International Journal of Geoinformatics <p><strong>Aim &amp; Scope</strong></p> <p>ISSN 2673-0014 (Online) | ISSN 1686-6576 (Printed)</p> <p><strong>International Journal of Geoinformatics</strong> aims at publishing scientific and technical developments in the diverse field of Geoinformatics encompassing Remote Sensing, Photogrammetry, Geographic Information System, and Global Positioning Systems. Papers dealing with innovations in theoretical, experimental and system design aspects are welcome. Routine applications without significant findings will not be considered.</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.</p> <p><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. From 2014, IJG was published both 4 issues (March, June, September and December) <strong>hardcopy and online</strong>. Online version is enhancing the citations and also found easy to access by reader.</p> <p>Therefore, starting 2021, IJG will publish only online version but <strong>numbers of issue are increased to 6 issues as (February, April, June, August, October and December).</strong></p> <p>Please register (<a href="">Subscribe with Us</a>) and be a member to have a full access authority and avail many benefits. However, "Open Access" papers can be freely accessed and downloaded.</p> <p><a title="Subscribe with Us" href=""><img src="" alt="" width="10" height="6" /></a></p> Geoinformatics International en-US International Journal of Geoinformatics 1686-6576 Spatio-temporal Analysis of Land Surface Temperature Changes in Java Island from Aqua and Terra MODIS Satellite Imageries Using Google Earth Engine <p><em>Java Island is the island with the most population globally, which is experiencing an increase in population from year to year. This population growth causes an increase in the use of natural resources, which can further increase the potential for climate change. One of the parameters of climate change in an area is Land Surface Temperature (LST). In situ LST observations in the field require a huge number of stations; for that reason, the use of satellites is the right choice. This study analyzes changes in LST spatially and temporally for 16 years, from January 2005 to December 2020, based on Terra and Aqua MODIS satellite imagery using Google Earth Engine as a data processing tool. LST processing was performed gradually to generate the average daily maximum LST of Terra and Aqua,&nbsp; monthly average LST, and annual average LST.&nbsp; This study found the correlation coefficient between the Terra and Aqua LST data and the BMKG weather station temperature data of 0.2599 to 0.8361. It indicated a moderate to very strong correlation. The most significant annual LST change occurred from 2015 to 2016 experiencing a temperature decrease of 1.6 °C and 2.0 °C, respectively, for Terra and Aqua.&nbsp; There was an area of 35105 km<sup>2</sup> (2010-2011) and 65420 km<sup>2</sup> (2015-2016) experiencing LST increases and decreases of at least 1.5°C, respectively. Areas experiencing a temperature increase were mainly in the northern part of East Java Province and the eastern part of Central Java Province. Meanwhile, the areas that experienced a temperature drop were mainly northern East Java, eastern Central Java, and West Java Province. Annual LST fluctuations indicate the changes in land used and land cover, both spatial and temporal.</em></p> L.M. Jaelani C.A. Handayani Copyright (c) 2022 International Journal of Geoinformatics 2022-10-27 2022-10-27 18 5 1 12 10.52939/ijg.v18i5.2365 Evaluation of Drought in the North of Thailand using Meteorological and Satellite-Based Drought Indices <p><em>This research attempts to evaluate drought impact on vegetation dynamics using various drought indices including the vegetation condition index (VCI), the temperature condition index (TCI), the vegetation health index (VHI) and The standardized precipitation index (SPI).&nbsp; Monthly VCI, TCI and VHI values were obtained from multi-temporal Terra/MODIS products from 2000 to 2017. Temporal and spatial scales of drought occurrences were detected from seasonal variations and drought severity maps generated from these drought indices. The correlation analysis was analyzed to identify the dominant factors that control vegetation variability. The results found that VHI was better to detect vegetation health in the mountainous areas at higher altitudes and lower temperatures. VCI and SPI captured drought occurrences for paddy fields in the southern part of the region where there was lower rainfall and vegetation cover. </em><em>The result can be applied for crop and drought early warnings in the region.