Siberia is an important sensitive area with regard to global environmental change. Due to the limited availability of high resolution remote sensing data, previously there was a general lack of in-depth understanding of land cover and change in Siberia. Based on the land cover classification of China's 30 m global land cover (GLC) data product (GlobeLand30) in 2000 and 2010, this study analyzed the progress of land cover change in Siberia between 2000 and 2010 using spatial statistical method and land cover type transition matrix. Land cover changes in Siberia showed significant spatial and temporal variations between 2000 and 2010. Overall, the area that experienced most clear land cover change was west Siberia. The area of forests and grasslands decreased substantially and the change mainly took place in the traditional forest industry regions. The total area of wetland significantly increased and this change occurred mainly in the River Ob and Yenisei in west Siberia. Cultivated land decreased slightly mainly in the traditional agricultural region of the southwest. Built-up areas expanded rapidly, which mainly distributed in cities along the Trans-Siberian Railway. Land cover change in Siberia showed distinct temporal and spatial disparities primarily due to two reasons: industrial development and climate warming..
：Land use form of rural settlements transformed profoundly in the process of rapid industrialization and urbanization in China. By selecting seven rural settlements of different geomorphic types in the Aluke'rqin Banner located in the farming-pastoral transitional zone in Inner Mongolia and examining land use change through a survey, we discuss the relationship between morphological features of the rural settlements and farmers’ livelihood. Participatory rural appraisal method and geographic information system and remote sensing techniques were employed in the survey and analysis. The results show that: (1) Morphological features of rural settlements were closely related to livelihood of rural households, especially with regard to the quantity and quality of cultivated land and grassland and livelihood activities. Along with the increase of population, conversion of grassland to cultivated land, and diversification of rural household livelihood activities, rural pastoral settlements transformed into agro-pastoral settlements. (2) Land use types of agro-pastoral settlements were gradually diversified through time. Before the Reform and Opening-up of China in 1978, agricultural production was the dominant livelihood activity of rural households. Homestead was the primary land use type of rural settlements. After the Reform and Opening-up, however, livelihood activities of rural households gradually diversified and became increasingly non-agricultural. Commercial land, industrial warehousing land, and land for public service provision expanded rapidly in the rural settlements. (3) Homestead takes a significant share in agro-pastoral settlements. Cropping and animal husbandry are important productive activities for rural households. Corresponding to the livelihood demands of rural households,within the settlements homesteads are divided into production and ancillary production lands including colony house, vegetable garden, and warehouse in rural households. Both per capital construction land and homestead area in the case study settlements are larger than the national standard, which indicates an adaptive land use in response to the livelihood demands of the agro-pastoral resettlements. Therefore, the authors recommend that the governments should take concrete measures in the process of rural residential land consolidation that take into consideration the livelihood demands of rural households in this particular area.
The Jiangsu muddy coastal zone is one of the key bases of cropland complementary resources in China. In 2009, the Chinese government approved the development plan of the Jiangsu coastal zone, wherein the tidal flat will be reclaimed and developed into new farmland. Potential land productivity in the coastal area can reflect its capacity to supply food for the country, and is the basis for maintaining the sustainability of the regional agricultural production. There exist various potential land productivity models in China and worldwide. Models based on the process of crop physiology and ecology were used at the field scale, such as the Crop-Environment Resource Synthesis System (CERES) and World Food Studies (WOFOST). Land productivity models based on light, temperature, precipitation, and soil properties—the Classification and Evaluation Techniques of Farmland and Evaluation System of Land Productivity (ESLP)—have been used in China. However, the soil validation coefficients in these two models are based on the evaluation of soil quality and did not consider the relationship between crop yields and soil properties. This article takes the reclamation zones in Rudong County, Jiangsu Province as a case study and attempts to improve the soil validation coefficient in potential land productivity models. It incorporates the percentage of soil fertility contribution (PSFC) and soil salinity factor as soil validation coefficients into the model of potential land productivity to reflect the quality of land. We used the field survey data on rice and wheat yields to verify the feasibility of the potential land productivity model in the coastal area of China. The results show that the PSFC of rice production in the Jiangsu coastal area was about 55%~59%. The PSFC of wheat production in the study area was 50%~80%. The rice and wheat production in the reclamation zones in 1951 and 1974 was not affected by soil salinity because the soils in these reclamation zones were not saline. The rice and wheat production in the reclamation zones in 1982 and 2007 were influenced by soil salinity. The salinity factors of rice and wheat production in the reclamation zones in 1982 were 0.73 and 1.00, respectively. The salinity factors of rice and wheat production in the reclamation zones in 2007 were 0 and 0.35. In 2007 the soil in the reclamation zone was no longer suitable for growing rice paddy. The rice and wheat potential productivity corrected by PSFC in the un-desalinized reclamation zones in 1982 were 12235.84 and 6502.23 kg/hm2. The rice and wheat potential productivity corrected by soil salinity in the un-desalinized reclamation zones in 1982 were 15677.42 and 10329.39 kg/hm2. The rice and wheat potential productivity corrected by PSFC and soil salinity in the un-desalinized reclamation zones in 1982 were 8934.97 and 6502.23 kg/hm2. The actual field yields of rice and wheat (9750 and 6000 kg/hm2) are consistent with the potential productivity corrected by PSFC and soil salinity, and is far less than the potential productivity corrected by soil salinity. Improved fertilization can increase land production. The result of this research can be useful for evaluating newly reclaimed farmland resources and for calculating crop production in the coastal reclamation zones.
