Geoplanning Journal of Geomatics and Planning最新文献

{"title":"Land Provision for Decent and Affordable Housing for Low-Income Community in Salatiga City","authors":"S. Sunarti, N. Yuliastuti, I. Indriastjario","doi":"10.14710/GEOPLANNING.6.2.113-121","DOIUrl":"https://doi.org/10.14710/GEOPLANNING.6.2.113-121","url":null,"abstract":"The needs land for urban housing construction was increasingly difficult andmore pricey, so for low-income communities for able owned a house was not easy.Limited of land in an urban area, especially in small cities such as Salatiga, its land wasnot all can be used in housing constructions. This condition needed an interventionfrom the local government to facilitate their needs for housing could be fulfilled. Basedon the problems, the goals of this research studied a providing of land for decent andaffordable housing for low-income communities in Salatiga. The method used was amixed method with a sequential explanation strategy, that is by overlaying secondarydata on the land potential map from various sources that can be used for decenthousing with primary data, such as interview and document review with localgovernment to reduce of housing cost. The results of the study figure out that housingused a land owned by the village government can be affordable for low-incomecommunities with price less expensive below the standard set by the government.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48886443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Landscape Pattern Relationship with Dengue Incidence in Peninsular Malaysia","authors":"Nuramalina Binti Mohamad, W. Ibrahim, A. Ludin","doi":"10.14710/geoplanning.6.1.31-42","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.31-42","url":null,"abstract":"Dengue is the most common urban disease that is most prevalent in tropical areas. WHO 2009 stated that these diseases has grown a public health concern due to the risk of dengue infection that has increased dramatically between 50 and 100 million cases every year. This issue was very corresponded with landscape and environment changes. The objective of this paper is to discuss how landscape patterns in relation to dengue incidence.  Open website; idengue were highly contributed in this study to locate the most risky area for dengue fever incidence at the township level. Geographic information system (GIS) was used to demonstrate the spatial patterns of all dengue cases in Johor Bahru and Geoprocessing was used to measure the boundary of risk according to the distribution of dengue outbreak. After that, to analyze the spatial landscape pattern, satellite images were used.  Spatial descriptive analysis shows non-strata housing, open space, road, planned commercial, strata housing and drainage system network is the most prevalence land use activity for dengue incidence in Iskandar Region. The finding shows the common landscape composition that relates to dengue cases. In conclusion, the future development of land use should be considered on landscape pattern towards rapid urbanization. ","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.31-42","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43207136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric Accuracy Assessment for Shoreline Derived from NDWI, MNDWI, and AWEI Transformation on Various Coastal Physical Typology in Jepara Regency using Landsat 8 OLI Imagery in 2018","authors":"A. Wicaksono, P. Wicaksono","doi":"10.14710/geoplanning.6.1.55-72","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.55-72","url":null,"abstract":"Landsat 8 OLI imagery and water index utilization is expected to be able to complete the shoreline data that is difficult to obtain by using terrestrial and hydrographic surveys. In fact, coastal areas in Indonesia have a variety of coastal physical typology so that each water index characteristic in obtaining shoreline data needs to be understood in order to use water index method effectively. The objectives of this study are to map the shoreline using NDWI, MNDWI, and AWEI transformations and assess the shoreline geometric accuracy on various coastal physical typology. The shoreline derived from water index is obtained from Landsat 8 OLI imagery, while the reference shoreline for accuracy assessment is obtained from visual interpretation on Planet Scope imagery. Threshold 0 and subjective threshold based on per coastal physical typology sample experiments are used to separate land-sea. The horizontal accuracy standard of the shoreline derived from water index uses the regulation from Geospatial Information Agency of Indonesia No.15 in 2014 on technical guidelines for basic map accuracy. The results consisted of 1:100,000 scale shoreline map and shoreline geometric accuracy per coastal physical typology. Based on the shoreline geometry accuracy assessment, NDWI has the lowest shoreline geometry accuracy on artificial coast (RMSE=24.13 m). MNDWI has the lowest shoreline geometry accuracy on land deposition coast (RMSE=15.84 m), marine deposition coast (RMSE=29.53 m), and volcanic coast (RMSE=10 m). AWEIsh has the lowest shoreline geometry accuracy on the organic coast (RMSE=13.47 m), while AWEI does not superior to any coastal physical typology.