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Rapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park / Emma L. Davis in Remote sensing, vol 13 n° 11 (June-1 2021)
[article]
Titre : Rapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park Type de document : Article/Communication Auteurs : Emma L. Davis, Auteur ; Andrew Trant, Auteur ; Robert G. Way, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbuste
[Termes IGN] Arctique
[Termes IGN] Canada
[Termes IGN] changement climatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] détection de changement
[Termes IGN] écosystème
[Termes IGN] écotone
[Termes IGN] géostatistique
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] parc naturel national
[Termes IGN] régression logistique
[Termes IGN] surveillance de la végétation
[Termes IGN] toundraRésumé : (auteur) Northern protected areas guard against habitat and species loss but are themselves highly vulnerable to environmental change due to their fixed spatial boundaries. In the low Arctic, Torngat Mountains National Park (TMNP) of Canada, widespread greening has recently occurred alongside warming temperatures and regional declines in caribou. Little is known, however, about how biophysical controls mediate plant responses to climate warming, and available observational data are limited in temporal and spatial scope. In this study, we investigated the drivers of land cover change for the 9700 km2 extent of the park using satellite remote sensing and geostatistical modelling. Random forest classification was used to hindcast and simulate land cover change for four different land cover types from 1985 to 2019 with topographic and surface reflectance imagery (Landsat archive). The resulting land cover maps, in addition to topographic and biotic variables, were then used to predict where future shrub expansion is likely to occur using a binomial regression framework. Land cover hindcasts showed a 235% increase in shrub and a 105% increase in wet vegetation cover from 1985/89 to 2015/19. Shrub cover was highly persistent and displaced wet vegetation in southern, low-elevation areas, whereas wet vegetation expanded to formerly dry, mid-elevations. The predictive model identified both biotic (initial cover class, number of surrounding shrub neighbors), and topographic variables (elevation, latitude, and distance to the coast) as strong predictors of future shrub expansion. A further 51% increase in shrub cover is expected by 2039/43 relative to 2014 reference data. Establishing long-term monitoring plots within TMNP in areas where rapid vegetation change is predicted to occur will help to validate remote sensing observations and will improve our understanding of the consequences of change for biotic and abiotic components of the tundra ecosystem, including important cultural keystone species. Numéro de notice : A2021-442 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13112085 Date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.3390/rs13112085 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97832
in Remote sensing > vol 13 n° 11 (June-1 2021) . - n° 2085[article]Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece / Stavroula Dimitriadou in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)
[article]
Titre : Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece Type de document : Article/Communication Auteurs : Stavroula Dimitriadou, Auteur ; Konstantinos G. Nikolakopoulos, Auteur Année de publication : 2021 Article en page(s) : n° 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ArcMap
[Termes IGN] changement climatique
[Termes IGN] climat méditerranéen
[Termes IGN] évapotranspiration
[Termes IGN] Grèce
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de Monteith
[Termes IGN] système d'information géographique
[Termes IGN] température
[Termes IGN] utilisation du sol
[Termes IGN] variation saisonnièreRésumé : (auteur) The present study develops ArcMap models to implement the following three methods: FAO-56 Penman–Monteith (FAO PM), Hargreaves–Samani (HS) and Hansen, with the former used as a reference. Moreover, three models implementing statistical indices (RMSD, MB, NMB) are also created. The purpose is threefold, as follows: to investigate the variability in the daily mean reference evapotranspiration (ETo) for the Decembers and Augusts during 2016–2019, over Peloponnese, Greece. Furthermore, to investigate the agreement between the methods’ ETo estimates, and examine the former along with MODIS ET (daily) averaged products. The study area is a complex Mediterranean area. Meteorological data from sixty-two stations under the National Observatory of Athens (NOA), and MODIS Terra LST products, have been employed. FAO PM is found sensitive to wind speed and depicts interactions among climate parameters (T, evaporative demand and water availability) in the frame of climate change. The years 2016–2019 are four of the warmest since the preindustrial era. Hargreaves–Samani’s estimations for the Decembers of 2016–2019 were almost identical to MODIS ET, despite their different physical meaning. However, for the Augusts there are considerable discrepancies between the methods’ and MODIS’s estimates, attributed to the higher evaporative demand in the summertime. The GIS models are accurate, reliable, time-saving, and adjustable to any study area. Numéro de notice : A2021-522 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060390 Date de publication en ligne : 05/06/2021 En ligne : https://doi.org/10.3390/ijgi10060390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97959
in ISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 390[article]The Loop Effect: how climate change impacts the mitigation potential of the French forest sector / Philippe Delacote in Journal of Forest Economics, vol 36 n° 3 ([01/06/2021])
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Titre : The Loop Effect: how climate change impacts the mitigation potential of the French forest sector Type de document : Article/Communication Auteurs : Philippe Delacote, Auteur ; Antonello Lobianco, Auteur ; Sylvain Caurla, Auteur ; Jean-Daniel Bontemps , Auteur ; Anna Lungarska, Auteur ; Pierre Mérian , Auteur ; Miguel Rivière, Auteur ; Ahmed Barkaoui, Auteur Année de publication : 2021 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 201 - 264 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] dioxyde de carbone
[Termes IGN] économie forestière
[Termes IGN] industrie forestière
[Termes IGN] modèle numérique
