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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 9 Documents
 1 
Search results for , issue "Vol 12, No 1 (2025)" : 9 Documents clear
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.
Automatic Image Processing for Detecting Courtyards Geo-Locations of Urban Fabric of ‎Mosul Old City Ismaeel, Emad Hani; Omer, Mazin Jaber; Al-Nima, Raid Rafi
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.12.1.1-14

Abstract

In the post-conflict periods, cities often suffer significant damage, requiring more effort to rebuild. However, proper reconstruction requires documentation of the previous urban fabric. Aerial photography is an important element in documenting the components of the urban fabric. In 2017, extensive destruction occurred in many areas of Mosul's Old City (MOC), with some districts suffering so much damage that the distinctive urban fabric was lost. The MOC is characterized by its dense urban structure and the presence of internal courtyards within its buildings. This paper aims to utilize historical aerial photographs to relocate the position of building courtyards in parts of the MOC urban fabric, as one of the first steps in a comprehensive plan to represent them in the absence of the necessary documents and surveys. The methodology proposed in this paper involves a series of automated image processing (AIP) stages, where the position of the courtyard can be determined in the form of a network whose geolocation can be easily identified. This study offers a stepwise and semi-automated methodology for courtyard location determination. Furthermore, this study demonstrates the efficacy of applying automated image processing techniques in the context of preventive conservation and protection of urban structures in historic cities. However, the study encountered limitations related to the type and accuracy of the available aerial images. Additionally, the potential use of more advanced software could yield more accurate results or facilitate the generalization of findings to other cities, a direction suggested for future research.
The Ecological Impact of Urban Expansion in Oasis Environments: A combined Cartographic and Landscape Analysis Dechaicha, Assoule; Arab, Walid; Alkama, Djamel
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.12.1.123-138

Abstract

Current patterns of urban expansion are mostly considered as impulsive, leading to numerous negative consequences for our biosphere. This disturbing fact has not gone unnoticed in the sprawling oasis cities of the Algerian Sahara, where palm groves are the primary victim. Furthermore, any approach taken to preserve oasis ecosystems requires considering ecological variables. In this perspective, the present study seeks to highlight the spatial growth process of the Laghouat oasis in southern Algeria, during the period 1986 - 2019. The methodology employed is based on the supervised classification of four Landsat satellite images to initiate a cartographic analysis and a landscape quantification of the land use evolution. The analysis is focused on two LUC classes: built-up areas and palm groves. The results of the cartographic analysis highlighted two completely opposite spatiotemporal trends: a significant growth of built-up areas, against a considerable decline in palm groves. The monitoring of the landscape metrics also revealed two different behaviours: growth by densification and elongation of the urban fabric, versus progressive morcellation and fragmentation of the palm groves. These findings pointed to the negative impact of uncontrolled extensions on both the palm groves and the overall oasis ecosystem. This research highlighted the importance of landscape metrics in assessing various forms of spatial urban growth and may support urban planners in choosing the optimal solutions for oasis sustainability.

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