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Tree height growth modelling using LiDAR-derived topography information / Milan Kobal in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 419 Titre : Tree height growth modelling using LiDAR-derived topography information Type de document : Article/Communication Auteurs : Milan Kobal, Auteur ; David Hladnik, Auteur Année de publication : 2021 Article en page(s) : n° 419 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Abies alba [Termes IGN] croissance des arbres [Termes IGN] données lidar [Termes IGN] données topographiques [Termes IGN] gestion forestière durable [Termes IGN] hauteur des arbres [Termes IGN] hétérogénéité environnementale [Termes IGN] karst [Termes IGN] modèle numérique de surface [Termes IGN] modélisation de la forêt [Termes IGN] semis de points [Termes IGN] Slovénie Résumé : (auteur) The concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant sinkholes and outcrops, exhibit diverse microtopography. Understanding the variation in the growth of trees in a heterogeneous topography is important for sustainable forest management. An R script for detailed stem analysis was used to reconstruct the height growth histories of individual trees (steam analysis). The results of this study reveal that the topographic factors influencing the height growth of silver fir trees can be detected within forest stands. Using topography modelling, we classified silver fir trees into groups with significant differences in height growth. This study provides a sound basis for the comparison of forest site differences and may be useful in the calibration of models for various tree species. Numéro de notice : A2021-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060419 date de publication en ligne : 19/06/2021 En ligne : https://doi.org/10.3390/ijgi10060419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97935 [article]

Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery / Zifeng Wang in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112281 Titre : Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery Type de document : Article/Communication Auteurs : Zifeng Wang, Auteur ; Junguo Liu, Auteur ; Jinbao Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Asie du sud-est [Termes IGN] bassin hydrographique [Termes IGN] données hydrographiques [Termes IGN] données topographiques [Termes IGN] extraction de traits caractéristiques [Termes IGN] image Sentinel-MSI [Termes IGN] modèle numérique de surface [Termes IGN] réseau de drainage [Termes IGN] réseau fluvial Résumé : (auteur) Extraction of drainage networks is an important element of river flow routing in hydrology and large-scale estimates of river behaviors in Earth sciences. Emerging studies with a focus on greenhouse gases reveal that small rivers can contribute to more than half of the global carbon emissions from inland waters (including lakes and wetlands). However, large-scale extraction of drainage networks is constrained by the coarse resolution of observational data and models, which hinders assessments of terrestrial hydrological and biogeochemical cycles. Recognizing that Sentinel-2 satellite can detect surface water up to a 10-m resolution over large scales, we propose a new method named Remote Sensing Stream Burning (RSSB) to integrate high-resolution observational flow location with coarse topography to improve the extraction of drainage network. In RSSB, satellite-derived input is integrated in a spatially continuous manner, producing a quasi-bathymetry map where relative relief is enforced, enabling a fine-grained, accurate, and multitemporal extraction of drainage network. RSSB was applied to the Lancang-Mekong River basin to derive a 10-m resolution drainage network, with a significant reduction in location errors as validated by the river centerline measurements. The high-resolution extraction resulted in a realistic representation of meanders and detailed network connections. Further, RSSB enabled a multitemporal extraction of river networks during wet/dry seasons and before/after the formation of new channels. The proposed method is fully automated, meaning that the network extraction preserves basin-wide connectivity without requiring any postprocessing, hence facilitating the construction of drainage networks data with openly accessible imagery. The RSSB method provides a basis for the accurate representation of drainage networks that maintains channel connectivity, allows a more realistic inclusion of small rivers and streams, and enables a greater understanding of complex but active exchange between inland water and other related Earth system components. Numéro de notice : A2021-191 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112281 date de publication en ligne : 21/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112281 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97112 [article]

Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm / Mehrdad Bijandi in Transactions in GIS, Vol 25 n° 1 (February 2021)  

