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- Title
A New High-Resolution Rural Built-Up Land Extraction Method Based on Artificial Surface Index with Short-Wave Infrared Downscaling.
- Authors
Zhu, Wenlu; Yuan, Chao; Tian, Yichen; Wang, Yingqi; Li, Liping; Hu, Chenlu
- Abstract
The complexity of surface characteristics in rural areas poses challenges for accurate extraction of built-up areas from remote sensing images. The Artificial Surface Index (ASI) emerged as a novel and accurate built-up land index. However, the absence of short-wave infrared (SWIR) bands in most high-resolution (HR) images restricts the application of index-based methods in rural built-up land extraction. This paper presents a rapid extraction method for high-resolution built-up land in rural areas based on ASI. Through the downscaling techniques of random forest (RF) regression, high-resolution SWIR bands were generated. They were then combined with visible and near-infrared (VNIR) bands to compute ASI on GaoFen-2 (GF-2) images (called A S I G F ). Furthermore, a red roof index (RRI) was designed to reduce the probability of misclassifying built-up land with bare soil. The results demonstrated that SWIR downscaling effectively compensates for multispectral information absence in HR imagery and expands the applicability of index-based methods to HR remote sensing data. Compared with five other indices (UI, BFLEI, NDBI, BCI, and PISI), the combination of ASI and RRI achieved the optimal performance in built-up land enhancement and bare land suppression, particularly showcasing superior performance in rural built-up land extraction.
- Subjects
REMOTE sensing; RANDOM forest algorithms; RURAL geography
- Publication
Remote Sensing, 2024, Vol 16, Issue 7, p1126
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs16071126