Applied Geomatics最新文献

{"title":"Mobile-based image interpretation and geotagging using artificial intelligence and open-source geospatial technology","authors":"Arati Paul,&nbsp;Sakshi Chauhan,&nbsp;Dibyendu Dutta","doi":"10.1007/s12518-023-00522-x","DOIUrl":"10.1007/s12518-023-00522-x","url":null,"abstract":"<div><p>Image geotagging is a process where geographic coordinates are attached to an image. Mobile-based geotagging application has many advantages, viz. real-time monitoring, ensuring data authenticity etc. Since an ordinary mobile camera cannot interpret the geotagged images, they are manually analysed later for a specific purpose. Therefore, the human interpreters are to put their time and effort to analyse the images. This becomes difficult when the number of images is more. The heterogeneity of captured images, in terms of intensity, viewing angle etc., limits the application of traditional image processing techniques for automatic image interpretation. Hence, artificial intelligence (AI)–based image processing technique needs to be employed that enables machines to learn from instances and provide assistance in field photo interpretation. In the present work, a smartphone-based application, embedded with enhanced capabilities of AI and geospatial technology, has been developed using open-source technology. The application employs AI to detect certain categories’ semantic objects and automatically generates their details. The mean of detection precision, recall and F1 score are estimated as 0.96, 0.91 and 0.93, respectively. The present work successfully demonstrates the use of open-source technology for AI-enabled geotagging and dissemination of ground information through WebGIS application.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 4","pages":"795 - 805"},"PeriodicalIF":2.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89477878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the complexities of land transformation and its impact on urban sustainability through land surface temperature analysis","authors":"Saleha Jamal,&nbsp;Mohd Saqib,&nbsp;Wani Suhail Ahmad,&nbsp;Manal Ahmad,&nbsp;Md Ashif Ali,&nbsp;Md Babor Ali","doi":"10.1007/s12518-023-00521-y","DOIUrl":"10.1007/s12518-023-00521-y","url":null,"abstract":"<div><p>Due to the ongoing population increase over the past years, fast and unchecked urbanization has been occurring in the urban centers of developing nations like India. As a result, land transformation is taking place at a fast pace leading to the creation of urban heat island (UHI). Urban heat island (UHI) constitutes a significant human alteration to the Earth system. Hence, this study presents a rigorous and comprehensive analysis of the impact of land use and cover on land surface temperature (LST) in Aligarh City, Uttar Pradesh, India, using multi-dimensional satellite data. The research collected Landsat data for four different phases (1991, 2001, 2011, and 2021) and analyzed it in conjunction with land use and cover (LULC) data to identify trends and variations. The result shows a consistent increase in LST since 1991, with built-up and bare land areas exhibiting the highest temperatures across all phases. Moreover, the study found that impervious land had the most significant effect on LST, followed by water bodies and vegetation cover. The analysis of the proportion of the area with the lowest and highest LST showed interesting trends, with a greater portion of Aligarh City experiencing a temperature range between 15 and 16 °C in 2021 compared to previous years. However, the study also found that 13.55% of the area had a maximum LST of over 17 °C, which is higher than the previous measurement of 9.04%, and has been steadily increasing since 1991. The accuracy of the study was verified by detecting elevated temperatures in non-porous areas and cooler temperatures near green zones and water bodies. This study’s contribution to the research community lies in the data-driven, systematic analysis of the complex relationship between land use and cover and LST in an urban environment. The study’s findings suggest that alterations in land use/cover patterns have a significant impact on LST, which has important implications for urban planning policies. The research provides valuable insights for urban planners, policymakers, and city officials, as it highlights the need for sustainable and efficient urban planning policies to mitigate the effects of urban heat islands and rising temperatures. The study’s results have broader implications beyond Aligarh City and can inform land-use planning and policymaking in other cities facing similar challenges. This research presents a comprehensive analysis that can serve as a framework to inform land-use planning and policymaking, contributing to the development of sustainable and efficient urban environments.