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A high-resolution gravimetric geoid model for Kingdom of Saudi Arabia / Ahmed Zaki in Survey review, vol 54 n° 386 (September 2022)
[article]
Titre : A high-resolution gravimetric geoid model for Kingdom of Saudi Arabia Type de document : Article/Communication Auteurs : Ahmed Zaki, Auteur ; Saad Mogren, Auteur Année de publication : 2022 Article en page(s) : pp 375 - 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Arabie Saoudite
[Termes IGN] géoïde altimétrique
[Termes IGN] géoïde gravimétrique
[Termes IGN] geoïde marin
[Termes IGN] intégrale de Stokes
[Termes IGN] modèle de géopotentiel
[Termes IGN] modèle numérique de surface
[Termes IGN] nivellement avec assistance GPS
[Termes IGN] transformation rapide de FourierRésumé : (auteur) A high-resolution gravimetric geoid model for the Kingdom of Saudi Arabia area was determined. A data set of 459,848 land gravity, 80,632 shipborne marine gravity data, DTU17 altimetry gravity model, and XGM2019e global geopotential model. The computation strategy followed for modelling of the gravimetric geoid is based on the Remove-Compute-Restore with Residual Terrain Model reduction and the 1D- Fast Fourier Transform approach technique. The geoid heights have been determined by using the Stokes integral with Wong–Gore modification. The accuracy of the resulting geoid models was evaluated by comparing them with 5385 GPS/levelling points. The geoid accuracy over all the kingdom is better than 11 cm in STD sense and the comparison in sub-areas obtained accuracy range from 2.8 to 11.9 cm according to the density of gravity observations. Numéro de notice : A2022-657 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1944544 Date de publication en ligne : 29/06/2021 En ligne : https://doi.org/10.1080/00396265.2021.1944544 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101508
in Survey review > vol 54 n° 386 (September 2022) . - pp 375 - 390[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)
[article]
Titre : Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine Type de document : Article/Communication Auteurs : Luis Carrasco, Auteur ; Go Fujita, Auteur ; Kensuke Kito, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 277 - 289 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] cartographie historique
[Termes IGN] détection de changement
[Termes IGN] Google Earth
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] Japon
[Termes IGN] phénologie
[Termes IGN] photographie aérienne
[Termes IGN] réflectance de surface
[Termes IGN] rizière
[Termes IGN] signature spectraleRésumé : (auteur) Mapping the expansion or reduction of rice fields is fundamental for food and water security, greenhouse gas emission accounting, and environmental management. The historical mapping of rice fields with satellite images is challenging because of the limited availability of remote sensing and training data from past decades. The use of phenology-based algorithms has been proposed for mapping rice fields because they can take advantage of rice fields’ characteristic spectral signature during the transplanting phase and do not need training data. However, in order to employ phenology-based algorithms effectively for the historical rice mapping of large areas, we need to incorporate automatized methods able to deal with non-usable data (e.g., cloud cover) and with spatial inconsistencies in the number of available images for each pixel. Here we propose the combination of a pixel-based, phenological algorithm with the temporal aggregation of all available Landsat images to produce national level historical maps of rice fields in Japan from the 1980s onwards. We used temporally aggregated metrics (median, percentiles, etc.), derived from spectral indices of a large number of images within the Google Earth Engine, to minimize the issue of inconsistent image availability and reduce the effects of outliers in phenology-based algorithms. We produced seven rice field maps, for the periods 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, 2010–14, and 2015–19. The overall map accuracies ranged from 83% to 95% when validated with visually interpreted aerial photography. We detected a 23% decrease in the area of rice fields at a country level, although the changes varied greatly among prefectures. Here we present the first freely available historical rice field maps of Japan from the 1980s onwards, together with the source code, and a web application that enables the exploration of the maps and data relating to the derived rice field area changes. The application of temporal aggregation is promising for dealing with the gap-filling of large amounts of satellite data, reducing the issue of data outliers and providing an effective use of the historical Landsat archive for phenology-based crop detection algorithms. Our maps could greatly help researchers, conservationists and policymakers studying the drivers and consequences of rice field changes, and our methods could be extrapolated to map rice fields at large scales in other regions of the world. Numéro de notice : A2022-665 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.07.018 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.07.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101527
in ISPRS Journal of photogrammetry and remote sensing > vol 191 (September 2022) . - pp 277 - 289[article]Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements / Devendra Shashikant Nagale in Geodesy and Geodynamics, vol 13 n° 5 (September 2022)
[article]