[Vedettes matières IGN] Economie forestièreRésumé : (auteur) Objectives: Evaluate the capacity of temperate forest resources to both provide climate change mitigation and to sustain the downstream timber sector explicitly considering the cascade of biophysical and economic drivers (in particular, climate change impacts and subsequent adaptation actions) and their uncertainty. Methodology: A recursive bio-economic model of French forest resources, management, and timber markets has been coupled for this study with spatial statistical models of forest response to climate change long-term scenarios and land-use change. Main Results: (a) Climate change impacts on tree mortality are greater than those on tree growth variations; (b) Due to increasing competition with agriculture, climate change may reverse current trends in forest area expansion; (c) Due to rising average tree sizes, volume growth strongly declines over time and may eventually cease within the next century; (d) Future climate change impacts already have strong consequences on today’s forest investment profitability; (e) The relative importance of forest substitution over forest sequestration increases as the timeframe increases; (f) While the forest sector has the potential to counterbalance a significant share of the national carbon emissions, this potential is threatened by climate change and the need to adapt to it. Profit-driven forest management does increase mitigation; (g) Uncertainty derived from using different climatic models over the same IPCC storyline has the same order of magnitude as the uncertainty derived from using the same climatic model under different storylines. Numéro de notice : A2021-062 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1561/112.00000522 En ligne : http://dx.doi.org/10.1561/112.00000522 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96699
in Journal of Forest Economics > vol 36 n° 3 [01/06/2021] . - pp 201 - 264[article]The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)
[article]
Titre : The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries Type de document : Article/Communication Auteurs : Nagihan Aslan, Auteur ; Dilek Koc-San, Auteur Année de publication : 2021 Article en page(s) : n° 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image proche infrarouge
[Termes IGN] Normalized Difference Built-up Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] occupation du sol
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] température au sol
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (auteur) The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period. Numéro de notice : A2021-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060416 Date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.3390/ijgi10060416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97936
in ISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 416[article]Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change / Jiawei Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)
[article]
Titre : Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change Type de document : Article/Communication Auteurs : Jiawei Huang, Auteur ; Melissa S. Lucash, Auteur ; Robert M. Scheller, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1155 - 1178 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] carte de la végétation
[Termes IGN] changement climatique
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] modélisation de la forêt
[Termes IGN] monde virtuel
[Termes IGN] réalité virtuelle
[Termes IGN] visualisation 3D
[Termes IGN] Wisconsin (Etats-Unis)
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Communicating and understanding climate induced environmental changes can be challenging, especially using traditional representations such as graphs, maps or photos. Immersive visualizations and experiences offer an intuitive, visceral approach to otherwise rather abstract concepts, but creating them scientifically is challenging. In this paper, we linked ecological modeling, procedural modeling, and virtual reality to provide an immersive experience of a future forest. We mapped current tree species composition in northern Wisconsin using the Forest Inventory and Analysis (FIA) data and then forecast forest change 50 years into the future under two climate scenarios using LANDIS-II, a spatially-explicit, mechanistic simulation model. We converted the model output (e.g., tree biomass) into parameters required for 3D visualizations with analytical modeling. Procedural rules allowed us to efficiently and reproducibly translate the parameters into a simulated forest. Data visualization, environment exploration, and information retrieval were realized using the Unreal Engine. A system evaluation with experts in ecology provided positive feedback and future topics for a comprehensive ecosystem visualization and analysis approach. Our approach to create visceral experiences of forests under climate change can facilitate communication among experts, policy-makers, and the general public. Numéro de notice : A2021-384 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1830997 Date de publication en ligne : 10/11/2020 En ligne : https://doi.org/10.1080/13658816.2020.1830997 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97641
in International journal of geographical information science IJGIS > vol 35 n° 6 (June 2021) . - pp 1155 - 1178[article]Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May-2 2021)PermalinkA compilation of snow cover datasets for Svalbard: A multi-sensor, multi-model study / Hannah Vickers in Remote sensing, vol 13 n°10 (May-2 2021)PermalinkMixture effect on radial stem and shoot growth differs and varies with temperature / Maude Toïgo in Forest ecology and management, vol 488 (May-15 2021)PermalinkAn improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm / Jian Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)PermalinkAutomatic detection and classification of low-level orographic precipitation processes from space-borne radars using machine learning / Malarvizhi Arulraj in Remote sensing of environment, vol 257 (May 2021)PermalinkDetection of rainstorm pattern in arid regions using MODIS NDVI time series analysis / Mohamed E. Hereher in Geocarto international, vol 36 n° 8 ([01/05/2021])PermalinkElectrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])PermalinkIntegrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC4A / Olivier Bock in Earth System Science Data, vol 13 n° 5 (May 2021)PermalinkLearning from multimodal and multitemporal earth observation data for building damage mapping / Bruno Adriano in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkMulticriterial method of AHP analysis for the identification of coastal vulnerability regarding the rise of sea level: case study in Ilha Grande Bay, Rio de Janeiro, Brazil / Julia Caon Araujo in Natural Hazards, vol 107 n° 1 (May 2021)Permalink