Artificial mangrove species mapping using Pléiades-1: An evaluation of pixel-based and object-based classifications with selected machine learning algorithms

Remote Sensing

Volumn 10, Issue 2, 2018, Pages

  Wang, Dezhi ^a   Wan, Bo ^a   Qiu, Penghua ^b   Su, Yanjun ^c   Guo, Qinghua ^c   Wu, Xincai ^a  

^a CHINA UNIVERSITY OF GEOSCIENCES   (China)

^b HAINAN NORMAL UNIVERSITY   (China)

^c INSTITUTE OF BOTANY   (China)

Author keywords

Artificial mangrove; Decision tree; Object based; Pixel based; Random forest; Support vector machine

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; DECISION TREES; IMAGE ANALYSIS; LEARNING SYSTEMS; MAPPING; PIXELS; PLANTS (BOTANY); POPULATION DISTRIBUTION; REFORESTATION; REMOTE SENSING; SUPPORT VECTOR MACHINES;

ARTIFICIAL MANGROVE; CLASSIFICATION ACCURACY; OBJECT BASED; OBJECT BASED IMAGE ANALYSIS; OBJECT-BASED CLASSIFICATIONS; RANDOM FORESTS; REMOTE SENSING TECHNIQUES; STATISTICALLY SIGNIFICANT DIFFERENCE;

LEARNING ALGORITHMS;

EID: 85042521399     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs10020294     Document Type: Article

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