Titre : Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements Type de document : Article/Communication Auteurs : Devendra Shashikant Nagale, Auteur ; Suresh Kannaujiya, Auteur ; Param K. Gautam, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 445 - 455 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] coefficient de corrélation
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] données GRACE
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] mousson
[Termes IGN] Népal
[Termes IGN] pondération
[Termes IGN] série temporelle
[Termes IGN] sismicité
[Termes IGN] surcharge hydrologique
[Termes IGN] variation saisonnièreRésumé : (auteur) The Himalayan terrain is an epitome of ongoing convergence and geodetic deformation where both tectonic and non-tectonic forces prevail. In this study, the Gravity Recovery and Climate Experiment (GRACE) and Global Positioning System (GPS) datasets are used to assess the impact of seasonal loading on deformation with seismicity in Nepal. The recorded GPS data from 21 Global Navigation Satellite System (GNSS) stations during 2017–2020 are processed with respect to ITRF14 and the Indian reference frame, and the Center for Space Research (CSR) mascon RL06 during 2002–2020 is adopted to estimate the terrestrial water storage (TWS) change over the Ganga-Brahmaputra River basin. The results indicate that the hydrological loading effect or TWS change shows high negative, high positive, and moderately positive values in pre-monsoon, co-monsoon, and post-monsoon months, respectively. The detrended GPS data of both horizontal and vertical components correlate with the seasonal TWS change using the Pearson correlation coefficient at each GNSS site. In addition, the correlation coefficient has been interpolated using inverse distance weighting to investigate the regional TWS influence on geodetic displacement. In the north component, the correlation coefficient ranges from −0.6 to 0.6. At the same time, the TWS is positively correlated with geodetic displacement (0.82) in the east component, and the correlation coefficient is negative (−0.69) in the vertical component. The negative correlation signifies an inverse relationship between seasonal TWS variation and geodetic displacements. The strain rate is estimated, which shows higher negative values in pre-monsoon than in post-monsoon. Similarly, the effect of seismicity is 47.90% for pre-monsoon, 15.97% for co-monsoon, and 17.56% for post-monsoon. Thus we can infer that the seismicity decreases with the increase of seasonal hydrological loading. Furthermore, the effect of strain is much higher in pre-monsoon than in post-monsoon since the impact of co-monsoon continues to persist on a small scale in the post-monsoon season. Numéro de notice : A2022-762 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.geog.2022.02.006 Date de publication en ligne : 20/05/2022 En ligne : https://doi.org/10.1016/j.geog.2022.02.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101780
in Geodesy and Geodynamics > vol 13 n° 5 (September 2022) . - pp 445 - 455[article]Mapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression / Haoyu Wang in Remote sensing of environment, vol 278 (September 2022)
[article]
Titre : Mapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression Type de document : Article/Communication Auteurs : Haoyu Wang, Auteur ; Xiuyuan Zhang, Auteur ; Shihong Du, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113088 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] apprentissage profond
[Termes IGN] carte d'occupation du sol
[Termes IGN] cartographie thématique
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] croissance urbaine
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de régression
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (auteur) Global urbanization changes land cover patterns and affects the living environment of humans. However, urbanization and its evolution process, i.e., conversions among diverse land covers, are hard to measure, as existing land cover maps usually have low temporal resolutions; conversely, long-term and temporally dense land cover maps, such as vegetation-impervious-soil decomposition maps base on MODIS, ignore the important land cover of cropland in urban evolution process (UEP). To resolve the issue, this study suggests a novel model named time-extended non-crop vegetation-impervious-cropland (Time V-I-C) to represent and quantify different stages of UEP; then, a normalized multi-objective T-ConvLSTM (NMT) method is proposed to unmix cropland, non-crop vegetation, and impervious based on the intra-annual remotely-sensed time series, and obtain their fractions in each pixel for generating UEP maps. Consequently, UEP maps from 2001 to 2018 are generated for two Chinese urban agglomerations, i.e., Beijing-Tianjin-Hebei and Yangtze River Delta urban agglomerations. The mapping results have high accuracies with a small standard error of regression (SER) of 13.1%, small root mean square error (RMSE) of 12.6%, and small mean absolute error (MAE) of 8.4%, and the maps reveal the different UEP in the two urban agglomerations. Therefore, this study provides a new idea for expressing UEP and contributes to a wide range of urbanization studies and sustainable city development. Numéro de notice : A2022-511 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1016/j.rse.2022.113088 Date de publication en ligne : 25/05/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113088 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101049
in Remote sensing of environment > vol 278 (September 2022) . - n° 113088[article]Point-of-interest detection from Weibo data for map updating / Xue Yang in Transactions in GIS, vol 26 n° 6 (September 2022)
[article]
