The brightness temperature adjusted dust index: An improved approach to detect dust storms using MODIS imagery

被引:36
|
作者
Yue, Huanbi [1 ,2 ]
He, Chunyang [1 ,2 ]
Zhao, Yuanyuan [3 ]
Ma, Qun [1 ,2 ]
Zhang, Qiaofeng [4 ]
机构
[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, CHESS, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China
[3] Beijing Forestry Univ, Key Lab State Forestry Adm Soil & Water Conservat, Beijing 100083, Peoples R China
[4] Murray State Univ, Dept Geosci, Murray, KY 42071 USA
基金
中国国家自然科学基金;
关键词
Dust storms; MODIS; BADI; Northeast Asia; AEROSOL PROPERTIES; TRANSPORT; IDENTIFICATION; DIFFERENCE; VEGETATION; RETRIEVAL; PRODUCTS; DESERTS; EVENTS; SAHARA;
D O I
10.1016/j.jag.2016.12.016
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Moderate Resolution Imaging Spectroradiometer (MODIS) imagery provides a good data source for timely and accurate monitoring of dust storms. However, effective MODIS-based dust indices are inadequate. In this study, we proposed an improved brightness temperature adjusted dust index (BADI) by integrating the brightness temperatures of three thermal infrared MODIS bands: band(20) (3.66-3.84 mu m), band(31) (10.78-11.28 mu m) and band(32) (11.77-12.27 mu m). We used the BADI to monitor several representative dust storms over the Northeast Asia between 2000 and 2011. When compared to commonly used MODISbased dust indices, such as the brightness temperature difference index in band(32) and band(31) (BTD32-31) and the normalized difference dust index (NDDI), the BADI captured the spatial extent and density of dust storms more accurately. The BADI detected dust storm extent with an overall accuracy >90%, which was 7% and 29% higher than the results derived from BTD32-31 and NDDI, respectively. The BADI also demonstrated good agreement with the density indicator of MODIS Deep Blue Aerosol Optical Depth (R-2=0.59, P <0.01). We suggest that the BADI is an effective tool to monitor large-scale dust storms. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:166 / 176
页数:11
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