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Mapping 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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 6 (June 2022) . - pp 1166 - 1184 Titre : Mapping monthly population distribution and variation at 1-km resolution across China Type de document : Article/Communication Auteurs : Zhifeng Cheng, Auteur ; Jianghao Wang, Auteur ; Yong Ge, Auteur Année de publication : 2022 Article en page(s) : pp 1166 - 1184 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] analyse spatiale [Termes IGN] autocorrélation spatiale [Termes IGN] Chine [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] figuration de la densité [Termes IGN] krigeage [Termes IGN] population [Termes IGN] série temporelle [Termes IGN] téléphonie mobile Résumé : (auteur) Fine-grained inner-annual population data are instrumental in climate change response, resource allocation, and epidemic control. However, such data are currently scarce due to the lack of human-related indicators with both high temporal resolution and long-term coverage that can be used in the process of population spatialization. Here, we estimate monthly 1-km gridded population distribution across China in 2015 using time-series mobile phone positioning data. We construct a hybrid downscaling model to map the gridded population by incorporating random forest and area-to-point kriging. The estimated monthly population products appear to capture inner-annual population variations, especially during special periods, such as the festival, holiday, and short-term labor flow period, which are characterized by large-scale population movements. Additionally, compared with census data, the hybrid model-based results obtained exhibit higher consistency than popular global population products across all spatial extents. Our monthly 1-km data products for the population distribution across China in 2015 provide a credible dataset that can be employed in studies aimed at accurate population-dependent decisions. Numéro de notice : A2022-407 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1854767 Date de publication en ligne : 07/12/2020 En ligne : https://doi.org/10.1080/13658816.2020.1854767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100724 [article]

Mapping 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])  

Public [article]  inGeocarto international > vol 37 n° 8 [01/05/2022] . - pp 2198 - 2214 Titre : Mapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data Type de document : Article/Communication Auteurs : Santanu Malik, Auteur ; Tridip Bhowmik, Auteur ; Umesh Mishra, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2198 - 2214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte d'occupation du sol [Termes IGN] estimation bayesienne [Termes IGN] géostatistique [Termes IGN] gestion durable [Termes IGN] Inde [Termes IGN] krigeage [Termes IGN] modèle de simulation [Termes IGN] puits de carbone [Termes IGN] régression [Termes IGN] réseau neuronal artificiel [Termes IGN] sol arable Résumé : (auteur) Prediction and accurate digital soil mapping (DSM) of soil organic carbon (SOC) at a local scale is a key factor for any agro-ecological modelling. This study aims to use remote sensing and terrain derivatives to provide a reliable method for SOC prediction. An advanced geostatistical-based empirical Bayesian Kriging regression (EBKR) method was used and performance was compared with the artificial neural network (ANN) and hybrid ANN, i.e. ANN-OK (ordinary kriging) and ANN-CK (cokriging). The result showed that the hybrid ANN model performs better than ANN, whereas the EBKR method outperforms all other methods with the highest R2 of 0.936. The DSM map shows that the highest SOC concentration was found in easternmost part of the study area with grass and agricultural land. This work shows the robustness of the EBKR prediction method over other techniques. The study will also aid the policymakers in adopting sustainable land use management. Numéro de notice : A2022-505 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1815864 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1080/10106049.2020.1815864 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101026 [article]

Mapping forest site quality at national level / Ana Aguirre in Forest ecology and management, vol 508 (March-15 2022)  

Public [article]  inForest ecology and management > vol 508 (March-15 2022) . - n° 120043 Titre : Mapping forest site quality at national level Type de document : Article/Communication Auteurs : Ana Aguirre, Auteur ; Daniel Moreno-Fernández, Auteur ; Iciar A. Alberdi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120043 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] autocorrélation spatiale [Termes IGN] carte forestière [Termes IGN] climat local [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Espagne [Termes IGN] gestion forestière durable [Termes IGN] inventaire forestier étranger (données) [Termes IGN] krigeage [Termes IGN] modèle numérique [Termes IGN] sécheresse [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Determining site quality is essential in order to develop sustainable forest management, allowing more appropriate silvicultural decisions to be made. However, most studies carried out in Spain have focused on a few species and at local scale, which makes it difficult to apply the findings or conduct studies at larger scales. The aim of this study is to obtain a site quality map at national scale for the main forest species (Pinus sylvestris, Pinus uncinata, Pinus pinea, Pinus halepensis, Pinus nigra, Pinus pinaster, Pinus canariensis, Pinus radiata, Abies alba, Juniperus thurifera, Quercus robur, Querus petraea, Quercus pyrenaica, Quercus faginea, Quercus ilex, Quercus suber, Populus nigra, Eucalyptus globulus, Eucalyptus camaldulensis, Fagus sylvatica, Castanea sativa, Quercus pubescens, Populus × canadensis, Betula alba). National Forest Inventory (NFI) data has been used to develop site quality models using the site form (SF) concept (dominant height- dominant diameter relationship). Universal Kriging techniques have been used to identify both the geographical trend linked to site factors (climatic, soil and physiographic variables) and their spatial autocorrelation to estimate the SF for every species. Finally, the information was interpolated for each tile of the Spanish National Forest Map in which the species considered was present, thus obtaining a SF national map for each species. The results reveal biologically consistent SF models, indicating that both NFI data and SF are suitable for studying site quality at national level. The variables used differ among the species analyzed, altitude being the most important variable for estimating SF models, while aridity and soil variables are less important. The results obtained could provide an important tool for forest managers working at national level with the main forest species in Spain. This methodology could be used for larger areas, such as at European level, and would allow some species to be analyzed at larger scales. Numéro de notice : A2022-161 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1016/j.foreco.2022.120043 Date de publication en ligne : 25/01/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120043 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99780 [article]

