Chenchen Shi

Land Cover Mapping Based on Multisource Spatial Data Mining Approach for Climate Simulation: A Case Study in the Farming-Pastoral Ecotone of North China

The land use and land cover change (LUCC) is one of the prime driving forces of climate change. Most attention has been paid to the influence of accuracy of the land cover data in numerous climate simulation projects. The accuracy of the temporal land use data from Chinese Academy of Sciences (CAS) is higher than 90%, but the high-precision land cover data is absent. We overlaid land cover maps from different sources, and the grids with consistent classification were selected as the sample grids. By comparing the results obtained with different decision tree classifiers with the WEKA toolkit for data mining, it was found that the C4.5 algorithm was more suitable for converting land use data of CAS classification to land cover data of IGBP classification. We reset the decision rules with Net Primary Productivity (NPP) and Normalized Difference Vegetation Index (NDVI) as the indicators. The accuracy of the reclassified land cover data was proven to reach 83.14% through comparing with the Terrestrial Ecosystem Monitoring Sites and high resolution images. Therefore, it is feasible to produce the temporal land cover data with this method, which can be used as the parameters of dynamical downscaling in the regional climate simulation.

Land Use Zoning for Conserving Ecosystem Services under the Impact of Climate Change: A Case Study in the Middle Reaches of the Heihe River Basin

Ecosystem services are the benefit human populations derive directly and indirectly from the natural environment. They suffer from both the human intervention, like land use zoning change, and natural intervention, like the climate change. Under the background of climate change, regulation services of ecosystem could be strengthened under proper land use zoning policy to mitigate the climate change. In this paper, a case study was conducted in the middle reaches of the Heihe River Basin to assess the ecosystem services conservation zoning under the change of land use associated with climate variations. The research results show the spatial impact of land use zoning on ecosystem services in the study area which are significant reference for the spatial optimization of land use zoning in preserving the key ecosystem services to mitigate the climate change. The research contributes to the growing literature in finely characterizing the ecosystem services zones altered by land use change to alleviate the impact of climate change, as there is no such systematic ecosystem zoning method before.

Land-Use-Oriented Conservation of Ecosystem Services

Ecosystem services suffer from both the human intervention, such as land-use zoning change, and the natural intervention, such as climate change. In this chapter, we first conducted land-use zoning for conserving ecosystem services in the middle reaches of the Heihe River Basin (HRB). Under the background of climate change, regulation services of ecosystem could be strengthened under proper land-use zoning policy to mitigate climate change. We conducted a case study in the middle reaches of the HRB to assess the ecosystem service conservation zoning under the change of land use associated with climate variations. The results show the spatial impact of land-use zoning on ecosystem services in the study area which are significant reference for the spatial optimization of land-use zoning in preserving the key ecosystem services to mitigate climate change. The research contributes to the growing literature in finely characterizing the ecosystem service zones altered by land-use change to alleviate the impact of climate change, as there is no such systematic ecosystem zoning method before. Further, we introduced ecosystem-based adaptation measures for climate change in Qinghai Province. The change of land surface can exert significant influence on the future climate change. We analyzed the effects of herdsmen’s adaptation to climate change on the livestock breeding, income, and land surface dynamics with a land surface parameterization scheme. The empirical analysis was first carried out on the impacts of the adaptation measures of herdsmen on their income in the context of the climate change with the positive mathematical programming (PMP) model on the basis of the household survey data in the Three-River Source Region, an ecologically fragile area in Qinghai Province, China. Then, the land surface parameterization process is analyzed based on the agent-based model (ABM), which involves the herdsmen’s adaptation measures on climate change, and it also provides reference for the land surface change projection. The result shows that the climate change adaptation measures will have a positive effect on increasing the amount of herdsman’s livestock and income as well as future land surface dynamics. Some suggestions on the land-use management were finally proposed, which can provide significant reference information for the land-use planning. Finally, we introduced how to build resilience to climate change for conserving ecosystem servers. The ecosystem resilience plays a key role in maintaining a steady flow of ecosystem services and enables quick and flexible responses to climate change, and maintaining or restoring the ecosystem resilience of forests is a necessary societal adaptation to climate change; however, there is a great lack of spatially explicit ecosystem resilience assessments. Drawing on principles of the ecosystem resilience highlighted in the literature, we built on the theory of dissipative structures to develop a conceptual model of the ecosystem resilience of forests. A hierarchical indicator system was designed with the influencing factors of the forest ecosystem resilience, including the stand conditions and the ecological memory, which were further disaggregated into specific indicators. Furthermore, indicator weights were determined with the analytic hierarchy process (AHP) and the coefficient of variation method. Based on the remote sensing data, forest inventory data, so forth, the resilience index of forests was calculated. The result suggests that there is a significant spatial heterogeneity of the ecosystem resilience of forests, indicating it is feasible to generate large-scale ecosystem resilience maps with this assessment model, and the results can provide a scientific basis for the conservation of forests, which is of great significance to the climate change mitigation.

