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Ecological environment assessment can not only provide significant references for effective solutions to regional ecological problems, but also promote the benign interaction of socio-economic-ecological development. This study selected the Heihe River Basin (HRB) as the typical area to comprehensively evaluate the ecological environment from 2010 to 2030 based on the dynamics of land system (DLS) model, which is coupled with the biological abundance index (BAI), vegetation coverage index (VCI), water density index (WDI), land degradation index (LDI), and eco-environment quality index (EQI). The results indicate that the BAI and VCI will be high in the south and east, low in the north and west in general. Under the future baseline scenario, the changes of biological abundance, vegetation coverage, and deteriorating land in the midstream and downstream regions will may seriously hinder restoration of the ecological environment. In particular, the BAI in the midstream and downstream regions will decline more rapidly, with a rate of 10.30% and 18.59%, respectively. The water area will be scattered and less abundant overall, but the WDI in the midstream, that is up to 3.86 in 2030, will be higher than that in other regions. Results also show that the regions with high EQI are mainly located in the northeast and south region. It is predicted that the ecological fragile zones in the future will mainly distribute in the midstream and downstream regions, especially in Jiayuguan City and Jinta County. The EQI will drop by 44.28% and 11.40% during 2010-2030 without external conditions intervened. In addition, Qilian Mountain, Jiuquan City, Gaotai County, Linze County, and Shandan County will also have relatively strong recovery capacities under the influence of ecological policies. All above could provide the basis for the development of future watershed ecological environment management and protection planning.

In arid regions, land development and degradation (LDD) is sustained by the undesirable land development, human production and living, and climate change. Therefore, the understanding of LDD processes and their driving mechanism in the arid or semi-arid regions is significant to guarantee the sustainable development of ecological environment. This study explored the critical LDD processes in the Heihe River Basin (HRB) during 1990-2010 with the spatio-temporal evaluation of critical land use dynamics and its land quality changing trends. Then, the driving mechanism of cultivated land development process, grassland degradation process and water resource change process were analyzed by a simultaneous equations model which took the interaction of three processes into account. The results showed that the mutual transfers of cultivated land were primarily gathered in the middle reaches from 1990 to 2010. Its area grew by 13.5% and the average dynamic degree remained at 0.61%. The transfers between grassland and cultivated land, unused land were more remarkable, which led to the decline of grassland quality and even grassland degradation. Water area maintained a dynamic balance with almost unchanged area, but its dynamic trend was initially increasing and then decreasing. However, the average degradation of land quality in the whole study area is continuously alleviated. These changes were mainly due to the interaction of the LDD processes above, as well as socio-economic and climate change. Among them，agricultural research investments could restrain the unordered expansion of cultivated land resource for a relatively short period of time. Meanwhile, the variable of whether it is the main grain producing county is the main driver of grassland and water resource degradation in this region. These conclusions will provide scientific references for ecological land restoration and land quality improvement in the HRB.

Forestland dynamics can affect the ecological security of a country and even the global environment, and therefore it is of great practical significance to understand the characteristics of temporal and spatial variations of forestland. Taking Jiangxi Province as the study area, this study first explored the driving mechanism of the natural environment and social economy on deforestation and afforestation using a simultaneous equation model. The results indicate that population size, topographic and geomorphologic factors, climate, and location play leading roles in influencing forestland density fluctuations. Specifically, the population size, economic development level, gross value of forestry production, climate conditions, and government policies are key influencing factors of afforestation. Deforestation is mainly influenced by agricultural population, non-agricultural economy, forestry production, forestry density, location, transportation, and climate. In addition, this study simulated the spatial distribution of land use and analyzed the spatial characteristics and variation trends of forestland area and quality under the Representative Concentration Pathways (RCPs) climate scenarios from 2010 to 2030 using the Conversion of Land Use and its Effects (CLUE) model. The results indicate that forestland declines under the Asia-Pacific integrated model (AIM) climate scenario. The environment tends to be heavily damaged under this kind of scenarios, and measures should be taken in order to protect the environment. Although the model for energy supply strategy alternatives and their general environmental impact (MESSAGE) scenario is to some extent better than the AIM scenario, destruction of the environment will still occur, and it is necessary to restrain deforestation and convert shrub land into forestland or garden land. These results can provide significant information for environmental protection, forest resource exploitation, and utilization in the areas experiencing deforestation and afforestation.

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

Food safety and its related influencing factors in China are the hot research topics currently, and cultivated land conversion is one of the significant factors influencing food safety in China. Taking the North China Plain as the study area, this paper examines the changes of cultivated land area using satellite images, estimates land productivity from 1985 to 2005 using the model of Estimation System for Land Productivity (ESLP), and analyzes the impact of cultivated land conversion on the land production. Compared with the grain yield data from statistical yearbooks, the results indicate that ESLP model is an effective tool for estimating land productivity. Land productivity in the North China Plain showed a slight decreasing trend from 1985 to 2005, spatially, increased from the north to the south gradu- ally, and the net changes varied in different areas. Cultivated land area recorded a marginal decrease of 8.0 × 10 5 ha, mainly converted to other land uses. Cultivated land conversion had more significant negative impacts on land produc- tion than land productivity did. Land production decreased by about 6.48 × 10 6 t caused by cultivated land conversion between 1985 and 2005, accounting for 91.9% of the total land production reduction. Although the land productivity increased in Anhui and Jiangsu provinces, it can not offset the overall adverse effects caused by cultivated land con- version. Therefore, there are significant meanings to control the cultivated land conversion and improve the land pro- ductivity for ensuring the land production in the North China Plain.

