Mapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysis

Remote Sensing

Dagmar Haase¹  Conghe Song²  Qian Yu³  Junxiang Li⁴  Caiyan Wu⁴  Yuhan Liu⁵  Linke Ouyang⁵  Meng Wang⁵  Ji Han⁵ 

[1] Department of Geography, Humboldt-Universität zu Berlin, 10117 Berlin, Germany;Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;Department of Geosciences, University of Massachusetts, Amherst, MA 01003, USA;Department of Landscape Architecture, School of Design, Shanghai Jiao Tong University, Shanghai 200240, China;Shanghai Key Laboratory of Urbanization Processes and Ecological Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China;

关键词: impervious surface area;    phenology information;    Fisher transformation;    linear spectral mixture analysis;    endmember variability;    Google Earth Engine;   

DOI  :  10.3390/rs14071673

来源: DOAJ

【 摘 要 】

The impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions.

【 授权许可】

Unknown