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.55-72","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43264323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the Alternative Locations of Street Vendor Stabilization in Surakarta, Indonesia","authors":"M. J. Rahayu, I. Buchori, R. Widjajanti, R. A. Putri","doi":"10.14710/geoplanning.6.1.43-54","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.43-54","url":null,"abstract":"The arrangement of street vendors is continuously undertaken by the government of Surakarta City for the sake of attaining the city order and public welfare. The inclination of the Stabilization success level in achieving the goal of street vendor arrangement strategy indicates that the location characteristics conforming to the street vendors’ preferences become one of the determinations in terms of the arrangement success. This article aims at mapping the alternative locations of street vendor Stabilization in Surakarta by applying the spatial analysis resting upon Geographic Information System (GIS) by means of two stages. They encompass: 1) identifying the conditions of the existing street vendor Stabilization locations, and 2) formulating the alternative locations of street vendor Stabilization based on the criteria which entail the proximate main activities, the crowds of environment, and the availability of state-owned land. The result of spatial analysis indicates that there are 19 alternative locations in Surakarta which are aligned with the criteria and can be utilized for new street vendor Stabilization locations.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.43-54","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46629301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging Integrated Bike-Sharing with Existing Bus Rapid Transit (BRT) to Reduce Motor Vehicle in Central Jakarta Municipal","authors":"Daniella Daniella, Achmad Amri Dharma Wangsa","doi":"10.14710/geoplanning.6.1.13-20","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.13-20","url":null,"abstract":"Jakarta is one of the most congested cities in the world due to a plethora of motor vehicles used in the city. One of the government actions to address the issue is by implementing Bus Rapid Transit (BRT) as an alternative public transportation mode. However, according to the convenience walking distance standard, the BRT coverage the inhabitant to choose motor vehicle rather than walking. This paper purposes Bike-Sharing as the smart transportation mode to overcome such issue and predict the three potential places to establish sharing-bike stations according to the convenience walking distance standard. In this paper the walking distance is classified into 100 mater range (300 meter, 400 meter and 500 meter) projected using the euclidean distance principle. As the result for 300 meter standard, there are 809 potential bike-sharing stations consist of 164 main stations and 645 feeder stations, while the 400 meter standard needs 541 potential stations with 140 stations serve the BRT station directly and 401 stations as the feeder. Furthemore, with 500 meter standard, 359 stations consist of 131 main stations and 228 feeder stations is needed.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.13-20","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48321991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EVALUATION OF MODIS-DERIVED LST PRODUCTS WITH AIR TEMPERATURE MEASUREMENTS IN CYPRUS","authors":"A. Georgiou, Stefani Varnava","doi":"10.14710/GEOPLANNING.6.1.1-12","DOIUrl":"https://doi.org/10.14710/GEOPLANNING.6.1.1-12","url":null,"abstract":"Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to ground-based near surface air (Tair) measurements obtained from 4 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean 8-day value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlations (r > 0.96) and biases ranging from 1.9oC to 4.1oC. MODIS capture overall variability with a slightly systematic overestimation of seasonal fluctuations of surface temperature. For the evaluation of intra-seasonal temperature variability, MODIS showed biases up to 6.7oC in summer with a tendency to overestimate the variability while in cold seasons, limited biases were presented (0.10oC ± 0.50oC) with a tendency to underestimate the variability. Finally, there was no indication of tendency for MODIS to systematically under- or overestimate the amplitude of the inter-annual variability analysis. The presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. Overall, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/GEOPLANNING.6.1.1-12","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45589560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Distribution of Potential Area for Community Forest Development in Grindulu Watershed","authors":"A. Miardini, P. D. Susanti","doi":"10.14710/geoplanning.6.1.73-80","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.73-80","url":null,"abstract":"The effect of deforestation on environmental degradation shifted the orientation of forest management into carrying capacity of the watershed. Based on Law No. 41/1999 on Forestry, mandates adequacy forest area defined a minimum of 30% of the watershed area which fulfilled by public forest and private forest. State forest area has limitations, so the development of community forests is needs for optimal forest area in a watershed is required. The purpose of this study was to determine the spatial distribution of potential areas for community forest development in Grindulu Watershed. The potential of community forest was examined through an interpretation of Landsat 8 of 2016 Path/Row 119/668 for land availability and the transformation of NDVI (Normalized Difference Vegetation Index) as the density classifier. The classification of forest density was low density class of 5148.12 hectares or 7.20% (NDVI = 0 to 0.356), moderate density class of 12,076.39 hectares or 16.88% (NDVI = 0.356 to 0.590), and high density class of 54,294.04 ha or 75.92% (NDVI = 0.590 to 0.841). The land available for prioritized community forest development was 37,774.40 hectares (52.82%) in the form of dry-fields, shrubs, grasses, farms, which were located outside the protected areas and production forest. Based on the assessment of field surveys which were conducted proportionally at 89 samples, known good accuracy results by 0.84. Potential area for community forest development was 31,281.54 ha (43.74%) including in Pacitan (9 districts) of 29,111.98 hectares, Ponorogo (5 districts) of 263.29 hectares, and Wonogiri (2 districts) of 1,906.27 hectares.