Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index

Development of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, ex...

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Main Authors: Xinyang Yu, Younggu Her, Xicun Zhu, Changhe Lu, Xuefei Li
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/9/5274
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spelling doaj-ab93833865a04ce4914531c94afbc53b2021-05-31T23:30:08ZengMDPI AGSustainability2071-10502021-05-01135274527410.3390/su13095274Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction IndexXinyang Yu0Younggu Her1Xicun Zhu2Changhe Lu3Xuefei Li4College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, ChinaTropical Research and Education Center, Department of Agricultural and Biological Engineering, Institute of Food and Agricultural Sciences, University of Florida, Homestead, FL 33031, USACollege of Resources and Environment, Shandong Agricultural University, Tai’an 271018, ChinaKey Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing 100101, ChinaLinyi Natural Resources Development Service Center, Linyi 276000, ChinaDevelopment of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, examined by ground truth data, and then applied to the Hexi Corridor in northwest China. The arable land and its change patterns during 1990–2020 were extracted and identified using 40 Landsat TM/OLI images acquired in 1990, 2000, 2010, and 2020. The results demonstrated that the proposed method can distinguish arable land areas accurately, with the User’s (Producer’s) accuracy and overall accuracy (kappa coefficient) exceeding 0.90 (0.88) and 0.89 (0.87), respectively. The mean relative error calculated using field survey data obtained in 2012 and 2020 was 0.169 and 0.191, respectively, indicating the feasibility of the ALEI method in arable land extracting. The study found that arable land area in the Hexi Corridor was 13217.58 km<sup>2</sup> in 2020, significantly increased by 25.33% compared to that in 1990. At 10-year intervals, the arable land experienced different change patterns. The study results indicate that ALEI index is a promising tool used to effectively extract arable land in the arid area.https://www.mdpi.com/2071-1050/13/9/5274arable land extraction indexarid regionLandsat imageInfrared bandShortwave bandHexi Corridor
collection DOAJ
language English
format Article
sources DOAJ
author Xinyang Yu
Younggu Her
Xicun Zhu
Changhe Lu
Xuefei Li
spellingShingle Xinyang Yu
Younggu Her
Xicun Zhu
Changhe Lu
Xuefei Li
Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
Sustainability
arable land extraction index
arid region
Landsat image
Infrared band
Shortwave band
Hexi Corridor
author_facet Xinyang Yu
Younggu Her
Xicun Zhu
Changhe Lu
Xuefei Li
author_sort Xinyang Yu
title Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
title_short Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
title_full Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
title_fullStr Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
title_full_unstemmed Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index
title_sort multi-temporal arable land monitoring in arid region of northwest china using a new extraction index
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2021-05-01
description Development of a high-accuracy method to extract arable land using effective data sources is crucial to detect and monitor arable land dynamics, servicing land protection and sustainable development. In this study, a new arable land extraction index (ALEI) based on spectral analysis was proposed, examined by ground truth data, and then applied to the Hexi Corridor in northwest China. The arable land and its change patterns during 1990–2020 were extracted and identified using 40 Landsat TM/OLI images acquired in 1990, 2000, 2010, and 2020. The results demonstrated that the proposed method can distinguish arable land areas accurately, with the User’s (Producer’s) accuracy and overall accuracy (kappa coefficient) exceeding 0.90 (0.88) and 0.89 (0.87), respectively. The mean relative error calculated using field survey data obtained in 2012 and 2020 was 0.169 and 0.191, respectively, indicating the feasibility of the ALEI method in arable land extracting. The study found that arable land area in the Hexi Corridor was 13217.58 km<sup>2</sup> in 2020, significantly increased by 25.33% compared to that in 1990. At 10-year intervals, the arable land experienced different change patterns. The study results indicate that ALEI index is a promising tool used to effectively extract arable land in the arid area.
topic arable land extraction index
arid region
Landsat image
Infrared band
Shortwave band
Hexi Corridor
url https://www.mdpi.com/2071-1050/13/9/5274
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