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 3","pages":"719 - 741"},"PeriodicalIF":2.7,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50053335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal Autocorrelation of Sentinel-1 SAR Imagery for Detecting Settlement Expansion","authors":"J. Kapp, J. Kemp","doi":"10.3390/geomatics3030023","DOIUrl":"https://doi.org/10.3390/geomatics3030023","url":null,"abstract":"Urban areas are rapidly expanding globally. The detection of settlement expansion can, however, be challenging due to the rapid rate of expansion, especially for informal settlements. This paper presents a solution in the form of an unsupervised autocorrelation-based approach. Temporal autocorrelation function (ACF) values derived from hyper-temporal Sentinel-1 imagery were calculated for all time lags using VV backscatter values. Various thresholds were applied to these ACF values in order to create urban change maps. Two different orbital combinations were tested over four informal settlement areas in South Africa. Promising results were achieved in the two of the study areas with mean normalized Matthews Correlation Coefficients (MCCn) of 0.79 and 0.78. A lower performance was obtained in the remaining two areas (mean MCCn of 0.61 and 0.65) due to unfavorable building orientations and low building densities. The first results also indicate that the most stable and optimal ACF-based threshold of 95 was achieved when using images from both relative orbits, thereby incorporating more incidence angles. The results demonstrate the capacity of ACF-based methods for detecting settlement expansion. Practically, this ACF-based method could be used to reduce the time and labor costs of detecting and mapping newly built settlements in developing regions.","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"43 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77524279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the capability of high-resolution satellite data in delineating the potential distribution of common invasive alien plant species in the Tshivhase Tea Estate","authors":"Fhulufhedzani Nembambula,&nbsp;Oupa E. Malahlela,&nbsp;Lutendo Mugwedi","doi":"10.1007/s12518-023-00520-z","DOIUrl":"10.1007/s12518-023-00520-z","url":null,"abstract":"<div><p>Invasive alien plants (IAPs) continue to exert significant impacts on agriculture in many countries, resulting in food insecurity. IAPs reduce agricultural production through competition and parasitism with planted crops. More recently, the IAPs continue to extend their plasticity to tea plantations, especially in tropical and subtropical areas. This study thus aimed at exploring the potential of SPOT 7 and Sentinel 2 satellite data in mapping the occurrence and co-occurrence of three common IAPs <i>Solanum mauritianum</i>, <i>Lantana camara</i>, and <i>Chromolaena odorata</i> in the Tshivhase Tea Estate in Limpopo Province, South Africa. The stepwise logistic regression models were generated for <i>Solanum mauritianum</i> and <i>Lantana camara</i> occurrence as well as the observed and conditional co-occurrence probability of <i>S. mauritianum</i> (P1), <i>L. camara</i> (P2) and <i>C. odorata</i> (P3). From the remote sensing indices, the Brightness Index (BI) was significant in most SPOT 7 stepwise logistic regression models at <i>p</i>&lt;0.05 whereas the blue, red, and near infrared (NIR) bands and standard deviation (STDv) variables were significant at <i>p</i>&lt;0.05 in most of the Sentinel 2 models. The SPOT 7 model performed Sentinel-2 models, thus resulting in the area under the curve (AUC) of 0.96 for the conditional co-occurrence of <i>S. mauritianum</i> (P1) and <i>L. camara</i> (P2). The Sentinel 2 model yielded an AUC of 0.83. The SPOT 7 model performed superior in mapping the conditional co-occurrence of <i>S. mauritianum</i> and <i>L. camara</i> than the Sentinel 2 model. These results suggest that high spatial resolution satellite images like SPOT 7 can delineate the potential distribution of IAPs in the tea plantation and thus assisting in management strategies geared towards IAP’s elimination and control.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 3","pages":"683 - 695"},"PeriodicalIF":2.7,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-023-00520-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50074013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing","authors":"Noor-ul Huda,&nbsp;Shakeel Mahmood,&nbsp;Rida Sajjid,&nbsp;Muhammad Irfan Ahamad","doi":"10.1007/s12518-023-00519-6","DOIUrl":"10.1007/s12518-023-00519-6","url":null,"abstract":"<div><p>This study aims to detect changes that occurred in Ravi River channel over the period of last three decades (1990 to 2020). This paper spatially and temporally assesses the changes and geo-visualize variation of Ravi River using Landsat imageries. The maximum likelihood image classification technique has been used to process and analyze the spatial data in geographic information system (GIS) environment. It was found from the results that vegetation cover has gradually decreased from 976 km² in 1990 to 905 km² in 2019, whereas the built-up land had increased from 82 to 188 km² in the same temporal extent. Generally, the channel is shifted from east to west and the growth of built-up land to towards river which has pushed the channel. Similarly, the extreme discharge also causes change in channel shifting. Minor floods have been occurred after 2010 but Ravi is not affected much as their discharge was not that much higher to put any abrupt or significant effect on Ravi River’s channel pattern.