Next Generation Agricultural Stress Index System (ASIS) for Agricultural Drought Monitoring

Abstract

Over the past 40 years, drought has affected more people in the world than any other natural hazard, affecting large segments of the population and destroying the natural resource base, livestock and livelihoods. Recent projections show that drought events are expected to increase in frequency and intensity due to climate change. According to studies conducted by the Food and Agriculture Organization of the United Nations (FAO), 83% of all damages and losses caused globally by drought between 2006 and 2016 have been absorbed by agriculture, putting a large part of the world’s population at risk of food insecurity. This study shows the advantage of scaling-up FAO’s agricultural drought monitoring and early warning system (ASIS) and building the bridge with the anticipatory action, drought financial mechanisms, social protection and other initiatives for preventing the deterioration of food security and strengthening resilience. The results of the methodology that is based on and supported by the digital innovation, machine learning, matured knowledge and experiences accumulated over the past 10 years are illustrated with practical examples from different countries, ecological environments and crops. A fused time series of Advanced Very-High-Resolution Radiometer (AVHRR) data from Meteorological Operational satellite (METOP) and National Oceanic and Atmospheric Administration (NOAA) was used to produce a consistent time series of a vegetation health index (VHI) at 1 km spatial resolution from 1984 to present. VHI is multiplied by the crop coefficient (kc) to provide more responsiveness to the VHI anomaly that occurs during sensitive phenological phases to water stress such as a flowering and grain filling. The weighted VHI (wVHI) is integrated from the start of the season (SOS) up to the end of season (EOS). Once the temporal analysis of wVHI is completed, the spatial average is calculated using the values of pixels within a specific crop mask and administrative unit. The system proposed different vegetation indices to assess the impact of drought in agriculture; including an agricultural drought forecast that provide more time to the decision makers for implementing anticipatory actions to mitigate the drought in agriculture. Next generation agricultural stress index system (ASIS) offers full capabilities to support: parametric crop insurance, social protection schemes, early action, national drought management plans and to guide public investments.

AI and climate resilience governance

“…Most common application domains associated with “policy appraisal” category are water governance and quality followed by disaster management. These studies conduct policy option analysis by ( Figure 5 ): Evaluating impact of policies in the past : these studies take a backward-looking analysis approach and mainly use machine learning techniques in image processing 26 , 27 , 28 or analyzing socio-economic survey data 29 to evaluate impact of adaptation and risk reduction policies on the physical, social, and economic recovery of communities following a disaster. Evaluating potential impact of policies before their implementation : these studies use either modeling or participatory approach to evaluate and compare potential impacts of different policies.…”

How Well Do EO-Based Food Security Warning Systems for Food Security Agree? Comparison of NDVI-Based Vegetation Anomaly Maps in West Africa

“…These systems are not included in the study because, they either provide incomplete regional coverage, or the remote sensing data they use are shared with the previously mentioned systems. [15], [16] [17], [18] [19], [20] a Cumulative value of NDVI since the Start-Of-Season.…”

“…Coarse-resolution crop monitoring systems are essential for decision-makers, and we are not convinced that vegetation anomaly maps produced at a higher spatial resolution would be better for national or regional crop monitoring as, to cite [20], it is very difficult for a government to take actions at a granular level lower than the district or municipality, such as a farm or commune. The future for EO crop monitoring will certainly include data from the next generation of hyperspectral and thermal satellites with higher spatial resolution and revisit time.…”

Assessing the Probability of Drought Severity in a Homogeneous Region

“…It is a multifaceted phenomenon that periodically fluctuates in many regions worldwide and becomes a cause of negative impacts [5,6]. Its impacts directly or indirectly affect humans' activities more than other natural hazards [3,4,7,8]. Furthermore, it negatively affects vast areas in several ways, such as distressing the region's economy, recreation, water resources, waterfowl, hydroelectric energy, forestry, and other environmental locations [9][10][11].…”