Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data
With the rapid increase in the costs of rural labour and the adjustment of planting structures, the phenomenon of farmland abandonment has appeared in China. It is of great significance to promptly and accurately grasp the information on dynamic temporal and spatial changes in abandoned farmland to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/13/2549 |
| _version_ | 1797528322462187520 |
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| author | Zhonghui Wei Xiaohe Gu Qian Sun Xueqian Hu Yunbing Gao |
| author_facet | Zhonghui Wei Xiaohe Gu Qian Sun Xueqian Hu Yunbing Gao |
| author_sort | Zhonghui Wei |
| collection | DOAJ |
| description | With the rapid increase in the costs of rural labour and the adjustment of planting structures, the phenomenon of farmland abandonment has appeared in China. It is of great significance to promptly and accurately grasp the information on dynamic temporal and spatial changes in abandoned farmland to ensure national food security and the sustainable use of cultivated land. Luquan District in Hebei, China was selected as the research area based on multispectral images from Sentinel-2A, Landsat-7, and Landsat-8 combined with methods of random forest (RF) classification and vegetation index change detection. Rules for the identification of abandoned farmland were also developed, and remote sensing monitoring of the abandonment status of the cultivated land was also carried out in the study area. We also obtained the spatial distribution of abandoned and reclaimed farmland and analysed the frequency of farmland abandonment. The results show that the overall accuracy of the land-use time-series map ranged from 90.20% to 96.92% for the study period of 2010–2020. The average rate of farmland abandonment in the study area was 10.62%, with the lowest rate (5.83%) in 2020 and the highest (14.09%) in 2012. From 2011 to 2020, the maximum farmland abandonment area was 3906.02 hm<sup>2</sup>, and the minimum area was 1618.74 hm<sup>2</sup>. The farmland abandonment area showed a trend of first increasing and then decreasing. From 2012 to 2020, the maximum area of reclaimed farmland was 291.49 hm<sup>2</sup>, and the highest rate of reclamation was 14.26%. The overall reclamation rate was low. The abandonment frequency of most of the abandoned farmland was 1–3 years, covering an area of 8193.73 hm<sup>2</sup>, which comprised 79% of the total area of abandoned farmland. The frequency of abandonment was inversely proportional to the area of abandoned farmland. Farmland abandonment mainly occurred in hilly areas. We expect that our results can provide case studies for long time series in farmland abandonment research and can provide a reference for studying the driving factors, risk assessment, and policymaking with respect to abandoned farmland. |
| first_indexed | 2024-03-10T09:56:36Z |
| format | Article |
| id | doaj.art-3d60a1ea41fd483aa7a805058517f278 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:56:36Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3d60a1ea41fd483aa7a805058517f2782023-11-22T02:14:53ZengMDPI AGRemote Sensing2072-42922021-06-011313254910.3390/rs13132549Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing DataZhonghui Wei0Xiaohe Gu1Qian Sun2Xueqian Hu3Yunbing Gao4Beijing Research Center for Information Technology in Agriculture, Beijing 100097, ChinaBeijing Research Center for Information Technology in Agriculture, Beijing 100097, ChinaBeijing Research Center for Information Technology in Agriculture, Beijing 100097, ChinaBeijing Research Center for Information Technology in Agriculture, Beijing 100097, ChinaBeijing Research Center for Information Technology in Agriculture, Beijing 100097, ChinaWith the rapid increase in the costs of rural labour and the adjustment of planting structures, the phenomenon of farmland abandonment has appeared in China. It is of great significance to promptly and accurately grasp the information on dynamic temporal and spatial changes in abandoned farmland to ensure national food security and the sustainable use of cultivated land. Luquan District in Hebei, China was selected as the research area based on multispectral images from Sentinel-2A, Landsat-7, and Landsat-8 combined with methods of random forest (RF) classification and vegetation index change detection. Rules for the identification of abandoned farmland were also developed, and remote sensing monitoring of the abandonment status of the cultivated land was also carried out in the study area. We also obtained the spatial distribution of abandoned and reclaimed farmland and analysed the frequency of farmland abandonment. The results show that the overall accuracy of the land-use time-series map ranged from 90.20% to 96.92% for the study period of 2010–2020. The average rate of farmland abandonment in the study area was 10.62%, with the lowest rate (5.83%) in 2020 and the highest (14.09%) in 2012. From 2011 to 2020, the maximum farmland abandonment area was 3906.02 hm<sup>2</sup>, and the minimum area was 1618.74 hm<sup>2</sup>. The farmland abandonment area showed a trend of first increasing and then decreasing. From 2012 to 2020, the maximum area of reclaimed farmland was 291.49 hm<sup>2</sup>, and the highest rate of reclamation was 14.26%. The overall reclamation rate was low. The abandonment frequency of most of the abandoned farmland was 1–3 years, covering an area of 8193.73 hm<sup>2</sup>, which comprised 79% of the total area of abandoned farmland. The frequency of abandonment was inversely proportional to the area of abandoned farmland. Farmland abandonment mainly occurred in hilly areas. We expect that our results can provide case studies for long time series in farmland abandonment research and can provide a reference for studying the driving factors, risk assessment, and policymaking with respect to abandoned farmland.https://www.mdpi.com/2072-4292/13/13/2549cultivated land abandonmentreclamationchange detectiontime-series analysisremote sensing monitoring |
| spellingShingle | Zhonghui Wei Xiaohe Gu Qian Sun Xueqian Hu Yunbing Gao Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data Remote Sensing cultivated land abandonment reclamation change detection time-series analysis remote sensing monitoring |
| title | Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data |
| title_full | Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data |
| title_fullStr | Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data |
| title_full_unstemmed | Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data |
| title_short | Analysis of the Spatial and Temporal Pattern of Changes in Abandoned Farmland Based on Long Time Series of Remote Sensing Data |
| title_sort | analysis of the spatial and temporal pattern of changes in abandoned farmland based on long time series of remote sensing data |
| topic | cultivated land abandonment reclamation change detection time-series analysis remote sensing monitoring |
| url | https://www.mdpi.com/2072-4292/13/13/2549 |
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