Mapping abandoned agricultural land in Kyzyl-Orda,Kazakhstan using satellite remote sensing |
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| Institution: | 1. Department of Remote Sensing, Würzburg University, Am Hubland, 97074 Würzburg, Germany;2. CAREC, Almaty, Kazakhstan;3. University of Bonn, Germany;1. Institute of Landscape Ecology SAS, Akademická 2, 949 01 Nitra, Slovakia;2. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland;3. Institute of Landscape Ecology SAS, Stefánikova 3, 814 99 Bratislava, Slovakia;4. Department of Theoretical Geodesy, Slovak University of Technology, Radlinského 11, 813 68 Bratislava, Slovakia;5. Soil Science and Censervation Research Institute, Gagarinova 10, 827 13 Bratislava, Slovakia;1. Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;2. Geography Department, Ivan Franko University of Lviv, Str. Doroshenka 41, 79000 Lviv, Ukraine;3. Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Department of Structural Development of Farms and Rural Areas, Theodor-Lieser-Str. 2, 06120 Halle (Saale), Germany;4. Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;5. Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, DK-1350 København K, Denmark;6. Institute of Steppe of the Ural Branch of the Russian Academy of Science (RAS), Pionerskaya str. 11, 460000 Orenburg, Russia;1. Institute of Geography and Spatial Management, Jagiellonian University, ul. Gronostajowa 7, 30-387 Krakow, Poland;2. Institute of Forest Resources Management, University of Agriculture in Kraków, al. 29 Listopada 46, 31-425 Kraków, Poland;3. WSL, Swiss Federal Research Institute WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland;1. Institute of Geography, Slovak Academy of Sciences, ?tefánikova 49, Bratislava 814 73, Slovakia;2. Institute of Landscape Ecology, Slovak Academy of Sciences, Akademická 2, Nitra 949 01, Slovakia;1. College of Resources and Environment, Southwest University, Chongqing 400716, China;2. Department of Agricultural and Resource Economics, University of Maryland, College Park, MD, USA;3. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;4. Department Geographical Sciences, University of Maryland, College Park, MD, USA;5. International Institute for Applied Systems Analysis, Laxenburg, Austria;1. Georges Lemaitre Earth and Climate Research Centre, Earth and Life Institute, Université Catholique de Louvain, 1348 Louvain-La-Neuve, Belgium;2. Fonds de la Recherche Scientifique F.R.S.—FNRS, 1000 Brussels, Belgium;3. Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Theodor-Lieser-Strasse 2, 06120 Halle (Saale), Germany;4. Geography Department, Humboldt Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;5. Department of Geosciences and Natural Resources Management, University of Copenhagen, Øster Voldgade 10, 1350 København K, Denmark;6. Institute of Steppe of the Ural Branch of the Russian Academy of Science (RAS), Pionerskaya str. 11, 460000 Orenburg, Russia;7. Integrative Research Institute on Transformations of Human–Environment Systems (IRI THESys), Humboldt Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany |
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| Abstract: | In many regions worldwide, cropland abandonment is growing, which has strong and known environmental and socio-economic consequences. Yet, spatially explicit information on the spatial pattern of abandonment is sparse, particularly in post-Soviet countries of Central Asia. When thriving reaching for key Millennium Development Goals such as food security and poverty reduction, the issue of cropland abandonment is critical and therefore must be monitored and limited, or land use transformed into an alternative one. Central Asia experienced large changes of its agricultural system after the collapse of the Soviet Union in 1991. Land degradation, which started already before independence, and cropland abandonment is growing in extent, but their spatial pattern remains ill-understood. The objective of this study was to map and analyse agricultural land use in the irrigated areas of Kyzyl-Orda, southern Kazakhstan, Central Asia. For mapping land use and identifying abandoned agricultural land, an object-based classification approach was applied. Random forest (RF) and support vector machines (SVM) algorithms permitted classifying Landsat and RapidEye data from 2009 to 2014. Overlaying these maps with information about irrigated land parcels, installed during the Soviet period, allowed indicating abandoned fields. Fusing the results of the two approaches, RF and SVM, resulted in classification accuracies of up to 97%. This was statistically significantly higher than with RF or SVM alone. Through the analysis of the land use trajectories, abandoned agricultural fields and a clear indication of abandoned land were identified on almost 50% of all fields in Kyzyl-Orda with an accuracy of approximately 80%. The outputs of this study may provide valuable information for planners, policy- and decision-makers to support better-informed decision-making like reducing possible environmental impacts of land abandonment, or identifying areas for sustainable intensification or re-cultivation. |
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| Keywords: | Abandoned cropland mapping Central Asia Aral sea Land use trajectories Decision fusion Time-series |
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