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The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 10 (October 2022) . - pp 665 - 671 Titre : The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Tianyu Guo, Auteur ; Chengye Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 665 - 671 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] Chine [Termes IGN] couvert végétal [Termes IGN] Google Earth Engine [Termes IGN] hétérogénéité spatiale [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-OLI [Termes IGN] industrie minière [Termes IGN] mine [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] régression géographiquement pondérée [Termes IGN] régression multiple [Termes IGN] réseau neuronal artificiel Résumé : (auteur) To determine the fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas, six types of data were used as driving factors and three methods —multi-linear regression (MLR), geographically weighted regression (GWR), and geographically weighted artificial neural network (GWANN)— were adopted in the modeling. The experiments, conducted in Shengli mining areas located in Xilinhot city, China, show that the MLR model without consideration of spatial heterogeneity and spatial non-stationarity performs the worst and that the GWR model presents obvious location differences, since it predefines a linear relationship which is unable to describe FVC for some locations. The GWANN model, improving on these defects, is the most suitable model for the FVC driving process in mining areas; it outperforms the other two models, with root-mean-square error (RMSE) and mean absolute percentage error (MAPE) reaching 0.16 and 0.20. It has improvements of approximately 24% in RMSE and 33% in MAPE compared to the MLR model, and those values grow to 59% and 71% when compared with the GWR model. Numéro de notice : A2022-813 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00070R3 Date de publication en ligne : 01/10/2022 En ligne : https://doi.org/10.14358/PERS.21-00070R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101973 [article]

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Heat wave-induced augmentation of surface urban heat islands strongly regulated by rural background / Shiqi Miao in Sustainable Cities and Society, vol 82 (July 2022)  

Public [article]  inSustainable Cities and Society > vol 82 (July 2022) . - n° 103874 Titre : Heat wave-induced augmentation of surface urban heat islands strongly regulated by rural background Type de document : Article/Communication Auteurs : Shiqi Miao, Auteur ; Wenfeng Zhan, Auteur ; Jiameng Lai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103874 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] Chine [Termes IGN] climat tropical [Termes IGN] couvert végétal [Termes IGN] densité de la végétation [Termes IGN] données environnementales [Termes IGN] forêt [Termes IGN] humidité de l'air [Termes IGN] ilot thermique urbain [Termes IGN] image Terra-MODIS [Termes IGN] nuit [Termes IGN] température au sol [Termes IGN] zone humide [Termes IGN] zone rurale Résumé : (auteur) The impact of heat waves (HWs) on surface urban heat islands (SUHIs) has been widely studied, but the spatial pattern of SUHI responsiveness to HWs across various climates remains unclear, and the influence of HW intensity on SUHI responsiveness has not been systematically quantified. Using MODIS land surface temperature data, here we investigated the responsiveness of SUHI to HWs (quantified as ∆I) as well as its variations with HW intensity in 354 cities in seven climate zones across China. We find that during HW periods, the SUHI and surface urban cool island are augmented in the humid and arid regions of China, respectively. The inter-city heterogeneity in rural vegetation coverage accounts for such a spatial pattern. In eastern China, the ∆I peaks in the north subtropical climate (0.72 ± 0.54 K for daytime and 0.29 ± 0.23 K for the nighttime) probably for its specific rural farming method. With the intensification of HWs, the augmentation effect can be further enhanced for the north subtropical, warm temperate, and arid temperate climates during the day and for almost all the climates at night. These findings can help advance the understanding of the responsiveness of SUHI to extreme climatic events. Numéro de notice : A2022-375 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2022.103874 Date de publication en ligne : 13/04/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103874 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100624 [article]

