自然资源学报 ›› 2013, Vol. 28 ›› Issue (7): 1243-1254.doi: 10.11849/zrzyxb.2013.07.016
包刚1,2,3, 包玉海1, 覃志豪2, 周义2, 黄明祥1,4, 张宏斌3
收稿日期:
2012-07-19
修回日期:
2012-12-06
出版日期:
2013-07-20
发布日期:
2013-07-20
通讯作者:
包玉海(1965-),男,内蒙古科右中旗人,教授,博士,主要从事土地利用/覆盖变化、自然灾害遥感监测与风险评估研究。E-mail:baoyuhai@imnu.edu.cn
E-mail:baoyuhai@imnu.edu.cn
作者简介:
包刚(1978-),男,蒙古族,内蒙古库伦旗人,博士研究生,主要从事遥感与地理信息系统应用研究。E-mail:baogang@imnu.edu.cn
基金资助:
国家重点基础研究发展计划(973计划)项目(2010CB951504);国家自然科学基金项目(41161060);内蒙古自然科学基金项目(2012MS0607);内蒙古师范大学"十百千"人才计划项目。
BAO Gang1,2,3, BAO Yu-hai1, QIN Zhi-hao2, ZHOU Yi2, HUANG Ming-xiang1,4, ZHANG Hong-bin3
Received:
2012-07-19
Revised:
2012-12-06
Online:
2013-07-20
Published:
2013-07-20
摘要:
以北京大学"无人机遥感载荷综合试验场"为试验区,采集草地植被覆盖度(Vegetation Cover, VC)和相应样方冠层高光谱反射率数据,并对比研究了高光谱反射率三种变换形式(小波能量系数、主成分和植被指数)与VC之间的关系模型。结果表明:在三种变换形式中,植被指数模型(R2大于0.8,RMSE小于等于0.018 8)优于基于小波变换和主成分分析的VC模型;经过对高光谱数据进行小波分解获得的第二和第四小波能量系数与VC之间存在显著的对数相关(R2分别为0.811和0813;RMSE分别为0.019 9和0.019 8);以多个小波能量系数作为自变量的VC多元回归模型明显优于基于主成分的多元线性回归,R2和RMSE分别提高0.058和0.030;将高光谱EVI模型与TM-EVI数据相结合生成的试验区VC空间分布总体上呈北部和南部植被覆盖度高(分别>75%和>55%),中部相对低(15%~55%)的特征,与其土地利用/覆被特征相吻合。
中图分类号:
包刚, 包玉海, 覃志豪, 周义, 黄明祥, 张宏斌. 高光谱植被覆盖度遥感估算研究[J]. 自然资源学报, 2013, 28(7): 1243-1254.
BAO Gang, BAO Yu-hai, QIN Zhi-hao, ZHOU Yi, HUANG Ming-xiang, ZHANG Hong-bin. Hyper-spectral Remote Sensing Estimation for the Vegetation Cover[J]. JOURNAL OF NATURAL RESOURCES, 2013, 28(7): 1243-1254.
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