This paper presents a scenario-based assessment of global future food security. To do that, the socio-economic and climate change scenarios were defined for the future and were linked to an integrated modeling framework. The crop yields simulated by the GIS-based Environmental Policy Integrated Climate (EPIC) model and crop areas simulated by the crop choice decision model were combined to calculate the total food production and per capita food availability, which was used to represent the status of food availability and stability. The per capita Gross Domestic Product (GDP) simulated by IFPSIM model was used to reflect the situation of food accessibility and affordability. Based on these two indicators, the future food security status was assessed at a global scale over a period of approximately 20 years, starting from the year 2000. The results show that certain regions such as South Asia and most African countries will likely remain hotspots of food insecurity in the future as both the per capita food availability and the capacity of being able to import food will decrease between 2000 and 2020. Low food production associated with poverty is the determining factor to starvation in these regions, and more efforts are needed to combat hunger in terms of future actions. Other regions such as China, most Eastern European countries and most South American countries where there is an increase in per capita food availability or an increase in the capacity to import food between 2000 and 2020 might be able to improve their food security situation.
This paper calculated spatial accessibility of all counties (city, urban district) in China with cost weighted distance method. Region divisions of county accessibility were conducted, and relation of traffic accessibility and population aggregation was discussed in this paper. The results indicated that county accessibility in China had mainly low values and a distribution structure of circle layer and reverse-to-natural gradient. There was an obvious correlation between county accessibility and population density in China. With these analyses, inner mechanisms of population migration in different traffic conditions and region types were revealed, and can provide useful proposals to regional planning, traffic planning and smart distribution of people in China.
With the rapid increase of the number and influence of floating population in China, it is urgently needed to understand the regional types of China’s floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population, this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then, the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China’s 2000 census data at county level. The results show: (1) The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously, and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. (2) The modified composite-index identification method, by using the share of a region’s certain type of floating population to the total in China as weights, can effectively correct the over- or under-estimated errors due to the rather large or small total population of a region. (3) The spatial patterns of different regional types of China’s floating population are closely related to the regional differentiation of their natural environment, population density and socio- economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation, more than 800 mm precipitation, rather higher population densities and economic development levels.
Beijing is facing a huge challenge to manage the growth of its built-up area whilst also retaining both productive arable land and land for conservation purposes in order to simultaneously realize the three aims of economic development, protecting arable land and generating environmental improvements. Meanwhile, London, as a world city with more than 200 years of industrialization and urbanization, has accumulated rich theoretical and practical experiences for land use planning in a major urban area, such as the creation of Garden Cities, a designated Green Belt and New Towns. This paper firstly analyzes the main characteristics of the spatial distribution of the built-up area, arable land and conservation land in Beijing. Then, some of the key aspects of urban fringe planning in the London region are examined. Lastly, several implications from the experience of London are provided with respect to land-use planning for Beijing, concentrating on a re-appraisal of land-use functions around Beijing, measures to improve the green belt, the development of small towns to house rural-urban migrants and urban overspill, and effective implementation of land-use planning.
Local spatial interaction between neighborhood land-use categories (i.e. neighborhood interaction) is an important factor which affects urban land-use change patterns. Therefore, it is a key component in cellular automata (CA)-based urban geosimulation models towards the simulation and forecast of urban land-use changes. Purpose of this paper is to interpret the similarities and differences of the characteristics of neighborhood interaction in urban land-use changes of different metropolitan areas in Japan for providing empirical materials to understand the mechanism of urban land-use changes and construct urban geosimulation models. Characteristics of neighborhood interaction in urban land-use changes of three metropolitan areas in Japan, i.e. Tokyo, Osaka, and Nagoya, were compared using such aids as the neighborhood interaction model and similarity measure function. As a result, urban land-use in the three metropolitan areas was found to have had similar structure and patterns during the study period. Characteristics of neighborhood interaction in urban land-use changes are quite different from land-use categories, meaning that the mechanism of urban land-use changes comparatively differs among land-use categories. Characteristics of neighborhood interaction reveal the effect of spatial autocorrelation in the spatial process of urban land-use changes in the three metropolitan areas, which correspond with the characteristics of agglomeration of urban land-use allocation in Japan. Neighborhood interaction amidst urban land-use changes between the three metropolitan areas generally showed similar characteristics. The regressed neighborhood interaction coefficients in the models may represent the general characteristics of neighborhood effect on urban land-use changes in the cities of Japan. The results provide very significant materials for exploring the mechanism of urban land-use changes and the construction of universal urban geosimulation models which may be applied to any city in Japan.
