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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 181 Documents
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Groundwater Nitrate Modeling in Tehran Metropolis Using Artificial Neural Network and Kriging Methods Nickbeen, Fatemeh; Salmanmahiny, Abdolrassoul
Geoplanning: Journal of Geomatics and Planning Vol 11, No 2 (2024)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.11.2.177-188

Abstract

This study examined the relationship between groundwater quality and land use in Tehran. For this purpose, the possible relationship between the types of land uses and the concentration of nitrate in groundwater parameters was modelled using a Multi-Layer Perceptron (MLP) artificial neural network in geographic information system (GIS). The optimal network model was selected based on the mean root mean square error (RMSE) and correlation coefficient. Interpolation through Kriging was also performed to compare its results with those of the predicted model derived from an artificial neural network. The results showed that the neural network has a high capability for predicting and modelling groundwater nitrate concentration compared to the Kriging method. The high accuracy (RMSE: 0.003) of the neural network makes it a useful tool in relevant management issues. Our results of network sensitivity analysis were similar to scientific findings regarding the factors influencing the formation of nitrate in groundwater. Model outputs in the form of maps, tables, and graphs allowed the study of the role of each variable and the extent of its impact on groundwater quality. Performing various simulations and modelling of groundwater pollution provides an effective benchmark towards optimizing the management, control, planning, and decision-making in urban areas and can lead to economic and environmental savings.
Utilizing Open Access Spatial Data for Flood Risk Mapping: A Case Study in the Upper Solo Watershed Jumadi, J; Danardono, Danardono; Priyono, Kuswaji Dwi; Roziaty, Efri; Masruroh, Heni; Rohman, Arif; Amin, Choirul; Hadibasyir, Hamim Zaky; Fikriyah, Vidya N.; Nawaz, Muhammad; Sattar, Farha; Lotfata, Aynaz
Geoplanning: Journal of Geomatics and Planning Vol 11, No 2 (2024)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.11.2.189-204

Abstract

Indonesia is experiencing a rise in natural disasters due to its geographical position within a tropical region, with the Upper Solo River watershed exhibiting a heightened risk of flooding. This region has already suffered numerous floods due to excessive precipitation and insufficient drainage. Susceptibility, hazard, and risk studies have been conducted to investigate this phenomenon but have been limited to specific regions within the catchment area. This study aims to construct a GIS-based flood risk model using Open-Access Spatial Data (OASD) based on diverse physical characteristics, urbanization levels, and population. We used several OASD, including SRTM, Sentinel 2 MSI, GPM v6, NASA-USDA Enhanced SMAP Global Soil Moisture Data, GHS-SMOD R2023A - Global Human Settlement Layers, and GHSL: Global Population Surfaces 1975-2030 (P2023A). The model integrates the risk parameters to identify flood risk using a weighted overlay in ArcGIS. The results demonstrate spatial heterogeneity in flood risk throughout the watershed. The result also reveals that Surakarta City, with a high proportion of its area in the 'High' (57.3%) and 'Very High' (29.54%) risk categories, is at the highest risk of flooding within the watershed. The study enhances understanding of this topic by comprehensively evaluating flood hazards, vulnerabilities, and risks. It highlights the significance of utilizing low-cost OASD to improve flood preparedness and response strategies.
Statistical Analysis of Short-Term Shoreline Change Behavior Along The Southern Cilacap Coasts of Indonesia Mutaqin, Bachtiar W.; Munandar, Ariko V.; Jatmiko, Jatmiko; Harini, Rika; Purnama, Ig.L. Setyawan
Geoplanning: Journal of Geomatics and Planning Vol 11, No 2 (2024)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.11.2.165-176

Abstract

There is a threat of extreme waves and a moderate risk level of coastal erosion in Bunton Village. Based on the preliminary assessment, there is huge erosion of the shoreline and visible changes in the shoreline temporally. However, there is no statistical data on short-term shoreline change behavior in this area. Hence, this research aims to analyze statistically the short-term shoreline change behavior to understand the conditions and phenomena that occur on the coast of Bunton Village. Landsat images spanning the years 2002 to 2022, with recording intervals of 5 years each, were used to identify the shoreline data, which was later analyzed using the Digital Shoreline Analysis System (DSAS). Statistical analyses of short-term shoreline change behavior were obtained using the End Point Rate (EPR) and Net Shoreline Movement (NSM) approaches. Over a 20-year period, the Bunton coastal area experiences dynamic changes that are primarily due to erosion, with an average distance change of -255.5 meters and an average speed of -14.6 meters per year (very high erosion). The existence of the electric steam power plant (ESPP) in Adipala, which built a breakwater in 2012, has been proven to increase the erosion process. Shoreline change in this area can affect various landuses and tourism activities as well as trigger environmental problems in the Bunton coastal area.
Modelling Itasy Lake Water Quality by Long Short Term Memory (LSTM) using Landsat8 Data Frederick, Randrianiaina Jerry Jean Christien; Itokiana, Rakotonirina Rija; Rasoloariniaina, Jean Robertin; Razafindramisa, Fils Lahatra
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.45-56

