PENGARUH PASANG SURUT TERHADAP DINAMIKA PERUBAHAN HUTAN MANGROVE DI KAWASAN TELUK BANTEN
Abstract
Kata kunci: Mangrove, Dinamika perubahan mangrove, Data Spasial, Pasang Surut
ABSTRACT
The extent of Indonesia's mangrove forest declines from the initial area of about 4.5 million ha to 1.9 million ha. The decline in the area of mangrove forest is most dominant due to the damage caused by human factors. Monitoring the extent of mangrove forest destruction by using conventional methods takes a long time and is expensive. Monitoring this level of damage is very important for the stakeholders in managing the mangrove forest area. Utilization of spatial data can facilitate and accelerate in interacting with objects found on the surface of the earth. Stages in this research outline include three parts, namely pre-field stage, field stage and post-field stage. The pre-field stage includes data collection to be used, image processing, and land cover identification in the research area for each year of image recording. The cover data of the extraction from remote sensing image data in each recording year is then separated from mangrove land cover data. The mangrove land cover data for the recording year 2017 is then used as the unit of analysis used as the reference base for information retrieval in the field by using the sample. The post-field stage is intended to process the data collected, statistical analysis, test the accuracy of the results of changes and assess the capabilities of remote sensing images in identifying mangrove forests and transfer of their utility functions. The mangrove forest in Banten regency is about 681.86 Ha. The largest spread of mangrove forest is in Tirtayasa and Pontang sub-districts. The two sub-districts have a percentage value of 29.75% and 28.46% of the total mangrove forest area in Banten Bay. The smallest extent of distribution is in Kramatwatu District which is only about 3.11% or 21.19 Ha of the total area of mangrove forest in Banten Bay.
Keywords: Mangrove, Dynamics of mangrove changes, Spatial Data, Tidal