The spatial differentiation of land use changes of Tuticorin is studied using high resolution LISS III satellite imagery and Maximum Likelihood algorithms. The classification accuracy of 95.2% was obtained. In this study, the land use of Tuticorin is classified as settlement, salt pan, agricultural land, wasteland, water bodies and shrubs. The settlement area is increased to 4.6 km2 during the year 2001 and 2006. The settlement area change is mainly driven by growth of industries and migration of people from peripheral villages. Shrub is increased to 3.63 km2 in the six year period. Water logging due to growth of shrubs in Tuticorin leads to several environmental and health hazard. This study warrants proper urban planning for Tuticorin for sustainable use of resource and environment.
Geomorphologic maps are one of the most fundamental materials of the natural environment. They have been widely used in scientific research, resource exploration and extraction, education and military affairs etc. An editorial committee was established in 2001 to collect materials for researching and compiling a set of new 1:1,000,000 geomorphologic atlas of China. A digital geomorphologic database was created with visual interpretation from Landsat TM/ETM imageries and SRTM-DEM etc. The atlas compiled from the database was finished. The main characteristics of the atlas are as follows: Firstly, Landsat TM/ETM imageries, published geomorphologic maps or sketches, geographical base maps, digital geological maps, and other thematic maps were collected, which were uniformly geometrically rectified, clipped into uniform sheets, and stored in the foundation database. Secondly, based on the legends of 15 sheets 1:1,000,000 maps published in the 1980s, a geomorphologic classification system was built by combining morphology and genesis types. The system comprised seven hierarchical layers: basic morphology, genesis, sub-genesis, morphology, micro-morphology, slope and aspect, material composition and lithology. These layers were stored in the database during visual image interpretation. About 2000 kinds of morpho- genesis and 300 kinds of morpho-structure were interpreted. Thirdly, the legend system was built, which included color, symbol bases and note bases etc., compilation standards and procedures were developed, 74 sheets of 1:1,000,000 covering all land and sea territories of China were compiled, the 1:1,000,000 geomorphologic atlas of the People’s Republic of China was finished and published. The atlas will fill the blanks in national basic scale thematic maps, and the geomorphologic database could be applied widely in many fields in the future.
Spatial relations, reflecting the complex association between geographical phenomena and environments, are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization, an important geographical issue, is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter, the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong, located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan, Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan, Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.
Afforestation in China’s subtropics plays an important role in sequestering CO2 from the atmosphere and in storage of soil carbon (C). Compared with natural forests, plantation forests have lower soil organic carbon (SOC) content and great potential to store more C. To better evaluate the effects of afforestation on soil C turnover, we investigated SOC and its stable C isotope (δ13C) composition in three planted forests at Qianyanzhou Ecological Experimental Station in southern China. Litter and soil samples were collected and analyzed for total organic C, δ13C and total nitrogen. Similarly to the vertical distribution of SOC in natural forests, SOC concentrations decrease exponentially with depth. The land cover type (grassland) before plantation had a significant influence on the vertical distribution of SOC. The SOC δ13C composition of the upper soil layer of two plantation forests has been mainly affected by the grass biomass 13C composition. Soil profiles with a change in photosynthetic pathway had a more complex 13C isotope composition distribution. During the 20 years after plantation establishment, the soil organic matter sources influenced both the δ13C distribution with depth, and C replacement. The upper soil layer SOC turnover in masson pine (a mean 34% of replacement in the 10 cm after 20 years) was more than twice as fast as that of slash pine (16% of replacement) under subtropical conditions. The results demonstrate that masson pine and slash pine plantations cannot rapidly sequester SOC into long-term storage pools in subtropical China.