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 3","pages":"759 - 772"},"PeriodicalIF":2.7,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50030869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seafloor and Ocean Crust Structure of the Kerguelen Plateau from Marine Geophysical and Satellite Altimetry Datasets","authors":"Polina Lemenkova","doi":"10.3390/geomatics3030022","DOIUrl":"https://doi.org/10.3390/geomatics3030022","url":null,"abstract":"The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the Cretaceous history of the continents. This is reflected in the varying age of the oceanic crust adjacent to the plateau and the highly heterogeneous bathymetry of the Kerguelen Plateau, with seafloor structure differing for the southern and northern segments. Remote sensing data derived from marine gravity and satellite radar altimetry surveys serve as an important source of information for mapping complex seafloor features. This study incorporates geospatial information from NOAA, EMAG2, WDMAM, ETOPO1, and EGM96 datasets to refine the extent and distribution of the extracted seafloor features. The cartographic joint analysis of topography, magnetic anomalies, tectonic and gravity grids is based on the integrated mapping performed using the Generic Mapping Tools (GMT) programming suite. Mapping of the submerged features (Broken Ridge, Crozet Islands, seafloor fabric, orientation, and frequency of magnetic anomalies) enables analysis of their correspondence with free-air gravity and magnetic anomalies, geodynamic setting, and seabed structure in the southwest Indian Ocean. The results show that integrating the datasets using advanced cartographic scripting language improves identification and visualization of the seabed objects. The results include 11 new maps of the region covering the Kerguelen Plateau and southwest Indian Ocean. This study contributes to increasing the knowledge of the seafloor structure in the French Southern and Antarctic Lands.","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82541399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria decision analysis method in Fetam-Yisir catchment, Blue Nile Basin, Ethiopia","authors":"Endalkachew Abebaw Gizaw,&nbsp;Getnet Taye Bawoke,&nbsp;Melkamu Meseret Alemu,&nbsp;Zelalem Leyew Anteneh","doi":"10.1007/s12518-023-00518-7","DOIUrl":"10.1007/s12518-023-00518-7","url":null,"abstract":"<div><p>Detecting the potential region of the groundwater resource is a difficult issue all over the world. Nowadays, advanced geospatial technologies are excellent tools for efficient planning, managing, and assessing groundwater resources, particularly in data-scarce developing nations. Remote sensing (RS) and GIS-based multi-criteria decision analysis (MCDA) methods were applied to delineate the groundwater potential (GWP) in the Fetam-Yisir catchment, Blue Nile Basin, Ethiopia. Nine thematic layers: slope, geomorphology, normalized difference vegetation index (NDVI), topographic elevation, geology, land use/land cover (LULC), soil, rainfall, and drainage density from satellite and conventional data were used. The analytical hierarchy process (AHP) of an MCDA was employed to compute the corresponding normalized weight for the class in a layer and weights for the thematic layers on the base of their relative significance to the GWP. Integration of all thematic maps has been done using the “Weighted overlay” tool to obtain a GWP map. The GWP map is then validated using observed boreholes, and springs yield data. The verification of the final GWP zone map against yield data confirms 82% agreement indicating the authenticity of the method. The final GWP output confirmed that 43% area of the Fetam-Yisir catchment falls in a “good” GWP zone; 42%, 7.45%, 7.4%, and 0.02% of the area fall in “moderate,” “very good,” “poor,” and “very poor” GWP zones, respectively. The sensitivity analysis divulges that the GWP map is highly sensitive to slope with a mean variation index of 1.45%. Thus, this study can be used for effective groundwater exploration, development, and sustainable abstraction, as well as it guides the researchers in locating the GWP zone.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 3","pages":"659 - 681"},"PeriodicalIF":2.7,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50007695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the spatial spread of unplanned slum areas in Zagazig City, Egypt, using geographic information systems","authors":"Mourad Henane Ramzy Abd-Almalek,&nbsp;Inaam Mahmoud Bandari,&nbsp;Hossam Kotb Al-Sayed,&nbsp;Ahmed Al-Shahat Al-Minshawi","doi":"10.1007/s12518-023-00512-z","DOIUrl":"10.1007/s12518-023-00512-z","url":null,"abstract":"<div><p>The research dealt with the application of the spatial spread analysis of the slums housing areas in the city of Zagazig using geographic information systems, and the spatial distribution pattern of the slums and the regions were classified in terms of the area into (large, medium, and small). And it determined the spatial spread of these areas: the central area of the city with a radius of 1.5 km, the next area on the borders of the urban boundary with a distance of about 1.5: 3 km, and the area outside the urban