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Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India / Rabin Chakrabortty in Geocarto international, vol 37 n° 23 ([15/10/2022])
[article]
Titre : Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India Type de document : Article/Communication Auteurs : Rabin Chakrabortty, Auteur ; Subodh Chandra Pal, Auteur ; Fatemeh Rezaie, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6713 - 6735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie des risques
[Termes IGN] Inde
[Termes IGN] inondation
[Termes IGN] mousson
[Termes IGN] optimisation par essaim de particules
[Termes IGN] réseau neuronal artificiel
[Termes IGN] réseau neuronal profond
[Termes IGN] risque naturel
[Termes IGN] vulnérabilitéRésumé : (auteur) Flood-susceptibility mapping is an important component of flood risk management to control the effects of natural hazards and prevention of injury. We used a remote-sensing and geographic information system (GIS) platform and a machine-learning model to develop a flood susceptibility map of Kangsabati River Basin, India where flash flood is common due to monsoon precipitation with short duration and high intensity. And in this subtropical region, climate change’s impact helps to influence the distribution of rainfall and temperature variation. We tested three models-particle swarm optimization (PSO), an artificial neural network (ANN), and a deep-leaning neural network (DLNN)-and prepared a final flood susceptibility map to classify flood-prone regions in the study area. Environmental, topographical, hydrological, and geological conditions were included in the models, and the final model was selected based on the relations between potentiality of causative factors and flood risk based on multi-collinearity analysis. The model results were validated and evaluated using the area under receiver operating characteristic (ROC) curve (AUC), which is an indicator of the current state of the environment and a value >0.95 implies a greater risk of flash floods. The AUC values for ANN, DLNN, and PSO for training datasets were 0.914, 0.920, and 0.942, respectively. Among these three models, PSO showed the best performance with an AUC value of 0.942. The PSO approach is applicable for flood susceptibility mapping of the eastern part of India, a subtropical region, to allow flood mitigation and help to improve risk management in this region. Numéro de notice : A2022-750 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1953618 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1953618 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101742
in Geocarto international > vol 37 n° 23 [15/10/2022] . - pp 6713 - 6735[article]A model-based scenario analysis of the impact of forest management and environmental change on the understorey of temperate forests in Europe / Bingbin Wen in Forest ecology and management, vol 522 (October-15 2022)
[article]
Titre : A model-based scenario analysis of the impact of forest management and environmental change on the understorey of temperate forests in Europe Type de document : Article/Communication Auteurs : Bingbin Wen, Auteur ; Haben Blondeel, Auteur ; Dries Landuyt, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120465 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de sensibilité
[Termes IGN] azote
[Termes IGN] biodiversité
[Termes IGN] changement climatique
[Termes IGN] dynamique de la végétation
[Termes IGN] Europe centrale
[Termes IGN] forêt tempérée
[Termes IGN] gestion forestière durable
[Termes IGN] impact sur l'environnement
[Termes IGN] modèle de simulation
[Termes IGN] sous-étage
[Termes IGN] système d'aide à la décision
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) The temperate forest understorey is rich in terms of vascular plant diversity and plays a vital functional role. Given the sensitivity of this forest layer to forest management and global environmental change and the limited knowledge on its long-term dynamics, there is a need for decision support systems that can guide temperate forest managers to optimize their management in terms of understorey outcomes. In this study, using understorey resurvey data collected from across temperate Europe, we developed Generalized Additive Models (GAM) to predict four understorey properties based on forest management and environmental change data, and implemented this model in a web-based tool as a prototype understorey Decision Support System (DSS). Using seventy-two combined climate change, nitrogen(N) deposition and forest management scenarios, applied to two case study regions in Europe, we predicted temperate forest understorey biodiversity dynamics between 2020 and 2050. A sensitivity analysis subsequently allowed to quantify the relative importance of canopy opening, N deposition and climate change on understorey dynamics. Our study showed that, regardless of regions, understorey richness and the proportion of forest specialists generally decreased among most scenarios, but the proportion of woody species and the understorey vegetation total cover increased. Climate warming, N deposition, and increases in canopy openness all influenced understorey dynamics. Climate warming will shift composition towards a selection of forest generalists and woody species, but a less open canopy could mitigate this shift by increasing the proportion of forest specialists. The case studies also showed that these responses can be context-dependent, especially in terms of responses to N deposition. Numéro de notice : A2022-710 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120465 Date de publication en ligne : 19/08/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120465 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101587
