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Comparison of different global DTMs and GGMs over Sri Lanka / Weeramuni Javana Praboni De Silva in Journal of applied geodesy, vol 17 n° 1 (January 2023)  

Public [article]  inJournal of applied geodesy > vol 17 n° 1 (January 2023) . - pp 29 - 38 Titre : Comparison of different global DTMs and GGMs over Sri Lanka Type de document : Article/Communication Auteurs : Weeramuni Javana Praboni De Silva, Auteur ; Herath Mudiyanselage Indika Prasanna, Auteur Année de publication : 2023 Article en page(s) : pp 29 - 38 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] géoïde altimétrique [Termes IGN] MERIT [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] modèle de géopotentiel [Termes IGN] Sri Lanka [Vedettes matières IGN] Altimétrie Résumé : (auteur) Digital Elevation Models (DEMs) are real-world geographical databases that are important in studying many Earth related topics. Because the vertical accuracy of global DEMs differs across regions due to various reasons, acquiring reliable heights for a region using global height models is crucial. The objective of this study is to compare and assess the most reliable global height model for Sri Lanka. The official height system in Sri Lanka is the Mean Sea Level (MSL) based orthometric height system. In this study, the quality of ASTER, SRTM, NASADEM, MERIT, and DEMs compiled from digitized contour data of Sri Lanka was evaluated using the known heights of the Fundamental Benchmarks (FBMs) of Sri Lanka. In addition, recently published high-resolution Global Geopotential Models (GGMs) were used for the accuracy assessments of gravity related quantities computed using DEMs. The SGG-UGM-2 GGM, which showed the minimum STD and RMSE of geoid undulation difference was found as the best fit GGM over Sri Lanka. It was found that the NASADEM at its highest resolution, which gave the lowest RMSE of 2.954 m was the best global DEM for Sri Lanka. Numéro de notice : A2023-050 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2022-0026 Date de publication en ligne : 07/11/2022 En ligne : https://doi.org/10.1515/jag-2022-0026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102376 [article]

The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 1 (January 2023) . - pp 47 - 55 Titre : The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan Type de document : Article/Communication Auteurs : Muhammad Nasar Ahmad, Auteur ; Zhenfeng Shao, Auteur ; Akib Javed, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 47 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] automate cellulaire [Termes IGN] carte thématique [Termes IGN] classification semi-dirigée [Termes IGN] détection de changement [Termes IGN] données vectorielles [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] MNS SRTM [Termes IGN] modèle dynamique [Termes IGN] occupation du sol [Termes IGN] Pakistan [Termes IGN] surveillance de l'urbanisation [Termes IGN] utilisation du sol Résumé : (auteur) Rapid urbanization has become an immense problem in Lahore city, causing various socio-economic and environmental problems. Therefore, it is noteworthy to monitor land use/land cover (LULC) change detection and future LULC patterns in Lahore. The present study focuses on evaluating the current extent and modeling the future LULC developments in Lahore, Pakistan. Therefore, the semi-automatic classification model has been applied for the classification of Landsat satellite imagery from 2000 to 2020. And the Modules of Land Use Change Evaluation (MOLUSCE) cellular automata (CA-ANN) model was implemented to simulate future land use trends for the years 2030 and 2040. This study project made use of Landsat, Shuttle Radar Topography Mission Digital Elevation Model, and vector data. The research methodology includes three main steps: (i) semi-automatic land use classification using Landsat data from 2000 to 2020; (ii) future land use prediction using the CA-ANN (MOLUSCE) model; and (iii) monitoring change detection and interpretation of results. The research findings indicated that there was a rise in urban areas and a decline in vegetation, barren land, and water bodies for both the past and future projections. The results also revealed that about 27.41% of the urban area has been increased from 2000 to 2020 with a decrease of 42.13% in vegetation, 2.3% in barren land, and 6.51% in water bodies, respectively. The urban area is also expected to grow by 23.15% between 2020 and 2040, whereas vegetation, barren land, and water bodies will all decline by 28.05%, 1.8%, and 12.31%, respectively. Results can also aid in the long-term, sustainable planning of the city. It was also observed that the majority of the city's urban area expansion was found to have occurred in the city's eastern and southern regions. This research also suggests that decision-makers and municipal Government should reconsider city expansion strategies. Moreover, the future city master plans of 2050 must emphasize the relevance of rooftop urban planting and natural resource conservation. Numéro de notice : A2023-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.14358/PERS.22-00102R2 Date de publication en ligne : 01/01/2023 En ligne : https://doi.org/10.14358/PERS.22-00102R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102357 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2023011	SL	Revue	Centre de documentation	Revues en salle	Disponible