boundaries, including Shaybah and Nakaria, about 3: 4.5 km. The results of the research revealed that small slum areas are the most prevalent in the central region, representing <span>(61.54%)</span> and an area of <span>(13.22%)</span>, but large areas represent a total area of <span>(49.11%)</span> and therefore small areas can be removed and large areas developed. With the provision of alternative and safe housing according to a plan and decision of the state. And by defining future development policies and dealing with priorities, priority is given to the closest and largest region of the central region in Zagazig city, according to decisions and studies by the state in the following order: 16, 36, 21, 27, 31, 32, 33, 15, 35, 37, 34, 17, 24, 28, 20, 22, 19, 39, 38, 30, 25, 8, 4, 26, 23, 5, 7, 29, 12, 18, 2, 13, 14, 6, 3, 11, 9, 10, 1.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 2","pages":"483 - 496"},"PeriodicalIF":2.7,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-023-00512-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50045712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of Remote Sensing Approaches and Soft Computing for Infrastructure Monitoring","authors":"A. Kyriou, Vassiliki Mpelogianni, K. Nikolakopoulos, P. Groumpos","doi":"10.3390/geomatics3030021","DOIUrl":"https://doi.org/10.3390/geomatics3030021","url":null,"abstract":"During the past few decades, remote sensing has been established as an innovative, effective and cost-efficient option for the provision of high-quality information concerning infrastructure to governments or decision makers in order to update their plans and/or take actions towards the mitigation of the infrastructure risk. Meanwhile, climate change has emerged as a serious global challenge and hence there is an urgent need to develop reliable and cost-efficient infrastructure monitoring solutions. In this framework, the current study conducts a comprehensive review concerning the use of different remote-sensing sensors for the monitoring of multiple types of infrastructure including roads and railways, dams, bridges, archaeological sites and buildings. The aim of this contribution is to identify the best practices and processing methodologies for the comprehensive monitoring of critical national infrastructure falling under the research project named “PROION”. In light of this, the review summarizes the wide variety of approaches that have been utilized for the monitoring of infrastructure and are based on the collection of remote-sensing data, acquired using the global navigation satellite system (GNSS), synthetic aperture radar (SAR), light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV) sensors. Moreover, great emphasis is given to the contribution of the state-of-the-art soft computing methods throughout infrastructure monitoring aiming to increase the automation of the procedure. The statistical analysis of the reviewing publications revealed that SARs and LiDARs are the prevalent remote-sensing sensors used in infrastructure monitoring concepts, while regarding the type of infrastructure, research is orientated onto transportation networks (road and railway) and bridges. Added to this, deep learning-, fuzzy logic- and expert-based approaches have gained ground in the field of infrastructure monitoring over the past few years.","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"16 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85433673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gravity corrections for the updated italian levelling network","authors":"Riccardo Barzaghi,&nbsp;Daniela Carrion,&nbsp;Marianna Carroccio,&nbsp;Renzo Maseroli,&nbsp;Giacomo Stefanelli,&nbsp;Giovanna Venuti","doi":"10.1007/s12518-023-00516-9","DOIUrl":"10.1007/s12518-023-00516-9","url":null,"abstract":"<div><p>The Italian official height system is defined through a high precision levelling network established and maintained by the Istituto Geografico Militare - IGM. During the last 20 years, IGM has performed levelling campaigns on almost the whole peninsular area of Italy with the aim of both densifying the existing network and updating the reference heights. This paper reports about the procedure applied to correct the levelling observations for the gravity effects and the assessment on the results. The needed gravity values were predicted from the Italian gravity dataset (IGD), and both from EGM2008 and XGM2019e high resolution global gravity models. A new formulation of the normal correction as well as the standard orthometric correction were applied. The IGD derived corrections proved to be effective by reducing the misclosure error of critical loops below the tolerance level. Gravity data derived from EGM2008 and XGM2019e proved to be too poor for the correction purposes, as it was also confirmed by a comparison against available observed data, with RMS of the differences, in Alpine ares, ranging between 50 and 100 mGal.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"15 3","pages":"773 - 780"},"PeriodicalIF":2.7,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12518-023-00516-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50047839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}