Research and compilation of the Geomorphologic Atlas of the People's Republic of China (1:1,000,000)

National Natural Science Foundation of China [40871177, 40830529]

Spatial and temporal flows of China's forest resources: Development of a framework for evaluating resource efficiency

Science & Technology Basic Work Program of China: Scientific Survey of the Middle-lower Reaches of Lantsang River and the Great Shangri-La Region [2008FY110300]; National Basic Research Program of China (973 Program): Ecosystem Services and Ecological Safety of the Major Terrestrial Ecosystems of China [2009CB421106]; National Natural Science Foundation of China [30670374]; EU ; European Commission, DG Research [003874]

Simulation study of China's net primary production

Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA, GEOPRO). Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process mechanism models of CASA, GLOPEM and CEVSA, the following conclusions could be made: (1) during the last 20 years, NPP change in China followed closely the seasonal change of climate affected by monsoon with an overall trend of increasing; (2) simulated average seasonal NPP was: 0.571 +/- 0.2 GtC in spring, 1.573 +/- 0.4 GtC in summer, 0.6 +/- 0.2 GtC in autumn, and 0.12 +/- 0.1 GtC in winter. Average annual NPP in China was 2.864 +/- 1 GtC. All the five models were able to simulate seasonal and spatial features of biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases.

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

The regional types of China's floating population: Identification methods and spatial patterns

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.

Analysis of arable land loss and its impact on rural sustainability in Southern Jiangsu Province of China

Rapid urbanization and industrialization in southern Jiangsu Province have consumed a huge amount of arable land. Through comparative analysis of land cover maps derived from TM images in 1990, 2000 and 2006, we identified the trend of arable land loss. It is found that most arable land is lost to urbanization and rural settlements development. Urban settlements, rural settlements, and industrial park-mine-transport land increased, respectively, by 87 997 ha (174.65%), 81 041 ha (104.52%), and 12 692 ha (397.99%) from 1990 to 2006. Most of the source (e.g., change from) land covers are rice paddy fields and dryland. These two covers contributed to newly urbanized areas by 37.12% and 73.52% during 1990-2000, and 46.39% and 38.86% during 2000-2006. However, the loss of arable land is weakly correlated with ecological service value, per capita net income of farmers, but positively with grain yield for some counties. Most areas in the study site have a low arable land depletion rate and a high potential for sustainable development. More attention should be directed at those counties that have a high depletion rate but a low potential for sustainable development. Rural settlements should be controlled and rationalized through legislative measures to achieve harmonious development between urban and rural areas, and sustainable development for rural areas with a minimal impact on the ecoenvironment. (C) 2009 Elsevier Ltd. All rights reserved.