JOURNAL ARTICLE

Winter Wheat Mapping Using Landsat 8 Images and Geographic Object-Based Image Analysis

Tengfei SuShengwei Zhang

Year: 2017 Journal:   Transactions of the ASABE Vol: 60 (3)Pages: 625-633   Publisher: American Society of Agricultural and Biological Engineers

Abstract

Abstract. Winter wheat is a major food source in many areas, so it is necessary to construct an effective approach for its monitoring based on satellite data. By taking advantage of geographic object-based image analysis (GEOBIA), a winter wheat classification framework was established. Two stages, which included scale selection and feature analysis, were incorporated into the new approach. The scale selection stage was implemented based on an unsupervised method, so human intervention for tuning the scale parameter of image segmentation can be largely saved. The feature analysis stage was performed on the basis of a random forest classification model, and in the experiment this step allowed for feature reduction, which was validated to be beneficial to the classification performance. Keywords: Feature analysis, GEOBIA, Scale selection, Winter wheat.

Keywords:
Scale (ratio) Segmentation Feature (linguistics) Feature selection Selection (genetic algorithm) Pattern recognition (psychology) Stage (stratigraphy) Computer science Object (grammar) Image segmentation Image (mathematics) Remote sensing Artificial intelligence Data mining Cartography Geography Geology

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3
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0.16
FWCI (Field Weighted Citation Impact)
0
Refs
0.53
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Topics

Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
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