A review of satellite-based global agricultural monitoring systems available for Africa

Abstract The increasing frequency and severity of extreme climatic events and their impacts are being realized in many regions of the world, particularly in smallholder crop and livestock production systems in Sub-Saharan Africa (SSA). These events underscore the need for timely early warning. Satellite Earth Observation (EO) availability, rapid developments in methodology to archive and process them through cloud services and advanced computational capabilities, continue to generate new opportunities for providing accurate, reliable, and timely information for decision-makers across multiple cropping systems and for resource-constrained institutions. Today, systems and tools that leverage these developments to provide open access actionable early warning information exist. Some have already been employed by early adopters and are currently operational in selecting national monitoring programs in Angola, Kenya, Rwanda, Tanzania, and Uganda. Despite these capabilities, many governments in SSA still rely on traditional crop monitoring systems, which mainly rely on sparse and long latency in situ reports with little to no integration of EO-derived crop conditions and yield models. This study reviews open-access operational agricultural monitoring systems available for Africa. These systems provide the best-available open-access EO data that countries can readily take advantage of, adapt, adopt, and leverage to augment national systems and make significant leaps (timeliness, spatial coverage and accuracy) of their monitoring programs. Data accessible (vegetation indices, crop masks) in these systems are described showing typical outputs. Examples are provided including crop conditions maps, and damage assessments and how these have integrated into reporting and decision-making. The discussion compares and contrasts the types of data, assessments and products can expect from using these systems. This paper is intended for individuals and organizations seeking to access and use EO to assess crop conditions who might not have the technical skill or computing facilities to process raw data into informational products

A comparison of global agricultural monitoring systems and current gaps

Global and regional scale agricultural monitoring systems aim to provide up-to-date information regarding food production to different actors and decision makers in support of global and national food security. To help reduce price volatility of the kind experienced between 2007 and 2011, a global system of agricultural monitoring systems is needed to ensure the coordinated flow of information in a timely manner for early warning purposes. A number of systems now exist that fill this role. This paper provides an overview of the eight main global and regional scale agricultural monitoring systems currently in operation and compares them based on the input data and models used, the outputs produced and other characteristics such as the role of the analyst, their interaction with other systems and the geographical scale at which they operate. Despite improvements in access to high resolution satellite imagery over the last decade and the use of numerous remote-sensing based products by the different systems, there are still fundamental gaps. Based on a questionnaire, discussions with the system experts and the literature, we present the main gaps in the data and in the methods. Finally, we propose some recommendations for addressing these gaps through ongoing improvements in remote sensing, harnessing new and innovative data streams and the continued sharing of more and more data

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

This review presents the current state of aflatoxin risk prediction models and their potential for value actors throughout the food chain in sub-Saharan Africa, with a specific focus on improving smallholder farmer management practices. Several empirical and mechanistic models have been developed either in academic research or by private sector aggregators and processors in high-income countries including Australia, the USA, and Southern Europe, but these models have been only minimally applied in sub-Saharan Africa, where there is significant potential and increasing need due to climate variability. Predictions can be made based on historic occurrence data using either a mechanistic microbiological framework for aflatoxin accumulation or an empirical model based on statistical correlations with climate conditions and local agronomic factors. Model results can then be distributed to smallholders through private, public, or mobile extension services, used by policymakers for strategy or policy, or utilised by private sector institutions for management decisions. Specific agricultural advice can be given during the three most critical points in the phenological cycle: preseason insight including sowing timing and crop varieties, preharvest advice about management and harvest timing, and postharvest optimal practices including storage, drying, and market information. Model development for sub-Saharan Africa is limited by a dearth of georeferenced aflatoxin occurrence data and real-time high resolution climate data; the wide diversity of farm typologies each with significant information and technology gaps; a prevalence of informal market structures and lack of economic incentives systems; and general lack of awareness around aflatoxins and best management practices to mitigate risk. Given advancements towards solving these challenges, predictive aflatoxin models can be integrated into decision support platforms to focus on optimisation of value for smallholders by minimising yield and nutritional losses, which can propagate value throughout the production and postharvest phases

Development of a national and sub-national crop calendars data set compatible with remote sensing derived land surface phenology

Crop calendars are a fundamental component of agricultural production monitoring systems since they help analysts to focus on the seasons when different crop types are actually growing in the field. The Earth Observation based early warning system ASAP (Anomaly hot Spots of Agricultural Production) uses land surface phenology (LSP) metrics as proxy for crop calendars and applies parameters, such as the start and end of the season (SOS and EOS respectively) to define the period of active agricultural vegetation growth at pixel level. However, such information is not crop specific and it remains therefore relevant to use crop calendars from independent sources providing crop specific key phenological timings, such as sowing, growing and harvesting. Several institutions, including FAO and USDA make available crop calendars at the national level, which are widely used for agricultural monitoring. The LSP derived SOS and EOS metrics can be associated with sowing and harvesting from such crop calendars. This report describes a method for the attribution of each growing season derived from LSP to a crop type listed in existing crop calendars. Based on a set of rules, we compare the growing seasons derived from LSP with the timings of the crop calendars, and select those crops where a match between LSP and crop calendar information is found. Agricultural statistics, including harvested area and production, are used in order to verify the correct identification and relevance of crop types by country. The method also allows to downscale the existing national level crop calendars to the sub-national level. It therefore makes available sub-national level crop calendars, which are highly valuable for crop monitoring at that scale. The resulting crop calendars are available in the ASAP download section: https://mars.jrc.ec.europa.eu/asap/download.phpJRC.D.5-Food Securit

