Timing is Everything-Drought Classification for Risk Assessment

Drought is one of the most severe natural disasters with a high risk for human livelihoods. Remote sensing based drought indices can identify dry periods using, e.g., precipitation or vegetation information. Besides frequency, duration, and intensity, the timing of a drought onset and duration are i...

Full description

Saved in:
Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing 2020, Vol.13, p.428-433
Main Authors: Graw, Valerie, Ghazaryan, Gohar, Schreier, Jonas, Gonzalez, Javier, Abdel-Hamid, Ayman, Walz, Yvonne, Dall, Karen, Post, Joachim, Jordaan, Andries, Dubovyk, Olena
Format: Article
Language:English
Subjects:
Agriculture
Crop production
Disasters
Drought
Drought index
Drought indices
Duration
Earth Observing System
Economics
Environmental impact
Environmental risk
Extreme drought
Growing season
Indexes
Livelihoods
Natural disasters
phenology
Rain
Rainfall
Regional development
Remote sensing
risk analysis
Risk assessment
Seasons
Socioeconomic aspects
Soil moisture
time series analysis
Timing
Vegetation
Vegetation mapping
weighted linear combination (WLC)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Drought is one of the most severe natural disasters with a high risk for human livelihoods. Remote sensing based drought indices can identify dry periods using, e.g., precipitation or vegetation information. Besides frequency, duration, and intensity, the timing of a drought onset and duration are important variables to measure the drought impact and risk. This article classifies drought events based on the timing of the drought and with regard to their impact on vegetation production during different crop growing stages. Drought and nondrought seasons are analyzed in Eastern Cape Province, South Africa. Here, the impact of a drought on vegetation production highly depends on the starting point and the duration of rainfall during the growing season. Weighted linear combination was applied based on vulnerable vegetation growing stages in the phenology to classify drought severity per season. Particularly the extreme drought season in 2015/2016 as well as the normal nondrought season in 2011/2012 was emphasized. The developed approach serves as input to quantify drought impact per cropping season from local to regional scales. Integration of socio-economic information can further complement this hazard information to support the quantification of the actual drought risk.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2019.2963576