Self-trained deep forest with limited samples for urban impervious surface area extraction in arid area using multispectral and polsar imageries

HIGHLIGHTS

• who: Ximing Liu and colleagues from the State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China University of Chinese Academy of Sciences, Beijing, China have published the research work: Self-Trained Deep Forest with Limited Samples for Urban Impervious Surface Area Extraction in Arid Area Using Multispectral and PolSAR Imageries, in the Journal: Sensors 2022, 6844 of 17/09/2017
• what: To tackle these issues a deep-forest (STDF)-based ISA extraction method is proposed which exploits the complementary information contained in and polarimetric . . .
  

   

  

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