Analisis Model Pengembangan Kawasan Ekowisata Mangrove Potensial Berbasis Hyper Spectral of Remote Sensing dan Analytical Hierarchy Process
Abstract
Studies on potential mangrove ecotourism development models based on hyperspectral of remote sensing and analytical hierarchy process are needed to identify and analyze land suitability with socio-cultural and economic characteristics of local communities. This study connects the results of satellite image data processing using NDVI, SAVI, EVI, and NDWI approaches with decision support systems in setting priority programs for Zone 1, Zone 2, and Zone 3 development models in potential mangrove areas East Tobelo District, North Halmahera Regency, North Maluku Province, Indonesia. In the AHP approach, four criteria will be analyzed comprehensively, as follows: first, the arrangement and management of mangrove ecotourism areas (K1); second, training, mentoring, and community empowerment of mangrove ecotourism (K2) development areas; third, preservation of local social and cultural values (K3); fourth, the construction of facilities and infrastructure supporting mangrove ecotourism (K4). The results of this study show that the overall average value of raster data calculation results through the Hyper Spectral of Remote Sensing approach using NDVI, SAVI, EVI, and NDWI algorithms based on zone 1, zone 2, zone 3 mangrove areas of East Tobelo District, indicates medium or sufficient category density conditions and dense or dense, and has enough moisture or water in the measured area. Thus, Zone 1, Zone 2, and Zone 3 can be optimized into tourist destinations through community-based mangrove ecotourism. In addition, based on the results of the weighting of criteria and sub-criteria, normalization, and calculation of eigenvalue, lambda maximum, CI, and CR in the AHP method, it can be seen that K1 and Zone 1 obtained the highest rank, as well as showing the priority scale in the development of community-based mangrove ecotourism in East Tobelo District, North Halmahera Regency, North Maluku Province, Indonesia.
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