We analyzed the Normalized Difference Vegetation Index (NDVI) from satellite images and precipitation data from meteorological stations from 1998 to 2007 in the Dongting Lake wetland watershed to better understand the eco-hydrological effect of atmospheric precipitation and its relationship with vegetation. First, we analyzed its general spatio-temporal distribution using its mean, standard deviation and linear trend. Then, we used the Empirical Orthogonal Functions (EOF) method to decompose the NDVI and precipitation data into spatial and temporal modes. We selected four leading modes based on North and Scree test rules and analyzed the synchronous seasonal and inter-annual variability between the vegetation index and precipitation, distinguishing time-lagged correlations between EOF modes with the correlative degree analysis method. According to our detailed analyses, the vegetation index and precipitation exhibit a prominent correlation in spatial distribution and seasonal variation. At the 90% confidence level, the time lag is around 110 to 140 days, which matches well with the seasonal variation.
Based on data collected over five years of monitoring the Lower Tarim River, we analyzed the variability of soil moisture content (SMC) and the relationship between SMC, groundwater table depth (GWD) and vegetation by using the methods of coefficient of variation (Cv), Pearson correlation and regression. The results of the variability of SMC indicate that it rose with increase in depth of soil layer – SMC in the soil layer of 0–60 cm was relatively small compared to SMC in the soil layer of 100–260 cm which showed a significant increase in variability. SMC and GWD before and after ecological water diversions exhibited significant differences at the site of the Yingsu transect and its vicinity of the watercourse, especially SMC in the soil layer of 100–260 cm increased significantly with a significant rise of GWD and reached maximum values at a GWD of about 4 m. Plant coverage and species diversity significantly improved with increases in SMC in the soil layer of 100–260 cm, both of them approached the maximum values and 92.3% of major plant species were able to grow when SMC was > 10%. To restore the ecosystem of desert riparian forest along the Lower Tarim River, the GWD must be maintained at < 4 m in the vicinity of the watercourse and at about 4 m for the rest of this arid region.
Based on the static opaque chamber method, the respiration rates of soil microbial respiration, soil respiration, and ecosystem respiration were measured through continuous in-situ experiments during rapid growth season in semiarid Leymus chinensis steppe in the Xilin River Basin of Inner Mongolia, China. Soil temperature and moisture were the main factor affecting respiration rates. Soil temperature can explain most CO2 efflux variations (R2=0.376–0.655) excluding data of low soil water conditions. Soil moisture can also effectively explain most of the variations of soil and ecosystem respiration (R2=0.314–0.583), but it can not explain much of the variation of microbial respiration (R2=0.063). Low soil water content (≤5%) inhibited CO2 efflux though the soil temperature was high. Rewetting the soil after a long drought resulted in substantial increases in CO2 flux at high temperature. Bivariable models based on soil temperature at 5 cm depth and soil moisture at 0–10 cm depth can explain about 70% of the variations of CO2 effluxes. The contribution of soil respiration to ecosystem respiration averaged 59.4%, ranging from 47.3% to 72.4%; the contribution of root respiration to soil respiration averaged 20.5%, ranging from 11.7% to 51.7%. The contribution of soil to ecosystem respiration was a little overestimated and root to soil respiration little underestimated because of the increased soil water content that occurred as a result of plant removal.
Tropical forests have been recognized as having global conservation importance. However, they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa, India, during 1973–2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest, open forest, scrub land, agriculture, barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation, shifting cultivation, dam and road construction, unregulated management actions, and social pressure. A significant increase of 1222.8 km2 agriculture area (1973–2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences, including decline in forest cover, soil erosion, and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests, which are rapidly being deforested.