International Journal of Geoinformatics https://journals.sfu.ca/ijg/index.php/journal <p>ISSN 2673-0014 (Online)<br />ISSN 1686-6576 (Printed)</p> <p><strong>Online version description for website</strong><strong> </strong></p> <p><strong><em>International Journal of Geoinformatics</em></strong> is a peer reviewed journal in the field of Remote Sensing, Geographic Information Systems (GIS), Photogrammetry and Global Positioning Systems (GPS). It publishes papers in the application of RS/GIS/GPS in various fields: environment, health, disaster, agriculture, planning, development, business etc. It has an International Editorial Board and a panel of Peer Reviewers to ensure the quality of research papers. This will enhance citations and H-Index. International Journal of Geoinformatics is indexed by prestigious indexing services such as <strong>SCOPUS, EBSCO, British Library, Google Scholar, Geoscience Australia etc</strong>. We are trying for more indexing services to include IJG.<br /><strong>International Journal of Geoinformatics</strong> has been published in two formats, as printed version ISSN 1686-6576 and electronic version ISSN 2673-0014. The first printed edition has been published since 2005 and now years 12 and also electronic version has been published in Vol. 1, No. 1, March, 2005.</p> Geoinformatics International en-US International Journal of Geoinformatics 1686-6576 Modeling Urban Growth and Land-Use changes using GIS Based Cellular Automata: Case of Benslimane in Morocco https://journals.sfu.ca/ijg/index.php/journal/article/view/2057 <p><em>Sustainable urban planning and management require reliable land change models, which can be used to improve decision-making. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries, however, there exist a very few studies showing the application of these models and their performances. The study encompasses spatio-temporal land use/land cover (LULC) monitoring (1989–2019) and urban growth modelling (1999–2039) of Benslimane, Morocco to deduce the past and future urban growth paradigm and its influence on varied LULC classes integrating geospatial techniques and Cellular Automata (CA). The study focused on scrutinizing the reliability of the CA algorithm to function independently for urban growth modelling, provided with strong model calibration. For this purpose, satellite data of four stages of time at equal intervals along with the population density, the distance to the city center, the slope and the distance to the roads are used. The satellite-based LULC during 1989-2019 reported an increase of 3.8 Sq. Km (variation of 318%) between 1989 and 2019. The spatial variation analysis using the principal component analysis (PCA) technique exhibit high similarity in classification ranging from 89% to 91%. The projected LULC exhibit that the urban area will increase to 5,044 Sq. Km in 2019, primarily in the west and southwest parts. Between 2019-2039, urban growth will replace and transform other LULC (net loss of 1,364 Sq. Km), followed by vegetation cover (net loss of 0.345 Sq. Km).</em></p> M. Benchelha F. Benzha H. Rhinane Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 1 14 Comparison of Logistics Time of R3A and R3B for Transportation of Lychee Product https://journals.sfu.ca/ijg/index.php/journal/article/view/2059 <p><em>This research presents the logistics management information system (LMIS) for the supply chain of lychee products of Phayao Province, Thailand. The main aim of this research is to develop a management application for Phayao’s agricultures to improve their competitive abilities on Chinese markets by utilizing a prediction method for traffic congestion based on both real-time and anticipated road traffic. The loss of productivity caused by traffic congestion has become a huge and increasingly heavy burden on Phayao farmers. Therefore, the prediction of urban road network traffic flow and the rapid and accurate evaluation of traffic congestion is of great significance to solve this problem. By using traffic data obtained by distance, road conditions, transportation safety, traffic density, and customs clearance, the local farmers in Phayao can deliver lychee products on time and reduce the loss of high emissions and environmental pollution caused by traffic congestion effectively.</em></p> T. Cheosuwan T. Udomsripaiboon Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 15 25 10.52939/ijg.v17i6.2059 The Comparison of Spatial Models in Peak Ground Acceleration (PGA) Study https://journals.sfu.ca/ijg/index.php/journal/article/view/2061 <p><em>This study was conducted to compare the performance of three different spatial analysis models: Inverse Distance Weighted (IDW), Ordinary Kriging,­­ and Regularized Spline interpolation technique to determine the best fit model representing Peak Ground Acceleration (PGA) in West Java Province, Indonesia. The three models are commonly used in spatial visualization, but have different calculation methods. The calculations were performed using available formulas while the spatial modeling was conducted using the algorithms in GIS software. Meanwhile, the accuracy of the spatial model and factual calculation was determined through the Root Mean Square Error (RMSE). The results showed differences for both spatial distribution and maximum and minimum values for each model. However, IDW was observed to be the model which approaches the factual value of the PGA calculation as indicated by its RMSE value of 0.772352 in comparison with the 7.169879 (Ordinary Kriging) and 1.140802 (Regularized Spline).