Web-service-based Monitoring and Analysis of Global Agricultural Drought

Deng, Minghua; Di, Liping; Han, Weiguo; Yagci, Ali Levent; Peng, Chunming; Heo, Gil

doi:10.14358/pers.79.10.929

Cited by 56 publications

(18 citation statements)

References 28 publications

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“…Accordingly, a threshold of −1 was used for SPI-3, with values below the threshold representing moderate to extreme drought conditions. With respect to VCI, Kogan [57] proposed a threshold of 35% for identifying drought conditions, which has widely been adopted by the drought monitoring community [18,58]. Related to this, we applied the drought classification stated by Klisch and Atzberger [59] for VCI (see Table 2), in which the 35% threshold indicates moderate to extreme drought conditions.…”

Section: Detection Of Agriculturally Relevant Droughtsmentioning

confidence: 99%

“…Numerous studies and approaches dealing with remote sensing-based drought monitoring and with a focus on the African continent have been published. In this connection, operational approaches on global-and continental-scale drought monitoring [6,[17][18][19][20] as well as remote sensing-based studies on droughts in Africa focussing on selected regions and/or periods are to be mentioned. Here, topics of current interest are the ongoing debate on the Sahelian "greening" [21][22][23], drought during 2010/2011 in the Horn of Africa [13,[24][25][26], rainfall and vegetation-related drought dynamics in southern Africa [27][28][29][30], continental-scale drought assessment [12,31,32] as well as the relation between droughts in Africa and ENSO [9,[33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

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Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

2017

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Droughts are amongst the most destructive natural disasters in the world. In large regions of Africa, where water is a limiting factor and people strongly rely on rain-fed agriculture, droughts have frequently led to crop failure, food shortages and even humanitarian crises. In eastern and southern Africa, major drought episodes have been linked to El Niño-Southern Oscillation (ENSO) events. In this context and with limited in-situ data available, remote sensing provides valuable opportunities for continent-wide assessment of droughts with high spatial and temporal resolutions. This study aimed to monitor agriculturally relevant droughts over Africa between 2000–2016 with a specific focus on growing seasons using remote sensing-based drought indices. Special attention was paid to the observation of drought dynamics during major ENSO episodes to illuminate the connection between ENSO and droughts in eastern and southern Africa. We utilized Tropical Rainfall Measuring Mission (TRMM)-based Standardized Precipitation Index (SPI) with 0 . 25 ∘ resolution and Moderate-resolution Imaging Spectroradiometer (MODIS)-derived Vegetation Condition Index (VCI) with 500 m resolution as indices for analysing the spatio-temporal patterns of droughts. We combined the drought indices with information on the timing of site-specific growing seasons derived from MODIS-based multi-annual average of Normalized Difference Vegetation Index (NDVI). We proved the applicability of SPI-3 and VCI as indices for a comprehensive continental-scale monitoring of agriculturally relevant droughts. The years 2009 and 2011 could be revealed as major drought years in eastern Africa, whereas southern Africa was affected by severe droughts in 2003 and 2015/2016. Drought episodes occurred over large parts of southern Africa during strong El Niño events. We observed a mixed drought pattern in eastern Africa, where areas with two growing seasons were frequently affected by droughts during La Niña and zones of unimodal rainfall regimes showed droughts during the onset of El Niño. During La Niña 2010/2011, large parts of cropland areas in Somalia (88%), Sudan (64%) and South Sudan (51%) were affected by severe to extreme droughts during the growing seasons. However, no universal El Niño- or La Niña-related response pattern of droughts could be deduced for the observation period of 16 years. In this regard, we discussed multi-year atmospheric fluctuations and characteristics of ENSO variants as further influences on the interconnection between ENSO and droughts. By utilizing remote sensing-based drought indices focussed on agricultural zones and periods, this study attempts to contribute to a better understanding of spatio-temporal patterns of droughts affecting agriculture in Africa, which can be essential for implementing strategies of drought hazard mitigation.

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Section: Detection Of Agriculturally Relevant Droughtsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

2017

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“…A system for drought monitoring and prediction can be a vital tool to facilitate drought response while saving money, time, and lives [134]. Drought indicators can be based on one variable or a combination of variables.…”

Section: Drought Monitoring and Predictionmentioning

confidence: 99%

Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid Regions

Klemas

Pieterse

2015

The Handbook of Environmental Chemistry

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“…The National Environmental Satellite, Data, and Information Service (NESDIS) provided the weekly global VHI products generated following a method developed by Kogan (1997). Bai and Di (2012) and Deng et al (2013) reported a Global Agricultural Drought Monitoring and Forecasting System (GADMFS) which is a web-based service system developed for researchers and policy-makers. This paper focuses on the design and performance evaluation of a drought monitoring system, DroughtWatch, developed for monitoring drought conditions in China.…”

Section: Introductionmentioning

confidence: 99%

A drought monitoring operational system for China using satellite data: design and evaluation

Niu

Boken

et al. 2014

Geomatics, Natural Hazards and Risk

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Droughts occur frequently in China and their real-time monitoring and timely reporting are required for prevention and mitigation. This paper presents a method for developing an operational drought monitoring system for China. The method is based on various components such as Moderate Resolution Imaging Spectroradiometer data access, data processing, indices calculations, drought monitoring and analysis, and information dissemination. The system was tested by monitoring drought conditions in the early spring of 2009 in the Hai Basin of China. Results were compared with the in situ data-based indices. It was found that the system was capable of monitoring spatial variation in vegetation conditions attributed to droughts. The traditional meteorological drought index and yield data were collected to evaluate the system performance. A stronger relationship was found between the vegetation health index and the three-month standard precipitation index for the rainfed cropped areas. The relationship between the drought-area percentage and the winter wheat yield reduction percentage for 16 counties was stronger for the April-May period than for the February-March period. The drought monitoring system could explain about 60% of the variance in the winter wheat yields.

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Web-service-based Monitoring and Analysis of Global Agricultural Drought

Cited by 56 publications

References 28 publications

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000–2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO

Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid Regions

A drought monitoring operational system for China using satellite data: design and evaluation

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