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Social and Behavioral Sciences Commons

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Geography

Faculty Publications

2017

Automated supervised classification

Articles 1 - 2 of 2

Full-Text Articles in Social and Behavioral Sciences

Mapping Typical Urban Lulc From Landsat Imagery Without Training Samples Or Self-Defined Parameters, Hui Li, Cuizhen Wang, Cheng Zhong, Zhi Zhang, Qingbing Liu Jul 2017

Mapping Typical Urban Lulc From Landsat Imagery Without Training Samples Or Self-Defined Parameters, Hui Li, Cuizhen Wang, Cheng Zhong, Zhi Zhang, Qingbing Liu

Faculty Publications

Land use/land cover (LULC) change is one of the most important indicators in understanding the interactions between humans and the environment. Traditionally, when LULC maps are produced yearly, most existing remote-sensing methods have to collect ground reference data annually, as the classifiers have to be trained individually in each corresponding year. This study presented a novel strategy to map LULC classes without training samples or assigning parameters. First of all, several novel indices were carefully selected from the index pool, which were able to highlight certain LULC very well. Following this, a common unsupervised classifier was employed to extract the …


Mapping Typical Urban Lulc From Landsat Imagery Without Training Samples Or Self-Defined Parameters, Hui Li, Cuizhen Wang, Cheng Zhong, Zhi Zhang, Qingbin Liu Jul 2017

Mapping Typical Urban Lulc From Landsat Imagery Without Training Samples Or Self-Defined Parameters, Hui Li, Cuizhen Wang, Cheng Zhong, Zhi Zhang, Qingbin Liu

Faculty Publications

Land use/land cover (LULC) change is one of the most important indicators in understanding the interactions between humans and the environment. Traditionally, when LULC maps are produced yearly, most existing remote-sensing methods have to collect ground reference data annually, as the classifiers have to be trained individually in each corresponding year. This study presented a novel strategy to map LULC classes without training samples or assigning parameters. First of all, several novel indices were carefully selected from the index pool, which were able to highlight certain LULC very well. Following this, a common unsupervised classifier was employed to extract the …