more farmland favorable for farming in gullies instead of land reclamation on the slopes, which could indirectly protect the GFG project.

DOI

[19]
Liu Yansui, Jin Xiaoyan, Hu Yecui, 2006. Study on the pattern of rural distinctive eco-economy based on land resources: A case study of Suide county in Loess Hilly Areas.Journal of Natural Resources, 21(5): 738-745. (in Chinese)Based on the theory of regional human-land system in hilly gully areas of the Loess Plateau,this paper analyzed the characteristic of agricultural resources and current status of social and economic development of Suide county in northern Shaanxi province,a typical case in Loess Plateau,and elucidated the interactive nature between explorations in ecological resources to aim at eco-environmental construction and the rural economic development.Results indicated that the factors restricting agricultural sustainable development in this study area are as follows:vulnerable ecological environment,serious soil and water erosion,shortage of water resources,poor economic condition,etc.Then based on the analysis of realistic social and environmental conditions,this paper discussed the effective ways to utilize ecological resources and develop eco-economy of Suide county in hilly gully areas of the Loess Plateau.Driven by the western great development strategies during 2000-2004,the forest and orchard land in the study area increased by 7 178.5ha and 7 097.7ha,respectively.Furthermore,according to the characteristics of topography and rules of water and soil erosion,the typical optimal utilization technologies of land resources such as dry farming and saving irrigation technology,demonstration and popularization of tree planting practical technology,ecoagriculture for water protection technology,had been put forward.Finally,in order to guide the development of rural economy for building socialist new countryside in new stages,this paper also put forward three typical rural ecological economic patterns including Caragana korshinskii(Ningtiao) shelter industrialization model,three-dimensional soil and water protection agricultural model,and ecological resources development model in small watershed scale.

DOI

[20]
Liu Yansui, Li Yuheng, 2014. China’s land creation project stands firm. Nature, 511: 410.

[21]
Liu Yansui, Li Yuheng, 2017. Revitalize the world's countryside.Nature, 548(7667): 275-277.

DOI

[22]
Liu Yansui, Yang Yuanyuan, Li Yurui et al., 2017. Conversion from rural settlements and arable land under rapid urbanization in Beijing during 1985-2010.Journal of Rural Studies, 51: 141-150.61Spatiotemporal characteristics of rural settlements loss and arable land depletion during urbanization was explored.61Different degrees of rural non-agriculturalization were zoned.61Spatial modes of rural non-agriculturalization along the urban-rural gradient and the motorways were proposed.

DOI

[23]
Liu Yansui, Zhang Ziwen, Zhou Yang, 2018a. Efficiency of construction land allocation in China: An econometric analysis of panel data.Land Use Policy, 74: 261-272.The optimal allocation of land resources is an important prerequisite for sustainable land use and for synergic development of regional resources-environment-economy. The question on how to optimize and allocate the regional land resources has become a hotspot in land use and land cover change studies. However, the allocative efficiency of China’s construction land is currently a rather rudimentary and subjective issue. This study used an extended Cobb-Douglas production function to measure the allocative efficiency of construction land at the national and regional levels using balanced provincial panel data from the 1985–2014 period. The results showed that China’s construction land has exhibited a significant increasing trend over the past three decades, and its growth rate in the central region was relatively higher than that in the eastern and western regions. There is little or no available arable land that can be occupied by construction uses in China’s economically developed provinces. Further investigations demonstrated that capital, labor and land investment all contributed to the non-agricultural GDP growth in China. The allocative efficiency of construction land in the eastern region was greater than that in the central and western regions. The efficiency of construction land allocation in China needs to be further improved, and the intensive utilization of land resource is necessary, particularly in the context of China’s “new normal” economy. Because of the regional disparities in the efficiency of construction land allocation, formulating specific region-oriented land use planning may be more urgent. These findings can provide policymakers with a sound basis for land use and urban planning.

DOI

[24]
Liu Zhengjia, Liu Yansui, Li Yurui, 2018b. Anthropogenic contributions dominate trends of vegetation cover change over the farming-pastoral ecotone of northern China.Ecological Indicators, 95: 370-378.

