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  5. Spatial distribution of arable and abandoned land across former Soviet Union countries

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Article
English
2018

Spatial distribution of arable and abandoned land across former Soviet Union countries

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English
2018
Scientific Data
Vol 5 (1)
DOI: 10.1038/sdata.2018.56

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Dmitry Schepaschenko
Dmitry Schepaschenko

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Myroslava Lesiv
Dmitry Schepaschenko
Elena Moltchanova
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Abstract

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

How to cite this publication

Myroslava Lesiv, Dmitry Schepaschenko, Elena Moltchanova, Rostyslav Bun, Martina Dürauer, Alexander V. Prishchepov, Florian Schierhorn, Stephan Estel, Tobias Kuemmerle, Camilo Alcántara, Nataliia Kussul, Maria Shchepashchenko, O. V. Kutovaya, О. В. Мартыненко, Viktor Karminov, А. Shvidenko, Peter Havlík, Florian Kraxner, Linda See, Steffen Fritz (2018). Spatial distribution of arable and abandoned land across former Soviet Union countries. Scientific Data, 5(1), DOI: 10.1038/sdata.2018.56.

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Publication Details

Type

Article

Year

2018

Authors

20

Datasets

0

Total Files

0

Language

English

Journal

Scientific Data

DOI

10.1038/sdata.2018.56

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