Spatial distribution of lead (Pb) in soil: a case study in a contaminated area of the Czech Republic / Nicolas Francos in Geomatics, Natural Hazards and Risk, vol 13 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 610 - 620 Titre : Spatial distribution of lead (Pb) in soil: a case study in a contaminated area of the Czech Republic Type de document : Article/Communication Auteurs : Nicolas Francos, Auteur ; Asa Gholizadeh, Auteur ; Eyal Ben-Dor, Auteur Année de publication : 2022 Article en page(s) : pp 610 - 620 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] autocorrélation spatiale [Termes IGN] contamination [Termes IGN] distribution spatiale [Termes IGN] image infrarouge [Termes IGN] interpolation spatiale [Termes IGN] krigeage [Termes IGN] plomb [Termes IGN] qualité du sol [Termes IGN] République Tchèque Résumé : (auteur) For decades, the Příbram district in the Czech Republic has been affected by industrial and mining activities, which are the main sources of heavy metal pollutants and negatively affect soil quality. A recent study examined visible–near-infrared (VNIR), shortwave-infrared (SWIR), and X-ray fluorescence (XRF) spectroscopy to model soil lead (Pb) content in a selected area located in Příbram. Following that study, and using the data, we examined the spatial distribution of Pb content in the soil, with a combination of traditional techniques (Moran’s I, hotspot analysis, and Kriging). One of the novel points of this work is the use of the Getis–Ord hotspot analysis before the execution of Kriging interpolation to better emphasize clustering patterns. The results indicated that Pb was a spatially dependent soil property and through extensive in-situ sampling, it was possible to generate an accurate interpolation model. The high-Pb hotspots coincided with topographic obstacles that were modeled using topographic profiles extracted from Google Earth, indicating that Pb content does not always exhibit a direct relationship with topographic height as a result of runoff, due to the contribution of topographic steps. This observation provides a new perspective on the relationship between Pb content and topographic patterns. Numéro de notice : A2022-872 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2039786 Date de publication en ligne : 23/02/2022 En ligne : https://doi.org/10.1080/19475705.2022.2039786 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102166 [article]

Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data / Xiaofang Sun in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Public [article]  inGeocarto international > vol 36 n° 14 [01/08/2021] . - pp 1549 - 1564 Titre : Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data Type de document : Article/Communication Auteurs : Xiaofang Sun, Auteur ; Bai Li, Auteur ; Zhengping Du, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1549 - 1564 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] carbone [Termes IGN] carte de la végétation [Termes IGN] classification barycentrique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données ICEsat [Termes IGN] données lidar [Termes IGN] données multisources [Termes IGN] Geoscience Laser Altimeter System [Termes IGN] image Terra-MODIS [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Kiangsi (Chine) [Termes IGN] krigeage [Termes IGN] modèle numérique de surface [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] régression des moindres carrés partiels Résumé : (auteur) An accurate estimation of forest aboveground biomass (AGB) is important for carbon accounting. In this study, six methods, including partial least squares regression, regression kriging, k-nearest neighbour, support vector machines, random forest and high accuracy surface modelling (HASM), were used to simulate forest AGB. Forest AGB was mapped by combining Geoscience Laser Altimeter System data, optical imagery and field inventory data. The Normalized Difference Vegetation Index (NDVI) and Wide Dynamic Range Vegetation Index (WDRVI0.2) of September and October, which had a stronger correlation with forest AGB than that of the peak growing season, were selected as predictor variables, along with tree cover percentage and three GLAS-derived parameters. The results of the different methods were evaluated. The HASM model had the best modelling accuracy (small MAE, RMSE, NRMSE, RMSV and NMSE and large R2). A forest AGB map of the study area was generated using the optimal model. Numéro de notice : A2021-555 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1655799 Date de publication en ligne : 28/08/2019 En ligne : https://doi.org/10.1080/10106049.2019.1655799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98108 [article]

The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran / Hojatolah Ganjkhanlo in Geocarto international, vol 35 n° 16 ([01/12/2020])  

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A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

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Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

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A web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)  

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A citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) / Ilyas Yalcin in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

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Development of a GIS and model-based method for optimizing the selection of locations for drinking water extraction by means of riverbank filtration / Yan Zhou (2020)  

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Développement d’un « ModelBuilder » pour l’évaluation de la recharge nette : cas de la nappe phréatique de Zéramdine Beni Hassène (Tunisie) / Imen Hentati in Géomatique expert, n° 128 (juin - juillet 2019)

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Embedding road networks and travel time into distance metrics for urban modelling / Henry Crosby in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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Exercices corrigés de géostatistique / Chantal de Fouquet (2019)

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Kriging and moving window kriging on a sphere in geometric (GNSS/levelling) geoid modelling / M. Ligas in Survey review, vol 50 n° 359 (March 2018)  

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