DOI

[25]
Liu Zhengjia, Liu Yansui, Li Yurui, 2019. Extended warm temperate zone and opportunities for cropping system change in the Loess Plateau of China. International Journal of Climatology, 39: 658-669.

DOI

[26]
Lü Yihe, Fu Bojie, Feng Xiaoming et al., 2012. A policy-driven large scale ecological restoration: Quantifying ecosystem services changes in the Loess Plateau of China.PLoS One, 7: e31782.As one of the key tools for regulating human-ecosystem relations, environmental conservation policies can promote ecological rehabilitation across a variety of spatiotemporal scales. However, quantifying the ecological effects of such policies at the regional level is difficult. A case study was conducted at the regional level in the ecologically vulnerable region of the Loess Plateau, China, through the use of several methods including the Universal Soil Loss Equation (USLE), hydrological modeling and multivariate analysis. An assessment of the changes over the period of 2000-2008 in four key ecosystem services was undertaken to determine the effects of the Chinese government's ecological rehabilitation initiatives implemented in 1999. These ecosystem services included water regulation, soil conservation, carbon sequestration and grain production. Significant conversions of farmland to woodland and grassland were found to have resulted in enhanced soil conservation and carbon sequestration, but decreased regional water yield under a warming and drying climate trend. The total grain production increased in spite of a significant decline in farmland acreage. These trends have been attributed to the strong socioeconomic incentives embedded in the ecological rehabilitation policy. Although some positive policy results have been achieved over the last decade, large uncertainty remains regarding long-term policy effects on the sustainability of ecological rehabilitation performance and ecosystem service enhancement. To reduce such uncertainty, this study calls for an adaptive management approach to regional ecological rehabilitation policy to be adopted, with a focus on the dynamic interactions between people and their environments in a changing world.

DOI PMID

[27]
Ning Jia, Liu Jiyuan, Kuang Wenhui et al., 2018. Spatiotemporal patterns and characteristics of land-use change in China during 2010-2015.Journal of Geographical Sciences, 28(5): 547-562.Land use/cover change is an important theme on the impacts of human activities on the earth systems and global environmental change. National land-use changes of China during 2010–2015 were acquired by the digital interpretation method using the high-resolution remotely sensed images, e.g. the Landsat 8 OLI, GF-2 remote sensing images. The spatiotemporal characteristics of land-use changes across China during 2010–2015 were revealed by the indexes of dynamic degree model, annual land-use changes ratio etc. The results indicated that the built-up land increased by 24.6×10 3 km 2 while the cropland decreased by 4.9×10 3 km 2 , and the total area of woodland and grassland decreased by 16.4×10 3 km 2 . The spatial pattern of land-use changes in China during 2010–2015 was concordant with that of the period 2000–2010. Specially, new characteristics of land-use changes emerged in different regions of China in 2010–2015. The built-up land in eastern China expanded continually, and the total area of cropland decreased, both at decreasing rates. The rates of built-up land expansion and cropland shrinkage were accelerated in central China. The rates of built-up land expansion and cropland growth increased in western China, while the decreasing rate of woodland and grassland accelerated. In northeastern China, built-up land expansion slowed continually, and cropland area increased slightly accompanied by the conversions between paddy land and dry land. Besides, woodland and grassland area decreased in northeastern China. The characteristics of land-use changes in eastern China were essentially consistent with the spatial govern and control requirements of the optimal development zones and key development zones according to the Major Function-oriented Zones Planning implemented during the 12th Five-Year Plan (2011–2015). It was a serious challenge for the central government of China to effectively protect the reasonable layout of land use types dominated with the key ecological function zones and agricultural production zones in central and western China. Furthermore, the local governments should take effective measures to strengthen the management of territorial development in future.