：The Qinghai-Tibet Plateau is a hotspot area for global climate change research and a key area for ecological protection in China. Land cover change research in this area can significantly contribute to optimizingland use pattern and improving ecological services and natural conditions of the region. Among various methods for land cover change detection, linear spectral unmixing (LSU) is an effective approach to monitor land cover change by using remote sensing technology. In this study, we chose Naidong County in Tibet as the study area and adopted the linear spectral unmixing technology to detect the ratio of vegetation, bare soil, and rock for each pixel of three Landsat TM/ETM images from 1988, 2000, and 2010. The vegetation component of the result was compared with NDVI. The results show that: (1) The study area has high proportion of mixed pixels, and LSU can deal with the complex features of land cover changes effectively. (2) The proportion of bare soil reduced evidently while rock and vegetation coverage increased from1988 to 2010. It proves that vegetation cover had recovered to some degree while rocky desertification expanded rapidly. (3) Through comparing the vegetation component with NDVI we conclude that LSU is applicable for the identification of land cover change of the Qinghai-Tibet Plateau.
Using the 3S (RS, GIS, GPS) technologies, quantitative analysis method of landscape patterns, and the 30 m resolution land use/land cover data, this study examines the spatiotemporal characteristics of land use/land cover change in the grassland restoration areas in China from 2000 to 2010. We apply two parameters land use transfer matrix and land use dynamic degree to explore the speed and regional differentiation of land use change. This study analyzes the characteristics of landscape patterns at the class and landscape levels in the study area and explores the ecological effect of land use pattern and regional ecological processes. The results show that: (1) Grassland, woodland, wetland, farmland, tificial surface, and others were the main landscape types in the study area in the past decade. The ecosystem structure was stable. About 0.37% of the total grassland area in 2000 experienced change in land use/land cover types. The area of woodlands, wetlands, farmlands, and tificial surface expanded. The area of "others" has declined. (2) The dynamic degree of regional land use was less than one percent in the recent ten years. The speed of land use and land cover change was low, and regional differentiation of change between the provinces was small. (3) The matrix of the landscape did not change in the study area. Landscape fragmentation index values decreased progressively; landscape diversity rose continuously; landscape aggregation and continuity decreased slightly; the landscape maintained relative integrity. The grassland restoration program implementation evidently improved the structure and stability of the land use / land cover.
Satellite remote sensing is an important technique for cropland resources survey, while time series of remote sensing images, particularly, are of great practical significance for cropland extraction. Optical remote sensing imagery is largely affected by illumination and atmospheric conditions, which limits available satellite images within a year, especially where cloudy or rainy weather frequently occurs. Synthetic Aperture Radar (SAR), on the other hand, is able to acquire data throughout the day under any weather condition. However, owing to the influence of speckle noise, very little work has been done to use SAR image time series for feature extraction. This study examines the applicability of SAR image time series for cropland extraction, and Xuzhou City in Jiangsu Province was chosen as the study area. A total of 11 ENVISAT ASAR images covering the study area and dated from December 2009 to December 2010 were selected to establish a SAR time series as experimental data. Thirty cropland sampling regions with the size of 5 pixels × 5 pixels were visually chosen to calculate the consistency of cropland backscatter signatures in the temporal domain, at both neighboring location (inside each sampling region) and remote location (beyond the sampling regions). Euclidean distance method, correlation method, and dynamic time warp (DTW) method were then adopted to extract cropland pixels in the study area. The experiment results show high backscattering consistency for neighboring cropland pixels, with a coefficient of variation of 9.96%. A lower but still satisfactory backscattering consistency was derived by remote cropland pixels in the study area, with a coefficient of variation of 15.27%. Despite the inherent speckle noises of SAR data, the general characteristics of time series for cropland backscatter coefficient correspond well with crop calendar. For the three selected methods, correlation method performed best, which produced a correctness of 86.25% and completeness of 80.70%. Euclidean method took the second place, with a correctness of 76.40% and a completeness of 71.93%. DTW achieved the lowest accuracy, with a correctness of 62.15% and completeness of 77.78%. This research shows that as a new data organizing form, time series of SAR images can be used for cropland extraction effectively.