Titre : Point-of-interest detection from Weibo data for map updating Type de document : Article/Communication Auteurs : Xue Yang, Auteur ; Jie Gao, Auteur ; Xiaoyun Zheng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2716 - 2738 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] commerce de détail
[Termes IGN] détection automatique
[Termes IGN] détection de changement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] géocodage
[Termes IGN] inférence
[Termes IGN] information sémantique
[Termes IGN] mise à jour cartographique
[Termes IGN] point d'intérêt
[Termes IGN] Wuhan (Chine)Résumé : (auteur) Points-of-interest (POIs) geographic information system data are increasingly important for supporting map generation and navigation services, although updating their semantic and location information still largely depends on manual labor. In this study, we propose a novel method to automatically detect the changes in POIs from Chinese text and check-in position data provided by the Chinese social media platform, Weibo. The proposed method includes three steps: (1) POI name recognition; (2) location confirmation; (3) and change detection. First, we propose recognizing a POI's name from Weibo text using the improved conditional random field algorithm. Then, we detect the location of each named POI by integrating the text address with the check-in position. The changes in the detected POIs are recognized by extracting the status words from Weibo text and a three-level status word database. To verify the effectiveness of the proposed method, we examine Wuhan as a case and detect the changes in the commercial POI using real-world Weibo data collected from January to September 2020. Based on the validation of three common map platforms, the data provided and the manual field investigation of 55 random samples, the identification accuracies for newly added POIs, the unchanged POIs, and expired POIs are approximately 100, 95.8, and 91.7%, respectively. Numéro de notice : A2022-734 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12982 Date de publication en ligne : 04/09/2022 En ligne : https://doi.org/10.1111/tgis.12982 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101701
in Transactions in GIS > vol 26 n° 6 (September 2022) . - pp 2716 - 2738[article]Rapid source models of the 2021 Mw 7.4 Maduo, China, earthquake inferred from high-rate BDS3/2, GPS, Galileo and GLONASS observations / Jianfei Zang in Journal of geodesy, vol 96 n° 9 (September 2022)PermalinkTowards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping / Sandro Martinis in Remote sensing of environment, vol 278 (September 2022)PermalinkDetection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])PermalinkAn automatic approach for tree species detection and profile estimation of urban street trees using deep learning and Google street view images / Kwanghun Choi in ISPRS Journal of photogrammetry and remote sensing, vol 190 (August 2022)PermalinkAn investigation into heat storage by adopting local climate zones and nocturnal-diurnal urban heat island differences in the Tokyo Prefecture / Christopher O'Malley in Sustainable Cities and Society, vol 83 (August 2022)PermalinkDetecting preseismic signals in GRACE gravity solutions: Application to the 2011 Tohoku Mw 9.0 earthquake / Isabelle Panet in Journal of geophysical research : Solid Earth, vol 127 n° 8 (August 2022)PermalinkDetection 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)PermalinkFull-waveform classification and segmentation-based signal detection of single-wavelength bathymetric LiDAR / Xue Ji in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkIdentification of urban agglomeration spatial range based on social and remote-sensing data - For evaluating development level of urban agglomerations / Shuai Zhang in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkIncorporation 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)PermalinkSimulation of the potential impact of urban expansion on regional ecological corridors: A case study of Taiyuan, China / Wei Hou in Sustainable Cities and Society, vol 83 (August 2022)PermalinkSpatial assessment of ecosystem services provisioning changes in a forest-dominated protected area in NE Turkey / Can Vatandaslar in Environmental Monitoring and Assessment, vol 194 n° 8 (August 2022)PermalinkThe influence of data density and integration on forest canopy cover mapping using Sentinel-1 and Sentinel-2 time series in Mediterranean oak forests / Vahid Nasiri in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkTracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016–2020 / Rong Zhang in International journal of applied Earth observation and geoinformation, vol 112 (August 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)PermalinkUsing attributes explicitly reflecting user preference in a self-attention network for next POI recommendation / Ruijing Li in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkA model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway / Reza Sanayeia in Geocarto international, vol 37 n° 14 ([20/07/2022])PermalinkPS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan / Sajid Hussain in Geocarto international, vol 37 n° 13 ([15/07/2022])PermalinkAn accurate train positioning method using tightly-coupled GPS + BDS PPP/IMU strategy / Wei Jiang in GPS solutions, vol 26 n° 3 (July 2022)PermalinkA comparison of three multi-criteria decision-making models in mapping flood hazard areas of Northeast Penang, Malaysia / Rofiat Bunmi Mudashiru in Natural Hazards, vol 112 n° 3 (July 2022)PermalinkDetection of diseased pine trees in unmanned aerial vehicle images by using deep convolutional neural networks / Gensheng Hu in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkEffects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea / Mehmet Emin Ayhan in Marine geodesy, vol 45 n° 4 (July 2022)PermalinkA framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method / Yongyang Xu in Computers, Environment and Urban Systems, vol 95 (July 2022)PermalinkHeat wave-induced augmentation of surface urban heat islands strongly regulated by rural background / Shiqi Miao in Sustainable Cities and Society, vol 82 (July 2022)PermalinkInteractive visual analytics of moving passenger flocks using massive smart card data / Tong Zhang in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)PermalinkQuantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkA second-order attention network for glacial lake segmentation from remotely sensed imagery / Shidong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkStreet-view imagery guided street furniture inventory from mobile laser scanning point clouds / Yuzhou Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkEstimating feature extraction changes of Berkelah Forest, Malaysia from multisensor remote sensing data using and object-based technique / Syaza Rozali in Geocarto international, vol 37 n° 11 ([15/06/2022])PermalinkAssessing and mapping landslide susceptibility using different machine learning methods / Osman Orhan in Geocarto international, vol 37 n° 10 ([01/06/2022])PermalinkCoupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction / Tianhong Zhao in Computers, Environment and Urban Systems, vol 94 (June 2022)PermalinkDetecting interchanges in road networks using a graph convolutional network approach / Min Yang in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)PermalinkExtracting the urban landscape features of the historic district from street view images based on deep learning: A case study in the Beijing Core area / Siming Yin in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)PermalinkA 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)PermalinkGIS-based assessment of long-term traffic accidents using spatiotemporal and empirical Bayes analysis in Turkey / Saffet Erdoğan in Applied geomatics, vol 14 n° 2 (June 2022)PermalinkGraph-based block-level urban change detection using Sentinel-2 time series / Nan Wang in Remote sensing of environment, vol 274 (June 2022)PermalinkLarge-scale automatic identification of urban vacant land using semantic segmentation of high-resolution remote sensing images / Lingdong Mao in Landscape and Urban Planning, vol 222 (June 2022)PermalinkMapping monthly population distribution and variation at 1-km resolution across China / Zhifeng Cheng in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)PermalinkA phenology-based vegetation index classification (PVC) algorithm for coastal salt marshes using Landsat 8 images / Jing Zeng in International journal of applied Earth observation and geoinformation, vol 110 (June 2022)PermalinkPhysical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data / Sanat Agrawal in Cartographica, vol 57 n° 2 (Summer 2022)PermalinkVariance based fusion of VCI and TCI for efficient classification of agriculture drought using MODIS data / Anjana N.J. Kukunuri in Geocarto international, vol 37 n° 10 ([01/06/2022])PermalinkAnalyzing spatio-temporal pattern of the forest fire burnt area in Uttarakhand using Sentinel-2 data / Shailja Mamgain in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)PermalinkComparative analysis of gradient boosting algorithms for landslide susceptibility mapping / Emrehan Kutlug Sahin in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkNovel hybrid models combining meta-heuristic algorithms with support vector regression (SVR) for groundwater potential mapping / A'Kif Al-Fugara in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkResearch on automatic identification method of terraces on the Loess plateau based on deep transfer learning / Mingge Yu in Remote sensing, vol 14 n° 10 (May-2 2022)PermalinkSpatial-temporal variation of satellite-based gross primary production estimation in wheat-maize rotation area during 2000–2015 / Wenquan Xie in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkBuilding Information Modelling (BIM) for property valuation: A new approach for Turkish Condominium Ownership / Nida Celik Simsek in Survey review, vol 54 n° 384 (May 2022)PermalinkChineseTR: A weakly supervised toponym recognition architecture based on automatic training data generator and deep neural network / Qinjun Qiu in Transactions in GIS, vol 26 n° 3 (May 2022)PermalinkDeveloping a data-fusing method for mapping fine-scale urban three-dimensional building structure / Xinxin Wu in Sustainable Cities and Society, vol 80 (May 2022)PermalinkFramework for automatic coral reef extraction using Sentinel-2 image time series / Qizhi Zhang in Marine geodesy, vol 45 n° 3 (May 2022)PermalinkHow do voice-assisted digital maps influence human wayfinding in pedestrian navigation? / Yawei Xu in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)PermalinkLandslide susceptibility assessment considering spatial agglomeration and dispersion characteristics: A case study of Bijie City in Guizhou Province, China / Kezhen Yao in ISPRS International journal of geo-information, vol 11 n° 5 (May 2022)PermalinkMapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data / Santanu Malik in Geocarto international, vol 37 n° 8 ([01/05/2022])PermalinkProduction of optimum forest roads and comparison of these routes with current forest roads: a case study in Maçka, Turkey / Faruk Yildirim in Geocarto international, vol 37 n° 8 ([01/05/2022])PermalinkCrop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information / Murali Krishna Gumma in Geocarto international, vol 37 n° 7 ([15/04/2022])PermalinkAn exact statistical method for analyzing co-location