112 research outputs found

    Does Anthropogenic Land Use Change Play a Role in Changes of Precipitation Frequency and Intensity over the Loess Plateau of China?

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    Human transformation of landscapes is pervasive and accelerating across the Earth. However, existing studies have not provided a comprehensive picture of how precipitation frequency and intensity respond to vegetation cover change. Therefore, this study took the Loess Plateau as a typical example, and used satellite-based Normalized Difference Vegetation Index (NDVI) data and daily gridded climatic variables to assess the responses of precipitation dynamics to human-induced vegetation cover change. Results showed that the total precipitation amount exhibited little change at the regional scale, showing an upward but statistically insignificant (p > 0.05) trend of 7.6 mm/decade in the period 1982⁻2015. However, the frequency of precipitation with different intensities showed large variations over most of the Loess Plateau. The number of rainy days (light, moderate, heavy, very heavy and severe precipitation) increased in response to increased vegetation cover, especially in the central-eastern Loess Plateau. Anthropogenic land cover change is largely responsible for precipitation intensity changes. Additionally, this study also observed high spatially explicit heterogeneity in different precipitation intensities in response to vegetation cover change across the Loess Plateau. These findings provide some reference information for our understanding of precipitation frequency and intensity changes in response to regional vegetation cover change in the Loess Plateau

    Introduction to land use and rural sustainability in China

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    Revitalize the world’s countryside

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    Mapping of land degradation from space: A comparative study of Landsat ETM + and ASTER data

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    The purpose of this study is to compare the role of spectral and spatial resolutions in mapping land degradation from space-borne imagery using Landsat ETM + and ASTER data as examples. Land degradation in the form of salinization and waterlogging in Tongyu County, western Jilin Province of northeast China was mapped from an ETM + image of 22 June 2002 and an ASTER image recorded on 24 June 2001 using supervised classification, together with several other land covers. It was found that the mapping accuracy was achieved at 56.8% and higher for moderately degraded (e.g. salinized) farmland, and over 80% for severely degraded land (e.g. barren) from both ASTER and ETM + data. The spatial resolution of the ASTER data exerts only a negligible effect on the mapping accuracy. The 30 m ETM + outperforms the ASTER image of both 15 m and 30 m resolution in consistently generating a higher overall accuracy as well as a higher user's accuracy for barren land. The inferiority of ASTER data is attributed to the highly repetitive spectral content of its six shortwave infrared bands. It is concluded that the spectral resolution of an image is not as important as the information content of individual bands in accurately mapping land covers automatically

    China's land creation project stands firm

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    Analysis of the guarantee degree of irrigation water resources and its spatial difference in Northeast China

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    It is significant for rational and high effective utilization of agricultural water resources and the upgrade of agricultural production capacity. Based on the key factors that influence demand and supply of regional irrigation water resources, the model that is used to calculate the guarantee degree of regional irrigation water resources was developed. And then this model was applied to the area of Northeast China. The result showed that the state of demand and supply of regional irrigation water resources in Northeast China was in equilibrium on the whole and its value of P equaled to 95%. But the supply of irrigation water resources in Northeast China has been on the verge of deficiency. At the same time, a distinct spatial difference of the guarantee degrees of irrigation water resources in Northeast China was found by means of model and map analysis

    Solar power brings money to rural areas

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