</em></p> <p><strong>&nbsp;</strong></p> <p><strong>Keywords:</strong> Vegetation condition, drought monitoring, Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Standardized Precipitation Index (SPI)&nbsp;</p> W. Thavorntam Shahnawaz Copyright (c) 2022 International Journal of Geoinformatics 2022-10-27 2022-10-27 18 5 13 26 10.52939/ijg.v18i5.2367 Modeling Dynamic Urban Growth Using Cellular Automata and Geospatial Technique: Case of Casablanca in Morocco <p><em>The rapid urbanisation contribute to the spatial expansion in cities.However, the rapid and unmanaged urban growth, degraded the urban environment. In casablanca</em> <em>the economic engine of Morocco, the rapid urbanization was a result of demographic explosion, rural exodus, and the introduction of new urban projects. Understanding the interdependencies between urban growth patterns, infrastructure, and socioeconomic indicators is a critical step in achieving a sustainable urban development. In order to help Casablanca's sustainable growth, this study used remote sensing data to evaluate past urban land use changes. This study was conducted to examine past urban land cover change on the basis of remote sensing data collected between 1989 and 2019. To forecast the city's expansion for the years 2019e2029, an integrated Cellular Automata urban growth model was used. The research looked into the CA algorithm's capacity to work independently for urban development modeling satellite data from four time periods at equal intervals, as well as population density, distance to the city center, slope, and distance to roadways, are used for this purpose. Between 1989 and 2019, the satellite-based LULC reported an increase of 61.77Km2 (an 88 percent increase). The principle component analysis (PCA) technique was used to analyze geographic variation and found good classification similarity ranging from 87 to 90%. Based on the anticipated LULC, the built-up area will grow to 131.88 km2 in 2019, mostly in the west and southwest. Urbanization will replace and transform other LULC (net loss of 15.348Km2) between 2019 and 2029, followed by plant cover (net loss of 1.608Km2).</em></p> N. Benchelha M. Bezza N. Belbounaguia S. Benchelha M. Benchelha Copyright (c) 2022 International Journal of Geoinformatics 2022-10-27 2022-10-27 18 5 27 40 10.52939/ijg.v18i5.2369 The Method for Delimiting the Maritime Boundary in the Internal Waters Between Ba Ria-Vung Tau Province and the Coastal Provinces of Vietnam <p><em>The study is based on the legislative documents and the locality's management situation, which propose defining maritime boundaries in the internal waters of the Baria-Vung Tau coastal province of Vietnam. Defining the boundary is a legal document that serves as a foundation for local administrative management as well as a document that supports relevant policies, such as clearly defining the scope of objects operating in local waters. This is also a document for local governments to use as a foundation for marine resource management, determining the extent of marine space for planning purposes, and allocating a portion to organizations and individuals to use and exploit by Vietnamese government regulations. The national topographic map of the VN2000 system established by the Ministry of Natural Resources and Environment has been adjusted and supplemented with the latest data used to build the plan. The determination of maritime boundaries has been technicalized and applied in many countries. All methods are based on the fairness principle, which two sides can agree to and accept. The results provide technical solutions to define maritime boundaries based on coastal morphological characteristics, management situation, and legal documents of the State of Vietnam.</em></p> <p>&nbsp;</p> <p><strong>Keywords: </strong>Administrative Boundaries, Maritime Boundaries, The Major Direction</p> T.N.Q. Phan N.L. Hoang T.B.H. Dinh T.D. Pham Copyright (c) 2022 2022-10-27 2022-10-27 18 5 41 51 10.52939/ijg.v18i5.2371 Bayesian Network Integration with GIS for the Analysis of Areas Vulnerable to the Outbreak of COVID-19 in Bangkok, Thailand <p><em>The COVID-19 pandemic prompted a search for a new method of preventing the spread of this virus. This study established a model of the areas in Bangkok which were vulnerable to the COVID-19 pandemic by using a combination of the Bayesian network (BN) and the geographic information system (GIS). The model was developed using a data-driven approach and was evaluated with 10-fold cross validation and ROC analysis. The results demonstrated that the proposed method effectively predicted the vulnerability of disease outbreak. The most vulnerable areas to the pandemic were around the center and in the west of Bangkok, while the areas of low vulnerability were found in the north and east of the city. Population density and the aerosol index were highly influential factors in the outbreaks, affirmed by sensitivity analysis. Furthermore, the model used to conduct a scenario analysis resulted in the identification of vulnerability management strategies.