on a street network and its computational implementation / Wataru Morioka in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)PermalinkAssessment 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])PermalinkClustering with implicit constraints: A novel approach to housing market segmentation / Xiaoqi Zhang in Transactions in GIS, vol 26 n° 2 (April 2022)PermalinkCoastal observation of sea surface tide and wave height using opportunity signal from Beidou GEO satellites: analysis and evaluation / Feng Wang in Journal of geodesy, vol 96 n° 4 (April 2022)PermalinkEstimation and testing of linkages between forest structure and rainfall interception characteristics of a Robinia pseudoacacia plantation on China’s Loess Plateau / Changkun Ma in Journal of Forestry Research, vol 33 n° 2 (April 2022)PermalinkExploring the association between street built environment and street vitality using deep learning methods / Yunqin Li in Sustainable Cities and Society, vol 79 (April 2022)PermalinkMining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction / Jincai Huang in Transactions in GIS, vol 26 n° 2 (April 2022)PermalinkParcel-based summer maize mapping and phenology estimation combined using Sentinel-2 and time series Sentinel-1 data / Yanyan Wang in International journal of applied Earth observation and geoinformation, vol 108 (April 2022)PermalinkResearch on machine intelligent perception of urban geographic location based on high resolution remote sensing images / Jun Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 4 (April 2022)PermalinkSimulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)PermalinkSpatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran / Naeim Mijani in Transactions in GIS, vol 26 n° 2 (April 2022)PermalinkSpecies level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery / Semiha Demirbaş Çağlayana in Geocarto international, vol 37 n° 6 ([01/04/2022])PermalinkVolunteered geographic information mobile application for participatory landslide inventory mapping / Raden Muhammad Anshori in Computers & geosciences, vol 161 (April 2022)PermalinkAn 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)PermalinkDeep-learning-based multispectral image reconstruction from single natural color RGB image - Enhancing UAV-based phenotyping / Jiangsan Zhao in Remote sensing, vol 14 n° 5 (March-1 2022)PermalinkDevelopment of a single-wavelength airborne bathymetric LiDAR: System design and data processing / Kai Guo in ISPRS Journal of photogrammetry and remote sensing, vol 185 (March 2022)PermalinkDynamic linkage between urbanization, electrical power consumption, and suitability analysis using remote sensing and GIS techniques / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)PermalinkEarly warning of COVID-19 hotspots using human mobility and web search query data / Takahiro Yabe in Computers, Environment and Urban Systems, vol 92 (March 2022)PermalinkEstimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds / Jiayuan Lin in Urban Forestry & Urban Greening, vol 69 (March 2022)PermalinkEstimation 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)PermalinkEstimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image / Sinan Kaptan in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkEvaluating Sentinel-1A datasets for rice leaf area index estimation based on machine learning regression models / Lamin R. Mansaray in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkEvaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China / Longfei Xie in Canadian Journal of Forest Research, Vol 52 n° 3 (March 2022)PermalinkExploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China / Zhen Li in Sustainable Cities and Society, vol 78 (March 2022)PermalinkFlood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)PermalinkGIS-based employment availabilities by mode of transport in Kuwait / S. Alkheder in Applied geomatics, vol 14 n° 1 (March 2022)PermalinkMonitoring of phenological stage and yield estimation of sunflower plant using Sentinel-2 satellite images / Omer Gokberk Narin in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkUltrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach / Linyuan Li in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)PermalinkUnderstanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea / Yang Xu in Computers, Environment and Urban Systems, vol 92 (March 2022)PermalinkUsing street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)PermalinkAboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkMulti-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkMulti-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests / Chong Zhang in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkSimulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkSimulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model / Hasan Aksoy in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkAnalysis of factors affecting adoption of volunteered geographic information in the context of national spatial data infrastructure / Munir Ahmad in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)PermalinkAnalysis of spatio-temporal changes in forest biomass in China / Weiyi Xu in Journal of Forestry Research, vol 33 n° 1 (February 2022)PermalinkApplication of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkBuilding footprint extraction in Yangon city from monocular optical satellite image using deep learning / Hein Thura Aung in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkA combination of convolutional and graph neural networks for regularized road surface extraction / Jingjing Yan in IEEE Transactions on geoscience and remote sensing, vol 60 n° 2 (February 2022)Permalink