Journal of Geographical Sciences >
Urban expansion and intra-urban land evolution as well as their natural environmental constraints in arid/semiarid regions of China from 2000-2018
Pan Tao (1987-), Associate Professor, specialized in urban land use. E-mail: pantao@qfnu.edu.cn |
Received date: 2022-05-28
Accepted date: 2023-03-24
Online published: 2023-07-24
Supported by
Natural Science Foundation Youth Program of Shandong Province(ZR2021QD134)
Humanity and Social Science Youth Foundation of the Ministry of Education of China(21YJCZH111)
National Natural Science Foundation of China(31770515)
Rapid urbanization has occurred in arid/semiarid China, threatening the sustainability of fragile dryland ecosystems; however, our knowledge of natural environmental constraints on multiscale urban lands in this region is still lacking. To solve this issue, this study retrieved 15-m multiscale urban lands. Results indicated that urban area increased by 68% during 2000-2018, and one-third of the increase was contributed by only three large cities. The coverage of impervious surface area (ISA) and vegetated area (VA) increased by 16.6% and 1.38%, respectively. Such land-cover change may be helpful in suppressing wind erosion and sand storms. We also found that the newly urban lands had relatively lower ISA and higher VA than the old urban lands, indicating an improved human settlement environment. Strong environmental constraints on urban expansion were identified, with cities in oasis urban environments (OUEs) that had water supply expanding 150% faster than cities in desert urban environments (DUEs). Urban development was also constrained by terrain, with 73% of the ISA expansion occurring in relatively flat areas. Overall, the aggregated pattern of urbanization and the increase in ISA and VA in the newly urbanized lands have improved water-use efficiency and ecological services and benefited desert ecosystem protection in arid/semiarid China.
PAN Tao , KUANG Wenhui , SHAO Hua , ZHANG Chi , WANG Xiaoyu , WANG Xinqing . Urban expansion and intra-urban land evolution as well as their natural environmental constraints in arid/semiarid regions of China from 2000-2018[J]. Journal of Geographical Sciences, 2023 , 33(7) : 1419 -1441 . DOI: 10.1007/s11442-023-2136-4
Figure 1 Geographic information of arid and semiarid regions of China |
Table 1 Detailed information of the 36 cities in this study |
Order | Name | Location | Landsat number | Order | Name | Location | Landsat number |
---|---|---|---|---|---|---|---|
1 | Urumqi | 43.87°N, 87.58°E | 143/029 | 19 | Jiayuguan | 39.08°N, 98.28°E | 135/032 |
2 | Baotou | 40.61°N, 109.97°E | 127/032 | 20 | Baiyin | 36.53°N, 104.16°E | 130/035 |
3 | Yinchuan | 38.48°N, 106.21°E | 129/032 | 21 | Jinchang | 38.49°N, 103.15°E | 132/033 |
4 | Hohhot | 40.82°N, 111.65°E | 127/032 | 22 | Bayannur | 40.76°N, 107.41°E | 129/032 |
5 | Lanzhou | 36.07°N, 103.79°E | 130/035 | 23 | Karamay | 45.58°N, 84.89°E | 145/028 |
6 | Xining | 36.62°N, 101.77°E | 132/035 | 24 | Alxa Left | 38.84°N, 105.68°E | 130/033 |
7 | Shihezi | 44.33°N, 86.05°E | 144/029 | 25 | Wuhai | 39.68°N, 106.81°E | 129/032 |
8 | Korla | 41.75°N, 86.15°E | 143/031 | 26 | Jiuquan | 39.71°N,98.51°E | 135/032 |