Smartphone digital photography for fractional vegetation cover estimation / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 5 (May 2022) . - pp 303 - 310 Titre : Smartphone digital photography for fractional vegetation cover estimation Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Yonghua Qu, Auteur ; Aleixandre Verger, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 303 - 310 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] analyse comparative [Termes IGN] champ visuel [Termes IGN] couvert végétal [Termes IGN] erreur moyenne quadratique [Termes IGN] forêt alpestre [Termes IGN] image à haute résolution [Termes IGN] image hémisphérique [Termes IGN] objectif grand angulaire [Termes IGN] téléphone intelligent Résumé : (Auteur) Accurate ground measurements of fractional vegetation cover (FVC) are key for characterizing ecosystem functions and evaluating remote sensing products. The increasing performance of cameras equipped in smartphones opens new opportunities for extensive FVC measurement through citizen science initiatives. However, the wide field of view (FOV) of smartphone cameras constitutes a key source of uncertainty in the estimation of vegetation parameters, which has been largely ignored. We designed a practical method to characterize the FOV of smartphones and improve the FVC estimation. The method was assessed in a mountainous forest based on the comparison with in situ fisheye photographs. After the FOV correction, the agreement of smart-phone and fisheye FVC estimates highly improved: root-mean-square error (RMSE) of 0.103 compared to 0.242 of the original smartphone FVC estimates without considering the FOV effect, mean difference of 0.074 versus 0.213, and coefficient of determination R 2 of 0.719 versus 0.353. Smartphone cameras outperform traditional fisheye cameras: the overexposure and low vertical resolution of fisheye photographs introduced uncertainties in FVCestimation while the insensitivity to exposure and high spatial resolution of smartphone cameras make photograph acquisition and analysis more automatic and accurate. The smartphone FVCestimates highly agree with the GF-1 satellite product: RMSE = 0.066, bias = 0.007, and R 2 = 0.745. This study opens new perspectives for the validation of satellite products. Numéro de notice : A2022-527 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00038R2 Date de publication en ligne : 01/05/2022 En ligne : https://doi.org/10.14358/PERS.21-00038R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101375 [article]

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Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 184 (February 2022) . - pp 203 - 214 Titre : Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data Type de document : Article/Communication Auteurs : Tianyu Hu, Auteur ; Dengjie Wei, Auteur ; Yanjun Su, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 203 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre urbain [Termes IGN] canopée [Termes IGN] Chine [Termes IGN] couvert végétal [Termes IGN] distribution spatiale [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Green area index [Termes IGN] image panoramique [Termes IGN] semis de points [Termes IGN] système de numérisation mobile Résumé : (auteur) Street trees are important components of an urban green space and understanding and measuring their ecological and cultural services is crucial for assessing the quality of streets and managing urban environments. Currently, most studies mainly focus on evaluating the ecological services of street trees by measuring the amount of greenness, but how to evaluate their aesthetic functions through quantitative measurements of street trees remain unclear. To address this problem, we propose a method to assess the aesthetic functions of street trees by quantifying the shape of greenness inspired by assessments of skyline aesthetics. Using a state-of-the-art mobile mapping system, we collected downtown-wide lidar data and panoramic images in Jinzhou City, Hebei Province, China. We developed a method for extracting the canopy line from the mobile lidar data, and then identified two basic elements, peaks and gaps, from street canopy lines and extracted six indexes (i.e., richness of peaks, evenness of peaks, frequency of peaks, total length of gaps, evenness of gaps and frequency of gaps) to describe the fluctuations and continuities of street canopy lines. We analyzed the abundance and spatial distribution of these indexes together with survey responses on the streets’ aesthetics and found that most of them were significantly correlated with human perception of streets. Compared to indexes of amount of greenness (e.g., green volume and green view index), these shape indexes have stronger influences on the physical aesthetic beauty of street trees. These findings suggest that a comprehensive assessment of the aesthetic function of street trees should consider both shape and amount of greenness. This study provides a new perspective for the assessment of urban green spaces and can assist future urban greening planning and urban landscape management. Numéro de notice : A2022-105 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.002 Date de publication en ligne : 15/01/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99602 [article]

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Fungal perspective of pine and oak colonization in Mediterranean degraded ecosystems / Irene Adamo in Forests, vol 13 n° 1 (January 2022)  

