Agricultural Drought Detection with MODIS Based Vegetation Health Indices in Southeast Germany
1
TUM School of Life Sciences, Ecoclimatology, Technical University of Munich, 85354 Freising, Germany
2
Institute for Earth Observation, Eurac Research, 39100 Bolzano-Bozen, Italy
3
Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Won-Ho Nam
Remote Sens. 2021, 13(19), 3907; https://doi.org/10.3390/rs13193907
Received: 15 September 2021
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Revised: 24 September 2021
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Accepted: 25 September 2021
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Published: 30 September 2021
(This article belongs to the Special Issue Drought Monitoring Using Satellite Remote Sensing)
Droughts during the growing season are projected to increase in frequency and severity in Central Europe in the future. Thus, area-wide monitoring of agricultural drought in this region is becoming more and more important. In this context, it is essential to know where and when vegetation growth is primarily water-limited and whether remote sensing-based drought indices can detect agricultural drought in these areas. To answer these questions, we conducted a correlation analysis between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) within the growing season from 2001 to 2020 in Bavaria (Germany) and investigated the relationship with land cover and altitude. In the second step, we applied the drought indices Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI) to primarily water-limited areas and evaluated them with soil moisture and agricultural yield anomalies. We found that, especially in the summer months (July and August), on agricultural land and grassland and below 800 m, NDVI and LST are negatively correlated and thus, water is the primary limiting factor for vegetation growth here. Within these areas and periods, the TCI and VHI correlate strongly with soil moisture and agricultural yield anomalies, suggesting that both indices have the potential to detect agricultural drought in Bavaria.
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Keywords:
NDVI; LST; TCI; VCI; VHI; soil moisture; crop yield; remote sensing; drought monitoring; corn
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MDPI and ACS Style
Kloos, S.; Yuan, Y.; Castelli, M.; Menzel, A. Agricultural Drought Detection with MODIS Based Vegetation Health Indices in Southeast Germany. Remote Sens. 2021, 13, 3907. https://doi.org/10.3390/rs13193907
AMA Style
Kloos S, Yuan Y, Castelli M, Menzel A. Agricultural Drought Detection with MODIS Based Vegetation Health Indices in Southeast Germany. Remote Sensing. 2021; 13(19):3907. https://doi.org/10.3390/rs13193907
Chicago/Turabian StyleKloos, Simon, Ye Yuan, Mariapina Castelli, and Annette Menzel. 2021. "Agricultural Drought Detection with MODIS Based Vegetation Health Indices in Southeast Germany" Remote Sensing 13, no. 19: 3907. https://doi.org/10.3390/rs13193907
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