基于直方图与像元分解模型的森林覆盖度遥感估算
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  • 英文篇名:Remote Sensing Estimation of Forest Coverage based on Histogram and Pixel Decomposition Model
  • 作者:董立新
  • 英文作者:Dong Lixin;Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites;National Satellite Meteorological Center;
  • 关键词:森林覆盖度 ; 像元分解模型 ; 直方图法 ; 三峡库区 ; 遥感
  • 英文关键词:Forest coverage;;Pixel decomposition model;;Histogram;;Three Gorges;;Remote sensing
  • 中文刊名:YGJS
  • 英文刊名:Remote Sensing Technology and Application
  • 机构:中国遥感卫星辐射测量与定标重点开放实验室;国家卫星气象中心;
  • 出版日期:2019-02-20
  • 出版单位:遥感技术与应用
  • 年:2019
  • 期:v.34;No.165
  • 基金:国家气候变化专项“气候与CO2浓度变化对高寒植被影响遥感评估”(CCSF-14-06);; 公益性行业专项第三次青藏高原大气科学试验课题“青藏高原卫星反演产品校验外场观测试验与产品改进与资料同化研究”(GYHY201406001-01);; 国务院三峡办项目“三峡工程生态与环境遥感动态与实时监测”(SX2002-004)联合资助
  • 语种:中文;
  • 页:YGJS201901014
  • 页数:11
  • CN:01
  • ISSN:62-1099/TP
  • 分类号:138-147+198
摘要
森林覆盖度是能够勾描出林分边界的森林覆盖率,定量化的覆盖度信息可体现其水平尺度的时空分异特性。像元分解模型在覆盖度遥感估算中得到了广泛应用,但仍然有很多问题,如很难找到一种树冠覆盖度的纯光谱端元,从而难以高精度地估算树冠覆盖度。为此,基于像元分解模型,结合使用土地利用和土壤类型数据,提出利用直方图法确定模型中不同类型植被——土壤端元参数,对区域尺度森林覆盖度进行估算,并利用三峡库区的历史野外161个样点的实测覆盖度数据进行验证,发现R~2达到0.74~0.85,计算结果比较满意。该方法将为区域尺度高分辨率森林覆盖度的遥感估算提供借鉴。
        Forest coverage is the percentage of forest cover for hooking out the forest stand boundary,and quantitative coverage information can be used for describing the temporal and spatial variability of vegetation in the horizontal scale.Pixel decomposition model has been widely used in remote sensing estimation of vegetation coverage.However,there are still many problems.For example,it is difficult to find a pure spectrum of tree canopy coverage to estimate the crown coverage with high accuracy in forest vegetation applications.In this paper,combining land use and soil type data,it is proposed to determine the endmember parameters of the different vegetation-soil types by using the histogram method based on pixel decomposition model for estimating the regional scale forest coverage in the Three Gorges.And the results were verified using the 161 samples of field data in the Three Gorges Reservoir area,R~2 was found to be 0.742 4~0.853 6,the estimated results are satisfactory.This method will provide a reference for remote sensing estimation of high-resolution forest coverage at regional scale.
引文
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