Pulau Tanakeke merupakan salah satu pulau dengan hutan mangrove yang luas di pesisir Sulawesi Selatan. Hutan mangrove ini menjadi ekosistem penting bagi masyarakat sekitar karena nilai ekologi maupun ekonominya. Namun, dalam kurun waktu sekitar tahun 1980-2000, keberadaan mangrove tersebut terancam oleh perubahan penggunaan lahan dan juga pemanfaatan yang berlebihan. Penelitian ini bertujuan untuk menganalisis perubahan temporal luas dan tingkat kerapatan hutan mangrove di Pulau Tanakeke antara tahun 2016 dan 2019. Metode analisis perubahan luasan hutan mangrove menggunakan data citra satelit Sentinel-2 multi temporal berdasarkan hasil klasifikasi hutan mangrove dengan menggunakan random forest pada platform Google Earth Engine. Akurasi keseluruhan hasil klasifikasi hutan mangrove tahun 2016 dan 2019 sebesar 91% dan 98%. Berdasarkan hasil analisis spasial diperoleh perubahan penurunan luasan mangrove yang signifikan dari 800,21 ha menjadi 640,15 ha. Kerapatan mangrove di Pulau Tanakeke sebagian besar tergolong kategori dalam kerapatan tinggi.
The topographic effect on satellite imagery has long been acknowledged and several methods have been proposed to address it. These methods mostly employ a digital elevation model to identify topographic conditions. The availability of various digital elevation models (DEMs) with different spatial resolutions prompts a thorough investigation to select suitable data for use when correcting the topographic effect on high-resolution satellite imagery. The release of Digital Elevation Model Nasional (DEMNAS) with its 8-meter spatial resolution provides a similar spatial resolution with SPOT-6/7 multispectral data (6 meters). This study presents our results for topographic correction performed using three different DEMs on orthorectified SPOT-6/7 multispectral data. These DEMs are Shuttle Radar Topography Mission (SRTM) and ALOS World 3D 30 meters (AW3D30), as well as DEMNAS. All three DEMs were resampled to match SPOT-6/7 spatial resolution (6 meters). Atmospheric correction using the MODTRAN-4 algorithm was conducted on the SPOT-6/7 multispectral images. Our study was conducted on two test sites located in the mountainous region over South Sulawesi Province, Indonesia. The Minnaert correction was chosen as the correction algorithm with the k constant calculated for each band over forest land cover. To evaluate the performance of each DEM, visual evaluation and statistical assessment were employed. Pixel values before and after topographic correction were compared over sunlit as well as shaded forest. Coefficient of variation (CV) was used as the statistical assessment tool. Our results show that AW3D30 is able to reduce the topographic effect on SPOT-6/7 multispectral images. The correlation (r) between image surface reflectance value and local illumination were reduced from 0.78 to -0.06 for the best performer on the NIR infrared band. CV was also reduced from 24.46 to 19.02 for the same NIR band. AW3D30 performed the best without the apparent under-and over-correction produced by the two other DEMs. Tweaks and modifications are found to be necessary to resolve the under-correction encountered when using SRTM and the over-correction associated with using DEMNAS on SPOT-6/7 multispectral imagery.
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