Impact Assessments on Agricultural Productivity of Land-Use Change

Currently, food safety and its related influencing factors in China are the hot research topics, and cultivated land conversion is one of the significant factors influencing food safety in China. In this chapter, we first investigated land degradation induced by land-use change. Land degradation is a complex process which involves both the natural ecosystem and the socioeconomic system, among which climate and land-use change are the two predominant driving factors. To comprehensively and quantitatively analyze the land degradation process, we employed the normalized difference vegetation index (NDVI) as a proxy to assess land degradation and further applied the binary panel logistic regression model to analyze the impacts of the driving factors on land degradation in the North China Plain. The results revealed that increasing in rainfall and temperature would significantly and positively contribute to the land improvement, and conversion from cultivated land to grassland and forest land showed positive relationship with land improvement, while conversion to built-up area will lead to land degradation. Besides, human agricultural intensification represented by fertilizer utilization will help to improve the land quality. The economic development may exert positive impacts on land quality to alleviate land degradation, although the rural economic development and agricultural production will exert negative impacts on the land and lead to land degradation. Infrastructure construction would modify the land surface and further resulted in land degradation. The findings of the research will provide scientific information for sustainable land management. Second, we predicted land-use conversions in the North China Plain based on the scenario analysis. Scenario analysis and dynamic prediction of land-use structure which involve many driving factors are helpful to investigate the mechanism of land-use change and even to optimize land-use allocation for sustainable development. In this study, land-use structure changes during 1988–2010 in North China Plain were discerned and the effects of various natural and socioeconomic driving factors on land-use structure changes were quantitatively analyzed based on an econometric model. The key drivers of land-use structure changes in the model are county-level net returns of land resource. In this research, we modified the net returns of each land-use type for three scenarios, including business as usual (BAU) scenario, rapid economic growth (REG) scenario, and coordinated environmental sustainability (CES) scenario. The simulation results showed that, under different scenarios, future land-use structures were different due to the competition among various land-use types. The land-use structure changes in North China Plain in the 40-year future will experience a transfer from cultivated land to built-up area, an increase of forestry land, and decrease of grassland. The results will provide some significant references for land-use management and planning in the study area. Third, we simulated shifting patterns of agroecological zones across China. An agroecological zone (AEZ) is a land resource mapping unit, defined in terms of climate, landform, and soils, and has a specific range of potentials and constraints for cropping (FAO 1996). The shifting patterns of AEZs in China driven by future climatic changes were assessed by applying the agroecological zoning methodology proposed by International Institute for Applied Systems Analysis (IIASA) and Food and Agriculture Organization of the United Nations (FAO) in this study. A data processing scheme was proposed to reduce systematic errors in projected climate data using observed data from meteorological stations. AEZs in China of each of the four periods: 2011–2020, 2021–2030, 2031–2040, and 2041–2050 were drawn. It is found that the future climate change will lead to significant local changes of AEZs in China and the overall pattern of AEZs in China is stable. The shifting patterns of AEZs will be characterized by northward expansion of humid AEZs to subhumid AEZs in south China, eastward expansion of arid AEZs to dry and moist semiarid AEZs in north China, and southward expansion of dry semiarid AEZs to arid AEZs in southwest China.