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scientifique

Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones / Lonesome Malambo in Remote sensing of environment, vol 266 (December 2021)  

Public [article]  inRemote sensing of environment > vol 266 (December 2021) . - n° 112711 Titre : Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones Type de document : Article/Communication Auteurs : Lonesome Malambo, Auteur ; Sorin C. Popescu, Auteur Année de publication : 2021 Article en page(s) : n° 112711 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] biome [Termes IGN] canopée [Termes IGN] données altimétriques [Termes IGN] données ICEsat [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écorégion [Termes IGN] Etats-Unis [Termes IGN] hauteur des arbres [Termes IGN] photon [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (auteur) Despite its critical importance to carbon storage modeling, forest vertical structure remains poorly characterized over large areas. Canopy height estimates from current satellite missions such as ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) offer promise to close this knowledge gap, but their validation is critically important to inform their measurement uncertainties and scientific utility. Using existing airborne laser scanning (ALS) data, the agreement of a variety of terrain and aboveground canopy height metrics including summary height statistics and percentiles, from ICESat-2’ Land, Water and Vegetation Elevation product (ATL08) product was assessed in 12 sites across six major biomes in the United States. The agreement between ATL08 and ALS heights was assessed using the mean bias (Bias, ATL08 – ALS), the mean absolute error (MAE) and their percent equivalents, percent bias (pBias) and percent MAE (pMAE), respectively. In general, the agreement between ATL08 and ALS terrain heights was high (Bias 0.18 m, pBias 0.1%) while canopy heights showed lower agreement (Bias −1.71 m, pBias −15.9%). Analyses by biome, time of acquisition and beam strength of the ICESat-2 photon data also showed generally higher agreement for ATL08 terrain than canopy heights. Analyses also showed the performance of ATL08 heights varied with canopy cover with ATL08 terrain heights showing the best agreement when canopy cover was between 40 and 70% while the best performance for ATL08 canopy heights was observed when canopy cover was greater than 80%. This observation, coupled with analyses by biome, indicate that ATL08 canopy heights are more suitable in relatively dense canopy environments such as conifer and broadleaf forests than relatively sparse environments such a temperate grassland and Savannas. Higher level canopy height percentiles (95th and 98th) showed higher agreement (mean Bias −12.5%) with ALS heights than lower percentiles (minimum, 25th, mean pBias ~39.2%). These findings indicate that ATL08 canopy heights show more promise for routine canopy height characterization using the 95th and 98% percentiles but is limited in characterizing intermediate vertical structure. The observed performance differences between ATL08 terrain and canopy heights are attributed to differences in photon sampling rates over terrain and canopy surfaces which, compounded with background noise in ICESat-2 photon data, led to different effectiveness for ATL08 processing routines in filtering terrain and off-terrain points. This assessment of the impact of a variety of factors provides the vegetation community with an understanding of the capabilities and limitations of height estimates from the ICESat-2 ATL08 product. Numéro de notice : A2021-922 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112711 Date de publication en ligne : 24/09/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112711 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99277 [article]

A quantitative comparison of regionalization methods / Orhun Aydun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2287 - 2315 Titre : A quantitative comparison of regionalization methods Type de document : Article/Communication Auteurs : Orhun Aydun, Auteur ; Mark V. Janikas, Auteur ; Renato Martins Assuncao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2287 - 2315 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] données localisées [Termes IGN] écorégion [Termes IGN] exploration de données [Termes IGN] partition d'image [Termes IGN] partitionnement [Termes IGN] segmentation en régions Résumé : (auteur) Regionalization is the task of partitioning a set of contiguous areas into spatial clusters or regions. The theoretical and empirical literature focusing on regionalization is extensive, yet few quantitative comparisons have been conducted. We present a simulation study and explore the quality of frequently used and state-of-the-art regionalization algorithms, namely AZP, AZP-SA, AZPTabu, ARISEL, REDCAP, and SKATER, where the number of regions is an exogenous variable. The simulated benchmark data set consists of model realizations that represent various complexities in spatial data. Model families are defined with respect to regions’ shapes, value-mixing between regions, and the number of underlying spatial clusters. We evaluate the performance of different regionalization methods for realizations families using internal and external measures of regionalization quality. A large number of regionalization quality metrics expose a detailed profile of the analyzed methods’ strengths and weaknesses. We investigate the computational efficiency of every method as a function of the number of spatial units studied. We summarize results for different region families and discuss circumstances that make a certain method more desirable. We illustrate different regionalization algorithms’ implications on defining ecological regions for the conterminous US and compare them against expert-defined ecoregions. Numéro de notice : A2021-760 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1905819 Date de publication en ligne : 05/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1905819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98789 [article]

