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Geoplanning : Journal of Geomatics and Planning
Published by Universitas Diponegoro
ISSN : -     EISSN : 23556544     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Geoplanning, Journal of Geomatics and Planning (E-ISSN: 2355-6544), is an open access journal (e-journal) focusing on the scientific works in the field of applied geomatics technologies for urban and regional planning including GIS, Remote Sensing and Satellite Image Processing. This journal is published every six months in April and October (2 issues per year), and developed by the Geomatics and Planning Laboratory, Department of Urban and Regional Planning, Diponegoro University
Arjuna Subject : -
Articles 14 Documents
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Search results for , issue "Vol 5, No 1 (2018)" : 14 Documents clear
GIS-BASED LANDSLIDE SUSCEPTIBILITY ASSESSMENT AND FACTOR EFFECT ANALYSIS BY CERTAINTY FACTOR IN UPSTREAM OF JENEBERANG RIVER, INDONESIA Putri Fatimah Nurdin; Tetsuya Kubota
Geoplanning: Journal of Geomatics and Planning Vol 5, No 1 (2018)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2038.59 KB) | DOI: 10.14710/geoplanning.5.1.75-90

Abstract

This study aimed to assess landslide susceptibility by employing certainty factors model (CF) to select the causative factors for landslide susceptibility mapping in Upstream of Jeneberang River, South Sulawesi. Indonesia. The landslide causative factors were: soil, slope angle, aspect, elevation, lithology, land use, distance to the river, drainage density, and precipitation. For validation purpose, landslide inventory map was randomly partition into two groups, 30% for the validation and 70% for the training. Landslide susceptibility maps were produced by logistic regression using original factor (all nine factors) and selected factor (four factors with positive CF value). The result of certainty factor analysis shows CF value is positive for elevation, land use, slope and drainage density. The accuracy of two landslide susceptibility maps were evaluated by calculating the area under the curve of Receiver Operating Characteristic (ROC) curves. The result shows the the success rate curve for nine factor map (80.2%)  is higher than four factor map (78%). But in case of closeness between success rate curve and predictive rate curve, certainty factors model has a closer distance. In this study, effect analysis studies show how the accuracy changes when the input factors are changed.
APPLICATION OF UAV WITH FISH-EYE LENSES CAMERA FOR 3D SURFACE MODEL RECONSTRUCTION Nugroho Purwono; Agung Syetiawan
Geoplanning: Journal of Geomatics and Planning Vol 5, No 1 (2018)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.5.1.115-130

Abstract

Application of Unmanned Aerial Vehicles (UAV) for images acquisiton has been widely applied in survey and mapping. One of non-metric camera as the sensor that can be mounted on the UAV is fish-eye lenses. Fish-eye lenses camera provides images with wide range coverage. However these images are distorted and make them more difficult to use for mapping or 3D modelling. This research is aimed to make a 3D surface model by images reconstruction and to estimate the geolocation accuracy of the model generated by UAV images processing. As the approach of the method, combines the automation of computer vision technique with the photogrammetric grade accuracy. The complete photogrammetric workflow implemented in Pix4D Mapper. Meanwhile, UAV platform used is DJI Phantom 2 Vision+. Sample location in this research is an area of Geospatial Laboratorium in Parangtritis, Yogyakarta. The covered area in this research is 3.934 Ha. From the results of 186 images obtained 2.47 cm value of average Ground Sampling Distance (GSD). Moreover the numbers of 3D points for Bundle Block Images Adjustment are 243,373 points with 0.4348 value of Mean Reprojection Error (pixels). The results of 3D Densified Points are 6,207,780 and 101.04 points of average density per-m3. Generally, geolocation acuracy of the model produced by using this method is between 2.47 - 4.94 cm. Thus, it can be concluded that UAV with fish-eye lenses camera can be used to reconstruct 3D surface model. However, images correction and calibration should be required to produce an accurate 3D model.
STUDY OF POTENTIAL MELAYU VILLAGE AS A HERITAGE AREA IN SEMARANG Nuzulia Anggita; Nany Yuliastuti
Geoplanning: Journal of Geomatics and Planning Vol 5, No 1 (2018)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1943.539 KB) | DOI: 10.14710/geoplanning.5.1.43-52

Abstract

The urban village is a settlement that was established in the early period of the formation city and is the embryo of Semarang. Melayu Village is a heritage area where the existing heritage assets is inseparable from the history of the past. The enviromental of Melayu Village is quality conditions suffered environmental degradation because the threat of catastrophic tidal flood, the level of residential density is high, and there are several old buildings that were damaged. Assets contained in this region shows the evolution of human life and settlements from time to time that are still functioning properly. The purpose of this study to assess the potential in Melayu Village as a heritage area. This study uses descriptive quantitative and spatial analysis. The results of this study indicate that RW IV and RW VII are potentially as a heritage district with a score of 2.4 that characterized by a socio-cultural conditions that their religious activities in the form of cultural activities. This is also supported by the discovery of artifacts buildings in RW VII that Layur Tower Mosque and Shrine Kam Hok Bio who survived and functioned until today. Based on the potential of Melayu Village already should be protected as a heritage area.
DROUGHT HAZARD CHARACTERISTIC USING SOIL MOISTURE DEFICIT INDEX MODELLING Lulu Mari Fitria; Septiana Fathurrohmah
Geoplanning: Journal of Geomatics and Planning Vol 5, No 1 (2018)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.5.1.91-100

Abstract

Drought happen when the rainfall decreases in the extreme condition for long period of  time (above normal). Drought hazard mapping can be analyzed by various approaches, like environmental approach, ecological approach, hydrological approach, meteorological approach, geological approach, agricultural approach, and many other. Badan Meteoroligi dan Geofisika (BMKG) measures the drought hazard by utilizing Standardized Precipitation Index (SPI)The comparison of rainfall rate through SPI has positive correlation with drought type, for example SPI 3 indicates agricultural drought; while SPI 6, SPI 9 and SPI 12 indicate hydrological drought. The analysis of drought hazard level also can be done using soil moisture level measurement. Soil moisture is the result of water shortages in the hydroclimatological concept. Soil moisture analysis utilizes several influenced variables, such as soil water, precipitation, evapotranspiration, and percolation. Each of variables was analyzed using GIS Software as a method of soil moisture modeling. Drought index level analysis is using soil moisture deficit index, which indicates that drought occurs if the index score less than (-0,5). Some assumptions used in this modeling are both SMDI modeling using WHC (Water Holding Capacity) and  without using WHC. This modeling used medium term analysis during 2007-2012 to prove the occurrence of extreme drought on 2009 and 2012 for measurement of drought level in agriculture area. Based on SMDI, it is known that the dangers of SMDI drought have positive correlation to SPI 3, SPI 6, SPI 9, and SPI 12, where SPI is in accordance with the interpretation of meteorolgy, agriculture, and hydrological drought indices. 

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