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Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 493 - 508 Titre : Occlusion probability in operational forest inventory field sampling with ForeStereo Type de document : Article/Communication Auteurs : Fernando Montes, Auteur ; Mariola Sánchez-González, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 493 - 508 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] biomasse forestière [Termes IGN] capteur optique [Termes IGN] couvert forestier [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] erreur systématique [Termes IGN] Espagne [Termes IGN] Fagus sylvatica [Termes IGN] gestion forestière [Termes IGN] image hémisphérique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle stéréoscopique [Termes IGN] Pinus sylvestris [Termes IGN] placette d'échantillonnage [Termes IGN] Pyrénées (montagne) [Termes IGN] volume en bois Résumé : (auteur) Field data in forest inventories are increasingly obtained using proximal sensing technologies, often under fixed-point sampling. Under fixed-point sampling some trees are not detected due to instrument bias and occlusions, hence involving an underestimation of the number of trees per hectare (N). The aim here is to evaluate various approaches to correct tree occlusions and instrument bias estimates calculated with data from ForeStereo (proximal sensor based on stereoscopic hemispherical images) under a fixed-point sampling strategy. Distance-sampling and the new hemispherical photogrammetric correction (HPC), which combines image segmentation-based correction for instrument bias with a novel approach for estimating the proportion of shadowed sampling area in stereoscopic hemispherical images, best estimated N and basal area (BA). Distance-sampling slightly overestimated N (11% bias, 0.60 Pearson coefficient with the reference measures) and BA (4%, 0.82). HPC provided less biased N estimates (-6%, 0.61) but underestimated BA (-8%, 0.83). HPC most accurately retrieved the diameter distribution. Numéro de notice : A2019-258 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.493 Date de publication en ligne : 07/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.493 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93060 [article]

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Towards assessment of cork production through National Forest Inventories / Maria Pasalodos-Tato in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 110 - 120 Titre : Towards assessment of cork production through National Forest Inventories Type de document : Article/Communication Auteurs : Maria Pasalodos-Tato, Auteur ; Iciar A. Alberdi, Auteur ; Isabel Canellas, Auteur ; Mariola Sánchez-González, Auteur Année de publication : 2018 Article en page(s) : pp 110 - 120 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Espagne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] production agricole végétale [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) The economic importance of cork in the Mediterranean region demands an accurate assessment of its production. Cork production is currently estimated by aggregating information provided by Regional Forest Services, but this approach results in a lack of robustness at the national level. The objective of the present study is to analyse the role of the Spanish National Forest Inventory (SNFI) as a potential source of data for quantifying cork weight at national level and the scope of National Forest Inventory data to define national trends in cork yield as well as to characterize the main types of cork producing forest stands in Spain. Data from the Second and Third SNFI are used together with the Spanish Forest Map. The results point to the suitability of SNFI to quantify cork production as long as the two main variables defining cork weight, namely cork thickness and debarking height, were correctly recorded in inventories. Although the Second SNFI complied with these requirements, from the Third SNFI the methodology changed, preventing the accurate estimation of cork weight. Based on this study recommendations are made to improve the estimation of cork weight at national level, e.g. to measure cork thickness in all the cork oaks in the plot and to take a sample of cork from the inventoried trees. This information would also make it possible to assess the cork quality in terms of cork thickness growth and to classify cork production in terms of suitability for producing high quality cork products. Numéro de notice : A2018-632 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx036 Date de publication en ligne : 03/10/2017 En ligne : https://doi.org/10.1093/forestry/cpx036 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93232 [article]

Basal area and diameter distribution estimation using stereoscopic hemispherical images / Mariola Sánchez-González in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 8 (August 2016) . - pp 605 - 616 Titre : Basal area and diameter distribution estimation using stereoscopic hemispherical images Type de document : Article/Communication Auteurs : Mariola Sánchez-González, Auteur ; Miguel Cabrera, Auteur ; Pedro Javier Herrera, Auteur Année de publication : 2016 Article en page(s) : pp 605 - 616 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'images [Termes IGN] courbe de Pearson [Termes IGN] diamètre des arbres [Termes IGN] image hémisphérique [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle stéréoscopique [Termes IGN] placette d'échantillonnage [Termes IGN] surface terrière [Termes IGN] tronc [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) In recent years, proximal sensing data has increasingly been used to optimize forest inventories. In this paper, we present a forest inventory methodology based on stereoscopic hemispherical images. An automated pixel-based approach and a user-guided “region growing” approach have been developed for image matching. To estimate the basal area, number of trees and mean diameter, the sampling probability is determined for each tree. The accuracy and precision of the estimates derived from stereoscopic hemispherical images was analyzed for a set of National Forest Inventory plots. The results revealed that tree matching depends on the species, the distance to the target tree and the diameter. The Pearson correlation coefficient was 0.86 for the mean diameter and 0.89 for the basal area, whereas for the number of trees per hectare it was 0.59. The proposed methods may be used in large scale forest inventories as a cost-efficient way of obtaining data on diameter distribution and basal area from field surveys following a two-stage scheme combined with remote sensing techniques. Numéro de notice : A2016-607 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.8.605 En ligne : http://dx.doi.org/10.14358/PERS.82.8.605 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81805 [article]