Nonagriculturalization Detection Based on Vector Polygons and Contrastive Learning With High-Resolution Remote Sensing Images

The conversion of agricultural lands, termed "nonagriculturalization," poses profound threats to food security and ecological stability. Remote sensing image change detection offers an invaluable tool for monitoring this phenomenon. However, most change detection techniques prioritize imag...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2024, Vol.17, p.18474-18488
Hauptverfasser:	Zhang, Hui, Liu, Wei, Zhu, Changming, Niu, Hao, Yin, Pengcheng, Dong, Shiling, Wu, Jialin, Li, Erzhu, Zhang, Lianpeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms Adaptive sampling Agricultural land Annotations Change detection Classification Clustering Clustering algorithms Contrastive learning contrastive learning (CL) cropland Datasets Deep learning Feature extraction Food conversion Food security Image quality Image resolution Image segmentation Learning Machine learning Monitoring Polygons Remote monitoring Remote sensing Training vector polygons Vectors
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