Exemplaires(1)

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079-2021111	SL	Revue	Centre de documentation	Revues en salle	Disponible

Extracting knowledge from legacy maps to delineate eco-geographical regions / Lin Yang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 250 - 272 Titre : Extracting knowledge from legacy maps to delineate eco-geographical regions Type de document : Article/Communication Auteurs : Lin Yang, Auteur ; Xinming Li, Auteur ; Qinye Yang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 250 - 272 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte ancienne [Termes IGN] carte climatique [Termes IGN] cartographie écologique [Termes IGN] Chine [Termes IGN] délimitation [Termes IGN] données cartographiques [Termes IGN] écorégion [Termes IGN] extraction de données [Termes IGN] logique floue [Termes IGN] sous ensemble flou [Termes IGN] zone tampon Résumé : (auteur) Legacy ecoregion maps contain knowledge on relationships between eco-region units and their environmental factors. This study proposes a method to extract knowledge from legacy area-class maps to formulate a set of fuzzy membership functions useful for regionalization. We develop a buffer zone approach to reduce the uncertainty of boundaries between eco-region units on area-class maps. We generate buffer zones with a Euclidean distance perpendicular to the boundaries, then the original eco-region units without buffer zones serve as the basic units to generate the probability density functions (PDF) of environmental variables. Then, we transform the PDFs to fuzzy membership functions for class-zones on the map. We demonstrate the proposed method with a climatic zone map of China. The results showed that the buffer zone approach effectively reduced the uncertainties of boundaries. A buffer distance of 10–15 km was recommended in this study. The climatic zone map generated based on the extracted fuzzy membership functions showed a higher spatial stratification heterogeneity (compared to the original map). Based on the fuzzy membership functions with climate data of 1961–2015, we also prepared an updated climatic zone map. This study demonstrates the prospects of using fuzzy membership functions to delineate area classes for regionalization purpose. Numéro de notice : A2021-025 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1806284 Date de publication en ligne : 17/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1806284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96692 [article]

A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions / Syed Adnan in Forest ecology and management, vol 433 (15 February 2019)  

Public [article]  inForest ecology and management > vol 433 (15 February 2019) . - pp 111 - 121 Titre : A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions Type de document : Article/Communication Auteurs : Syed Adnan, Auteur ; Matti Maltamo, Auteur ; David A. Coomes, Auteur ; Antonio Garcia-Abril, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 111 - 121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] classification ascendante hiérarchique [Termes IGN] classification barycentrique [Termes IGN] classification et arbre de régression [Termes IGN] coefficient de Gini [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] dynamique de la végétation [Termes IGN] écorégion [Termes IGN] hétérogénéité environnementale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Pinophyta [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) Reliable assessment of forest structural types (FSTs) aids sustainable forest management. We developed a methodology for the identification of FSTs using airborne laser scanning (ALS), and demonstrate its generality by applying it to forests from Boreal, Mediterranean and Atlantic biogeographical regions. First, hierarchal clustering analysis (HCA) was applied and clusters (FSTs) were determined in coniferous and deciduous forests using four forest structural variables obtained from forest inventory data – quadratic mean diameter , Gini coefficient , basal area larger than mean and density of stems –. Then, classification and regression tree analysis (CART) were used to extract the empirical threshold values for discriminating those clusters. Based on the classification trees, and were the most important variables in the identification of FSTs. Lower, medium and high values of and characterize single storey FSTs, multi-layered FSTs and exponentially decreasing size distributions (reversed J), respectively. Within each of these main FST groups, we also identified young/mature and sparse/dense subtypes using and . Then we used similar structural predictors derived from ALS – maximum height (), L-coefficient of variation (), L-skewness (), and percentage of penetration (), – and a nearest neighbour method to predict the FSTs. We obtained a greater overall accuracy in deciduous forest (0.87) as compared to the coniferous forest (0.72). Our methodology proves the usefulness of ALS data for structural heterogeneity assessment of forests across biogeographical regions. Our simple two-tier approach to FST classification paves the way toward transnational assessments of forest structure across bioregions. Numéro de notice : A2019-007 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.10.057 Date de publication en ligne : 03/11/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.10.057 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91600 [article]