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Rancakalong District is one of the Sumedang Regency districts bypassed by the Cileunyi-Sumedang-Dawuan (Cisumdawu) toll road. Most of this district area is an agricultural and plantation area. This study aims to identify changes in land cover in Rancakalong District from 2011 to 2020, to identify land cover changes in the villages that passed by the Cisumdawu toll road, and to determine the shift of respondents' jobs related to land ownership. The approach in this research is made by collecting secondary and primary data. Secondary data is collected from various related offices. The primary data were obtained through field observations, interviews, and questionnaires. Respondents were 100 farmers who owned land. The results showed that in Rancakalong District, from 2011 to 2020, a land cover change covered an area of 301.39 hectares. These changes occur in forest land cover, plantations/gardens, settlements, rice fields, shrubs, and dry land. The land cover that changed the most was forest covering an area of 131.50 hectares or 43.63%, and the minor was settlements that covered an area of 2.28 hectares or 0.76% of the total change. Twenty-four respondents changed their job related to land ownership in the villages passed by Cisumdawu Toll Road. In 2020, no respondents in four villages worked as farmers, and some people were unemployed. This study indicates that the construction of toll roads implies a shift in the area's land cover, which induces a change in the work of those employed in farming. [ABSTRACT FROM AUTHOR]

Landslides are one of the natural disasters that often occur in Indonesia, which can be caused by various factors such as slope and land use conditions. The density of vegetation and the type of land cover also have an impact on the binding process of water particles in the soil, which will also affect the stability of the soil. Based on BPBD data and landslide inventory, more than 50 landslides have occurred in Tawangmangu Sub-district. The objective of this research was to analysis distribution of landslide hazard in Tawangmangu Sub-district. In this study, we developed the Weight of Evidence method based on several parameters were considered such as slope, soil type, geology, vegetation density using the NDVI, land cover, distance to roads, and distance to rivers. The results showed that most of the villages in Tawangmangu Sub-district had a high level of landslide hazard of 1130.94 Ha or 18.95% of Tawangmangu Sub-district included in a very high hazard level and a high hazard level of 31.48%, or an area of 1878.73 Ha. 21.56%, or 1286.37 Ha, is included in the moderate hazard level, while the low and very low hazard levels cover 12.9% and 15.11% of the total area, respectively. The area is located on a slope of >20%, which is dominated by low to medium density, with land cover for settlements and plantations. The areas that have a higher level of landslide hazard include Gondosuli Village, Tawangmangu Village, Panjang Village, and Plumbon Village. Several villages that have a high level of danger can be used as a top priority for disaster management. In addition to the location where active landslides occur, further studies can be carried out, such as utilizing land according to its function based on topographic and geological characteristics. [ABSTRACT FROM AUTHOR]

The existence of a 1/50,000 scale RBI (Rupa Bumi Indonesia) map from the https://tanahair.indonesia.go.id/ site is quite complete. However, the thematic information or layer on the map is not updated, especially the land covertheme. Remote sensing technology with SAR (Synthetic Aperture Radar) sensors is suitable for conditions in Indonesia where there is always a limitation from cloud coverage. Sentinel-1 SAR imagery can be a solution for medium-scalethematic production of maps. Sentinel-1 SAR imagery has polarization data that can be explored to enrich image classification capabilities. This study evaluates which polarization combination is the most optimal for thematic landcover. There are six polarization combination schemes evaluated, which are: (VV, VH, VV), (VH/VV, VV, VH), (VV, VH, VV/VH), (VV+VH, VH, VV/VH), (VV-VH/VV+VH, VH, VV+VH/2), (VV, VH, VV-VH). Each polarization scheme provides a different backscatter value for each land cover object. This study uses two samples study areas represent highland and lowland in the coastal area. Only the highland area has tested for map updating. The interpretation of land cover objects is carried out by visual interpretation compared with RBI Map data and high-resolution optical images. The evaluation results show that the combination of VV, VH, and VV-VH polarization has given the best classification for overall results. This polarimetry combination has the potential for use in updating thethematic data of RBI maps. [ABSTRACT FROM AUTHOR]

The Tuntang watershed is one of the watersheds located in Central Java, a province in Indonesia with a massive level of economic and demographic development. From an ecological perspective, this can threaten the ecology of a landscape. Massive economic and social developments trigger changes in land use. Thus, the existing land will be intervened by human activities. The spatio-temporal analysis of the hemeroby index was used to analyze human land intervention in the Tuntang watershed. The data used in the spatio-temporal analysis are Land Use Land Cover data from remote sensing, Landsat imagery in 1990 and 2020. Based on the analysis of the Hemeroby index, changes in human intervention are increasing over time (1990-2020). These results indicate that the higher the hemeroby index, the wider and higher the level of disturbed land in the Tuntang watershed. Monitoring of land interventions is needed in order to create an ecosystem balance. [ABSTRACT FROM AUTHOR]

Surabaya city has been the center of economy and industry for several decades. It is a port city where all economic activities happen that affect the conversion of the land from its original cover into economic uses. As a result, the land and the open space areas become scarce. The same thing happened to green open spaces, which experienced a decrease in the number of areas. This research aims to find, calculate, analyze, and evaluate green open space using object-based image classification. With advanced remote sensing satellite technology such as Sentinel 2 MSI, the satellite can produce images for use to extract green open space. Google Earth Engine (GEE) offers image processing tools to extract land cover information, including green open space. SNIC (Simple Non-Iterative Clustering) algorithm is used to segment the images and then merge with PCA (Principal Component Analysis) of the GLCM (Gray level co-occurrences matrix) algorithm from the textural analysis. Both become critical processes of OBIA classification in this research. The result shows that the green open space area occupies only 19% of Surabaya City, which is still below the minimum 30% standard of green open space available in the city according to the law. [ABSTRACT FROM AUTHOR]