Technology development of satellite earth observation offers multi-spectral data, variations sensitivity of satellite sensors are very useful to detect existing conditions by using the remote sensing algorithm to extract the land cover and the phenomenon that has occurred. Ecosystems have bound tolerance to nature condition and organisms have adaptation limit to climate change. Method used in this study was the extraction of land cover by applying multi spectral analysis as Maximum Likelihood, object base image analysis, (LST) land surface temperature, and also the formula Threat of Land Expansion (TLE) to the environment. Result showed that multispectral and time series analysis gave the increasing dynamic of land expansion, especially for forest high density, which areas ranged from 29098.73 ha in 2000 to 19216.7 ha in 2018. The surface temperature increase was ± 2.8 C° in eighteen years. The temperature dynamic represented the micro climate changes, has followed stream of land expansion. TLE represented zone threats of land expansion to natural ecosystems. It was found that threat zone because land expansion. The area of high threat vale 0.4 around central human activity was a built up area.
Peatlands are the stretch of ecosystem landscape with unique characteristics, both physically, chemically, and biodiversity. Anthropogenic activities in peatland use and disasters pose a threat to the preservation of the peatland ecosystem, which has impacts toward abiotic to the element of biodiversity (biotic). The purpose of this research is to model how the threat of the peatland ecosystem by using spatial data modeling. The method in this research using cloud-based GIS data analysis from Google earth engine, modeling distance parameter to variable modeling of interaction among landscapes on the peatland, and weight sum the value over raster-based spatial layer to determinate the thereat in the peatland ecosystem. The results of this study found zones where hot spots often occur. Modeling with euclidean distance to all modeling variables (except temperature) gives a clear effect on how the threats from each landscape interact with each other. We found that the threat of peatland damage in the high threat class dominates the plantation area reaching 30.9% of the total peatland area, whereas the forest landscape only has a high threat with a percentage of 1.9% and a low threat which the ecosystem is stable and natural reaching over 34.7 %. From this model, we succeeded in bringing up the idea to determine the priority area for policies where need to be done in handling the protection of peatland ecosystems, especially in plantations where the highest percentage of the ecosystem threat is in the high level with integrated peatland management.
Keywords: Peatland ecosystem, landscape, threat
Helmeted hornbill (Rhinoplax vigil) is a protected wildlife in Indonesia according to enactment no. 5, 1999 about Conservation of Natural Resources and its Ecosystems and Government Regulation no. 9, 1999 about plant and wildlife preservation. Helmeted Hornbill habitats spread in five country regions: Myanmar, Thailand, Malaysia (Malayan Peninsula and Serawak), Brunei, and Indonesia (Sumatra and Borneo). Silokek Geopark which located in Sijunjung Regency, West Sumatra Province, Indonesia is an identified location of Helmeted Hornbill habitat existence. Beside its uniqueness in physics, this bird also have an ecological function as seed dispersal in nature. The utilization of Remote Sensing (RS) technology and and Geographic Information System (GIS) is highly useful in identification the Helmeted Hornbill habitat distribution in this research. Geographic dateset used in this research are Landsat OLI 8 imagery, Shuttle Radar Topographic Model (SRTM), Coordinate points of Helmeted Hornbill existence and location assesment, and other dataset related to administration boundary in Silokek Geopark. This research aims to find conservation priority zone of Helmeted Hornbill in Silokek Geopark. By utilizing Maximun Entropy (MaxEnt) algorithm with finding points and location assessment, we can determine the distribution of Helmeted Hornbill habitat in Silokek Geopark based on habitat likeness. This research produces the model of conservation priority zones in geopark silokek which are distributed in hilly protected forest area and the distributions are concentrated in the center and noth east part of our researc area. This model is highly influenced by forest texture (25.7%), distance of patches (24.3%), and distance of settlement.
Coastal flood in Indonesia, namely as banjir rob, is a phenomenon that increases seawater to inundate around the tidal area. In Tanjungpinang, cases of coastal floods become a serious problem for people living in this area. This research aims to model the coastal flood inundation by modeling water inundation with a maximum level increase scenario. Its model was used to estimate coastal floods' impact on houses, buildings, and infrastructures with scenario 2 meters of sea-level rise. On the other hand, the budget loss for restoration was estimated to study the effort of community adaptations with the ECLAC RAB method and observation to understand community adaptation. It was found that the spatial model succeeded in zoning inundation areas, which had a significant impact on houses, buildings, worship places, schools, and industrial at many 4112 units. From this case, the budget loss for the restoration of the physical environment was estimated at around 61994014.75 USD. In addition, the survey revealed the existing condition before and after the coastal flood. Several community efforts for adaptation were developing houses on stilt and hoarding the lowest land on-site location for build houses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.