</em></p> <p>&nbsp;</p> <p><strong>Keywords:</strong> COVID-19, Vulnerable disease area, Bayesian network, Geographic information system</p> B. Klanreungsang W. Suppawimut Copyright (c) 2022 2022-10-27 2022-10-27 18 5 53 69 10.52939/ijg.v18i5.2373 Influent Factor toward Based Helminth Infections among of Thai-Cambodian Border in Phusing District, Sisaket Province, Thailand <p><em>This cross-sectional study aimed to determine a) prevalence of helminth infection among pupils along six target Thai –Cambodian border primary schools in Phu Sing District, Sisaket Province via FECT under universal parasitology, and b) influent factors via constructed questionnaire. Three hundred subjects were as allocated sampling size under Taro Yamane formula within stratified simple random sampling was based for each school. The meeting among pupils parents and the local units of school-related and public health was formed for congruence and consents. Each pupil was provided Standard FECT while 125 items questionnaire, under five experts with reliability range between 0.80-0.95 formulas of Kr 20 and Cronbach alpha, were conducted as well. Descriptive statistics and stepwise multiple regression were applied. The results, respectively to the prevalence and influent factors, were as follows; </em></p> <p><em>1) The infected cases were 11.66%. Among the prevalence, sequentially, comprised the hookworm (74.00 %), Trichuris triciura (17.00 %), Ascaris lumbricoides (6.00 %), and Opisthorchis viverrini (3.00 %). Noticeable for high percentage data mode comprised age in 8-9 years who’s not attend boy scout regulation with wearing shoe uniform (77.10%), relevantly to, “not wearing shoes” (71.40%), family agricultural career (71.40%), majority of the Khmer ethnicity (71.40%), and unwell-cooked-food consuming (62.90%).</em></p> <p><em>2) Five Statistically Significant influent factors were, respectively to Standardized Regression Coefficient (β), (i) Self-care for prevention practice (β= 0.834), (ii)</em><em> Perceived its severity</em><em> (β= -0.298), (iii) Attitudes (β= -0.245), (iv)</em><em> Knowledge </em><em>(β= -0.134)</em><em>, </em><em>and (v)</em><em>Recognizing the benefits</em><em> (β= -0.081). Total predictive power was 85.60% (R<sup>2</sup>=0.856, p &lt;0.05).</em></p> <p><em>These results inter-supported to each other leading to accountability. “Not wearing shoes” and “Not well-cooked food eating” were for this crisis. The helminth-infection prevention should be on target behavior-changing as its output with additional school base regulation within a spontaneous holistic approach among collaborated units from school, family, community, profession, and policy under the five significant concerns related to cultural uniqueness of ethnicity and countryside agricultural ways as well as geographical concerns. The usefulness is the challenge to the effective holistic intervention integrated with GIS-based on stakeholders’ simultaneous collaboration within the concept of “One size will never fit all” especially in the distinctive areas.</em></p> P. Soncharoen J. Jongthawin C. Nithikathkul Copyright (c) 2022 2022-10-27 2022-10-27 18 5 71 86 10.52939/ijg.v18i5.2375 Quality Assessment of TanDEM-X DEM 12m Using GNSS-RTK and Airborne IFSAR DEM: A Case Study of Tuba Island, Langkawi <p><em>Digital elevation models (DEMs) have been recognized as a primary spatial dataset and essential for numerous </em><em>scientific</em><em> applications. The advent of TerraSAR-X for digital elevation measurement (TanDEM-X) has opened a new potential to obtain an accurate DEM. Nowadays, the demand/use of TanDEM-X DEM in scientific applications has become increasingly popular as it offers an alternative to the widely used DEMs: ASTER and SRTM DEM. Although many researches have been conducted to assess the performance of the TanDEM-X DEM at different locations in the world, however, only several multi-regional studies have been performed in Malaysian region. Currently, there are two types of DEMs published by DLR i.e., non-open access (12m and 30m resolution) and open access (90m resolution). In this article, the accuracy of TanDEM-X 12m has been comprehensively and systematically evaluated using 1284 GNSS-RTK control points over Tuba Island and airborne IFSAR-DEM as a reference height. Besides, four available global DEMs: TanDEM-X 90m, AW3D30 DEM, SRTM DEM, and ASTER DEM have also been evaluated to identify the accuracy of TanDEM-X DEM 12m. Based on the evaluation using GNSS-RTK points, TanDEM-X 12m exhibits the highest accuracy with an RMSE of ±1.553m. Unexpectedly, AW3D30 DEM shows a better performance compared to TanDEM-X 90m with RMSE of ±1.964m, followed by SRTM DEM with RMSE of ±3.296m Meanwhile, ASTER DEM exhibits the lowest accuracy with RMSE of ±4.100m The comparison of TanDEM-X 12m and the well-known DEM, SRTM DEM with airborne IFSAR-DEM shows the opposite results. Based on the topographic profile at flat and forest area, the SRTM-DEM exhibits better accuracy than TanDEM-X 12m</em></p> F.M. Pa’suya N. Talib R.H. Narashid A.F. Ahmad Fauzi F. Amri Mohd M.A. Abdullah Copyright (c) 2022 International