9 | Hulunbuir | 49.20°N, 119.79°E | 123/026 | 27 | Bole | 44.88°N, 82.09°E | 146/029 |
10 | Chifeng | 42.27°N,118.93°E | 122/031 | 28 | Zhangye | 38.95°N, 100.47°E | 133/033 |
11 | Ulanqab | 40.99°N, 113.12°E | 125/032 | 29 | Wuwei | 37.93°N, 102.63°E | 132/034 |
12 | Yining | 43.93°N, 81.29°E | 147/029 | 30 | Hotan | 37.11°N, 79.93°E | 146/034 |
13 | Kashi | 39.44°N, 76.01°E | 149/033 | 31 | Erdos | 39.59°N, 109.76°E | 127/032 |
14 | Hami | 42.86°N, 93.53°E | 138/030 | 32 | Tacheng | 46.74°N, 82.97°E | 146/028 |
15 | Tongliao | 43.63°N, 122.26°E | 120/030 | 33 | Xigaze | 29.26°N, 88.88°E | 139/040 |
16 | Changji | 44.00°N, 87.27°E | 143/029 | 34 | Altay | 47.82°N, 88.13°E | 143/027 |
17 | Aksu | 41.17°N, 80.27°E | 147/031 | 35 | Turpan | 42.96°N, 89.11°E | 141/030 |
18 | Silingrad | 43.94°N, 116.06°E | 124/029 | 36 | Atush | 39.72°N, 76.15°E | 149/032 |
Figure 2 The sub-pixel land compositions of impervious surface area, vegetation, and soil in sampled cities of Yining, Changji, Silingrad, and Hami. Note: Cities of Yining and Changji are located in oasis environments, in contrast, cities of Silingrad and Hami are located in desert environments. |
Figure 3 (a) A sample of an oasis urban environment, and the urban land is surrounded by green vegetation; (b) a sample of a desert urban environment, and the urban land is surrounded by bare soil. The background colors of (a) and (b) are true color syntheses from Landsat OLI images, with the R, G, and B layers of band 7, band 5, and band 3, respectively. |
Table 2 Intra-urban landscape ecology indicators |
Abbreviation | Index | Expression |
---|---|---|
PD | Patch Density | $PD=\frac{{{n}_{i}}}{A}(10,000)(100)$ |
LPI | Largest Patch Index | $LPI=\frac{\underset{j=1}{\overset{n}{\mathop{max}}}\,({{a}_{ij}})}{A}(100)$ |
LSI | Landscape Shape Index | $LSI=\frac{0.25\sum\limits_{k=1}^{m}{e_{ik}^{*}}}{\sqrt{A}}or=\frac{0.25{{E}^{*}}}{\sqrt{A}}$ |
CONNECT | Connectance index | $connect=\left[ \frac{\sum\limits_{j\ne k}^{n}{{{c}_{ijk}}}}{\frac{{{n}_{i}}({{n}_{i}}-1)}{2}} \right](100)$ |
SHDI | Shannon Diversity Index | $SHDI=-\sum\limits_{i=1}^{m}{{{P}_{i}}In({{P}_{i}})}$ |
Table 3 Validated indicators, including the transition matrix, overall classification accuracy, kappa statistics, reference pixels, classified pixels, number of correct pixels, producer’s accuracy, and user’s accuracy, were provided to calculate accuracies |
Land-cover | Ground truth pixels | Reference | Classified | Number | Producer’s | User’s | |||
---|---|---|---|---|---|---|---|---|---|
ISA | VA | BS | WB | Pixels | Pixels | Correct | Accuracy | Accuracy | |
ISA | 2734 | 42 | 207 | 25 | 3014 | 3008 | 2734 | 90.71% | 90.89% |
VA | 21 | 2075 | 18 | 14 | 2173 | 2128 | 2075 | 95.49% | 97.51% |
BS | 241 | 36 | 1295 | 6 | 1537 | 1578 | 1295 | 84.26% | 82.07% |
WB | 18 | 20 | 17 | 431 | 476 | 486 | 431 | 90.55% | 88.68% |
Year: 2000, Overall Classification Accuracy = 90.76% (i.e., 6535/7200), Kappa Statistics = 0.84 | |||||||||
ISA | 2838 | 29 | 181 | 12 | 3145 | 3060 | 2838 | 90.24% | 92.75% |
VA | 54 | 2033 | 20 | 3 | 2092 | 2110 | 2033 | 97.18% | 96.35% |
BS | 229 | 22 | 1365 | 3 | 1570 | 1619 | 1365 | 86.94% | 84.31% |
WB | 24 | 8 | 4 | 375 | 393 | 411 | 375 | 95.42% | 91.24% |