With the economic development and population growth, humans have changed ecosystems more rapidly and extensively to meet the rapidly growing demand for food, fresh water, timber, fiber and fuel. This has led to a substantial and largely irreversible loss of the biodiversity on earth. The ecosystem risk is created as a new concept to understand the environmental problems. Therefore, it is important to develop quantitative methods for regional ecosystem risk analysis. Yellow River Delta is the widest, most intact and youngest delta both in China and in the world; its ecosystem environment is much more vulnerable due to its special location and industrial structure. Therefore, it is very important to manage them wisely and strategically. Therefore, Yellow River Delta is selected as the case area to reveal the impacts of economic development on ecosystem risk in this study. This study selected the ecological quality index to show the potential ecosystem risk and estimated the impacts of economic development on ecosystem risk using the panel data model on the pixel level based on the GIS, RS technique. It's found that the economic development will have impacts on the ecological environment to a certain degree, however, these impacts can exchange to a greater degree with the development. Then more funds and advanced technologies can be used to promote the intensive development of land use, which may decrease the impacts of economic development on the environment. Therefore, we need to ensure the coordinated development of the economy and ecological environment. The research results provide meaningful decision-making information for the urbanization process and environmental protection in the Yellow River Delta.

There is plenty of forests in Northeast China which contributes a lot to the conservation of water and land resources, produces timber products, and provides habitats for a huge number of wild animals and plants. With changes of socio-economic factors as well as the geophysical conditions, there are dramatic changes on the spatial patterns of forest area. In this sense, it is of great significance to shed light on the dynamics of forest area changes to find the underlining reasons for shaping the changing patterns of forest area in Northeast China. To explore the dynamics of forest area change in Northeast China, an econometric model is developed which is composed of three equations identifying forestry production, conversion from open forest to closed forest and conversion from other land uses to closed forest so as to explore the impacts on the forest area changes from demographic, social, economic, location and geophysical factors. On this basis, we employ the Dynamics of Land System (DLS) model to simulate land-use conversions between forest area and non-forest cover and the land-use conversions within the sub-classes of forest area for the period 2000-2020 under business as usual scenario, environmental protection scenario and economic growth scenario. The simulation results show that forest area will expand continuously and there exist various kinds of changing patterns for the sub-classes of forest area, for example, closed forest will expand continuously and open forest and shrub will decrease a little bit, while area of other forest will keep intact. The research results provide meaningful decision-making information for conserving and exploiting the forest resources and making out the planning for forestry production in the Northeast China region.

In climate modeling, land use data is applied as underlying surfaces and definitively determines the simulation results of regional climate. Researches show that Land Use and Cover Change (LUCC) not only affects the terrestrial ecosystem biodiversity, energy balance, water cycle, but also exerts influence on climate and social economy (Berg et al. 2010; Liu and Diamond 2005). Besides, LUCC is a significant performance of material and energy interactions between human and global environment.

1 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing 100101, China 2Department of Geography, Delhi School of Economics, University of Delhi, Delhi 110007, India 3School of Soil and Water Conservation, Beijing Forestry University, Beijing 100038, China 4Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA 5Department of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Boca Raton, FL 33431-0991, USA

The purpose of this paper is to illustrate a modelling framework to simulate large-scale land use changes, and its effect on the structural and functional diversity of the ecosystem and social-economy based on the remotely sensed digital images. The improved DLS model is developed with three scenarios in China from 2001 to 2020. The projection results show that obvious land use changes will take place in the forestry area, grassland, cultivated land and unused land. Dramatic changes will appear in Cultivated area in Northeast China, Huang-Huai-Hai plain and Southwest China. The changes of forestry area are characterized by regional diversification. Grassland decreases mainly along the Great Wall of Inner Mongolia and on Tibets Plateau. The newly expanded urban land, comparably smaller, distributes mainly around the old towns or residential centers. There is no obvious change in water area. The unused area shrinks with the expansion of forest and grass area in Western China. Based on this study, the capability of improved DLS modelling framework in projecting the LUCC scenarios was tested successfully, and a conclusion was made that DLS model is an useful model in scenario construction.

The purpose of this study is to examine the conversions of forests in Northeast China during 1988-2005 by using a 1-km area percentage data model (1-km APDM) with remote sensing data and to find the spatiotemporal characteristics of land conversions between forests and other land uses/covers and internal conversions between forest cover types. Data were derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) images of bands 3, 5, and 4 acquired in 1988, 1995, 2000, and 2005. Research results show that in the period between 1988 and 2005, the forest area in Northeast China underwent dramatic changes, and 4.11 million ha of forest area was aggregately lost because of the conversions of forests to other land uses/covers; at the same time, the forest area also gained 2.00 million ha because of the conversions from other land uses/covers to forests. The results also demonstrate the forest degradation resulting from the conversions between different forest cover types. This research demonstrates the feasibility and importance of using the 1-km APDM at a finer resolution to trace the spatiotemporal patterns of the forest conversions.