Public [article]  inTransactions in GIS > Vol 25 n° 1 (February 2021) . - pp 551 - 574 Titre : Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm Type de document : Article/Communication Auteurs : Mehrdad Bijandi, Auteur ; Mohammad Karimi, Auteur ; Bahman Farhadi Bansouleh, Auteur ; Wim van der Knaap, Auteur Année de publication : 2021 Article en page(s) : pp 551 - 574 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données topographiques [Termes IGN] irrigation [Termes IGN] optimisation par colonie de fourmis [Termes IGN] parcelle agricole [Termes IGN] planification [Termes IGN] remembrement agricole [Termes IGN] surface cultivée [Termes IGN] utilisation du sol Résumé : (Auteur) In the process of agricultural land consolidation, the land parcels are optimally redesigned and rearranged in such a way that the dimensions of the resulting parcels are proportional to agricultural criteria such as irrigation discharge, soil texture, and cropping pattern. Besides these criteria, spatial factors like slope, road accessibility, volume of earthwork, and geometrical factors such as size and shape of parcels are also included in the design process of agricultural land partitioning. In this study, a land partitioning model was proposed using a multi‐objective artificial bee colony algorithm (MOABC‐LP) taking into consideration the mentioned factors. Initially, a feasible dimension range of parcels in a block was calculated based on irrigation efficiency. Two partitioning layouts were defined according to the topography and geometry of blocks. The proposed method was applied to a real study area and the results suggest that the land partitioning plan obtained by the MOABC‐LP model, in comparison with a designer's plan, not only makes the shape and size of parcels more compatible with the topographical and agricultural conditions of each block, but also reduces their cut‐and‐fill ratio. Numéro de notice : A2021-210 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12702 date de publication en ligne : 27/10/2020 En ligne : https://doi.org/10.1111/tgis.12702 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97159 [article]

A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings / Erich Peitzsch in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > Vol 21 n° 2 (February 2021) . - pp 533 - 557 Titre : A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings Type de document : Article/Communication Auteurs : Erich Peitzsch, Auteur ; Jordi Hendrikx, Auteur ; Daniel Stahle, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 533 - 557 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] avalanche [Termes IGN] Canada [Termes IGN] cerne [Termes IGN] croissance végétale [Termes IGN] dendrochronologie [Termes IGN] données topographiques [Termes IGN] échantillonnage [Termes IGN] Etats-Unis [Termes IGN] géomorphologie locale [Termes IGN] magnitude [Termes IGN] montagne Résumé : (auteur) Snow avalanches affect transportation corridors and settlements worldwide. In many mountainous regions, robust records of avalanche frequency and magnitude are sparse or non-existent. However, dendrochronological methods can be used to fill this gap and infer historical avalanche patterns. In this study, we developed a tree-ring-based avalanche chronology for large magnitude avalanche events (size ≥∼D3) using dendrochronological techniques for a portion of the US northern Rocky Mountains. We used a strategic sampling design to examine avalanche activity through time and across nested spatial scales (i.e., from individual paths, four distinct subregions, and the region). We analyzed 673 samples in total from 647 suitable trees collected from 12 avalanche paths from which 2134 growth disturbances were identified over the years 1636 to 2017 CE. Using existing indexing approaches, we developed a regional avalanche activity index to discriminate avalanche events from noise in the tree-ring record. Large magnitude avalanches, common across the region, occurred in 30 individual years and exhibited a median return interval of approximately 3 years (mean = 5.21 years). The median large magnitude avalanche return interval (3–8 years) and the total number of avalanche years (12–18) varies throughout the four subregions, suggesting the important influence of local terrain and weather factors. We tested subsampling routines for regional representation, finding that sampling 8 random paths out of a total of 12 avalanche paths in the region captures up to 83 % of the regional chronology, whereas four paths capture only 43 % to 73 %. The greatest value probability of detection for any given path in our dataset is 40 %, suggesting that sampling a single path would capture no more than 40 % of the regional avalanche activity. Results emphasize the importance of sample size, scale, and spatial extent when attempting to derive a regional large magnitude avalanche event chronology from tree-ring records. Numéro de notice : A2021-169 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.5194/nhess-21-533-2021 date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.5194/nhess-21-533-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97108 [article]

