THE BIG PICTURE - SATELLITE REMOTE SENSING APPLICATIONS IN RANGELAND ASSESSMENT AND CROP INSURANCE

Livestock Production/Industries, Risk and Uncertainty,

The potential and uptake of remote sensing in insurance: A review

Global insurance markets are vast and diverse, and may offer many opportunities for remote sensing. To date, however, few operational applications of remote sensing for insurance exist. Papers claiming potential application of remote sensing typically stress the technical possibilities, without considering its contribution to customer value for the insured or to the profitability of the insurance industry. Based on a systematic search of available literature, this review investigates the potential and actual support of remote sensing to the insurance industry. The review reveals that research on remote sensing in classical claim-based insurance described in the literature revolve around crop damage and flood and fire risk assessment. Surprisingly, the use of remote sensing in claim-based insurance appears to be instigated by government rather than the insurance industry. In contrast, insurance companies are offering various index insurance products that are based on remote sensing. For example, remotely sensed index insurance for rangelands and livestock are operational, while various applications in crop index insurance are being considered or under development. The paper discusses these differences and concludes that there is particular scope for application of remote sensing by the insurance industry in index insurance because (1) indices can be constructed that correlate well with what is insured; (2) these indices can be delivered at low cost; and (3) it opens up new markets that are not served by claim-based insurance. The paper finally suggests that limited adoption of remote sensing in insurance results from a lack of mutual understanding and calls for greater cooperation between the insurance industry and the remote sensing community

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

A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data

Index-Based Livestock Insurance has emerged as a promising market-based solution for insuring livestock against drought-related mortality. The objective of this work is to develop an explicit spatial econometric framework to estimate insurable indexes that can be integrated within a general insurance pricing framework. We explore the problem of estimating spatial panel models when there are missing dependent variable observations and cross-sectional dependence, and implement an estimable procedure which employs an iterative method. We also develop an out-of-sample efficient cross-validation mixing method to optimise the degree of index aggregation in the context of spatial index models

Coping strategies and vulnerability to climate change of households in Mali

Variable and low rainfall patterns combined with increasing population pressure have led to natural resources degradation in the Mopti region of Mali. This has forced both agricultural and pastoral communities to transform their production systems and social relations. To assess the adaptive capacities of these agro-pastoral communities to climate change, a participatory survey was conducted in the region between February and May 2009. The survey covered in total 175 households, covering 60 households per agro-ecological zone (i.e. the zones Séno and Gourma), with 15 households per village. In the Delta zone, 55 households were available for the interview. A multiple linear regression analysis was conducted to assess the relationship between household coping strategies and selected factors. The results showed that strategies adapted by agro-pastoral households to cope with climate change vary according to vulnerability factors such as the insufficiency of pastures for livestock, animals’ diseases and death, crop failure caused by erratic rainfall, human sickness, lack of water supply for the livestock, conflicts related to resource use, and several others. The major coping strategies identified were the reduction in the number of animals, storage of crop residues and other gramineous species for livestock, and grain for the population as well as seeking external help. Some major factors were identified to influence strategies of households to cope with climate change. The multiple linear regression analysis showed significant relationship between these influencing factors and coping strategies

Managing resources in erratic environments: an analysis of pastoralist systems in Ethiopia, Niger, and Burkina Faso

This study analyzes the links between risk and the kinds of property rights that have evolved to provide the mobility necessary to raise livestock in drought-prone countries in this case Burkina Faso, Ethiopia, and Niger. The study also evaluates the impact of cooperation on resource management in these environments. The express purpose of this research is to contribute to the current debate on resource management in highly variable environments, focusing on the impact of climate variability on and the role of cooperation in resource management. More specifically, a conceptual framework is developed to analyze the impact of climatic variability and cooperative capacity on land allocation patterns, stock densities, and patterns of herd mobility. Overall, the empirical results suggest that effective policies for sustainable land management and crisis-response plans may require the design and implementation of mechanisms to increase cooperative capacity.Range management Ethiopia, Range management Niger, Range management Burkina Faso, Pastoral systems,

Combining Crop Models and Remote Sensing for Yield Prediction: Concepts, Applications and Challenges for Heterogeneous Smallholder Environments

JRC, CCAFS jointly sponsored the workshop on June 13-14, 2012, at the JRC in Ispra, Italy, to identify avenues for exploiting remote sensing information to improving crop forecasting in smallholder farming environments. The workshop’s objectives were: 1) To advance the state-of-knowledge of data assimilation for crop yield forecasting; 2) To address challenges and needs for successful applications of data assimilation in forecasting crop yields in heterogeneous, smallholder environments; and, 3) To enhance collaboration and exchange of knowledge among data assimilation and crop forecasting groups. The workshop succeeded in bringing together scientists from around the world. This has enabled discussions on research and results and has greatly enhanced collaboration and exchange of knowledge, especially about data assimilation and crop forecasting

Integration of remote sensing, modeling, and field approaches for rangeland management and endangered species conservation in Central Asia

Integration of robust scientific approaches and on-the-ground conservation practice to “bridge the gap” between biologists and field managers is a perennial challenge in biodiversity conservation. In this thesis I present five, related case studies of integrating key scientific approaches (remote sensing techniques, habitat modeling and suitability analysis, and population modeling) with field practices to facilitate sustainable and locally accepted rangeland management, support conservation of snow leopard and Altai argali, and suggest options for tiger restoration in Central Asia. My synthesis of these case studies reveals that to advance regional long-term conservation initiatives, conservation science has to address relevant conservation problem directly, suggest solutions and recommendations that can be implemented by conservation managers given their capacity levels, fit into local knowledge systems as they pertain to the ecosystems under consideration, and focus on sharing lessons learned across projects