Year: 2018, Overall Classification Accuracy = 91.82% (i.e., 6611/7200), Kappa Statistics = 0.85 |
Abbreviations: WB, water body; BS, bare soil; VA, vegetated area; ISA, impervious surface area |
Figure 4 Sub-pixel land composition assessment of ISA, VA, and bare soil surfaces in 2000 and 2018 |
Figure 5 (a) Changes in urban areas during 2000-2018 in all cities in arid/semiarid China. The height of the column indicates the area of urban land in each city. Note: OUE, oasis urban environment; DUE, desert urban environment; (b) The six largest cities account for 50% of the urban expansion during 2000-2018 and 51% of the urban areas in 2018 among the 36 major cities in arid/semiarid China; (c) The mean urban land area of all cities. The solid black lines represent the median values, the crosses represent the means; from bottom to top, the four horizontal lines are the lower edge, the lower quartile, the upper quartile, and the upper edge, respectively. The circular dots represent outliers. |
Figure 6 Urban expansion and land-cover changes across all cities in arid/semiarid China in 2000 and 2018. In this figure, to clearly compare the size of each city in the spatial pattern, we set the scale of each city to 5 kilometers. Meanwhile, the outer border size of each city is set to a square with the side length of 1.2 cm. |
Figure 7 Fractional coverage of impervious surfaces area, vegetated area, bare soil, and water body in the study area in 2000 and 2018 (OUE: oasis urban environment, DUE: desert urban environment) |
Figure 8 (a) Changes in landscape patterns in the study area during 2000-2018. (b)-(e) Comparison of the landscape patterns of impervious surface area (ISA), vegetated area (VA), bare soil (BS), and water body (WB) in 2000 and 2018 using the five landscape indices: (b) PD, (c) LPI, (d) LSI, and (e) CONNECT. |
Table 4 Terrain effects on urban lands across all the studied cities in arid/semiarid China |
Study area | Units | All land-cover types | ISA | Vegetated areas | Bare soil | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
≤5° | 5°- 10° | 10°-15° | >15° | ≤5° | 5°- 10° | 10°-15° | >15° | ≤5° | 5°- 10° | 10°-15° | >15° | ≤5° | 5°- 10° | 10°-15° | >15° | ||
Urban land in 2000 | Area (km2) | 931 | 778 | 228 | 67 | 624 | 284 | 71 | 25 | 157 | 110 | 28 | 7 | 320 | 254 | 69 | 19 |
% | 46 | 39 | 11 | 3 | 62 | 28 | 7 | 2 | 52 | 36 | 9 | 2 | 48 | 38 | 10 | 3 | |
Expanded area | Area (km2) | 698 | 488 | 129 | 44 | 900 | 277 | 49 | 11 | 138 | 87 | 21 | 5 | 141 | 96 | 25 | 9 |
% | 51 | 36 | 9 | 3 | 73 | 22 | 4 | 1 | 55 | 35 | 8 | 2 | 52 | 35 | 9 | 3 | |
Urban land in 2018 | Area (km2) | 1629 | 1266 | 357 | 111 | 1524 | 562 | 119 | 36 | 295 | 197 | 49 | 13 | 266 | 196 | 53 | 16 |
% | 48 | 38 | 11 | 3 | 68 | 25 | 5 | 2 | 53 | 36 | 9 | 2 | 50 | 37 | 10 | 3 |
Figure 9 Terrain constraints on urban land development (i.e., ISA expansion) in Xining (a1, a2), Lanzhou (b1, b2), Alxa (c1, c2), and Karamay (d1, d2). Notes: To compare the different space sizes of each city, we set the scale of 10 kilometers. Meanwhile, the outer border size of each city was set to a square with the side length of 3.25 cm. |
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