Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

Afshar, Mahdi; Al-Yaari, Amen; Yılmaz, M. Tuğrul

doi:10.3390/rs13071251

Cited by 17 publications

(8 citation statements)

References 65 publications

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“…One possibility is the comparison of VIs with meteorological drought indices. It has been shown that the Normalized Difference Vegetation Index (NDVI) and Vegetation Optical Depth (VOD) could capture agricultural drought events in response to meteorological droughts within Europe [27]. In addition, it has been found that meteorological drought indices for shorter periods were associated with crop stress (defined via the Vegetation Condition Index (VCI) and Vegetation Health Index (VHI)), while longer accumulation periods correlated better with the vegetation status of forest areas.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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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Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…Studies have demonstrated the potential of vegetation parameters such as VOD to monitor drought impact on vegetation, particularly on forests (Konings et al, 2021), such as the Amazon in 2005, 2010 and 2015 (Saatchi et al, 2013;Liu et al, 2018;Petchiappan et al, 2022), and on tree mortality (Rao et al, 2019). Over croplands and pastures only very few studies have been performed using coarse resolution data, mostly passive microwave-based VOD (Buitink et al, 2020;Afshar et al, 2021;Likith et al, 2022) or the active microwave-based slope from the backscatter incidence angle relationship (Schroeder et al, 2016;Vreugdenhil et al, 2017;Steele-Dunne et al, 2019;Petchiappan et al, 2022). Most studies investigate satellite observations such as backscatter and brightness temperature directly, or use VOD.…”

Section: Vegetation Indicatorsmentioning

confidence: 99%

“…In general, a two-and threeweek lag was observed between decreasing SM and decreasing VOD and NIRv, respectively. Afshar et al (2021) assessed the potential of SMOS L-VOD (SMOS-IC v2) in comparison to NDVI for monitoring agricultural drought. Here standardized VOD and NDVI for drought and non-drought periods based on a 12-month SPI were compared.…”

Section: Anomaly Approachesmentioning

confidence: 99%

Microwave remote sensing for agricultural drought monitoring: Recent developments and challenges

et al. 2022

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Agricultural droughts are extreme events which are often a result of interplays between multiple hydro-meteorological processes. Therefore, assessing drought occurrence, extent, duration and intensity is complex and requires the combined use of multiple variables, such as temperature, rainfall, soil moisture (SM) and vegetation state. The benefit of using information on SM and vegetation state is that they integrate information on precipitation, temperature and evapotranspiration, making them direct indicators of plant available water and vegetation productivity. Microwave remote sensing enables the retrieval of both SM and vegetation information, and satellite-based SM and vegetation products are available operationally and free of charge on a regional or global scale and daily basis. As a result, microwave remote sensing products play an increasingly important role in drought monitoring applications. Here, we provide an overview of recent developments in using microwave remote sensing for large-scale agricultural drought monitoring. We focus on the intricacy of monitoring the complex process of drought development using multiple variables. First, we give a brief introduction on fundamental concepts of microwave remote sensing together with an overview of recent research, development and applications of drought indicators derived from microwave-based satellite SM and vegetation observations. This is followed by a more detailed overview of the current research gaps and challenges in combining microwave-based SM and vegetation measurements with hydro-meteorological data sets. The potential of using microwave remote sensing for drought monitoring is demonstrated through a case study over Senegal using multiple satellite- and model-based data sets on rainfall, SM, vegetation and combinations thereof. The case study demonstrates the added-value of microwave-based SM and vegetation observations for drought monitoring applications. Finally, we provide an outlook on potential developments and opportunities.

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“…The results showed that droughts occurred almost every year but with varying severity. Afshar et al ( 2021 ) calculated meteorological droughts using SPI in more than 24,000 pixels with a spatial resolution of 0.25 × 0.25 located in Central Europe. They compared the heterogeneous mean values of VIs in dry and wet periods resulting from meteorological droughts statistically to evaluate the ability of VIs in drought conditions.…”

Section: Introductionmentioning

confidence: 99%

Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province

Nejadrekabi

Eslamian

Zareian

2022

Int. J. Environ. Sci. Technol.

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Drought is a major water resources management issue in Iran. Khuzestan Province is in a drought state due to water shortage. Therefore, identifying areas at high risk of drought and when drought occurs is essential for drought management. For this purpose, this study used precipitation and temperature data of 12 selected stations and MODIS sensor images from the United States Geological Survey database in 2000–2017. The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Normalized Difference Vegetation Index (NDVI) were calculated using the Hargreaves–Samani method and ENVI software. Moreover, different spatial statistics techniques were used in the ArcGIS environment to analyze the results. Also, time series diagrams were drawn, and the trend was evaluated using the Mann–Kendall test. Finally, the distribution of NDVI values was investigated using EasyFit software, and the amount of drought damage was determined using NDVI. The investigation of the cluster maps of the Anselin Local Moran’s Index along with hot and cold spots formed for both SPEI and NDVI showed that drought severity was higher at the southern stations than at the semi-northern and northwestern ones in the province. Moreover, the survey results using the EasyFit software showed that the southern stations, including the Ahvaz, Mahshahr, and Omidiyeh-Aghajari stations, were more at risk of drought than the other stations due to the drought threshold. Furthermore, the total damage caused by drought for the Ahvaz and Abadan stations showed a damage rate of 50%.

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Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

Cited by 17 publications

References 65 publications

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

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

Microwave remote sensing for agricultural drought monitoring: Recent developments and challenges

Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province

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