Remote Sensing Monitoring of Cultivated Land Abandonment based on Multi-temporal Collaborative Change Detection

doi:10.11873/j.issn.1004-0323.2022.3.0539

Remote Sensing Technology and Application

2022, Vol. 37

Issue (3): 539-549 DOI: 10.11873/j.issn.1004-0323.2022.3.0539

Remote Sensing Monitoring of Cultivated Land Abandonment based on Multi-temporal Collaborative Change Detection

Zhonghui Wei^1,²(

),Hailiang Jin¹,Xiaohe Gu²(

),Yingru Yang³,Gengze Wang^1,²,Yuchun Pan²

^1.School of Surveying and Land Information Engineering，Henan Polytechnic University，Jiaozuo 454000，China
^2.Research Center of Information Technology，Beijing Academy of Agriculture and Forestry Sciences，Beijing 100097，China
^3.Shijiazhuang Academy of Agriculture and Forestry Sciences，Shijiazhuang 050041，China

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Abstract

Aiming at the problem of low precision of abandoned land extraction caused by complex land cover and broken land， a method of abandoned land information extraction based on multi temporal collaborative change detection was proposed. Taking Luquan District， Shijiazhuang City， Hebei Province as the research area， the Normalized Difference Vegetation Index （NDVI） of various types of cultivated land cover was analyzed by using sentinel 2a and Landsat 7 multispectral images and supported by field samples Based on the classification system of seasonal abandonment， perennial abandonment， winter wheat and perennial garden， a multi temporal collaborative change detection model was constructed to carry out remote sensing monitoring of cultivated land abandonment in the study area. The results show that the classification accuracy of seasonal and perennial abandoned farmland based on Sentinel 2A image is 95.83% and 96.55% respectively； the classification accuracy of seasonal and perennial abandoned farmland based on Landsat 7 image is 91.67% and 93.10% respectively； the seasonal abandoned farmland accounts for 4.7% and perennial abandoned farmland accounts for 7.1% in Luquan District in 2019. This method can quickly and accurately obtain the spatial distribution and area information of cultivated land in the study area， and has good extraction accuracy for abandoned land in different resolution images.

Key words: Cultivated land abandonment Sentinel-2A NDVI Multi temporal change detection Remote sensing monitoring

Received: 06 January 2021 Published: 25 August 2022

ZTFLH:

TP79

Corresponding Authors: Xiaohe Gu E-mail: 1024217621@qq.com;guxh@nercita.org.cn

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	Zhonghui Wei
	Hailiang Jin
	Xiaohe Gu
	Yingru Yang
	Gengze Wang
	Yuchun Pan

Cite this article:

Zhonghui Wei,Hailiang Jin,Xiaohe Gu,Yingru Yang,Gengze Wang,Yuchun Pan. Remote Sensing Monitoring of Cultivated Land Abandonment based on Multi-temporal Collaborative Change Detection. Remote Sensing Technology and Application, 2022, 37(3): 539-549.

URL:

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2022.3.0539 OR http://www.rsta.ac.cn/EN/Y2022/V37/I3/539

Fig.1 Location of the study area

Table 1 Image data list

Fig.2 Sketch map of remote sensing image

Fig.3 Cultivated land range and investigation samples in the study area

Fig.4 Technical flow chart

Table 2 Land cover types in different months

Fig.5 NDVI time series curve of typical features

Table 3 NDVI distribution interval of typical features in different phases

Fig.6 Change detection model

Fig. 7 Classification results of change detection

Fig. 8 Remote sensing monitoring map of cultivated land abandonment in Luquan district in 2019

Table 4 Accuracy evaluation of confusion matrix of Sentinel image classification results

Table 5 Accuracy evaluation of confusion matrix of Landsat7 ETM image classification results

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