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INDONESIA
Indonesian Journal of Geography
Published by Universitas Gadjah Mada
ISSN : 00249521     EISSN : 23549114     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Indonesian Journal of Geography ISSN 2354-9114 (online), ISSN 0024-9521 (print) is an international journal of Geography published by the Faculty of Geography, Universitas Gadjah Mada in collaboration with The Indonesian Geographers Association. Our scope of publications includes physical geography, human geography, regional planning and development, cartography, remote sensing, and geographic information system. IJG publishes its issues three times a year in April, August, and December.
Arjuna Subject : -
Articles 656 Documents
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Spatial Analysis of Developmental Population Data in Iraq Using Geographic Information Systems Basher Faisal Alsaadi; Majid Saddam Salim
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.112732

Abstract

This study integrates population and socio-economic data into key development indicators, including the Human Development Index (HDI) and its components (income, education, and health), along with population density, poverty, illiteracy, school enrollment, and health service coverage. The objective is to construct a spatial database and assess regional development disparities across Iraqi governorates. A mixed spatial–statistical approach was applied. Statistical analysis was conducted using SPSS, including descriptive statistics, Pearson correlation, multiple linear regression, and cluster analysis to examine relationships among variables and classify governorates into homogeneous development groups. Geographic Information Systems (GIS) using ArcGIS 10.8 were employed to build a spatial database, integrate socio-economic data with administrative boundary maps, and produce thematic maps for spatial visualization of development patterns and disparities. The results reveal significant spatial inequalities in Iraq. Northern governorates show higher levels of development, with HDI reaching 0.73 in Erbil, while central and southern governorates record lower values, down to 0.58 in Muthanna. Strong negative correlations were found between HDI and both poverty and illiteracy, while positive relationships were observed with education and health indicators. The study concludes that integrating GIS with statistical analysis enhances the identification of development gaps and provides a robust evidence base for sustainable spatial planning and policy formulation.Received: 2025-11-02 Revised: 2026-06-12 Accepted: 2026-07-28 Published: 2026-08-05
SWAT-Based Assessment of Land Use Dynamics on Precipitation–Discharge Interactions in the Sagileru Basin, India Dinagarapandi Pandi; Muthukrishna vellaisamy Kumarasamy
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.113880

Abstract

Hydrological variability in river basins is strongly influenced by LULC changes, particularly in tropical regions where rapid forest transformation and agricultural expansion alter rainfall–runoff processes. Understanding how these dynamic land surface changes affect precipitation–discharge relationships is essential for sustainable water and soil resource management. This study examines the impact of multi-temporal LULC changes on precipitation–discharge interactions in the Sagileru Basin, a tropical sub-catchment of the Pennar River basin, Andhra Pradesh, India. The SWAT hydrological model was implemented for the period 1990–2020 using topography, soil characteristics, daily meteorological data, and dynamic LULC datasets from 2000, 2010, and 2020. Model calibration and validation were carried out using SWAT-CUP (SUFI-2) with fourteen sensitive hydrological parameters and observed monthly discharge data. Model performance was evaluated using the coefficient of determination (R²), Nash–Sutcliffe efficiency (NS), and percentage bias (PBIAS). In addition, precipitation–discharge correlations were analyzed at the sub-catchment scale under different LULC scenarios. The model showed good performance, achieving R² and NS values of approximately 0.8 and low PBIAS (<1.0) during both calibration and validation periods. Results indicate that forest-dominated sub-catchments exhibit stronger precipitation–discharge correlations, whereas agricultural expansion and wasteland formation reduce correlation values by 0.12–0.30 in selected sub-catchments. Compared to similar SWAT-based studies conducted at basin scales, this study highlights pronounced spatial variability at the sub-catchment level. The integration of dynamic LULC analysis with long-term precipitation–discharge relationships provide valuable insights for prioritizing soil conservation and water management strategies in tropical watersheds.Received: 2025-12-05 Revised: 2026-04-07 Accepted: 2026-05-21 Published: 2026-08-12  
Analysis of Urban Development Dynamics and Flood Disasters in Samarinda City Alwin Alwin; Rini Rachmawati; Iswari Nur Hidayati; Slamet Suprayogi
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.115237

