Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanist...

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Main Authors: Fabian Löw, Alexander V. Prishchepov, François Waldner, Olena Dubovyk, Akmal Akramkhanov, Chandrashekhar Biradar, John P. A. Lamers
Format: Article
Language:English
Published: MDPI AG 2018-01-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/10/2/159
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spelling doaj-88f096999091467cb5d2ef6c14da4abf2020-11-24T22:55:57ZengMDPI AGRemote Sensing2072-42922018-01-0110215910.3390/rs10020159rs10020159Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time SeriesFabian Löw0Alexander V. Prishchepov1François Waldner2Olena Dubovyk3Akmal Akramkhanov4Chandrashekhar Biradar5John P. A. Lamers6International Centre for Agricultural Research in Dry Areas (ICARDA), 11431 Cairo, EgyptDepartment of Geosciences and Natural Resource Management (IGN), University of Copenhagen, 1165 København, DenmarkEarth and Life Institute-Environment, Université Catholique de Louvain, 2 Croix du Sud, 1348 Louvain-la-Neuve, BelgiumDepartment of Geography, Rheinische-Friedrich-Wilhelms-Universität, 53113 Bonn, GermanyInternational Centre for Agricultural Research in Dry Areas (ICARDA), 11431 Cairo, EgyptInternational Centre for Agricultural Research in Dry Areas (ICARDA), 11431 Cairo, EgyptDepartment of Geography, Rheinische-Friedrich-Wilhelms-Universität, 53113 Bonn, GermanyCropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003–2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, “stratum-specific” classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate ( p < 0.05) than a “global” classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.http://www.mdpi.com/2072-4292/10/2/159abandoned croplandAral Sea Basinchange detectionland usedecision fusionMODIS
collection DOAJ
language English
format Article
sources DOAJ
author Fabian Löw
Alexander V. Prishchepov
François Waldner
Olena Dubovyk
Akmal Akramkhanov
Chandrashekhar Biradar
John P. A. Lamers
spellingShingle Fabian Löw
Alexander V. Prishchepov
François Waldner
Olena Dubovyk
Akmal Akramkhanov
Chandrashekhar Biradar
John P. A. Lamers
Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
Remote Sensing
abandoned cropland
Aral Sea Basin
change detection
land use
decision fusion
MODIS
author_facet Fabian Löw
Alexander V. Prishchepov
François Waldner
Olena Dubovyk
Akmal Akramkhanov
Chandrashekhar Biradar
John P. A. Lamers
author_sort Fabian Löw
title Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
title_short Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
title_full Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
title_fullStr Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
title_full_unstemmed Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series
title_sort mapping cropland abandonment in the aral sea basin with modis time series
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-01-01
description Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003–2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, “stratum-specific” classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate ( p < 0.05) than a “global” classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.
topic abandoned cropland
Aral Sea Basin
change detection
land use
decision fusion
MODIS
url http://www.mdpi.com/2072-4292/10/2/159
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