With the support of MSS images of the middle and late 1970s, TM images of the early 1990s and TM/ETM images of
2004, grassland degradation in the riverhead area of the Yellow River was investigated. The spatial and temporal
characteristics of the grassland degradation were analyzed. The results showed that the grassland degradation patterns
were formed basically in the middle and late 1970s. The grassland degradation is obviously characterized by
fragmentation, coverage decrease, swamp meadow drying, sandification and salification. The spatial heterogeneity of the
type and degree of grassland degradation was significant. Sandification and salification mainly occurred in north-western
alpine steppe, coverage decrease mainly in north central alpine steppe, and fragmentation and coverage decrease mainly
in south-western alpine meadow. The grassland degradation is a continuous change process which has a large influenced
area and is in a long-term scale. Slight and moderate degradation are more common, while serious degradation only
occurs in some local regions. Moderate and serious degradation tend to increase since mid and late 1970s. Large-scale
and moderate-degree degradation and desertification are generally typical characteristics of the grassland degradation in
the riverhead area of the Yellow River.
Northeast China is the national commercial grain base of China. It provides the critical food supply for other areas of the country every year. In this region dramatic changes, such as population increase, deforestation, grass land degeneration, wetland shrinking and so on, have taken place in recent several decades. The changes in resources and environment in this region have significant impacts on human living, social economy and many other aspects of the regional development. In this study uses Remote Sensing (RS), GIS and other information technology to reconstruct a digital Northeast China of the
last 100 years from year 1900 to 2000. This paper first introduces the Digital Northeast China of this 100 years which includes the system targets, data foundation and design frame. Then as a case study, the woodland resource changes after 1980s based on the completed dataset are analyzed. This Digital Northeast China is based on satellite remote sensing images (Landsat TM and ETM) and topology maps and can help people solve problems related to population, natural resources and environment. On the other hand, the Digital Northeast China system can help farmers make wise use of land, increase production and preserve environment simultaneously. Furthermore, using data contained in the system, geographical
scientists can analyze the resource and environment changes and make certain forecasts of the future development.
During the past 20 years, China’s agro-ecosystems have great changes in response to changes in climate and agricultural management. Agricultural productivity is of vital importance to the national food security and sustainable development. So far, agricultural statistics are the only source of the data about changes in agricultural productivity in national scale, and there is little geo-spatial information on these changes. Remote sensing provides an important tool to monitor the spatial and temporal variations at high resolution, but it had yet to used fully at regional and national scales to assess the interannual and long-term changes in agricultural productivity. This study estimated agricultural net primary productivity (ANPP) at the national level using a remote sensing-based production efficiency model, GLO-PEM. In the study, the arable area has been derived from TM data. ANPP was calculated from 8m, 10-day composite Advanced Very High Resolution Radiometers (AVHRR) data from 1981 to 2000 using GLO-PEM model. Using the data we analyzed the spatial variations in agricultural productivity in China between the 1980s and the 1990s. A 3-level hierarchy regionalization system is used in analyzing the spatial pattern and its changes in the agricultural productivity. China’s average agricultural ANPP increased 59.8 million tons from the 1980s to the 1990s. The increment of ANPP mainly occurred in the major cereal-planting plains, especially HuangHuaiHai Plain. The characteristics of land resources are the dominating factors to cause the changes at 10 years scale. There were some decreases, which mainly caused by the degradation on fragile lands, the rapid expansion of rural industries, and the urban development from high-quality arable lands.
Land-Use/Land-Cover Change (LUCC) affects farmland productivity by changing the quality of land resource and pattern of land-use. Based on meteorological data and land-use/cover observation dataset obtained from the dynamic serving system of National Resources and Environment Database (NRED), this paper calculated the Photosynthetic Thermal Productivity (PTP)of farmland, and analyzed impact of recent LUCC and climate fluctuation on PTP. Results showed that under the influence of LUCC, PTP distribution had an extensive and unbalanced change. LUCC increased China’s total PTP by 26.22 million tons,
while climate fluctuation increased it by 169.92 million tons. The ratio between LUCC and climate fluctuation was 1:6.48. Due to the direct effect of LUCC, PTP increased in the following regions: Northeastern Plain, Inner Mongolia, and Xinjiang province. This increase was primarily driven by plantation reclamation. PTP decreased in the Huang-Huai-Hai Plain, the Yangtse Rive delta, the Zhujiang delta, the Southeastern coastal provinces, the southeastern Sichuan basin and the Xinjiang oasis. The decrease was mainly caused by urban expansion.
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