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Article

Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach

1
Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Genscherallee 3, 53113 Bonn, Germany
2
Remote Sensing Research Group (RSRG), University of Bonn, Meckenheimer Allee 166, 53115 Bonn, Germany
3
Department of Crop Sciences, University of Göttingen, Von-Siebold-Str. 8, 37075 Göttingen, Germany
4
Leibniz Centre for Agricultural Landscape Research (ZALF), Eberswalder Str. 84, 15374 Müncheberg, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(24), 4030; https://doi.org/10.3390/rs12244030
Received: 28 October 2020 / Revised: 30 November 2020 / Accepted: 3 December 2020 / Published: 9 December 2020
(This article belongs to the Special Issue Remote Sensing of Dryland Environment)
Drought is one of the extreme climatic events that has a severe impact on crop production and food supply. Our main goal is to test the suitability of remote sensing-based indices to detect drought impacts on crop production from a global to regional scale. Moderate resolution imaging spectroradiometer (MODIS) based imagery, spanning from 2001 to 2017 was used for this task. This includes the normalized difference vegetation index (NDVI), land surface temperature (LST), and the evaporative stress index (ESI), which is based on the ratio of actual to potential evapotranspiration. These indices were used as indicators of drought-induced vegetation conditions for three main crops: maize, wheat, and soybean. The start and end of the growing season, as observed at 500 m resolution, were used to exclude the time steps that are outside of the growing season. Based on the three indicators, monthly standardized anomalies were estimated, which were used for both analyses of spatiotemporal patterns of drought and the relationship with yield anomalies. Anomalies in the ESI had higher correlations with maize and wheat yield anomalies than other indices, indicating that prolonged periods of low ESI during the growing season are highly correlated with reduced crop yields. All indices could identify past drought events, such as the drought in the USA in 2012, Eastern Africa in 2016–2017, and South Africa in 2015–2016. The results of this study highlight the potential of the use of moderate resolution remote sensing-based indicators combined with phenometrics for drought-induced crop impact monitoring. For several regions, droughts identified using the ESI and LST were more intense than the NDVI-based results. We showed that these indices are relevant for agricultural drought monitoring at both global and regional scales. They can be integrated into drought early warning systems, process-based crop models, as well as can be used for risk assessment and included in advanced decision-support frameworks. View Full-Text
Keywords: drought assessment; land surface temperature; evapotranspiration; yield anomaly; MODIS drought assessment; land surface temperature; evapotranspiration; yield anomaly; MODIS
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MDPI and ACS Style

Ghazaryan, G.; König, S.; Rezaei, E.E.; Siebert, S.; Dubovyk, O. Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach. Remote Sens. 2020, 12, 4030. https://doi.org/10.3390/rs12244030

AMA Style

Ghazaryan G, König S, Rezaei EE, Siebert S, Dubovyk O. Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach. Remote Sensing. 2020; 12(24):4030. https://doi.org/10.3390/rs12244030

Chicago/Turabian Style

Ghazaryan, Gohar, Simon König, Ehsan E. Rezaei, Stefan Siebert, and Olena Dubovyk. 2020. "Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach" Remote Sensing 12, no. 24: 4030. https://doi.org/10.3390/rs12244030

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