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Geographic information system data considerations in the context of the enhanced bathtub model for coastal inundation / Lauren Lyn Williams in Transactions in GIS, vol 26 n° 7 (November 2022)
[article]
Titre : Geographic information system data considerations in the context of the enhanced bathtub model for coastal inundation Type de document : Article/Communication Auteurs : Lauren Lyn Williams, Auteur ; Melanie Lück-Vogel, Auteur Année de publication : 2022 Article en page(s) : pp 3074 - 3089 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Afrique du sud (état)
[Termes IGN] ArcGIS
[Termes IGN] données lidar
[Termes IGN] milieu urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de points
[Termes IGN] submersion marine
[Termes IGN] système d'information géographiqueRésumé : (auteur) concerning digital surface models (DSMs) to determine: (a) the highest appropriate resolution achievable from available LiDAR data and consider variations between derived sub-meter DSMs; (b) optimal DSM horizontal resolution for coastal inundation modeling based on “out-the-box” solutions; and (c) mechanisms to address the challenge presented by DSMs regarding overhanging structures for a study site in False Bay, South Africa. Results showed that while sub-meter DSMs are achievable, low point cloud densities may result in the misrepresentation of structures, which affects the inundation extents. High horizontal resolution DSMs are required for inundation modeling in an urban setting to account for narrow thoroughfares. Challenges posed by first return LiDAR depicting bridges as solid structures could be circumvented by modifying the input water source for the eBTM processing. Numéro de notice : A2022-888 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1111/tgis.12995 Date de publication en ligne : 18/10/2022 En ligne : https://doi.org/10.1111/tgis.12995 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102232
in Transactions in GIS > vol 26 n° 7 (November 2022) . - pp 3074 - 3089[article]Modelling and accessing land degradation vulnerability using remote sensing techniques and the analytical hierarchy process approach / Abebe Debele Tolche in Geocarto international, vol 37 n° 24 ([20/10/2022])
[article]
Titre : Modelling and accessing land degradation vulnerability using remote sensing techniques and the analytical hierarchy process approach Type de document : Article/Communication Auteurs : Abebe Debele Tolche, Auteur ; Megersa Adugna Gurara, Auteur ; Quoc Bao Pham, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 7122 - 7142 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] dégradation des sols
[Termes IGN] Ethiopie
[Termes IGN] Google Earth
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] pédologie locale
[Termes IGN] précipitation
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] température au sol
[Termes IGN] topographie locale
[Termes IGN] vulnérabilitéRésumé : (auteur) Land degradation and desertification have recently become a critical problem in Ethiopia. Accordingly, identification of land degradation vulnerable zonation and mapping was conducted in Wabe Shebele River Basin, Ethiopia. Precipitation derived from Global Precipitation Measurement Mission (GMP), the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized difference vegetation index (NDVI) and land surface temperature (LST), topography (slope), and pedological properties (i.e., soil depth, soil pH, soil texture, and soil drainage) were used in the current study. NDVI has been considered as the most significant parameter followed by the slope, precipitation and temperature. Geospatial techniques and the Analytical Hierarchy Process (AHP) approach were used to model the land degradation vulnerable index. Validation of the results with google earth image shows the applicability of the model in the study. The result is classified into very highly vulnerable (17.06%), highly vulnerable (15.01%), moderately vulnerable (32.72%), slightly vulnerable (16.40%), and very slightly vulnerable (18.81%) to land degradation. Due to the small rate of precipitation which is vulnerable to evaporation by high temperature in the region, the downstream section of the basis is categorized as highly vulnerable to Land Degradation (LD) and vice versa in the upstream section of the basin. Moreover, the validation using the Receiver Operating Characteristic (ROC) curve analysis shows an area under the ROC curve value of 80.92% which approves the prediction accuracy of the AHP method in assessing and modelling LD vulnerability zone in the study area. The study provides a substantial understanding of the effect of land degradation on sustainable land use management and development in the basin. Numéro de notice : A2022-776 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1959656 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.1080/10106049.2021.1959656 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101831
in Geocarto international > vol 37 n° 24 [20/10/2022] . - pp 7122 - 7142[article]GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin / Raid Mahmood Faisal in Geocarto international, vol 37 n° 23 ([15/10/2022])
[article]
Titre : GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin Type de document : Article/Communication Auteurs : Raid Mahmood Faisal, Auteur Année de publication : 2022 Article en page(s) : pp 6826 - 6847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] ArcGIS
[Termes IGN] érosion
[Termes IGN] géomorphométrie
[Termes IGN] Iraq
[Termes IGN] modèle RUSLE
[Termes IGN] processus de hiérarchisation analytiqueRésumé : (auteur) This study examines the watersheds in the Bastora river basin and builds a geographic model within ARC GIS software. The work was divided into three phases. The first phase was to obtain the results of 14 morphometric parameters to determine priorities, by using AHP model to extract the relative weights of the parameters. Then, these weights are adopted in building (SDI, TOPSIS and SAW) models to determine levels of priorities. The outputs were classified into five categories according to the degree of their susceptibility to erosion. The second phase includes creating another model to provide necessary data and tools for building the RUSLE model. The final phase validates of pairs of models (TOPSIS-RUSLE), (SDI-RUSLE), and (SAW-RUSLE) using least squares tool for comparison between the results. The results indicate a highly statistically significant relationship among all the previous pairs of models with clear preference recorded for (TOPSIS-RUSLE) models relationship. Numéro de notice : A2022-751 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1950848 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1950848 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101743
