基于季相变化特征的撂荒地遥感提取方法研究

在我国西南地区耕种条件差，地块比较破碎，地块类型比较复杂，中低分辨率遥感数据难以满足撂荒地提取的需要。选取贵州修文县为试验区，基于高分辨率卫星遥感数据（哨兵2号），探索单期或多期影像在中国西南地区的撂荒地检测能力，构建撂荒地遥感监测方法，为今后我国西南地区撂荒地统计调查提供参考。结合野外调查数据，在划分不同撂荒地类型基础上，综合遥感影像的光谱特征、植被指数特征以及多时相植被指数变化特征分析，优选不同类别撂荒地遥感提取敏感特征集，利用CART决策树分类方法，提取不同类型的撂荒地。结果表明：①单个时相对不同类型的撂荒地识别能力差异显著，基于单时相影像，难以开展撂荒地高精度遥感监测提取；②不同时相的植被指数变化特征对撂荒地的识别能力较强，其中比值植被指数优于差值植被指数和归一化植被指数；③以贵州修文县为例，开展了撂荒地空间分布制图及撂荒面积统计分析，修文县撂荒地面积约为6 460 hm²，占修文县耕地面积的13%；④基于多时相高分辨遥感数据，通过季相变化特征构建的撂荒地检测方法，能够满足我国西南地区撂荒地高精度遥感监测提取，为大范围撂荒地遥感调查和制图提供技术参考。

Study on Extraction Method of Abandoned Farmland based on the Seasonal Variation Characteristics of Remotely Sensed Images

In southwestern China, the cultivation conditions are poor, the plots are relatively fragmented, and the types of plots are complex. Therefore, the use of low and medium resolution remote sensing data is not able to satisfy the needs of abandoned farmland extraction. This paper explored the ability of single or multi-phased high resolution remotely sensed images in detecting abandoned farmland in southwest China, using Xiuwen County, Guizhou Province, China as a case study area. Remote sensing based monitoring methods for abandoned farmland were developed, providing a reference for the statistical survey of abandoned farmland in southwest China.The extraction method of abandoned farmland was proposed based on the field survey data, considering different types of abandoned farmland. Sensitive feature sets of different types of abandoned farmland were identified from a series of features including the spectral characteristics, vegetation indices and multi-temporal difference vegetation indices. The CART decision tree classification method was applied on the selected sensitive features to extract abandoned farmland. The results showed that:(1) There was a significant difference in the recognition ability of single-phase image in extracting different types of abandoned farmland, so it was difficult to use only single-phase image to extract abandoned farmland with high accuracy; (2) The vegetation index change characteristics of different time phases had strong recognition ability for abandoned farmland, and the ratio vegetation index was better than the difference vegetation index and normalized vegetation index; (3) The spatial distribution map of abandoned farmland and the statistical analysis of abandoned farmland area were carried out in Xiuwen County, Guizhou Province. The area of abandoned farmland in Xiuwen County was about 6,460 hectares, accounting for 13% of the cultivated land area.（4）Based on multi-temporal high-resolution remote sensing data, the method of detecting abandoned farmland using seasonal variation characteristics can meet the requirements of high-precision extraction of abandoned farmland in southwest China, and the results provided technical reference for remote sensing survey and mapping of abandoned farmland in large-scale.