BLEI: Research on a Novel Remote Sensing Bare Land Extraction Index

Author:

He Chaokang1234ORCID,Wang Qinjun12356ORCID,Yang Jingyi123,Xu Wentao123,Yuan Boqi123

Affiliation:

1. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

2. International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

3. College of Resources and Environment, Yanqi Lake Campus, University of Chinese Academy of Sciences, Beijing 101408, China

4. College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

5. Kashi Aerospace Information Research Institute, Kashi 844199, China

6. Key Laboratory of the Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China

Abstract

Bare land, as a significant land cover type on the Earth’s surface, plays a crucial role in supporting land-use planning, urban management, and ecological environmental research through the investigation of its spatial distribution. However, due to the diversity of land-cover types on the Earth’s surface and the spectral complexity exhibited by bare land under the influence of environmental factors, it is prone to confusion with urban and other land features. In order to extract bare land rapidly and efficiently, this study introduces a novel bare land extraction index called the Bare Land Extraction Index (BLEI). Then, considering both Ganzi Tibetan Autonomous Prefecture and Urumqi, China as the study areas, we compared BLEI with three presented indices: the Bare-soil Index (BI), Dry Bare Soil Index (DBSI), and Bare Soil Index (BSI). The results show that BLEI exhibits excellent efficacy in distinguishing bare land and urban areas. It gets the most outstanding accuracy in bare land identification and mapping, with overall accuracy (OA), kappa coefficient, and F1-score of 98.91%, 0.97, and 97.89%, respectively. Furthermore, BLEI is also effective in distinguishing bare land from sandy soil, which can not only improve the mapping accuracy of bare land in soil-deserted areas but also provide technological support for soil research and land-use planning.

Funder

National Key R&D Program of China

Publisher

MDPI AG

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