The Bogowonto Hulu sub-watershed has high flooding potential, especially during the rainy season. This flooding causes physical, social, and economic losses for the local community and so the Bener Dam was built to reduce the volume of flooding in the area. This research aims to find out the effectiveness of the Bener Dam in overcoming the problem of flooding around the Bogowonto Hulu sub-watershed. The effectiveness of dams can be analysed by comparing the volume of the dam reservoir with the peak discharge amount generated. The value of peak discharge can be obtained using remote-sensing data and mathematical calculations following the rational method. Using this method, the estimated peak discharge value obtained for the watershed was 302.3 m3/s while the value of dam capacity was only 210 m3/s, giving 92.3 m3/s of flooding potential. It is necessary to reduce the potential for flooding by building an IR reservoir in the catchment area, so that rainwater is accommodated rather than being immediately depleted, and to reduce concentration time.

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.

<p><strong>Abstract.</strong> Related to the implementation of regional autonomy (UU No. 32 Tahun 2004), the determination of regional boundaries is one of the main factors in the implementation of regional government functions. Regional boundaries that are not clear at the border can trigger conflicts that can obstruct the development of society. The conflict is not only limited to social conflicts, but also conflicts in the administrative affairs of population and local government. If it is not immediately resolved, it can reduce the level of government service to the community. Remote sensing image technology and cartography become one of the options that can help facilitate in terms of cost efficiency and time effectiveness for mapping regional boundaries. This study utilizes remote sensing image to map regional boundaries using the cartometric and participatory methods. By drawing boundaries on work maps and measuring the position of points, distances and area coverage by using basic maps and other maps as a complement and also with verification from the local government as the participator to withdraw the limit. With the cartometric and participatory method and the help of remote sensing imagery in this study that can minimize field activities with the terms of the image used has a higher resolution than the base map used. The results of this study are the map Kaligesing sub-district boundary of Purworejo District, Central Java, that that has been verified. This verified map will be used for identifying the extend differences of this area, by comparing it to the Administration Map provided by the national government. Except that the result can be use to another research such as to boundary unit of disaster, or to make cadastral map in village level.</p>

Abstract. Multispectral imagery can be used for estimating production of oil palm fruit in a plantation. One of the multispectral imagery that capable for production estimation is Sentinel 2. Sentinel 2 is a free imagery that have great 10 m medium spatial resolution bands, which are red, green, blue, and near-infrared. These bands can be used to generate several generic vegetation index such as Ratio Vegetation Index (RVI) and normalized difference vegetation index (NDVI) also non-generic vegetation index such as modified soil adjusted vegetation index (MSAVI) and atmospherically resistant vegetation index (ARVI). Those vegetation index applied for estimating the production of oil palm fruit in PT. Perkebunan Nusantara VII's plantation at Rejosari, Natar. By-age separation method demonstrate that it has a better accuracy which is 87.5 % rather than normal method that fully transformed without being separated byage. The fully transformed method accuracy are 61.1 % for RVI, 59.1 % for NDVI, 55.3 % for MSAVI, and 62.1 % for ARVI.