Public [article]  inForests > vol 13 n° 1 (January 2022) . - n° 88 Titre : Fungal perspective of pine and oak colonization in Mediterranean degraded ecosystems Type de document : Article/Communication Auteurs : Irene Adamo, Auteur ; Svetlana Dashevskaya, Auteur ; Josu G. Alday, Auteur Année de publication : 2022 Article en page(s) : n° 88 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse [Termes IGN] champignon mycorhizien [Termes IGN] couvert végétal [Termes IGN] écosystème forestier [Termes IGN] forêt méditerranéenne [Termes IGN] Fungi [Termes IGN] humus [Termes IGN] litière [Termes IGN] Pinus sylvestris [Termes IGN] Quercus ilex [Termes IGN] Quercus pedunculata [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Forest restoration has become one of the most important challenges for restoration ecology in the recent years. In this regard, soil fungi are fundamental drivers of forest ecosystem processes, with significant implications for plant growth and survival. However, the post-disturbance recovery of belowground communities has been rarely assessed, especially in highly degraded systems such as mines. Our aim was to compare forests and mined systems for biomass and structure of fungal communities in soil during early stages of tree establishment after disturbance. We performed ergosterol analysis and PacBio and Illumina sequencing of internal transcribed spacer 2 amplicons across soil layers in P. sylvestris, Q. robur and Q. ilex (holm oak) forests and naturally revegetated mined sites. In pine forests, total fungal biomass was significantly higher in litter and humus compared to mineral layers, with dominance of the mycorrhizal genera Tomentella, Inocybe and Tricholoma. Conversely, in oak forests the most abundant mycorrhizal genera were Tomentella, Cortinarius and Sebacina, but the biomass of saprotrophic fungi was greater in the litter layer compared to mycorrhizal fungi, with the genus Preussia being the most abundant. In the revegetated mined sites, ectomycorrhizal fungi dominated in the humus and mineral layers, with the mycorrhizal genus Oidiodendron being dominant. In contrast, in holm oak forests saprotrophic fungi dominated both soil humus and mineral layers, with the genera of Alternaria, Bovista and Mycena dominating the soil humus forest layer, while the genus Cadophora dominated the mineral layer. The habitat-specific differences in soil fungal community composition and putative functions suggest that an understanding of soil–plant–microbial interactions for different tree species and use of specific soil/litter inoculum upon planting/seeding might help to increase the effectiveness of tree restoration strategies in Mediterranean degraded sites. Numéro de notice : A2022-081 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.3390/f13010088 Date de publication en ligne : 08/01/2022 En ligne : https://doi.org/10.3390/f13010088 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99474 [article]

Fractional vegetation cover estimation algorithm for FY-3B reflectance data based on random forest regression method / Duanyang Liu in Remote sensing, vol 13 n° 11 (June-1 2021)  

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Inversion of solar-induced chlorophyll fluorescence using polarization measurements of vegetation / Haiyan Yao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)  

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Complémentarité des images optiques Sentinel-2 avec les images radar Sentinel-1 et ALOS-PALSAR-2 pour la cartographie de la couverture végétale : application à une aire protégée et ses environs au Nord-Ouest du Maroc via trois algorithmes d’apprentissage automatique / Siham Acharki in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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Détection des zones de dégradation et de régénération de la couverture végétale dans le sud du Sénégal à travers l'analyse des tendances de séries temporelles MODIS NDVI et des changements d'occupation des sols à partir d'images LANDSAT / Boubacar Solly in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain / R. Niederheiser in GIScience and remote sensing, vol 58 n° 1 (February 2021)  

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Artificial neural networks in agriculture / Sebastian Kujawa (2021)  

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Modelling landslide hazards under global changes: the case of a Pyrenean valley / Séverine Bernardie in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)  

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Proposition d’un référentiel de description et de détection de la végétation dans une agglomération / Mathilde Segaud (2021) 

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Soil erosion / António Vieira (2021)  

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Télédétection synchronisée hyperspectrale et LiDAR à retour d’onde complet : application au suivi des littoraux sableux de la région Pays-de-la-Loire / Giovanni Frati (2021)  

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