Comparison between remote-sensing-based drought indices in East Java

3rd International Symposium on LAPAN-IPB Satellite For Food Security and Environmental Monitoring 2016

地球科学;轻工业;生态环境科学

Amalo, Luisa Febrina^1 ; Hidayat, Rahmat^2 ; Haris^3

Center for Environmental Research, Bogor Agricultural University (PPLH-LPPM), Bogor

16680, Indonesia^1

Department of Geophysics and Meteorology, Bogor Agricultural University, Bogor

16680, Indonesia^2

Gowa College of Agriculture (STTP), Gowa, Indonesia^3

关键词: Agricultural crops;    Drought conditions;    Drought indices;    Drought monitoring;    High temperature;    Land degradation;    Natural hazard;    Remote sensing data;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/54/1/012009/pdf
DOI  :  10.1088/1755-1315/54/1/012009

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Drought is natural hazard which has causing several impacts, such as decreasing of air and water quality, land degradation, forest fire, decreasing of agricultural crops production. Drought assessment using drought indices have widely conducted for drought monitoring. Remote-sensing-based indices defined as an index which using remote sensing data for mapping the drought condition in particular area or region. This research aims to compare remote-sensing-based drought indices, namely TCI, VCI and VHI to obtain a better understanding about the differentiation between each index, and their application for monitoring drought in East Java on El Nino year 2015. LST and EVI data were used to construct the indices. The result showed, each index proved to be useful, quick, sufficient and inexpensive tool for drought monitoring. However, each index has its differences. TCI proved to be detected drought sensitively in dry season or months when high temperature occurred. While VCI detected drought more sensitive in wet season as well (December-January-February to May) than TCI and VHI. Meanwhile, VHI which the enhancement of TCI and VHI has combined two indicators to provide better comprehension about drought occurrence.