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)  

Public [article]  inGIScience and remote sensing > vol 58 n° 1 (February 2021) . - pp 120 - 137 Titre : Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain Type de document : Article/Communication Auteurs : R. Niederheiser, Auteur ; M. Winkler, Auteur ; V. Di Cecco, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 120 - 137 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre [Termes IGN] Alpes [Termes IGN] carte de la végétation [Termes IGN] chambre de prise de vue numérique [Termes IGN] classification par forêts aléatoires [Termes IGN] classification semi-dirigée [Termes IGN] couvert végétal [Termes IGN] distribution de Poisson [Termes IGN] données topographiques [Termes IGN] indice de végétation [Termes IGN] module linéaire [Termes IGN] montagne [Termes IGN] occupation du sol [Termes IGN] photogrammétrie métrologique [Termes IGN] semis de points Résumé : (auteur) In this paper we present a low-cost approach to mapping vegetation cover by means of high-resolution close-range terrestrial photogrammetry. A total of 249 clusters of nine 1 m2 plots each, arranged in a 3 × 3 grid, were set up on 18 summits in Mediterranean mountain regions and in the Alps to capture images for photogrammetric processing and in-situ vegetation cover estimates. This was done with a hand-held pole-mounted digital single-lens reflex (DSLR) camera. Low-growing vegetation was automatically segmented using high-resolution point clouds. For classifying vegetation we used a two-step semi-supervised Random Forest approach. First, we applied an expert-based rule set using the Excess Green index (ExG) to predefine non-vegetation and vegetation points. Second, we applied a Random Forest classifier to further enhance the classification of vegetation points using selected topographic parameters (elevation, slope, aspect, roughness, potential solar irradiation) and additional vegetation indices (Excess Green Minus Excess Red (ExGR) and the vegetation index VEG). For ground cover estimation the photogrammetric point clouds were meshed using Screened Poisson Reconstruction. The relative influence of the topographic parameters on the vegetation cover was determined with linear mixed-effects models (LMMs). Analysis of the LMMs revealed a high impact of elevation, aspect, solar irradiation, and standard deviation of slope. The presented approach goes beyond vegetation cover values based on conventional orthoimages and in-situ vegetation cover estimates from field surveys in that it is able to differentiate complete 3D surface areas, including overhangs, and can distinguish between vegetation-covered and other surfaces in an automated manner. The results of the Random Forest classification confirmed it as suitable for vegetation classification, but the relative feature importance values indicate that the classifier did not leverage the potential of the included topographic parameters. In contrast, our application of LMMs utilized the topographic parameters and was able to reveal dependencies in the two biomes, such as elevation and aspect, which were able to explain between 87% and 92.5% of variance. Numéro de notice : A2021-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2020.1859264 date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1080/15481603.2020.1859264 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97295 [article]

Detecting classic Maya settlements with Lidar-derived relief visualizations / Amy E. Thompson in Remote sensing, vol 12 n° 17 (September 2020)  

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Recognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

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Methodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland / Izabela Karsznia in Geocarto international, vol 35 n° 7 ([15/05/2020])  

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Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation / Xianjin He in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

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Recent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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High‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)  

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Quantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) / William J. Schmelz in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 2 (February 2019)  

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Machine learning and geographic information systems for large-scale mapping of renewable energy potential / Dan Assouline (2019)  

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Geospatial data on the web / Linda Van Den Brink (2018)    

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L’utilisation des données écologiques de l’inventaire pour mieux appréhender les conditions locales de milieu (atelier de travail) [diaporama] / Philippe Dreyfus (2018)  

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