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An individual tree-based automated registration of aerial images to LiDAR Data in a forested area / Jun-Hak Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 9 (September 2016) . - pp 699 - 710 Titre : An individual tree-based automated registration of aerial images to LiDAR Data in a forested area Type de document : Article/Communication Auteurs : Jun-Hak Lee, Auteur ; Gregory S. Biging, Auteur Année de publication : 2016 Article en page(s) : pp 699 - 710 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] arbre (flore) [Termes IGN] Californie (Etats-Unis) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écosystème forestier [Termes IGN] forêt [Termes IGN] image aérienne [Termes IGN] point d'appui [Termes IGN] superposition d'images Résumé : (Auteur) In this paper, we demonstrate an approach to align aerial images to airborne lidar data by using common object features (tree tops) from both data sets under the condition that conventional correlation-based approaches are challenging due to the fact that the spatial pattern of pixel gray-scale values in aerial images hardly exist in lidar data. We extracted tree tops by using an image processing technique called extended-maxima transformation from both aerial images and lidar data. Our approach was tested at the Angelo Coast Range Reserve on the South Fork Eel River forests in Mendocino County, California. Although the aerial images were acquired simultaneously with the lidar data, the images had only approximate exposure point locations and average flight elevation information, which mimicked the condition of limited information availability about the aerial images. Our results showed that this approach enabled us to align aerial images to airborne lidar data at the single-tree level with reasonable accuracy. With a local transformation model (piecewise linear model), the RMSE and the median absolute deviation (MAD) of the registration were 9.2 pixels (2.3 meters) and 6.8 pixels (1.41 meters), respectively. We expect our approach to be applicable to fine scale change detection for forest ecosystems and may serve to extract detailed forest biophysical parameters. Numéro de notice : A2016-740 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.9.699 En ligne : https://doi.org/10.14358/PERS.82.9.699 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82275 [article]

Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley / L. Zhong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 799 - 813 Titre : Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley Type de document : Article/Communication Auteurs : L. Zhong, Auteur ; P. Gong, Auteur ; Gregory S. Biging, Auteur Année de publication : 2012 Article en page(s) : pp 799 - 813 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Californie (Etats-Unis) [Termes IGN] carte agricole [Termes IGN] classification par arbre de décision [Termes IGN] cultures [Termes IGN] Enhanced vegetation index [Termes IGN] évapotranspiration [Termes IGN] fusion d'images [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-TM [Termes IGN] image Terra-MODIS [Termes IGN] phénologie [Termes IGN] segmentation d'image Résumé : (Auteur) The overarching goal of this study was to map specific crop types in the Central Valley, California and estimate the effect of classification uncertainty on the calculation of crop evapotranspiration (ETc). A phenology-based classification (PBC) approach was developed to identify crop types based on phenological and spectral metrics derived from the time series of Landsat TM/ETM_ imagery. Phenological metrics, calculated by fitting asymmetric double sigmoid functions to temporal profiles of enhanced vegetation index (EVI), were capable of separating crop types with distinct crop calendars. An innovative method was used to compute spectral metrics to represent crops' spectral characteristics at certain phenological stages instead of any specific imaging date. Crop mapping using these metrics showed a stable performance without influences of low-quality data and inter-annual differences in imaging dates. The requirement for ground reference data by the PBC approach was low because classification algorithms were mostly built according to the knowledge on crop calendars and agricultural practices. Techniques including image segmentation, data fusion with MODIS imagery, and decision tree were incorporated to make the approach effective and efficient. Though moderate accuracy (~65.0 percent) was achieved, ETc calculated by the Food and Agriculture Organization (FAO) 56 method showed that the estimate of water use was not likely to be significantly affected by the classification error in PBC. All these advantages imply the strength of the PBC approach in the regular crop mapping of the Central Valley. Numéro de notice : A2012-428 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.799 En ligne : https://doi.org/10.14358/PERS.78.8.799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31874 [article]

True ortho-image production for forested areas from large-scale aerial photographs / Y. Sheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 3 (March 2003)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 3 (March 2003) . - pp 259 - 266 Titre : True ortho-image production for forested areas from large-scale aerial photographs Type de document : Article/Communication Auteurs : Y. Sheng, Auteur ; P. Gong, Auteur ; Gregory S. Biging, Auteur Année de publication : 2003 Article en page(s) : pp 259 - 266 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage [Termes IGN] correction des ombres [Termes IGN] couvert forestier [Termes IGN] déformation d'image [Termes IGN] dévers [Termes IGN] forêt [Termes IGN] modèle numérique de surface [Termes IGN] objet géographique 3D [Termes IGN] orthoimage [Termes IGN] orthoimage intégrale [Termes IGN] photographie à grande échelle [Termes IGN] photographie aérienne Résumé : (Auteur) An orthophoto is a fundamental information source in forestry. Orthophoto production is usally based on digital elevation models (DEM) ; however, the elevations of 3D objects suchs as buildings and trees, which are visible in large-scale photos, are not included in DEMs. Recently initiated "true orthophoto" generation has been dedicated to urban scenes, removing the displacement caused by both the terrain and buildings. This paper reports an effort on reducing occlusion and distortion caused by trees in true orthoimage generation for forested areas. Canopy surface models (CMS) depicting both the terrain and tree surfaces were used in forest orthoimage production. Z-buffer techniques were incorporated into indirect orthoimage production to remove occlusion. An angle-based strategy was applied to composite multi-occular images. The proposed techniques were applied in the generation of high-resolution orthoimages of redwood stand with 1:2 400-scale aerial photos. Numéro de notice : A2003-029 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.69.3.259 En ligne : https://doi.org/10.14358/PERS.69.3.259 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22326 [article]