ASAP Water Satisfaction Index

This technical report describes the Water Satisfaction Index model that used in the ASAP (Anomaly hotSpots of Agricultural Production) early warning system.JRC.D.5-Food Securit

Designing AfriCultuReS services to support food security in Africa

ABSTRACT: Earth observation (EO) data are increasingly being used to monitor vegetation and detect plant growth anomalies due to water stress, drought, or pests, as well as to monitor water availability, weather conditions, disaster risks, land use/land cover changes and to evaluate soil degradation. Satellite data are provided regularly by worldwide organizations, covering a wide variety of spatial, temporal and spectral characteristics. In addition, weather, climate and crop growth models provide early estimates of the expected weather and climatic patterns and yield, which can be improved by fusion with EO data. The AfriCultuReS project is capitalizing on the above to contribute towards an integrated agricultural monitoring and early warning system for Africa, supporting decision making in the field of food security. The aim of this article is to present the design of EO services within the project, and how they will support food security in Africa. The services designed cover the users' requirements related to climate, drought, land, livestock, crops, water, and weather. For each category of services, results from one case study are presented. The services will be distributed to the stakeholders and are expected to provide a continuous monitoring framework for early and accurate assessment of factors affecting food security in Africa.This paper is part of the AfriCultuReS project "Enhancing Food Security in African Agricultural Systems with the Support of Remote Sensing", which received funding from the European Union's Horizon 2020 Research and Innovation Framework Programme under grant agreement No. 77465

Quantitative methods for integrated food and nutrition security measurements. Lessons to be learned!

The Joint Research Centre (JRC) of the European Commission and the International Food Policy Research Institute (IFPRI) jointly organized an International Conference on Quantitative Methods for Integrated Food and Nutrition Security Measurements. The conference provided a platform for researchers, academics, professionals and decision-makers to define the state of the art for quantitative measurement of food and nutrition security (F&NS) by identifying the main practical challenges, sharing innovative methods and modelling techniques, and exploring best practices to scale up multi- and cross-sectoral F&NS collaboration and coordination at country, regional and global level. Moreover, in hosting an interdisciplinary forum, the conference offered the opportunity for participants to forge innovative partnerships for the development and promotion of improved methodologies to support evidence-based F&NS policies and decision-makers.JRC.D.5-Food Securit

Quantitative Methods for Integrated Food and Nutrition Security Measurement

Despite the importance of Food and Nutrition Security, great challenges remain to be addressed worldwide to reduce and eradicate hunger and malnutrition. The most recent report on the State of Food Insecurity in the World (2018) stated that, for developing regions taken as a whole, the share of undernourished people in the total population has recently increased in the period 2015-17 to 10.9% compared to its lowest (10.6%) in 2015. Although there has been substantial progress in the last decade, almost 821 million people are still undernourished globally. In part, the inability to tackle the problems relates to the lack of timely and more spatially explicit information to inform decision-making, humanitarian and development initiatives. On the other hand, monitoring progress of policies and actions to combat hunger and malnutrition requires innovative and practical measurements that take into account food and nutrition security (FNS) updated information. The availability of joint measurements for FNS is still low for the great demand of information in this subject. Nonetheless, some efforts have initiated in recent years by researchers and practitioners. Thus, in 2017 the Joint Research Centre (JRC) of the European Commission and the International Food Policy Research Institute (IFPRI) jointly organizing an International Conference on Quantitative Methods for Integrated Food and Nutrition Security Measurements. The conference provided a platform for researchers, academics, professionals and decision makers to define the state of the art for quantitative measurement of food and nutrition security (F&NS). The research work and keynotes presented helped identifying the main practical challenges, innovative methods or modeling techniques, and exploring best practices to scale up multi and cross-sectoral F&NS collaboration and coordination at country, regional and global level. Moreover, in hosting an interdisciplinary forum, the conference offered the opportunity for participants to forge innovative partnerships for the development and promotion of improved methodologies to support evidence-based F&NS policies and decision-making. The conference gathered research work mainly from Africa but also from Asia and included 80 participants from Africa, Asia and Europe. This document summarize the presentations, which included keynotes and research projects, included here according to their order in the program of the conference. Research projects presentations are summarized presenting when possible, their main motivation, methods and results, or else their title and authors for those under publication in scientific journals.JRC.D.5-Food Securit