The simulation and prediction of land surface temperature based on SCP and CA-ANN models using remote sensing data: A case study of Lahore / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 12 (December 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 12 (December 2022) . - pp 783 - 790 Titre : The simulation and prediction of land surface temperature based on SCP and CA-ANN models using remote sensing data: A case study of Lahore Type de document : Article/Communication Auteurs : Muhammad Nasar Ahmad, Auteur ; Shao Zhengfeng, Auteur ; Andaleeb Yaseen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 783 - 790 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] changement climatique [Termes IGN] changement d'utilisation du sol [Termes IGN] classification par réseau neuronal [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] MNS SRTM [Termes IGN] modèle de simulation [Termes IGN] Pakistan [Termes IGN] planification urbaine [Termes IGN] température au sol Résumé : (auteur) Over the last two decades, urban growth has become a major issue in Lahore, accelerating land surface temperature (LST) rise. The present study focused on estimating the current situation and simulating the future LST patterns in Lahore using remote sensing data and machine learning models. The semi-automated classification model was applied for the estimation of LST from 2000 to 2020. Then, the cellular automata-artificial neural networks (CA-ANN) module was implemented to predict future LST patterns for 2030 and 2040, respectively. Our research findings revealed that an average of 2.8 °C of land surface temperature has increased, with a mean LST value from 37.25 °C to 40.10 °C in Lahore during the last two decades from 2000 to 2020. Moreover, keeping CA-ANN simulations for land surface temperature, an increase of 2.2 °C is projected through 2040, and mean LST values will be increased from 40.1 °C to 42.31 °C by 2040. The CA-ANN model was validated for future LST simulation with an overall Kappa value of 0.82 and 86.2% of correctness for the years 2030 and 2040 using modules for land-use change evaluation. The study also indicates that land surface temperature is an important factor in environmental changes. Therefore, it is suggested that future urban planning should focus on urban rooftop plantations and vegetation conservation to minimize land surface temperature increases in Lahore. Numéro de notice : A2022-886 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.22-00071R2 Date de publication en ligne : 01/12/2022 En ligne : https://doi.org/10.14358/PERS.22-00071R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102208 [article]

Improving accuracy of local geoid model using machine learning approaches and residuals of GPS/levelling geoid height / Mosbeh R. Kaloop in Survey review, vol 54 n° 387 (November 2022)  

