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- W2387823997 abstract "Grassland classification is a fundamental need of grassland science.Meanwhile developing a comprehensive grassland classification system is also a challenge for grassland science because of the multivariable and multi-functional feature of grassland system.Comprehensive and Sequential Classification System of Grasslands(CSCS),one of well known grassland classification systems in China,was advanced in quantification indicators.However,the result of basic level classification often does not match well with the actual grassland type.After analysis of this problem,that there were at least two points needed to improve at the basic classification level of CSCS was pointed out.The first one,grasslands were grouped into classes according to indexes of precipitation and temperature,which characterize the near-surface atmosphere hydrothermal conditions instead of the actual habitat of low grass plant.The second one,data of precipitation and temperature coming from ground observation of weather station can only characterize conditions within a small area,but always be extrapolated to be on behalf of feature of the region.The suggestions that planar data of land surface temperature and soil moisture inverted by quantitative remote sensing should be introduced to the basic classification level of CSCS to replace parameters of precipitation and atmosphere temperature from ground observation were proposed." @default.
- W2387823997 created "2016-06-24" @default.
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- W2387823997 date "2012-01-01" @default.
- W2387823997 modified "2023-09-26" @default.
- W2387823997 title "Suggestions for Improvement of Moisture and Temperature Index in Comprehensive and Sequential Classification System of Grasslands Suitable for 3S Technology" @default.
- W2387823997 hasPublicationYear "2012" @default.
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