Application of geospatial and remote sensing data to support locust management

Klein I. Uereyen S. Eisfelder C. Pankov V. Oppelt N. Kuenzer C.
March 2023 Elsevier B.V.

International Journal of Applied Earth Observation and Geoinformation
2023 #117

Negative impacts on agricultural activities by different locust species are well documented and have always been one of the major threats to food security and livelihoods, especially for local communities. Locust management and control have led to less frequent and intense plagues and outbreaks worldwide. However, political insecurity and armed conflicts affect locust management, and can as well as changing climate, and land use management contribute to new outbreaks. In the context of the increasing world population and higher demand for agricultural production, locust pests will remain of high concern. Geospatial and remote sensing data have become an important source of information for different applications within locust research and management. However, there is still a gap between available information and actual practical usage. In this study, we demonstrate the importance of geospatial and remote sensing data and how this information can be prepared for a straightforward application for stakeholders. For this purpose, we use the h3-hexagonal hierarchical geospatial indexing system to simplify and structure spatial information into standardized hexagon units. The presented concept provides decision makers and ground teams with a simplified information database that contains area-wide information over time and space and can be used without detailed geospatial knowledge and background. The concept is designed for the use case of Italian locust management in the Pavlodar region (Kazakhstan) and based on actual practices. It can be extrapolated to any other study area or species of interest. Our results underline the importance of actual land management on locust presence. Up-to-date land management information can be derived from time-series analyses of remote sensing data. Furthermore, essential meteorological data are used to generate locust-specific climatic characteristics within the h3-system. Within this system, areal prioritizing for locust management can be achieved based on the included spatial information and experience from ongoing practices.

Calliptamus italicus , Earth observation , Food security , GIS , Insect pests , Locust , Outbreak , Plague , Remote sensing , Risk assessment

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German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Wessling, 82234, Germany
Pavlodar Regional Branch of SD Republican Methodological Center of Phytosanitary Diagnostics and Forecasts, Pavlodar, 140000, Kazakhstan
Department of Geography, Kiel University, Kiel, 24118, Germany
Julius-Maximilians-Universität Würzburg, Institute of Geography and Geology, 97074 Würzburg, Germany

German Remote Sensing Data Center (DFD)
Pavlodar Regional Branch of SD Republican Methodological Center of Phytosanitary Diagnostics and Forecasts
Department of Geography
Julius-Maximilians-Universität Würzburg

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