Abstract

Modeling lake water quality is very important to preserve and protect this resource. Several algorithms can be used to model lake water quality using in-situ measurement data. This work used The Long Short-Term Memory (LSTM) deep learning (DL) architecture to obtain models for modeling and predicting water quality parameters of Lake Itasy depending on the reflectance of Landsat8 OLI. The main purpose of this study was to identify the appropriate LSTM model in function of the optimization algorithms: Adagrad, RMSprop and Adam, in order to do the estimation on the date provided, according to the date of satellite image acquisition. The obtained results showed the performance of the developed LSTM model, with an Adaptive Moment Estimation (Adam) optimization algorithm that provided an excellent concordance between the collected and simulated water quality parameters. Moreover, the correlation coefficient (R²) was 0.993 for the conductivity and 0.977 for the dissolved oxygen concentration. The root mean square error (RMSE) values for conductivity and dissolved oxygen concentration were 0.898 and 0.228 respectively.  After choosing the best model, the water quality parameters of the Lake Itasy were estimated on May 25th 2020. The conductivity ranged from 46.8 µS.cm-1 to 66.5 µS.cm-1, and the dissolved oxygen concentration from 6.5 mg/L to 9.1 mg/L. These values indicate that the water from Lake Itasy respects the Malagasy norms in terms of conductivity and dissolved oxygen concentration
Tourism Potential Zone Mapping Using MCDM and Machine Learning Models in The State of Madhya Pradesh India Raha, Shrinwantu; Deb, Sayan
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.95-122

Abstract

The rich and diverse tourism attractions of Madhya Pradesh have long been recognized, but the Tourism Potential Zones (TPZs) have yet to be clearly identified. This research aimed to uncover these hidden potentials using a combination of Multi-Criteria Decision Making (MCDM) and machine learning techniques. TPZ was predicted using a approaches, including Analytic Hierarchy Process (AHP), Linear Model (LM), Elastic Net Model (EN), and K-Nearest Neighbors (KNN). Further, by combining the above models, a new ensemble model (AHP-LN-EN-KNN ensemble) was prepared. We followed the ROC-AUC (Area Under Curve) and Root Mean Squared Error (RMSE) as evaluation measures. The findings reveal a landscape of promise, with each model with accuracy levels ranging from 81.4% to 90.6%. The AUC values for the models ranged from approximately 70% to 95%, while the RMSE values ranged from 0.8 to 1.3. The ensemble model appeared with better accuracy (for training set 0.92 and for test set 0.88), higher AUC value (for training set 94.5% and for test set 89.4%) and the lowest RMSE (i.e., 0.71) value. On the other hand, the AHP was identified with higher combined RMSE (i.e., combined RMSE 1.08) and diminished AUC (i.e., for training set 70.1% and test set 70.2%). The northern, south-western, and middle regions emerge as high-potential areas, whilst the south-western edges languish with less promise. Meanwhile, the north-western expanse offers a scene of moderate potential. These findings not only inform, inspire, laying a foundation for Madhya Pradesh's long-term tourist growth.
Modelling Environmental Impact of Sea Dike and Toll Road in Semarang-Demak Indonesia Based on Satellite Imagery Data Widjonarko, Widjonarko; Purnaweni, Hartuti; Maryono, Maryono; Soeprobowati, Tri Retnaningsih
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.31-44

Abstract

The construction of the sea dike and Semarang-Demak toll road has severed the mangrove ecosystem inside the dike, as well as increased greenhouse gas impacts due to transportation activities and the growth of built-up areas around the dike and toll road. The aim of this research is to formulate a regression model based on spatial data that can be used to measure the impact of transportation activities and building intensity on LST. The data used in this study are the number of motorized vehicles crossing the main roads in Semarang City and LST obtained from the Landsat 8 thermal infrared sensor band in 2013 and 2019. This research utilizes Geographic Information System, Remote Sensing, and statistical methods to model the environmental impact of the sea dike and toll road development. This model used to predict the environmental impact of the sea dike and Semarang-Demak Toll Road in the future. The result shows that the increase in the number of motorized vehicles and building intensity has a high contribution to LST. Every additional 1,000 passenger cars on a road will make LST increase from 0.0150C to 0.0380C, whereas every 10% increase in land intensity will make LST increase by 0.030C. In addition, there is an increase in the LST value of 300C from 260C previously. This model is expected to provide input for each stakeholder to mitigate the potential environmental impacts of the Semarang-Demak Sea dike and toll road in the future, and hope that the Semarang-Demak Sea dike.
Land Cover Classification of Indonesian Archipelago Using Digital Spectroscopy to Support Spatial Planning in Indonesia Pamungkas, Guntur Bagus; Firmansyah, Muhammad Reffi; Sari, Ratna; Tamara, Anindya Putri; Zainul, Rahadian
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.57-68