in Geocarto international > vol 37 n° 23 [15/10/2022] . - pp 6826 - 6847[article]PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna / Xingxing Li in Journal of geodesy, vol 96 n° 10 (October 2022)
[article]
Titre : PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Hao Wang, Auteur ; Xin Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 65 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Androïd
[Termes IGN] antenne
[Termes IGN] données GNSS
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnement
[Termes IGN] rapport signal sur bruit
[Termes IGN] résolution d'ambiguïté
[Termes IGN] téléphone intelligentRésumé : (auteur) The release of GNSS raw measurement acquisition privileges on Google Android makes high-precision positioning on the low-cost smart devices possible. However, influenced by the inner linearly polarized antenna, the pseudorange and carrier phase noises of the smart device are much larger than those of the geodetic receiver. As a result, only meter-level positioning accuracy can be obtained based on the smart device’s original antenna. With the external survey-grade antenna enhancing, positioning accuracy of decimeter-level to centimeter-level can be obtained, but it still takes tens of minutes to converge and fix the ambiguity. However, a PPP-RTK method is proposed to achieve rapid integer ambiguity resolution (AR) with the regional atmospheric augmentation. In this contribution, an uncombined PPP-RTK model is developed using Android GNSS raw measurements with an external antenna, after carefully considering the coexistence of single- and dual-frequency signals on smart devices. A low-cost helical antenna is employed to enhance the Android GNSS data as it is capable to provide observation data of comparable quality with the survey-grade antenna and has several advantages of low weight, low-power consumption, and portability. Moreover, a series of quality control methods in the data preprocessing and ambiguity resolution are proposed for smartphone-based PPP-RTK to enhance the positioning results. To validate the proposed method, several experiments are carried out using raw measurements of Xiaomi Mi8 with an external low-cost helical antenna. The result shows that the ambiguity fixed solution can be obtained within 3 min in both static and kinematic scenarios. After the ambiguity resolution, centimeter-level positioning accuracy of (1.7, 2.1, 4.1) cm and (7.2, 4.5, 8.1) cm for the east, north, and up components can be achieved in static and kinematic scenarios, respectively. Numéro de notice : A2022-735 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01661-6 Date de publication en ligne : 27/09/2022 En ligne : https://doi.org/10.1007/s00190-022-01661-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101706
in Journal of geodesy > vol 96 n° 10 (October 2022) . - n° 65[article]A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])
[article]
Titre : A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers Type de document : Article/Communication Auteurs : Qasim Khan, Auteur ; Muhammad Usman Liaqat, Auteur ; Mohamed Mostafa Mohamed, Auteur Année de publication : 2022 Article en page(s) : pp 5832 - 5850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse en composantes principales
[Termes IGN] apprentissage automatique
[Termes IGN] aquifère
[Termes IGN] ArcGIS
[Termes IGN] classification bayesienne
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] eau souterraine
[Termes IGN] Emirats Arabes Unis
[Termes IGN] estimation par noyau
[Termes IGN] nitrate
[Termes IGN] vulnérabilitéRésumé : (auteur) Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This study proposes a novel method of mapping groundwater vulnerability using machine learning algorithms. In this study, point extraction method was used to extract point values from a grid of 646 points of seven raster layer in the Al Khatim study area of United Arab Emirates. These extracted values were classified based on nitrate concentration threshold of 50 mg/L into two classes. Machine learning models were developed, using depth to water (D), recharge (R), aquifer media (A), soil media (S), topography (T), vadose zone (I) and hydraulic conductivity (C), on the basis of nitrate class. Classified ‘groundwater vulnerability class values’ were trained using 10-fold cross-validation, using four machine learning models which were Random Forest, Support Vector Machine, Naïve Bayes and C4. 5. Accuracy showed the model developed by Random Forest gained highest accuracy of 93%. Four groundwater vulnerability maps were developed from machine learning classifiers and was compared with base method of DRASTIC index. The efficiency, accuracy and validity of machine learning based models were evaluated based on Receiver Operating Characteristics (ROC) curve and Precision-Recall curve (PRC). The results proved that machine learning is an efficient tool to access, analyze and map groundwater vulnerability. Numéro de notice : A2022-716 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1923833 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1923833 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101641
in Geocarto international > vol 37 n° 20 [20/09/2022] . - pp 5832 - 5850[article]Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)PermalinkParcel Manager: A parcel reshaping model incorporating design rules of residential development / Maxime Colomb in Transactions in GIS, vol 26 n° 6 (September 2022)PermalinkPourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? / Paul Courbon in XYZ, n° 172 (septembre 2022)PermalinkEvapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method / Juan Vicente Liendro Moncada in Geocarto international, Vol 37 n° 17 ([20/08/2022])PermalinkComparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation / Omer Faruk Atiz in Survey review, vol 55 n° 388 (January 2023)PermalinkStudy of crustal deformation in Egypt based on GNSS measurements / S.A. Younes in Survey review, vol inconnu ([01/08/2022])PermalinkUse of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)Permalink3D-GIS parametric modelling for virtual urban simulation using CityEngine / Ibrahim M. Badwi in Annals of GIS, vol 28 n° 3 (July 2022)PermalinkIntegration of GNSS observations with volunteered geographic information for improved navigation performance / Tarek Hassan in Journal of applied geodesy, vol 16 n° 3 (July 2022)PermalinkInvestigating the ability to identify new constructions in urban areas using images from unmanned aerial vehicles, Google Earth, and Sentinel-2 / Fahime Arabi Aliabad in Remote sensing, vol 14 n° 13 (July-1 2022)Permalink