Crops planting structure and karst rocky desertification analysis by Sentinel-1 data

Accurate crop planting structure (CPS) information and its relationship with the surrounding special environment can provide strong support for the adjustment of agricultural structure in areas with limited cultivated land resources, and it will help regional food security, social economy, and ecolo...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang Lingyu, Chen Quan, Zhou Zhongfa, Zhao Xin, Luo Jiancheng, Wu Tianjun, Sun Yingwei, Liu Wei, Zhang Shu, Zhang Wenhui
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	crop planting structure time series sar karst rocky desertification farmland geo-parcels Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/5b4033d455d846c4b3c809857dceb3b9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:5b4033d455d846c4b3c809857dceb3b9
record_format	dspace
spelling	oai:doaj.org-article:5b4033d455d846c4b3c809857dceb3b92021-12-05T14:10:49ZCrops planting structure and karst rocky desertification analysis by Sentinel-1 data2391-544710.1515/geo-2020-0272https://doaj.org/article/5b4033d455d846c4b3c809857dceb3b92021-08-01T00:00:00Zhttps://doi.org/10.1515/geo-2020-0272https://doaj.org/toc/2391-5447Accurate crop planting structure (CPS) information and its relationship with the surrounding special environment can provide strong support for the adjustment of agricultural structure in areas with limited cultivated land resources, and it will help regional food security, social economy, and ecological balance adjustment. However, due to the perennial cloudy, rainy, and scattered arable land in Karst mountainous areas, the monitoring of planting structure by traditional remote sensing methods is greatly limited. In this regard, we focus on synthetic aperture radar (SAR) remote sensing, which can penetrate clouds and rain, without light constraints to image. In this article, based on parcel-based temporal sequence SAR, the CPS in South China karst area was extracted by deep learning technology, and the spatial coupling relationship between CPS and karst rocky desertification (KRD) was analyzed. The results showed that: (a) The overall accuracy of CPS classification was 75.98%, which proved that the geo-parcel-based time series SAR has a good effect for the CPS mapping in the karst mountainous areas; (b) Through the analysis of the spatial relationship between the planting structure and KRD, we found that the lower KRD level caused the simpler CPS and the higher KRD grade caused more complex CPS and more richer landscape types. The spatial variation trend of CPS landscape indicates the process of water shortage and the deepening of KRD in farmland; (c) The landscape has higher connectivity (Contagion Index, CI 0.52–1.73) in lower KRD level and lower connectivity (CI 0.83–2.05) in higher KRD level, which shows that the degree of fragmentation and connection of CPS landscape is positively proportional to the degree of KRD. In this study, the planting structure extraction of crops under complex imaging environment was realized by using the farmland geo-parcels-based time series Sentinel-1 data, and the relationship between planting structure and KRD was analyzed. This study provides a new idea and method for the extraction of agricultural planting structure in the cloudy and rainy karst mountainous areas of Southwest China. The results of this study have certain guiding significance for the adjustment of regional agricultural planting structure and the balance of regional development.Wang LingyuChen QuanZhou ZhongfaZhao XinLuo JianchengWu TianjunSun YingweiLiu WeiZhang ShuZhang WenhuiDe Gruyterarticlecrop planting structuretime series sarkarstrocky desertificationfarmland geo-parcelsGeologyQE1-996.5ENOpen Geosciences, Vol 13, Iss 1, Pp 867-879 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	crop planting structure time series sar karst rocky desertification farmland geo-parcels Geology QE1-996.5
spellingShingle	crop planting structure time series sar karst rocky desertification farmland geo-parcels Geology QE1-996.5 Wang Lingyu Chen Quan Zhou Zhongfa Zhao Xin Luo Jiancheng Wu Tianjun Sun Yingwei Liu Wei Zhang Shu Zhang Wenhui Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
description	Accurate crop planting structure (CPS) information and its relationship with the surrounding special environment can provide strong support for the adjustment of agricultural structure in areas with limited cultivated land resources, and it will help regional food security, social economy, and ecological balance adjustment. However, due to the perennial cloudy, rainy, and scattered arable land in Karst mountainous areas, the monitoring of planting structure by traditional remote sensing methods is greatly limited. In this regard, we focus on synthetic aperture radar (SAR) remote sensing, which can penetrate clouds and rain, without light constraints to image. In this article, based on parcel-based temporal sequence SAR, the CPS in South China karst area was extracted by deep learning technology, and the spatial coupling relationship between CPS and karst rocky desertification (KRD) was analyzed. The results showed that: (a) The overall accuracy of CPS classification was 75.98%, which proved that the geo-parcel-based time series SAR has a good effect for the CPS mapping in the karst mountainous areas; (b) Through the analysis of the spatial relationship between the planting structure and KRD, we found that the lower KRD level caused the simpler CPS and the higher KRD grade caused more complex CPS and more richer landscape types. The spatial variation trend of CPS landscape indicates the process of water shortage and the deepening of KRD in farmland; (c) The landscape has higher connectivity (Contagion Index, CI 0.52–1.73) in lower KRD level and lower connectivity (CI 0.83–2.05) in higher KRD level, which shows that the degree of fragmentation and connection of CPS landscape is positively proportional to the degree of KRD. In this study, the planting structure extraction of crops under complex imaging environment was realized by using the farmland geo-parcels-based time series Sentinel-1 data, and the relationship between planting structure and KRD was analyzed. This study provides a new idea and method for the extraction of agricultural planting structure in the cloudy and rainy karst mountainous areas of Southwest China. The results of this study have certain guiding significance for the adjustment of regional agricultural planting structure and the balance of regional development.
format	article
author	Wang Lingyu Chen Quan Zhou Zhongfa Zhao Xin Luo Jiancheng Wu Tianjun Sun Yingwei Liu Wei Zhang Shu Zhang Wenhui
author_facet	Wang Lingyu Chen Quan Zhou Zhongfa Zhao Xin Luo Jiancheng Wu Tianjun Sun Yingwei Liu Wei Zhang Shu Zhang Wenhui
author_sort	Wang Lingyu
title	Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
title_short	Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
title_full	Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
title_fullStr	Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
title_full_unstemmed	Crops planting structure and karst rocky desertification analysis by Sentinel-1 data
title_sort	crops planting structure and karst rocky desertification analysis by sentinel-1 data
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/5b4033d455d846c4b3c809857dceb3b9
work_keys_str_mv	AT wanglingyu cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT chenquan cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT zhouzhongfa cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT zhaoxin cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT luojiancheng cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT wutianjun cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT sunyingwei cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT liuwei cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT zhangshu cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data AT zhangwenhui cropsplantingstructureandkarstrockydesertificationanalysisbysentinel1data
_version_	1718371668784578560

Crops planting structure and karst rocky desertification analysis by Sentinel-1 data

Ejemplares similares