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  SENSLAND LAB
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Cropland abandonment

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Fallow fileds in Wisconsin, 2019
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Abandoned fields in Uzbekistan, 2014
Cropland abandonment is a prominent form of land use change and an important indicator of economic growth and stability. Further, the unused lands may provide opportunities for conservation and carbon storage. However, cropland abandonment is often confused with other land use such as fallow, and thus is not routinely mapped with remote sensing. We aim to create cropland abandonment maps that have high precision in time and location. Better maps (i.e. with greater resolution) will help improve our understanding of the drivers that lead to cropland abandonment and are a crucial component for planning sustainable landscapes.

Related publications:
Yin, H. de Oliveira Brandao Jr., A. Buchner, B. Helmers, D. Luliano, B. G. Kimambo, N. Lewińska, K. E. Razenkova, E. Rizayeva, A. Rogova, N. Spawn, S. A. Xie, Y. H. and Radeloff, V. C. (2020): Monitoring cropland abandonment with Landsat time series. Remote Sensing of Environment. 246: 111873
​Yin, H. Butsic, V. Buchner, J. Kuemmerle, T. Prishchepov, A. Baumann, M. Bragina, E. Sayadyan, H. and Radeloff, V. (2019): Agricultural abandonment and re-cultivation during and after the Chechen Wars in the northern Caucasus. Global Environmental Change. 55: 149-159
Yin, H. Prishchepov, A. Kuemmerle, T. Bleyhl, B. Buchner, J. and Radeloff, V. (2018): Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series. Remote Sensing of Environment. 210: 12-24​

Grassland management

Grasslands, among the largest ecosystems in the world, provide valuable ecosystem services and harbor unique biodiversity. One important question for both land use management and agricultural policy is whether grasslands are used, and especially if they are mowed. However, mapping grassland use is challenging because it is highly dynamic over space and time, requiring dense time series of satellite imagery. With both Landsat and Sentinel-2 data being available, it is now possible to analyze dense time series of satellite imagery for grassland mapping. This project aims to develop approaches for detecting mowing events in grassland using a combined time series of Landsat and Sentinel-2 imagery.
The Sentinel-2 imagery showing grassland dynamics in France
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The enhanced vegetation index time series showing mowing events
Related publications:
Yin, H. Griffiths, P. Hoster, P and Radeloff, V. C. (in preparation): Mapping grassland use with Landsat and Sentinel-2 time series.

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