This paper presents the results from a quality and usability analysis of participatory land registration (PaLaR) in Indonesia's rural areas, focusing on data quality, cost, and time. PaLaR was designed as a systematic community-centered land titling project collecting requisite spatial and legal data. PaLaR was piloted in two communities situated in Tanggamus and Grobogan districts in Indonesia. The research compared spatial data accuracy between two approaches, PaLaR and the normal systematic land registration approach (PTSL) with respect to point accuracy and polygon area. Supplementary observations and interviews were undertaken in order to evaluate the effectiveness of the spatial and legal data collection, as well as logical consistency of the data collected by the community committee, using a mobile application. Although the two pilots showed a lower spatial accuracy than the normal method (PTSL), PaLaR better suited local circumstances and still delivered complete spatial and legal data in a more effective means. The accuracy and efficiency of spatial data collection could be improved through the use of more accurate GNSS antennas and a seamless connection to the national land databases. The PaLaR method is dependent on, amongst other aspects, inclusive and flexible community awareness programs, as well as the committed participation of the community and local offices.Land 2020, 9, 79 2 of 27 challenging [1]. Under the current legal and institutional framework, Indonesian systematic land titling activities are procedurally demanding and rigid, requiring active participation from communities, villages, and government officers, owing to uncoordinated and sporadic registration activities in the past [2].Fit for purposes land administration (FFP LA) principles aim to accelerate land registration activities utilizing spatial, institutional, and legal framework and also call for incremental improvement [3]. FFP LA has been tested, if not implemented, worldwide [4,5]. Although there are comprehensive FFP LA implementing guidelines available [6], see also [7], finding the best-fit land registration and spatial data collection method suitable for the country context remains a significant task in itself: there are no one size fits all approaches. Further, managing the financial, political, legal, and administrative aspects regarding large-scale registration campaigns remains challenging, even when FFP LA approaches are used.Indonesia's current progress on land registration provides an example to examine how quality, cost, and speed can be leveraged to reach the Indonesian government's goal of registering all unregistered land parcels by 2025. The central government launched PTSL (Pendaftaran Tanah Sistematik Lengkap-a complete systematic land registration for all land parcels using fixed boundary approaches with terrestrial and photogrammetry surveys) as mandated by the President through President Instruction No. 2/2018. Before PTSL was launched in 2017, the capacity for land mapping and certification was around one...

Semarang is one of the largest cities in Java Island that is very prone to tidal flood. In order to reduce the tidal flood risk, disaster managers and city planners need a well-planned natural disaster risk management method based on disaster risk map of the city area. Risk mapping alone is not enough; an efficient system to disseminate the result of risk mapping for general public is also needed. This work intends to solve a problem of arrangement and presentation of tidal flood risk mapping. In order to develop the disaster risk map, the validation and prediction of the tidal flood were done to produce a hazard map on the tidal flood. Subsequently, the maps of vulnerability and capacity of the study area were produced based upon VCA (Vulnerability Capacity Analysis) by using fuzzy logic and weighted method approaches. As a comparison to that, the calculation of tidal flood risk was also done by adopted to the Indonesian regulation of The Natural Disaster Risk Management Head PERKA BNPB No. 2 year 2012. Finally, the risk map online was designed and developed. This system has the function of information dissemination and spatial data download of the risk map result. The online map uses KML format for sharing spatial data attributes and uses Google Maps as the map engine. The online map also gets good responses through a usability test, where it can be concluded the onlin e map is effective, efficient, and satisfactory to users.

Land is a resource with limited availability, but has an ever-increasing demand. Land Consolidation is a realignment activity which can be an alternative in planning a regional development. Land Consolidation in Gadingsari Village is a Bantul Regency government program implemented in 2017 located in Nanggulan, Patihan and Wonoroto Villages involving 200 land parcels, with 172 participants for land consolidation and 111,467 m 2 of land. Land Consolidation produces land that has good accessibility and regularity of land parcels so it may triggers an increase in land value. An increase in land value can be estimated by modeling the land value before and after land consolidation. One method that is often used in the modeling of land values is the multiple variabel linear regression method. The method used in this study involves the price of land as the dependent variabel and the independent variabel, namely: (1) Road Class; (2) Distance of land parcels to the Economic Center; (3) Distance of land parcels to the Village Government; (4) Distance between land parcels to the tourist site; (5) Distance of land parcels to Health Facilities; (6) Area; (7) Distance of parcels to Main roads; (8) Distance between land parcels of land to the beach; and (9) Land Use. The model formed is then used to calculate the estimated value of land prices before and after the implementation of land consolidation. The estimated value of land produced by the land value model prior to land consolidation ranges from Rp. 11,000 to Rp. 370,000. While the estimated land value for the land value model after land consolidation ranges from Rp. 21,000 to Rp. 605,000.

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The problem due to differential terrain illumination on satellite imagery is experienced by most of areas which are on mountainous terrain. This may cause variations in reflectance of similar ground features which lead to a misclassification of land cover classes due to different topographic positions. This phenomenon most commonly occurred in the areas which are located on southern and northern hemisphere because of the low sun inclination. This problem has been a major interest for researchers to be solved prior to the land cover classification process. For satellite images which experience this kind of problem, topographic correction need to be applied in order to reduce the illumination effects prior to land cover classification process. This research is aimed at conducting topographic correction of multi spectral SPOT satellite data as well as evaluating the three topographic correction methods. They are Cosine which is based on Lambertian reflectance assumption, as well as Minnaert correction and C correction methods which are based on non-Lambertian reflectance assumption. The data used in this study are two scenes of SPOT images of forested mountainous area of Miyazaki Prefecture, Kyushu, Japan. Research steps had been conducted in this study including geometric correction, sample data collection for calculating Minnaert constants and C constants at location which represents the whole study area, topographic correction for two scenes SPOT images, and results analysis. The results show that Cosine method did not show good performance for the study area which is topographically dominated by rugged terrain. Whereas Minnaert method and C method gave satisfactory results as is indicated by the statistical data as well as visual interpretation. However the Minnaert correction method showed slightly better performance than the C correction method.