Abstract

Samarinda City as an economic, administrative center and a supporting region for the Capital City of Nusantara, It has experienced very good dynamics in both physical and socio-economic aspects. However, this dynamic development has been accompanied by an increase in the intensity and frequency of flooding disasters. The purpose of this study is to analyze the development of the city of Samarinda and its relationship to the phenomenon of flooding. The research uses the DPSIR (Driving forces-Pressures-States-Impacts-Responses) approach to examine the factors and impacts that will arise with economic, social, infrastructure, information technology, environmental, and disaster indicators. Spatial data analysis is carried out using GIS based on Landsat imagery in the period (2010-2025). The results show that the development of Samarinda City from 2010-2015 was very significant, with a transformation towards urbanization with a spatial pattern resembling an urban-rural mix towards an urban expansion zone pattern. This dynamic shows a shift in the morphology of urban space, with natural land being transformed into built-up space. The development of Samarinda from 2020-2025 indicates a phase of consolidation of built-up areas, where the pattern of urban sprawl is transforming into a regional metropolitan city. Land use change and mining expansion contribute to economic growth but cause the loss of the city's ecological functions, thereby increasing its vulnerability to flooding. Development of Samarinda. The results of the DPSIR analysis indicate that urbanization increases the demand for residential areas 10,158.12 ha (115%), Commercial Area 11941.08 ha (287%) leading to a reduction in forest area of 6,722.04 ha (64%). declining ecological functions, and vulnerability to flooding in the of Samarinda City. The results show that the development of Samarinda City from 2010-2015 was very significant, with a transformation towards urbanization with a spatial pattern resembling an urban-rural mix towards an urban expansion zone pattern.Received: 2026-01-06 Revised: 2026-04-06 Accepted: 2026-07-28 Published: 2026-08-08
Monitoring and predicting land use/land cover changes in the Da River basin in 2035 based on remote sensing and GIS technology Nguyen Tien Quang; Dang Thanh Tung; Truong Van Anh; Ngo Le An; Nguyen Xuan Tung
Indonesian Journal of Geography Vol 58, No 2 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aimed to analyze Land Use/Land Cover (LULC) dynamics in the Da River basin, approximately 52,000 km2, during the period 2015–2025 and to predict future changes up to 2035. Landsat-8 imagery processed on the Google Earth Engine (GEE) platform was used to generate multi-temporal LULC maps. A total of 6 LULC classes were classified using the Random Forest (RF) algorithm. The classification results reported high accuracy, with Overall Accuracy ranging from 91% to 94% and Kappa coefficients between 0.86 and 0.90. Furthermore, an integrated Cellular Automata–Artificial Neural Network (CA-ANN) model was used to simulate future LULC change up to 2035. This model integrated spatial influencing factors such as distance to roads, distance to rivers, elevation, slope, and neighborhood effects. Validation suggested excellent model performance with training/validation error < 0.02. The results showed that there was a continuous urbanization trend, with the built-up area projected to increase from 5.35% to 9.15% of the basin area by 2035, while Forest and Agricultural land were expected to decline. Bare land, Water bodies, and Other land exhibited relatively minor changes. These provided important information for sustainable land-use planning, watershed management, flood-risk mitigation, and environmental protection in the Da River basin. Moreover, CA-ANN model performed better than traditional statistical approaches because the concept captured nonlinear spatial processes and neighborhood interactions. These results supported land-use planning and River basin management, particularly for flood risk mitigation and environmental protection in the Da River basin.
Interpreting Hindu-Buddhist Archaeological Remains Distribution in Lasem, Central Java, Indonesia: A Landscape Archaeology Approach Andi Putranto; R Suharyadi; Eko Haryono; Lutfi Muta&#039;ali
Indonesian Journal of Geography Vol 58, No 2 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.117884

Abstract

Historical landscapes maintain enduring records of human–environment interactions, which can be analyzed through spatial patterns present in the landscape. Within geographical studies, landscape ecology offers a framework for interpreting these patterns by linking human activity to ecological gradients and spatial structure. This study investigates the spatial distribution of classical period archaeological remains in Lasem, North Java, employing a landscape archaeology approach that integrates ecological variables and spatial configuration.  The research conceptualizes archaeological remains as spatial patches situated within diverse ecological zones, such as volcanic uplands, alluvial plains, and coastal plain. Spatial analysis incorporated elevation, landform units, soil types, hydrological proximity, and distance-based relationships to key landscape elements. These variables were integrated with a qualitative spatial narrative to interpret how environmental conditions influenced historical land-use strategies.  The results show that the distribution of archaeological patches is closely linked to specific ecological settings, especially transitional zones between upland and alluvial landscapes and areas with reliable access to water resources. Archaeological remains are not evenly distributed but instead form patterned clusters that reflect adaptive responses to topography, hydrology, and land suitability. This spatial structure indicates that landscape configuration significantly influenced human activity during the classical period in Lasem.  By integrating landscape ecology with archaeological spatial data, this study highlights the value of geographical approaches for interpreting historical landscapes. The findings contribute to broader discussions on landscape structure, long-term land-use processes, and the application of ecological concepts to historical spatial analysis.Received: 2026-03-27 Revised: 2026-07-01 Accepted: 2026-04-14 Published: 2026-08-20  
Modeling Urban Population Dynamics Using Spatial Deep Learning: A Comparative Framework for Baghdad and Basra Yasir Aldabbagh
Indonesian Journal of Geography Vol 58, No 2 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.120098

Abstract

This study compares Linear Regression, Random Forest (RF), CNN, and Conv1D-LSTM+Attention for estimating WorldPop-derived population density on 500 m grids in Baghdad and Basra, Iraq (2015–2020). The raw panel contained 13,530 cell-year records, with 12,678 retained after excluding zero-population cells. Alongside conventional random partitions, all four models were evaluated using leave-one-quadrant-out spatial cross-validation. Mean spatial R² was negative for every model in both cities; for example, RF achieved −0.751 ± 1.130 in Basra and −1.096 ± 0.359 in Baghdad. These results contrast with random-split Conv1D-LSTM+Attention performance (R² = 0.833 in Basra; 0.199 in Baghdad), indicating that random partitions overstate out-of-area predictive skill. Moran’s I confirmed strong spatial dependence (Baghdad = 0.847; Basra = 0.946; both p = 0.001). In Basra, a naïve persistence baseline achieved R² = 0.692. Explainability analyses agreed strongly in Basra, where CNN permutation importance and RF-SHAP both identified nighttime lights as dominant; agreement was partial in Baghdad, where CNN ranked LST first while RF-SHAP ranked nighttime lights first. Bidirectional CNN and RF transfer increased RMSE by 33.6–303.8%, indicating poor cross-city portability. Overall, spatial validation is essential for satellite-based population modeling, and WorldPop circularity means the models primarily approximate an existing population surface rather than independent census ground truth.Received: 2026-06-02 Revised: 2026-08-11 Accepted: 2026-08-24 Published: 2026-08-27   

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