</em></p> H.M Ihsan A.J. Astari A.S. Bratanegara S.A. Aliyan E.P. Wulandari Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 27 33 10.52939/ijg.v17i6.2061 Geo-spatial Assessment of Flood Vulnerability Areas of the Gaza Strip Towards Preparedness and Humanitarian Response Planning https://journals.sfu.ca/ijg/index.php/journal/article/view/2063 <p><em>Nowadays, flood and drought will become more common as climate change causes. Due to climate change consequences, flood occurrence and its impact on Gaza people have been of great concern to the Palestinian water authority, as it has a negative influence on various humanitarian and social issues. The hazards and damages resulted by flooding cause loss of life, property, displacement of people and disruption of socioeconomic activities. This research focuses on assessing Gaza Strip vulnerability to flooding using analysis of GIS-based spatial information. Not only did it consider the physical-environmental flood vulnerability, it also investigated social flood vulnerability aspects e.g., population densities. Soil and slope were considered to have the highest weight in the vulnerability mapping, as they represent the main factors in urban hydro-ecosystem structure. The long term average rainfall, a climate function factor, has the lowest weight, because it could be considered as a threat factor in addition to a vulnerability factor. This research demonstrates that urban area and population density as strong factors influencing flood vulnerability for humanitarian and saving life purposes. The findings of Geospatial analysis were used to map vulnerable areas likely to be affected in the event of flood hazard and suggest future interventions and related adaptation strategies in Gaza areas for flood mitigation</em>.</p> T. Eshtawi M. Abdellatif D. Matar Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 35 44 10.52939/ijg.v17i6.2063 Automatic Lineaments Extraction using the Line Algorithm in the Denguélé District (North West of Ivory Coast) https://journals.sfu.ca/ijg/index.php/journal/article/view/2065 <p><em>The aim of this work was to apply the LINE Algorithm (Segment Extraction Algorithm) on Landsat 8 images for automatic lineament extraction in the Denguélé district.</em> <em>The Landsat 8 images had previously been subjected to the technique of Principal Component Analysis (PCA).</em> After that, we implemented the LINE algorithm<em>.&nbsp; Indeed, the LINE algorithm uses the following six (6) parameters : RADI (Radius of the filter) for improving the quality of the input image, GTHR (Threshold of the contour gradient), LTHR (Threshold of the contour length), FTHR (Threshold of mounting error), ATHR (Angular difference threshold between two</em> <em>contours </em>)<em> and DTHR (Distance chaining threshold to link</em> <em>two contours ) for lineament discrimination.</em><em> Analysis of the principal components PCA 1, PCA2 and PCA3 of bands 1, 2, 3, 4, 5 and 7 of the Landsat 8 images shows that they contain respectively 79.57;</em> <em>15.88 and 2.15%, this represents overall 97.6% of all channels. 3468 lineaments were extracted.</em> <em>The minimum and maximum lengths of the lineaments extracted are respectively 4201.08 m and 16167.59 m and their cumulative length is 18&nbsp;919 517.9 m.</em> <em>The lineaments average lengths are 5.55 km;</em> <em>5.75 km;</em> <em>5.6 km and 5.40 km respectively for NE-SW, NS, E-W and NW-SE directions.</em> <em>The analysis of the directions of the lineaments using a rose diagram with 10 ° of frequency, shows that the dominant directions are NE-SW (31.83% of the total lineaments), EW (28.71% of the total lineaments) and NS (27.91% of the total lineaments).</em></p> H. Pinatibi T.J.H. Coulibaly M. Soro Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 45 58 10.52939/ijg.v17i6.2065 Towards a Reliable and Sensitive Deep Learning Based Approach for Multi-Ship Detection in SAR Imagery https://journals.sfu.ca/ijg/index.php/journal/article/view/2067 <p><em>Synthetic Aperture Radar (SAR) images show promising results in monitoring maritime activities. Recently, Deep learning-based object detection techniques have impressive results in most detection applications but unfortunately there are challenging problems such as difficulty of detecting multiple ships, especially inshore ones. In this paper, a three-step ship detection process is described and a reliable and sensitive hybrid deep learning model is proposed as an efficient classifier in the middle step. The proposed model combines the finetuned Inception-Resnet-V2 model and the Long Short Term Memory model in two different approaches: parallel approach and cascaded approach. In experiments, the region proposal algorithm and the Non-Maxima suppression algorithm are applied in the first and last step in the three-step detection process. The comparative results show that the proposed approach in cascaded form outperforms the competitive recent state-of-the-art approaches by enhancement up to 16.3%, 16.5%, and 18.9% in terms of recall, precision and mean average precision, respectively. Moreover, the proposed approach shows high relative sensitivity for challenged cases of both inshore and offshore scenes by enhancement ratios up to 81.88% and 24.58%, respectively in recall perspective.