Agricultural Drought Detection with MODIS Based Vegetation Health Indices in Southeast Germany

Abstract

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.

Enhanced trends in spectral greening and climate anomalies across Europe

“…A correlation was performed to detect interdependency between surface reflectance and environmental control mechanisms. Similar approaches have recently been reported, for example, from Bavaria (Kloos et al, 2021) and Central Asia (Peng et al, 2021;Shen et al, 2021).…”

“…However, satellite-based remote sensing observations mostly build on coarse-grained NDVI pixel datasets, which are mixed data composites that can only provide an estimate of the actual land cover, particularly in climate-sensitive areas such as shrubland or tundra (Herrmann & Tappan, 2013 ; Nelson et al, 2022 ). But open-source NDVI time series data are highly suitable for supraregional monitoring of spectral surface reflection variability and allow the linkage to environmental and climate driving factors, such as soil moisture content and water availability (Chen et al, 2019 ; Kloos et al, 2021 ; Li et al, 2021 ; Peng et al, 2021 )—important factors that amplify climate-induced extreme weather events.…”

Can remote sensing enable a Biomass Climate Adaptation Index for agricultural systems?

“…The availability of simultaneous high spatiotemporal resolution remote sensing data is highly desirable for more effectively monitoring and predicting vegetation growth (Ning et al, 2015;Bento et al, 2020;Maselli et al, 2020;Kloos et al, 2021;Measho et al, 2021;Wang et al, 2021). It is now becoming easier to improve the spatiotemporal resolution of remote sensing data using machine learning to enhance vegetation monitoring and prediction capacity (Ferchichi et al, 2022).…”

Evaluating Nature-Based Solution for Flood Reduction in Spercheios River Basin Part 2: Early Experimental Evidence

“…Since it is expressed as a ratio, the NDVI has the advantage of minimizing certain types of noise and influences attributed to variations in irradiance, clouds, cloud shadows, atmospheric attenuation, and other parameters [40]. MODIS NDVI has been used in other studies for drought monitoring [43][44][45].…”

“…Since it is expressed as a ratio, the NDVI has the advantage of minimizing certain types of noise and influences attributed to variations in irradiance, clouds, cloud shadows, atmospheric attenuation, and other parameters [40]. MODIS NDVI has been used in other studies for drought monitoring [43][44][45] To examine NBS's impact on drought NDVI anomalies (difference between the average NDVI for a particular month of a given year and the average NDVI for the same month over the last 20 years), they have been calculated, before and after the NBS deployment on November 2019. For simplicity, we use only the summer months, since the summer season is prone to drought due to the overuse of water resources for irrigation in the area.…”