DOI

[28]
Nobre A D, Cuartas L A, Hodnett M et al., 2011. Height above the nearest drainage: A hydrologically relevant new terrain model.Journal of Hydrology, 404(1/2): 13-29.This paper introduces a new terrain model named HAND, and reports on the calibration and validation of landscape classes representing soil environments in Amazonia, which were derived using it. The HAND model normalizes topography according to the local relative heights found along the drainage network, and in this way, presents the topology of the relative soil gravitational potentials, or local draining potentials. The HAND model has been demonstrated to show a high correlation with the depth of the water table, providing an accurate spatial representation of soil water environments. Normalized draining potentials can be classified according to the relative vertical flowpath-distances to the nearest drainages, defining classes of soil water environments. These classes have been shown to be comparable and have verifiable and reproducible hydrological significance across the studied catchment and for surrounding ungauged catchments. The robust validation of this model over an area of 18,000 km 2 in the lower Rio Negro catchment has demonstrated its capacity to map expansive environments using only remotely acquired topography data as inputs. The classified HAND model has also preliminarily demonstrated robustness when applied to ungauged catchments elsewhere with contrasting geologies, geomorphologies and soil types. The HAND model and the derived soil water maps can help to advance physically based hydrological models and be applied to a host of disciplines that focus on soil moisture and ground water dynamics. As an original assessment of soil water in the landscape, the HAND model explores the synergy between digital topography data and terrain modeling, presenting an opportunity for solving many difficult problems in hydrology.

DOI

[29]
Park T, Lee W K, Woo S Y et al., 2011. Assessment of land-cover change using GIS and remotely-sensed data: A case study in Ain Snoussi area of northern Tunisia.Forest Science and Technology, 7(2): 75-81.

DOI

[30]
Qin C Z, Gao H R, Zhu L J et al., 2018. Spatial optimization of watershed best management practices based on slope position units.Journal of Soil and Water Conservation, 73(5): 504-517.

DOI

[31]
Qin Chengzhi, Zhu Axing, Shi Xun et al., 2009. Quantification of spatial gradation of slope positions.Geomorphology, 110: 152-161.

DOI

[32]
Reis S, 2008. Analyzing land use/land cover changes using remote sensing and GIS in Rize, North-East Turkey.Sensors, 8(10): 6188-6202.Mapping land use/land cover (LULC) changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities), negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS) in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel). In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude) by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2%) (especially in tea gardens), urban (117%), pasture (-72.8%) and forestry (-12.8%) areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.

DOI PMID

[33]
Rennó C D, Nobre A D, Cuartas L A et al., 2008. HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia.Remote Sensing of Environment, 112(9): 3469-3481.Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimensional spectral data. Accurate topographic data are required for the understanding of land surface processes at finer scales. Topographic detail has now become available with the Shuttle Radar Topographic Mission (SRTM) data. This new digital elevation model (DEM) shows the feature-rich relief of lowland rain forests, adding to the ability to map rain forest environments through many quantitative terrain descriptors. In this paper we report on the development of a new quantitative topographic algorithm, called HAND (Height Above the Nearest Drainage), based on SRTM-DEM data. We tested the HAND descriptor for a groundwater, topographic and vegetation dataset from central Amazonia. The application of the HAND descriptor in terrain classification revealed strong correlation between soil water conditions, like classes of water table depth, and topography. This correlation obeys the physical principle of soil draining potential, or relative vertical distance to drainage, which can be detected remotely through the topography of the vegetation canopy found in the SRTM-DEM data.

DOI

[34]
Tang Guoan, Yang Xin, 2015. ArcGIS Geographic Information System Spatial Analysis Experiment Tutorial. 2nd ed. Beijing: Science Press. (in Chinese)

[35]
Tarboton D G, 1997. A new method for the determination of flow directions and contributing areas in grid digital elevation models.Water Resources Research, 33(2): 309-319.A new procedure for the representation of flow directions and calculation of upslope areas using rectangular grid digital elevation models is presented. The procedure is based on representing flow direction as a single angle taken as the steepest downward slope on the eight triangular facets centered at each grid point. Upslope area is then calculated by proportioning flow between two downslope pixels according to how close this flow direction is to the direct angle to the downslope pixel. This procedure offers improvements over prior procedures that have restricted flow to eight possible directions (introducing grid bia) or proportioned flow according to slope (introducing unrealistic dispersion). The new procedure is more robust than prior procedures based on fitting local planes while retaining a simple grid based structure. Detailed algorithms are presented and results are demonstrated through test examples and application to digital elevation data sets.