Journal of Geoinformatics 2022-10-27 2022-10-27 18 5 87 103 10.52939/ijg.v18i5.2389 Spatial Factors Associated with fall among the Elderly in Thailand <p><em>Falls are the leading cause of injury-related visits to emergency departments around the world, including in Thailand, and the primary etiology of accidental deaths in elderly people. Falls among the elderly is an increasing problem, causing a high degree of morbidity, mortality, and use of health care services. This study statistically identified aimed to determine the association of the spatial factors with falls among elderly people in Thailand. The participant consisted of 40,489 elderly people and was conducted using a data set from the national statistical office of Thailand in 2017 and other data. A Moran’s I and local indicators of spatial association (Lisa) were used to identify the spatial autocorrelation between poverty incidence, the proportion of patients with non-communicable diseases, and the population-to- village health volunteers’ ratio with falls among elderly people in Thailand. The results showed that there was spatial global autocorrelation between poverty incidence, the proportion of patients with non-communicable diseases, and the population-to- village health volunteers among elderly people in Thailand with Moran’s I values of 0.176, 0.049, and 0.034, respectively. Therefore, the focus should be on promoting and preventing non-communicable diseases, as well as promoting income-generating jobs for the elderly by closely supervising village health volunteers and elderly caregivers to reduce the risk of falls among the elderly and improve their quality of life.&nbsp;</em></p> N. Nilnate C. Jirapornkul Y. Limmongkon Copyright (c) 2022 2022-10-27 2022-10-27 18 5 105 113 10.52939/ijg.v18i5.2391 Drought Assessment Using Remote Sensing and Geographic Information Systems (GIS) Techniques (Case Study: Klaten District) <p><em>Drought is a climate change phenomenon that is difficult to avoid, so disaster mitigation planning is needed to minimize the impact of damage. Drought potential mapping can take advantage of remote sensing data and analysis of spatial data using a Geographic Information System (GIS). Image extraction can produce Land Surface Temperature (LST) data, vegetation index obtained from the Normalized Difference Vegetation Index (NDVI) transformation, land use obtained from Object-Based Image Analysis (OBIA), and wetness index from the Normalized Difference Water Index (NDWI). This study integrates data between image extraction results and regional conditions such as rainfall, geological, soil types, and hydrogeology. Klaten Regency has the potential for very high-class drought covering an area of 101.53 ha. In Bayat District, the results of the identification of potential drought indicate very high levels of drought.</em></p> N. Bashit N.S. Ristianti D. Ulfiana Copyright (c) 2022 2022-10-27 2022-10-27 18 5 115 127 10.52939/ijg.v18i5.2393 Message from the Editor for October 2022 Issue <p>This issue contains papers related to the variability of LST in a tropics Island using Modis data and employing Google Earth Engine (GEE). There are two papers on drought assessment using meteorological and satellite remote sensing data. There are three papers on geospatial health monitoring, data analysis, and modeling. One paper on Covid 19 outbreak in Bangkok contains an interesting analysis. One paper is addressing a very important issue of spatial factors associated with ”Fall” among elderly citizens contains interesting novel insight and calls for further research in this domain. One paper addresses the very crucial role of geospatial technologies in delimiting maritime boundaries. This can be really useful for professionals managing coastal and maritime issues. Quality Assessment of TanDEM-X DEM 12 m resolution using GNSS RTK and airborne IFSAR DEM is investigated.</p> <p>I am sure the above research will be providing direction for acquiring new knowledge and related domains and more research will be carried out. Now, all the papers will be Open Access, so the citations are bound to increase rapidly. IJG has also changed the format of the online papers which is more friendly for internet searchability and hopefully contributes again to the enhancement of citations and impact factor of the International Journal of Geoinformatics.</p> <p>IJG-App is ready for launch for easy accessibility of the journal articles on mobiles and iPad. This will be done in an annual workshop in Bangkok to encourage easy and smart networking of Geospatial Scientists. We will reach all our contributors soon to share the information about the <strong>IJG International Annual Day</strong> workshop which may occur in January 2023. Thank you so much and best wishes for your professional growth.</p> <p>&nbsp;</p> <p>Dr. Nitin Kumar Tripathi<br><em>Editor-in-Chief<br></em><em></em></p> Nitin Tripathi Copyright (c) 2022 2022-10-01 2022-10-01 18 5