</em></p> M.A. Elshafey Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 59 70 Assessing the Hydrological and Sedimentary Reality of Amman/Zarqa Basin using the Soil and Water Assessment Tool https://journals.sfu.ca/ijg/index.php/journal/article/view/2069 <p><em>This study aims at analyzing and simulating the hydrological and sedimentary reality of Amman/Zarqa Basin using the Soil and Water Assessment Tool (SWAT) in order to support hydrological management plans for the basin; make the most of the available water resources in the basin; and build a hydrological database for the basin using climatic and hydrological data rendered by Jordan Meteorological Department. The study found that Amman/Zarqa Basin receives an average rainfall of 293.2 mm/year, the greater part of which is being lost by evaporation as 69.9% of the total precipitation is lost as a result of the actual evaporation process. On the other hand, the surface runoff receives 10.1% of the total precipitation on Amman/Zarqa Basin. The study concluded the need to intensify the reliance on the (SWAT) in the hydrological and sedimentary modeling processes of basins, as its results proved to be effective and efficient in the hydrological management of water basins and in the determination of the quantities of sediments produced by the runoff in the basin. Thus, it helps in determining the extent of feasibility of established hydrological projects such as the King Talal dam and determining the period taken by sediments to fill it.&nbsp; </em></p> A. Taran A. Al-Ghumaid F. Al-Mayouf Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 71 84 A GIS-Based Multicriteria Analysis of Land Suitability for Groundnut Crop in Nghe An Province, Vietnam https://journals.sfu.ca/ijg/index.php/journal/article/view/2071 <p><em>This study focuses on identifying the potential lands for growing groundnut in Dien Chau district of Nghe An province (Vietnam), where groundnut is one of the major crops and brings high income for farmers. Based on the ecological requirements of groundnut, six criteria, including Soil Type, Soil Texture, Soil Depth, Slope, Average Temperature, and Average Total Rainfall in the planting season, were used. The Analytic Hierarchy Process method, commonly used in agricultural land use planning, was utilized to determine each criterion's weights via experts’ opinions. A pairwise comparison matrix was established to support this assessment process. The results revealed that Soil Texture showed the highest weight (0.31727) for groundnut farming, which was followed by Average Temperature (0.21131), Soil Type (0.17426), and Soil Depth (0.13982). Slope and Average Total Rainfall were the lowest weight factors, with 0.08122 and 0.07612, respectively. The weighted sum overlay analysis was implemented by ArcGIS software to generate the spatial distribution of land suitability of groundnut. The land suitability map indicated that 6830.07 ha (22.26%) of the studied area was highly suitable (S1), 10413.85 ha (33.95%) was moderately suitable (S2), 4336.76 ha (14.14%) was marginally suitable (S3), and 424.99 ha (1.39%) was not suitable (N). The total area of constrained area, including Waterbody and Built-up Land, was 8671.39 ha, accounting for 28.27% of the total area. Finally, the proposed land for groundnut cultivation was 12928.69 ha. The outcomes of this study may be regarded as a good reference for local government in agricultural land use planning</em><em>.</em></p> D.L. Nguyen T.Y. Chou M.H. Chen T.V. Hoang T.P. Tran Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 85 95 10.52939/ijg.v17i6.2071 Pansharpening of Panchromatic Aerial Photographs by Combining Component Substitution and Multiresolution Analysis Fusion Algorithms https://journals.sfu.ca/ijg/index.php/journal/article/view/2073 <p class="PRec-Abstract"><span style="color: windowtext;">The monochromatic nature of aerial photographs may affect the accuracy of photogrammetric measurements. In this study, multispectral (MS) IKONOS images with 3.2 m spatial resolution are used to sharpen panchromatic (PAN) archival aerial photographs. An urban area with a variety of land use/cover (LULC) classes over the northeast region of Cairo city, Egypt has been selected. The proposed approach can be performed through two major steps. First and after pre-processing, Gram-Schmidt transform (GST) and wavelet fusion techniques were used to panshrpen the original MS bands. Second, a fuzzy majority voting (FMV) - based approach was designed to combine the results from the GST and wavelet techniques to predict the final high-resolution results. The results were visually, qualitatively, and quantitatively analyzed. Compared with GST and wavelet standard fusion techniques, the improved statistical indices, as well as the improved classification potential, confirmed the credibility of the proposed approach. </span></p> M. Salah Copyright (c) 2021 International Journal of Geoinformatics 2021-12-02 2021-12-02 17 6 97 109