Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

8th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing

地球科学;计算机科学

Taufik, Afirah^1 ; Ahmad, Sharifah Sakinah Syed^2

Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka

76100, Malaysia^1

Department of Industrial Computing, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka

76100, Malaysia^2

关键词: ANFIS (adaptive neuro fuzzy inference system);    Fuzzy inference systems;    Fuzzy logic approach;    Land cover classification;    Normalized difference vegetation index;    Normalized difference water index;    Normalized differences;    Parameter selection;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/37/1/012062/pdf
DOI  :  10.1088/1755-1315/37/1/012062

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.