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国产HJ-1B卫星数据的地表温度及湿度反演方法——以呼伦贝尔草原伊敏露天煤矿区为例

赵菲菲 包妮沙 吴立新 孙瑞

自然资源遥感2017,Vol.29Issue(3):1-9,9.
自然资源遥感2017,Vol.29Issue(3):1-9,9.DOI:10.6046/gtzyyg.2017.03.01

国产HJ-1B卫星数据的地表温度及湿度反演方法——以呼伦贝尔草原伊敏露天煤矿区为例

Retrieving land surface temperature and soil moisture from HJ-1B data: A case study of Yimin open-cast coal mine region in Hulunbeier grassland

赵菲菲 1包妮沙 2吴立新 1孙瑞1

作者信息

  • 1. 东北大学测绘遥感与数字矿山研究所,沈阳 110819
  • 2. 北京国测星绘信息技术有限公司,北京 100048
  • 折叠

摘要

Abstract

The soil moisture can be considered as an appropriate indicator to investigate the level of ecological environment disturbance resulting from mining activities in semi-arid grassland.The main objective of this research is to explore the applicability of Chinese HJ-1B data for LST and soil moisture monitoring around mining-affected areas on the local scale.The JM&S, Qin and Artis methods for temperature retrieval were comparatively analyzed.The relationship space of NDVI-LST was used to generate temperature vegetation dryness index(TVDI).Furthermore, the reference data including in situ soil moisture and MODIS LST products were used for "dry edge" correcting of TVDI.Some conclusions have been reached: The Qin's mono-window algorithm performs best in LST retrieval from HJ-1B data;there is a highest correlation between corrected TVDI value with C=0.3 and in situ soil moisture value;the feature of NDVI-LST space indicates that there is a linear relationship for "wet edge", while the relationship for "dry edge" is conic;the TVDI imagery and LST imagery show different drought conditions of different features.The obvious geographical heterogeneity has been found from the TVDI and LST imagery in this area as well.

关键词

国产环境卫星(HJ-1B)/露天煤矿区/干边模型/地表温度(LST)/土壤湿度/温度植被干旱指数(TVDI)

Key words

China HJ-1B satellite/open-cast coal mine region/dry-edge model/land surface temperature(LST)/soil moisture/temperature vegetation dryness index(TVDI)

分类

信息技术与安全科学

引用本文复制引用

赵菲菲,包妮沙,吴立新,孙瑞..国产HJ-1B卫星数据的地表温度及湿度反演方法——以呼伦贝尔草原伊敏露天煤矿区为例[J].自然资源遥感,2017,29(3):1-9,9.

基金项目

国家自然科学基金项目"干旱半干旱草原区露天煤矿土壤光谱特征模型研究"(编号: 4140010440)资助. (编号: 4140010440)

自然资源遥感

OA北大核心CSCDCSTPCD

2097-034X

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