Public [article]  inSurvey review > vol 54 n° 387 (November 2022) . - pp 505 - 518 Titre : Improving accuracy of local geoid model using machine learning approaches and residuals of GPS/levelling geoid height Type de document : Article/Communication Auteurs : Mosbeh R. Kaloop, Auteur ; Samui Pijush, Auteur ; Mostafa Rabah, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 505 - 518 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] apprentissage automatique [Termes IGN] géoïde gravimétrique [Termes IGN] géoïde local [Termes IGN] Koweit [Termes IGN] MNS SRTM [Termes IGN] modèle de géopotentiel [Termes IGN] nivellement avec assistance GPS [Termes IGN] processus gaussien [Termes IGN] régression [Termes IGN] régression multivariée par spline adaptative [Termes IGN] résidu Résumé : (auteur) This study aims to use GPS/Levelling data and machine learning techniques (MLs) to model a high precision local geoid for Kuwait. To improve the accuracy of a local geoid the global geopotential model and local terrain effect should be incorporated. The geoid model was improved based on the modelling of geoid residuals using three MLs. Minimax Probability Machine Regression (MPMR), Gaussian Process Regression (GPR), and Multivariate Adaptive Regression Splines (MARS) MLs were developed for modelling the calculated geoid residuals. The results show that the accuracy of the three MLs was improved compared to previous studies, and the accuracy of the GPR model was better than the other models. The standard deviations of Kuwait geoid undulation determined by GPS/Levelling, gravimetric, and developed GPR models were 1.377, 1.375, 1.375 m, respectively. Thus, the developed GPR model has successfully predicted an accurate geoid height of Kuwait with maximum variation approaches ±0.02 m. Numéro de notice : A2022-829 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1970918 Date de publication en ligne : 27/08/2021 En ligne : https://doi.org/10.1080/00396265.2021.1970918 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102013 [article]

Detection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])  

Public [article]  inGeocarto international > Vol 37 n° 17 [20/08/2022] . - pp 5017 - 5040 Titre : Detection of potential gold mineralization areas using MF-fuzzy approach on multispectral data Type de document : Article/Communication Auteurs : Tohid Nouri, Auteur Année de publication : 2022 Article en page(s) : pp 5017 - 5040 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] altération géologique [Termes IGN] analyse des mélanges spectraux [Termes IGN] appariement d'images [Termes IGN] diffraction [Termes IGN] image multibande [Termes IGN] Iran [Termes IGN] logique floue [Termes IGN] mine d'or [Termes IGN] MNS ASTER [Termes IGN] pixel [Termes IGN] prospection minérale [Termes IGN] sédiment [Termes IGN] spectrométrie Résumé : (auteur) The northeast area of Ardabil, a city located in northwestern Iran, is one of the potential gold mineralization areas. In this study, ASTER data were used to identify the alteration events in this region. For this purpose, a novel approach was used in which the fuzzy logic was implemented to extract the co-occurrence map of the endmembers. This method revealed alterations more accurately than SID. Stream sediment samples were employed to validate the obtained results. Since these samples are alluvial, their catchment basins were determined and overlaid with the alteration maps. To the best of the authors’ knowledge, this validation approach has not been used in previous studies. The extracted alteration zones were in high conformity to the stream sediment samples. Next, X-ray diffraction (XRD) analysis and field spectrometry were used for delineation of the mineralogical phases present in the anomalous areas. Finally, the potential gold mineralization zones were identified. Numéro de notice : A2022-701 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1903575 Date de publication en ligne : 07/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1903575 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101560 [article]

Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)  

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Incorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping / Jwan Al-Doski in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 8 (August 2022)  

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A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)  

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A GIS-based approach for identification of optimum runoff harvesting sites and storage estimation: a study from Subarnarekha-Kangsabati Interfluve, India / Manas Karmakar in Applied geomatics, vol 14 n° 2 (June 2022)  

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Glacier mass loss in the Alaknanda basin, Garhwal Himalaya on a decadal scale / S.N. Remya in Geocarto international, vol 37 n° 10 ([01/06/2022])  

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Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) / Safwan Mohammed in Geocarto international, vol 37 n° 6 ([01/04/2022])  

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An approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor / Litesh Bopche in Applied geomatics, vol 14 n° 1 (March 2022)  

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Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil / Aliny Aparecida Dos Reis in Geocarto international, vol 37 n° 5 ([01/03/2022])  

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Estimation of the height datum geopotential value of Hong Kong using the combined Global Geopotential Models and GNSS/levelling data / Panpan Zhang in Survey review, vol 54 n° 383 (March 2022)  

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Application of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image / Efosa Gbenga Adagbasa in Geocarto international, vol 37 n° 1 ([01/01/2022])  

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