Abstract

In the context of urban and regional planning, this study aims to produce land classification products covering 230 paths/rows throughout Indonesia, which can serve as an important tool in supporting planning and research projects. The research method used combines remote sensing in Geographic Information Systems (GIS) with the utilization of spectroscopy through QGIS software with Dzetsaka plugins (semi-automatic classification tools). Land cover classifications, which include water bodies, vegetation canopies, green open spaces, bare grounds, settlements, and built-up areas, as well as additional classifications of cloud cover, provide a comprehensive overview of land conditions in Indonesia. Based on the results of the study, the average distribution of land classes reached 10,116. The standard deviation was 14,786, which shows the level of variation in the data against the average value, with the higher value indicating the most significant variation in land classification. This study offers a more potential alternative by using Landsat 8 OLI 2022 satellite imagery data from the USGS as a basis for a more in-depth and accurate analysis of land classification. Thus, the results of this study not only contribute to mapping and understanding land use in Indonesia but also provide useful tools for supporting natural resource planning and management, as well as infrastructure development and sustainable development policies in Indonesia
Urban Morphology and Development of Mae Hong Son Old City: A Geospatial Analysis for Sustainable Heritage Conservation O-in, Supharerk
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.69-78

Abstract

This study investigates the urban morphology and development of Mae Hong Son's old city through geospatial analysis to support sustainable heritage conservation. It focuses on spatiotemporal changes in urban expansion by utilizing aerial photographs, high-resolution satellite imagery, and geospatial techniques including Change Detection and Kernel Density Estimation (KDE), to analyze the city’s development patterns from 1971 to 2023. The results indicate that the built-up area increased significantly from 0.47 km² in 1971 to 9.71 km² in 2023, while the number of buildings grew from 2,855 to 11,948 during the same period. These findings reveal significant physical transformations, primarily driven by economic growth and increased settlement in the early 20th century. Urban growth predominantly occurred in the northern part of the city, constrained by surrounding mountains and rivers. Despite modern urban development, Mae Hong Son has retained its unique identity through a combination of traditional wooden structures and contemporary architecture. The findings emphasize the need to balance modern urban expansion with the preservation of cultural heritage and offer insights for sustainable conservation planning in historic cities and it contributes to understand the historical urban dynamics of Mae Hong Son’s old city and provides recommendations for sustainable heritage conservation planning.
Coastal Metropolitan Dynamics in Poland's Tri-City and Indonesia's Semarang: NTL, BLFEI, and OBIA in Google Earth Engine Zaki, Abdurrahman; Jaskuła, Joanna
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.15-30

Abstract

The increasing global urbanization, particularly in coastal regions, coupled with the risks of climate change and land subsidence, underscores the need to monitor coastal urban development for sustainability. This study focused on the coastal metropolitan regions of Poland's Tri-City and Indonesia's Semarang, employing GIS, remote sensing (RS), and cloud computing. By integrating nighttime light (NTL) and the Built-Up Land Features Extraction Index (BLFEI) through Google Earth Engine (GEE) and Object-Based Image Analysis (OBIA), the study aimed to gain insights into urban development trends. The methodology encompassed image collection, analysis, and classification over three decades (1992, 2007, 2022). Despite efforts to enhance accuracy through built-up masking in subsequent years, the methodology achieved an overall accuracy of 95% for the 2022 maps, while maps in 1992 and 2007 fell short (overall accuracy ranging from 0.81 to 0.90) in comparison. The analysis revealed a gradual expansion of built-up areas in both regions, with Gdynia and Gdańsk emerging as primary drivers in the Tri-City metropolitan region and Semarang as the primary driver in the Semarang metropolitan region. Notably, the Semarang metropolitan region exhibited an increase in waterbody areas, attributed to coastal flooding and land subsidence challenges.
Post-Seismic Surface Deformation of The Tarakan Earthquake in 2015 Using The DInSAR Technique Pertiwi, Imanuela Indah; Trismahargyono, Trismahargyono; Marniati, Marniati; Purba, Joshua
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.79-94

Abstract

Deformation can help predict the presence and severity of an earthquake. SAR image data can be used to calculate post-seismic surface deformation using the InSAR and DInSAR methods. DInSAR (Differential Interferometric Synthetic Aperture Radar) is a well-established technology for monitoring subsidence and uplift with millimeter precision. This study uses SAR imagery to detect surface deformation caused by a magnitude M 6.1 earthquake on December 21, 2015, at 01:47:37 WIB in Tarakan Regency, North Borneo. The data used is Sentinel-1 satellite imagery in SLC (single-look complex) format, with a master image from December 18, 2015 (3 days before the earthquake), and a slave image from January 11, 2016 (21 days after). The interferogram generated by the Tarakan earthquake shows deformation patterns radiating in three directions: northeast, southeast-southwest, and southwest-northwest. Tarakan City, located south-southwest of the epicenter, experienced the highest subsidence deformation of 0.001–0.035 meters. On December 21, 2015, the Tana Tidung I Regency area, 33 kilometers southwest of the epicenter, showed the highest uplift deformation (0.019–0.079 meters). The largest uplift in Tana Tidung II Regency (0.069 meters), about 10 kilometers north of the epicenter, occurred near the fault zone. Surface deformation due to the Tarakan earthquake contributes to seismic hazard assessment in North Borneo and indicates other locally active faults. Uplift to the east and subsidence to the west of the epicenter suggest an oblique-normal fault, with dominant strike-slip motion and normal (downward) fault blocks to the west.

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