in Forest ecology and management > vol 522 (October-15 2022) . - n° 120465[article]Silvicultural experiment assessment using lidar data collected from an unmanned aerial vehicle / Diogo N. Cosenza in Forest ecology and management, vol 522 (October-15 2022)
[article]
Titre : Silvicultural experiment assessment using lidar data collected from an unmanned aerial vehicle Type de document : Article/Communication Auteurs : Diogo N. Cosenza, Auteur ; Jason Vogel, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120489 Langues : Anglais (eng) Descripteur : [Termes IGN] croissance végétale
[Termes IGN] données allométriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modélisation de la forêt
[Termes IGN] Pinus taeda
[Termes IGN] plantation forestière
[Termes IGN] sylviculture
[Vedettes matières IGN] ForesterieRésumé : (auteur) Collecting field data in silvicultural experiments can be challenging and time-consuming. Alternatively, unmanned aerial vehicles using laser scanners (UAV-lidar) can be used for cost-effective data collection in forest stands. This work aims to assess the capability of UAV-lidar to estimate biophysical forest attributes in silvicultural experiments. The showcase experiment refers to the IMPAC II (Intensive Management Practices Assessment Center II), a long-term project of 24 plots aiming to assess the effects of fertilization and weed control on forest growth and nutrient cycling in past and ongoing silvicultural treatments in a second rotation of loblolly pine (Pinus taeda L.) plantation at age 12 years. Treatment performances were assessed based on four biometric attributes related to forest productivity: Growing stock biomass (Mg ha−1), stem volume (m3 ha−1), dominant height (m), and leaf area index (LAI, m2 m−2). We used the area-based approach (ABA) and multiple linear models to characterize these forest attributes in the different silvicultural treatments and use their predictions to run the experiment analysis. Two groups of ALS-derived metrics were tested in the modeling, traditional metrics and a novel group of metrics based on plant area density (PAD) distribution. Models using PAD-based metrics increased the correlation between observed and predicted values (R2) from 0.27–0.40 to 0.50–0.85 when compared to the same models using traditional metrics, while the relative root mean square errors (RMSE%) of the predictions were reduced from 6–18% to 4–12%. Experiment analysis using UAV-lidar data and PAD-based model predictors led to the same results as those using field observations: i) fertilization was the most effective treatment for enhancing stand attributes, especially in terms of biomass, stem volume, and LAI; ii) weed control alone provided marginal improvements in the stands; iii) actively retreating stands in both first and second rotation led to increased growth when compared to the carryover effects. UAV-lidar using PAD-based metrics was effective in characterizing enhanced silvicultural treatments and might benefit studies involving understory assessment. Numéro de notice : A2022-314 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2022.120489 En ligne : https://doi.org/10.1016/j.foreco.2022.120489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102250
in Forest ecology and management > vol 522 (October-15 2022) . - n° 120489[article]Analysis of the spatial range of service and accessibility of hospitals designated for coronavirus disease 2019 in Yunnan Province, China / Liangting Zheng in Geocarto international, vol 37 n° 22 ([10/10/2022])
[article]
Titre : Analysis of the spatial range of service and accessibility of hospitals designated for coronavirus disease 2019 in Yunnan Province, China Type de document : Article/Communication Auteurs : Liangting Zheng, Auteur ; Jia Li, Auteur ; Wenying Hu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6519 - 6537 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] diagramme de Voronoï
[Termes IGN] données médicales
[Termes IGN] données routières
[Termes IGN] épidémie
[Termes IGN] interpolation inversement proportionnelle à la distance
[Termes IGN] interpolation par pondération de zones
[Termes IGN] maladie virale
[Termes IGN] médecine humaine
[Termes IGN] secours d'urgence
[Termes IGN] Yunnan (Chine)Résumé : (auteur) COVID-19 poses a major threat to global health care systems, and the recent surge in mortality rates confirms the importance of timely access to care. The capacity of medical service providers is reflected both in the spatial accessibility of medical institutions and in the spatial scope of their services. Therefore, this study aims to investigate the spatial scope of services and spatial accessibility of COVID-19-designated hospitals in Yunnan Province, China. Data are collected from multiple sources and included COVID-19 case data, road data, and data from designated hospitals for COVID-19 in Yunnan Province. The optimal spatial service range for designated hospitals is delineated using a weighted Voronoi diagram that takes into account the number of medical staff and the number of beds in the hospital. Traffic accessibility coefficients are introduced to analyze the spatial accessibility of COVID-19-designated hospitals, and the spatial accessibility of each designated hospital is visualized using the inverse distance weighting interpolation algorithm. The results show the following: (1) COVID-19 cases in Yunnan Province are concentrated in the central and northern regions. The largest single cells in the weighted Voronoi diagram are mainly Pu'er (59168 km2), Honghe (35569 km2), and Baoshan (46795 km2), and the time cost of attainting medical treatment is greater for residents in marginal areas. (2) Within the service space of designated hospitals, 90.24% of patients could obtain medical assistance within 2 h. Those in 52 (36.36%) counties within a municipal jurisdiction could obtain medical services within 2 h, and 76.47% of counties have above-average spatial accessibility. (3) Medical resources in Yunnan Province should be shifted toward the high-risk east-central region and the less spatially accessible in southern and western regions. Numéro de notice : A2022-728 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1943008 Date de publication en ligne : 09/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1943008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101674
