Remote Sensing and GIS Applications in Environmental Sciences

Rapid monitoring of mangrove cover changes using support vector machine algorithm in Google Earth Engine computing platform (Case study: Qeshm mangrove forests)

Document Type : Original Article

Authors

1 Master graduate from tabriz U, Department of RS & GIS

2 MSc. student of Remote Sensing and Geographic Information System, Faculty of Geography; University of Tehran

3 Associate Prof Department of Remote Sensing and GIS. Faculty of Planning and Environmental Sciences. University of Tabriz

4 Assistant Professor of Remote Sensing and Geographic Information System, Faculty of Planning and Environmental Sciences, University of Tabriz

Abstract

Mangrove forests are one of the most important tropical forests found along the tidal coast. These forests are one of the most vulnerable marine ecosystems that are changing over the years due to human activities. Therefore, their prompt and timely monitoring should be the goal of environmental planners. The aim of this study was to investigate the 30-year changes of mangrove forests in the northern part of Qeshm Island during 1986, 2000 and 2020. Based on the research objectives, the mangrove cover map was extracted by applying SVM algorithm to Landsat 5 and 8 images in the instantaneous environment of Google Earth Engine. The results of 30 years of change showed that mangrove forests during the research periods (1986 to 2020) have an increasing trend, so that the area of mangrove forests in 1986 increased from 5130.78 hectares to 5471.87 hectares in 2000, which in fact amounted to 6.23% The area of forests has increased. However, the area of these forests reached 5967.13 hectares in 2020, which is an increase of 14.02% compared to the mentioned area in 1986. the results of this study show that the increase of mangrove forests during the study periods has been the result of artificial afforestation by the natives in order to preserve this marine ecosystem in the region, which has led to the prosperity of tourism industry in Qeshm region. What has accelerated the processing process in the current study is the use of the SVM algorithm and the Google Earth Engine system.

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Main Subjects

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Remote Sensing and GIS Applications in Environmental Sciences
Volume 2, Issue 2 - Serial Number 2
June 2022
Pages 36-23