Predicting Surface Soil Organic Matter Contents with Remote Sensing Images in Mining Areas

ZENG Yuan-wen; CHEN Fu; WANG Yu-chen; ZHANG Shao-liang

您当前的位置：

首页 >

文章列表页 >

Predicting Surface Soil Organic Matter Contents with Remote Sensing Images in Mining Areas

- Predicting Surface Soil Organic Matter Contents with Remote Sensing Images in Mining Areas
- Bulletin of Soiland Water Conservation Vol. 32, Issue 2, Pages: 169-172(2013)
- 作者机构：
  
  中国矿业大学江苏省资源环境信息工程重点实验室,江苏,徐州,221116
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
ZENG Yuan-wen, CHEN Fu, WANG Yu-chen, et al. Predicting Surface Soil Organic Matter Contents with Remote Sensing Images in Mining Areas[J]. Bulletin of Soiland Water Conservation, 2013, 32(2): 169-172.
DOI：

ZENG Yuan-wen, CHEN Fu, WANG Yu-chen, et al. Predicting Surface Soil Organic Matter Contents with Remote Sensing Images in Mining Areas[J]. Bulletin of Soiland Water Conservation, 2013, 32(2): 169-172. DOI：

摘要

利用LandSat ETM+影像反演煤炭开采区表层土壤有机质含量的空间格局

对采样点各波段光谱反射率进行数学变换

并将所得结果与有机质含量进行相关性分析。挑选出敏感波段

建立了表层土壤有机质含量的光谱预测模型。结果表明

研究区表层土壤有机质含量与第5波段和第7波段反射率呈极显著的负相关关系(R分别为-0.585和-0.543

0.001);对反射率进行数学变换可以改善其与有机质之间的相关性;用第1波段反射率对数的倒数和第5波段反射率的倒数建立二元回归方程(R

=0.616 2

0.001)对研究区土壤有机质有很好的预测能力(R

=0.616 2

RMSE=0.89);有机质含量在10～15g/kg范围的图斑面积最大

占研究区总面积的50.44%;表层土壤有机质随开采沉陷坡度的增加呈减少的趋势;煤炭开采沉陷对表层土壤有机质含量的扰动属于失碳效应。

Abstract

Remotely sensed multispectral Landsat ETM+images were used to analyze the spatial pattern ofsurface soil organic matter across the coal mining area.Through the correlation analysis between organicmatter contents and ETM+ reflectance variations

wave bands sensitive to organic matter were selected

which were used to establish a prediction model of surface soil organic matter.It was shown that the surfacesoil organic matter contents in study area strongly negatively correlated with the reflectance values of ETM+5and ETM+7(R=-0.585and-0.543

p<0.001).The regression model were developed with the reciprocal of the log-transformed reflectance of ETM+3and the reciprocal of the reflectance of ETM+5(R2=0.616 2

p<0.001)

which predicted the spatial pattern of surface soil organic matter with acceptable accuracy(R2=0.616 2

RMSE=0.89).The area of 10～15g/kg organic matter contents accounted for 50.44%of the totalarea of study site.Surface soil organic matter decreased with the increasing subsidence slope of mining

andthe disturbing effect imposed by the mining activities is a carbon losing effect.

关键词

Keywords

references

Views

1353

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Spatiotemporal variation trends and driving factors of fractional vegetation cover in Jiangsu Province from 2013 to 2022

Using TM to Monitor the Desertification in West China

Remote Sensing Classification Method of Slope Field in Loess Hilly and Gully Area of Northern Shaanxi Province

Supervise of Eco-environmental Change Based on RS Methods and Causal Analysis in Maduo County in Upriver Regions of the Yellow River

Analysis of Soil Erosion Tendency in the Liaohe River Basin Using Remote Sensing and GIS

Related Author

Zhu Ji

Deng Furong

Zhao Chenxu

Liu Xingran

WEI Ya-xing

WANG Li-wen

WANG Yi-mou

LIU Yong-mei

Related Institution

Hebei International Joint Research Center for Remote Sensing of Agricultural Drought Monitoring/School of Land Science and Space Planning， Hebei GEO University

Department of Graduate Student, Changan University, Xian

Department of Environment and Engineering, Changan University, Xian

Department of Geoscience and Country’s Resource, Changan University, Xian

Institute of Hydrology and Water Resources, Tsinghua University

⁰