in Geocarto international > vol 37 n° 22 [10/10/2022] . - pp 6519 - 6537[article]Age-independent diameter increment models for mixed mountain forests / Albert Ciceu in European Journal of Forest Research, vol 141 n° 5 (October 2022)
[article]
Titre : Age-independent diameter increment models for mixed mountain forests Type de document : Article/Communication Auteurs : Albert Ciceu, Auteur ; Karol Bronisz, Auteur ; Juan Garcia-Duro, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 781 - 800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] croissance des arbres
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] échantillonnage
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt alpestre
[Termes IGN] forêt inéquienne
[Termes IGN] modèle de croissance végétale
[Termes IGN] modélisation de la forêt
[Termes IGN] peuplement mélangé
[Termes IGN] Picea abies
[Termes IGN] Roumanie
[Vedettes matières IGN] ForesterieRésumé : (auteur) Mixed mountain forests with an uneven-aged structure are characterized by a high tree-growth variability making traditional age-dependent growth models inapplicable. Estimating site productivity is yet another impediment for modelling tree growth in such forests. Uneven-aged mixed-stand forests are known for their high resilience, resistance and productivity, and are being promoted as a suitable alternative to even-aged, pure plantations for climate change adaptation and mitigation. However, their growth must be accurately measured and predicted, but diameter at the breast height (dbh) increment models specifically designed for uneven-aged mixed mountain forests are still rare. Using permanent sampling network data and 465 increment cores, we built two age-independent dbh increment (id) models for the main species of the study area, namely Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.). Mixed effects models and the algebraic difference approach were employed to develop id models based on empirical and commonly used theoretical growth functions. A past growth index was further developed and introduced in the model in order to explain the id variability. Several mixed effects calibration strategies were assessed in order to obtain the most accurate localized curve for new plots. Tree size, competition and biogeoclimatic variables were found to explain the id through the empirical growth function, while the growth index significantly improved the theoretical growth function for Norway spruce. The optimization of the calibration strategy for the mixed effects modelling framework enables the growth index implementation in forest practice as an accurate method for estimating site productivity. The accuracy of the two id models was similar: the root mean squared error of the empirical growth function varied between 0.940 and 1.042 cm for spruce, beech and fir, while the root mean squared error obtained through the theoretical growth function for spruce only was 1.105 cm. The basal area increment prediction at the plot level based on the theoretical growth function reached a root mean squared error of 0.043 m2 while using the empirical growth function the root mean squared error is 0.047 m2. The high accuracy obtained using age-independent models underlines their suitability for predicting growth in mixed uneven-aged forests. The developed models can be easily integrated into forest practice to accurately obtain id estimates. Numéro de notice : A2022-758 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-022-01473-5 Date de publication en ligne : 13/08/2022 En ligne : https://doi.org/10.1007/s10342-022-01473-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101767
in European Journal of Forest Research > vol 141 n° 5 (October 2022) . - pp 781 - 800[article]An analysis of twitter as a relevant human mobility proxy / Fernando Terroso-Saenz in Geoinformatica, vol 26 n° 4 (October 2022)PermalinkApplication of a graph convolutional network with visual and semantic features to classify urban scenes / Yongyang Xu in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)PermalinkChallenging the link between functional and spectral diversity with radiative transfer modeling and data / Javier Pacheco-Labradora in Remote sensing of environment, vol 280 (October 2022)PermalinkCorrecting laser scanning intensity recorded in a cave environment for high-resolution lithological mapping: A case study of the Gouffre Georges, France / Michaela Nováková in Remote sensing of environment, vol 280 (October 2022)PermalinkDeep learning-based local climate zone classification using Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lin Zhou in Geo-spatial Information Science, vol 25 n° 3 (October 2022)PermalinkDeep learning high resolution burned area mapping by transfer learning from Landsat-8 to PlanetScope / V.S. Martins in Remote sensing of environment, vol 280 (October 2022)PermalinkDetecting overmature forests with airborne laser scanning (ALS) / Marc Fuhr in Remote sensing in ecology and conservation, vol 8 n° 5 (October 2022)PermalinkDetermination of local geometric geoid model for Kuwait / Ahmed Zaki in Journal of applied geodesy, vol 16 n° 4 (October 2022)PermalinkDSNUNet: An improved forest change detection network by combining Sentinel-1 and Sentinel-2 images / Jiawei Jiang in Remote sensing, vol 14 n° 19 (October-1 2022)PermalinkEstimating urban functional distributions with semantics preserved POI embedding / Weiming Huang in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)Permalink