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.73-80","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48565941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monte Carlo Simulation for Outlier Identification Studies in Geodetic Network: An Example in A Levelling Network Using Iterative Data Snooping","authors":"M. T. Matsuoka, V. F. Rofatto, I. Klein, Alexandre Gomes, M. Guzatto","doi":"10.14710/geoplanning.6.1.21-30","DOIUrl":"https://doi.org/10.14710/geoplanning.6.1.21-30","url":null,"abstract":"Today with the fast and powerful computers, large data storage systems and modern softwares, the probabilities distribution and efficiency of statistical testing algorithms can be estimated using computerized simulation. Here, we use Monte Carlo simulation (MCS) to investigate the power of the test and error probabilities of the Baarda’s iterative data snooping procedure as test statistic for outlier identification in the Gauss-Markov model. The MCS discards the use of the observation vector of Gauss-Markov model. In fact, to perform the analysis, the only needs are the Jacobian matrix; the uncertainty of the observations; and the magnitude intervals of the outliers. The random errors (or residuals) are generated artificially from the normal statistical distribution, while the size of outliers is randomly selected using standard uniform distribution. Results for simulated closed leveling network reveal that data snooping can locate an outlier in the order of magnitude 5σ with high success rate. The lower the magnitude of the outliers, the lower is the efficiency of data snooping in the simulated network. In general, considering the network simulated, the data snooping procedure was more efficient for α=0.01 (1%) with 82.8% success rate.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/geoplanning.6.1.21-30","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44962451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"THE INFLUENCE OF SPRAWL DEVELOPMENT, INCOME, AND INFRASTRUCTURE ON ENERGY CONSUMPTION IN CENTRAL JAVA PROVINCE, INDONESIA","authors":"I. Buchori, Angrenggani Pramitasari, A. Sugiri, A. W. Sejati, M. Maryono, Y. Basuki","doi":"10.14710/GEOPLANNING.5.2.189-204","DOIUrl":"https://doi.org/10.14710/GEOPLANNING.5.2.189-204","url":null,"abstract":"Energy consumption is influenced by many factors. Sprawl development is often alleged as one of its driving factors. Other factors like the increase of community welfare and the improvement of regional infrastructures are often indicated to trigger energy consumption. This study is aimed at investigating the influence of sprawl development and other relevant factors on the energy consumption in Central Java Province, Indonesia. Other variables denoted to influence energy consumption used in this study are road density, people’s income represented by local Gross Domestic Product (GDP) per capita, and GDP growth rate. The observed energy is limited on vehicle fuels. After investigating the significance of correlations among variables, a multiple regression model is employed. By eliminating GDP per capita because of its multicollinearity with other dependent variables, the developed formula shows that fuel consumption is generated by 47.842 of sprawling index, added by 17.216 of road ratio and 17.5 of GDP growth rata, and reduced by a constant of 26.180. These measurements are expected to be useful for urban and regional managers in developing their region, especially in estimating the fuels’ consumption considering the determined regional policies.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/GEOPLANNING.5.2.189-204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45668577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Minimum Noise Fraction on Multispectral Imagery Data for Vegetation Canopy Density Modelling","authors":"A. M. Syarif, Ignatius Salivian Wisnu Kumara","doi":"10.14710/GEOPLANNING.5.2.251-258","DOIUrl":"https://doi.org/10.14710/GEOPLANNING.5.2.251-258","url":null,"abstract":"Minimum Noise Fraction (MNF) is known as one of the method to minimize noise on hyperspectral imagery. In addition, there are not many studies have tried to show the effect of MNF transform on multispectral data. This study purposes to determine the effect of MNF transform on the accuracy level of vegetation density modeling using 10 meters Sentinel-2A spatial resolution (multispectral data) and to know the cause. The study area is located in parts of Sapporo City, Hokkaido, Japan. Vegetation density is modelled through vegetation index approach, Normalized Difference Vegetation Index (NDVI). The results show that the coefficient correlation of vegetation density data and vegetation index regression after MNF transformation (0.801623) has higher value than the same regression without the MNF (0.794481). However, better correlation does not represent the better accuracy on vegetation density modeling. Accuracy calculation through standard error of estimate shows the use of MNF in multispectral data for vegetation density modeling causes the decrease of model accuracy value. The accuracy of vegetation density model without involving MNF transformation reached 91.402 %, while the model accuracy through MNF transformation before vegetation density modeling reached 90.889 %. The insignificant increased accuracy is occurred due to the limited number of multispectral image information compared to hyperspectral image data. ","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/GEOPLANNING.5.2.251-258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48518366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}