DOI

[36]
Tesfa T K, Tarboton D G, Watson D W et al., 2011. Extraction of hydrological proximity measures from DEMs using parallel processing.Environmental Modelling & Software, 26: 1696-1709.http://linkinghub.elsevier.com/retrieve/pii/S1364815211001794

DOI

[37]
Wang Qixiang, Fan Xiaohui, Qin Zuodong et al., 2012. Changes trends of temperature and precipitation in the Loess Plateau region of China, 1961-2010.Global and Planetary Change, 92/93: 138-147.78 The changing trends are tested with the gridded data based on all 214 station series. 78 The tests are conducted for the five management divisions of the region as well. 78 The warming rate is over two times larger than the Northern Hemisphere average. 78 The region-averaged annual precipitation shows a non-significant negative trend. 78 The Loess Plateau Region can be divided into two sub-regions in terms of climate change.

DOI

[38]
Wang Shuai, Fu Bojie, Piao Shilong et al., 2015. Reduced sediment transport in the Yellow River due to anthropogenic changes.Nature Geoscience, 9: 38-41.The sediment load of China[rsquor]s Yellow River has been declining. Analysis of 60 years of runoff and sediment load data attributes this decline to river engineering, with an increasing role of post-1990s land use changes on the Loess Plateau.

DOI

[39]
Xin Zhongbao, Xu Jiongxin, Zheng Wei, 2008. Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981-2006): Impacts of climate changes and human activities. Science in China Series D: Earth Sciences, 1: 67-78.Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.

DOI

[40]
Zhang Baoqing, Wu Pute, Zhao Xining et al., 2012. Changes in vegetation condition in areas with different gradients (1980-2010) on the Loess Plateau, China.Environmental Earth Sciences, 68(8): 2427-2438.This study characterized and compared changes in vegetation condition in areas with different gradients during the past three decades across the entire Loess Plateau. For this purpose, changes in vegetation type and vegetation coverage at sites with 0 - 15A degrees and > 15A degrees slope gradients were determined by analyzing land use data and Normalized Difference Vegetation Index (NDVI) data, respectively. The software Arc/Info 9.3, land use transformation matrix, linear regression analysis, and Mann-Kendall test were used for the data processing and analysis. Policy influences, human impacts, and climate variability were also taken into account to find the reasons for vegetation condition change. The results indicated that the "Grain-For-Green" project achieved initial success. Areas of farmland and grassland changed most extensively, and far greater areas of farmland were transformed into forest and grassland than vice versa. Moreover, the conversion of farmland to forest and grassland mainly occurred in areas where slopes exceeded 15A degrees, while grassland was mainly changed to farmland in areas with gentle slopes. Vegetation coverage on the Loess Plateau exhibited overall increases after the implementation of "Grain-For-Green" project. Regions with sparse vegetation have declined sharply, mostly in steeply sloped areas. Vegetation coverage has increased significantly in most regions, particularly in the parts traversed by the principal sediment source of the Yellow River, which could help to control the severe soil and water losses. However, regions with sparse vegetation on the Loess Plateau still covered 71.1 % of the total area in 2010. Therefore, it is important to further increase vegetation coverage in the future.

DOI

[41]
Zhou Yi, Tang Guoan, Yang Xin et al., 2010. Positive and negative terrains on northern Shaanxi Loess Plateau.Journal of Geographical Sciences, 20(1): 64-76.

DOI

[42]
Zhu Liangjun, Zhu Axing, Qin Chengzhi et al., 2018. Automatic approach to deriving fuzzy slope positions.Geomorphology, 304: 173-183.Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions.

DOI

Options
Outlines

/

〈 〉