Accurate Quantification of Grassland Cover Density in an Alpine Meadow Soil Based on Remote Sensing and GPS
Accurate Quantification of Grassland Cover Density in an Alpine Meadow Soil Based on Remote Sensing and GPS作者机构：Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 （China） Graduate School of Chinese Academy of Sciences Beijing 100039 （China）
出 版 物：《Pedosphere》 (土壤圈（英文版）)
年 卷 期：2005年第15卷第6期
页 面：778-783页
核心收录：
学科分类：07[理学] 0818[工学-地质资源与地质工程] 0903[农学-农业资源与环境] 0901[农学-作物学] 0713[理学-生态学]
主 题：alpine meadow soil grassland cover density quantitative remote sensing Qinghai Lake
摘 要：The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems (GPS). An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship (r2 = 0.745) between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.
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