Utilization of multitemporal imagery for analysis of changes in mangrove cover by Using Cloud Computing Method in the East Coast Region of Lampung Province

Open

Nirmawana Simarmata, Ketut Wikantika, Trika Agnestasia Tarigan, Muhammad Aldyansyah, Rizki Kurnia Tohir

2021 IOP Conference Series: Earth and Environmental Science Vol. 830 Issue 1 Conference paper Cited by 4 SDG 15SDG 17 Quartile

Abstract

The East Coast of Lampung Province has extraordinary potential, unique potential such as visual appeal. In addition, the coast also has the potential as a residential area, fishery cultivation, ponds, agriculture, ports, tourism and so on. However, behind its potential, the East Coast region of Lampung Province, especially the coastal area, is prone to destructive activities around the sea, the cause of the damage can be influenced by natural factors which include wave and tidal action. and human activities such as converting mangrove land to ponds. The purpose of this study was to analyze changes in mangrove area cover using multitemporal imagery from 1991 to 2019. The research data used were Landsat imagery and Sentinel imagery. Identification of mangrove areas can be done through interpretation of remote sensing technology. Changes in mangrove land cover can be detected using multitemporal imagery. It is early to see how widespread the changes have been in a certain time frame. The use of remote sensing technology is one method that is widely used to map and determine the condition of an area using the classification method. Classification is designed to derive thematic information by classifying phenomena based on criteria. Satellite image processing is carried out using the image classification method with cloud computing-based software, namely Google Earth Engine (GEE). The sampling points for classification are evenly distributed in the mangrove area. Apart from mangrove objects, samples were also taken from water objects, urban areas, vegetation, ponds and coastlines. This aims to distinguish mangrove objects from other objects. Based on the results of image processing, the accuracy test obtained on the land cover map is above 85% because the image resolution used is a medium resolution image. The results of the field survey indicated that there was a change in mangrove cover to become ponds which resulted in a reduction in the area of mangrove cover. © Published under licence by IOP Publishing Ltd.

Affiliations

Geomatics Engineering, Institut Teknologi Sumatera, Lampung, Indonesia; Geodesy and Geomatics Engineering, Institut Teknologi Bandung, Bandung, Indonesia; Ocean Engineering, Institut Teknologi Sumatera, Lampung, Indonesia; Forestry Engineering, Institut Teknologi Sumatera, Lampung, Indonesia

Research at a Glance

Premium content — register to unlock

Research at a Glance

Register to unlock

Topics & SDG Alignment

Premium content — register to unlock

Topics & SDG Alignment

Register to unlock

Collaboration

Premium content — register to unlock

Collaboration

Register to unlock

Author Profile (Selected)

Premium content — register to unlock

Author Profile (Selected)

Register to unlock

References Overview

Premium content — register to unlock

References Overview

Register to unlock

Journal & Source

Premium content — register to unlock

Journal & Source

Register to unlock

Metadata & Integrity

Premium content — register to unlock

Metadata & Integrity

Register to unlock