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Automated annual cropland mapping using knowledge-based temporal features / François Waldner in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 1 – 13 Titre : Automated annual cropland mapping using knowledge-based temporal features Type de document : Article/Communication Auteurs : François Waldner, Auteur ; Guadalupe Sepulcre Canto, Auteur ; Pierre Defourny, Auteur Année de publication : 2015 Article en page(s) : pp 1 – 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Argentine [Termes IGN] Belgique [Termes IGN] carte agricole [Termes IGN] carte d'occupation du sol [Termes IGN] Chine [Termes IGN] classification dirigée [Termes IGN] cultures [Termes IGN] série temporelle [Termes IGN] surveillance agricole [Termes IGN] Ukraine Résumé : (auteur) Global, timely, accurate and cost-effective cropland mapping is a prerequisite for reliable crop condition monitoring. This article presented a simple and comprehensive methodology capable to meet the requirements of operational cropland mapping by proposing (1) five knowledge-based temporal features that remain stable over time, (2) a cleaning method that discards misleading pixels from a baseline land cover map and (3) a classifier that delivers high accuracy cropland maps (>>80%). This was demonstrated over four contrasted agrosystems in Argentina, Belgium, China and Ukraine. It was found that the quality and accuracy of the baseline impact more the certainty of the classification rather than the classification output itself. In addition, it was shown that interpolation of the knowledge-based features increases the stability of the classifier allowing for its re-use from year to year without recalibration. Hence, the method shows potential for application at larger scale as well as for delivering cropland map in near real time. Numéro de notice : A2015-889 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.013 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79438 [article]

3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction / Xi Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 14 – 23 Titre : 3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction Type de document : Article/Communication Auteurs : Xi Zhu, Auteur ; Tiejun Wang, Auteur ; Roshanak Darvishzadeh, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 14 – 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] correction radiométrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] intensité lumineuse [Termes IGN] réflecteur [Termes IGN] télémétrie laser terrestre [Termes IGN] teneur en eau de la végétation Résumé : (auteur) Leaf water content (LWC) plays an important role in agriculture and forestry management. It can be used to assess drought conditions and wildfire susceptibility. Terrestrial laser scanner (TLS) data have been widely used in forested environments for retrieving geometrically-based biophysical parameters. Recent studies have also shown the potential of using radiometric information (backscatter intensity) for estimating LWC. However, the usefulness of backscatter intensity data has been limited by leaf surface characteristics, and incidence angle effects. To explore the idea of using LiDAR intensity data to assess LWC we normalized (for both angular effects and leaf surface properties) shortwave infrared TLS data (1550 nm). A reflectance model describing both diffuse and specular reflectance was applied to remove strong specular backscatter intensity at a perpendicular angle. Leaves with different surface properties were collected from eight broadleaf plant species for modeling the relationship between LWC and backscatter intensity. Reference reflectors (Spectralon from Labsphere, Inc.) were used to build a look-up table to compensate for incidence angle effects. Results showed that before removing the specular influences, there was no significant correlation (R2 = 0.01, P > 0.05) between the backscatter intensity at a perpendicular angle and LWC. After the removal of the specular influences, a significant correlation emerged (R2 = 0.74, P Numéro de notice : A2015-890 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.001 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79440 [article]

A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification / Tao Liu in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 34 – 47 Titre : A novel transferable individual tree crown delineation model based on Fishing Net Dragging and boundary classification Type de document : Article/Communication Auteurs : Tao Liu, Auteur ; Jungho Im, Auteur ; Lindi J. Quackenbush, Auteur Année de publication : 2015 Article en page(s) : pp 34 – 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] croissance des arbres [Termes IGN] données lidar [Termes IGN] estimation de précision [Termes IGN] forêt Résumé : (auteur) This study provides a novel approach to individual tree crown delineation (ITCD) using airborne Light Detection and Ranging (LiDAR) data in dense natural forests using two main steps: crown boundary refinement based on a proposed Fishing Net Dragging (FiND) method, and segment merging based on boundary classification. FiND starts with approximate tree crown boundaries derived using a traditional watershed method with Gaussian filtering and refines these boundaries using an algorithm that mimics how a fisherman drags a fishing net. Random forest machine learning is then used to classify boundary segments into two classes: boundaries between trees and boundaries between branches that belong to a single tree. Three groups of LiDAR-derived features—two from the pseudo waveform generated along with crown boundaries and one from a canopy height model (CHM)—were used in the classification. The proposed ITCD approach was tested using LiDAR data collected over a mountainous region in the Adirondack Park, NY, USA. Overall accuracy of boundary classification was 82.4%. Features derived from the CHM were generally more important in the classification than the features extracted from the pseudo waveform. A comprehensive accuracy assessment scheme for ITCD was also introduced by considering both area of crown overlap and crown centroids. Accuracy assessment using this new scheme shows the proposed ITCD achieved 74% and 78% as overall accuracy, respectively, for deciduous and mixed forest. Numéro de notice : A2015-891 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.002 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79441 [article]

Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments / Mbulisi Sibanda in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 55 – 65 Titre : Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments Type de document : Article/Communication Auteurs : Mbulisi Sibanda, Auteur ; Onisimo Mutanga, Auteur ; Mathieu Rouget, Auteur Année de publication : 2015 Article en page(s) : pp 55 – 65 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] biomasse forestière [Termes IGN] capteur multibande [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] image Sentinel-MSI [Termes IGN] Sentinel-2 [Termes IGN] télédétection aérospatiale Résumé : (auteur)The major constraint in understanding grass above ground biomass variations using remotely sensed data are the expenses associated with the data, as well as the limited number of techniques that can be applied to different management practices with minimal errors. New generation multispectral sensors such as Sentinel 2 Multispectral Imager (MSI) are promising for effective rangeland management due to their unique spectral bands and higher signal to noise ratio. This study resampled hyperspectral data to spectral resolutions of the newly launched Sentinel 2 MSI and the recently launched Landsat 8 OLI for comparison purposes. Using Sparse partial least squares regression, the resampled data was applied in estimating above ground biomass of grasses treated with different fertilizer combinations of ammonium sulfate, ammonium nitrate, phosphorus and lime as well as unfertilized experimental plots. Sentinel 2 MSI derived models satisfactorily performed (R2 = 0.81, RMSEP = 1.07 kg/m2, RMSEP_rel = 14.97) in estimating grass above ground biomass across different fertilizer treatments relative to Landsat 8 OLI (Landsat 8 OLI: R2 = 0.76, RMSEP = 1.15 kg/m2, RMSEP_rel = 16.04). In comparison, hyperspectral data derived models exhibited better grass above ground biomass estimation across complex fertilizer combinations (R2 = 0.92, RMSEP = 0.69 kg/m2, RMSEP_rel = 9.61). Although Sentinel 2 MSI bands and indices better predicted above ground biomass compared with Landsat 8 OLI bands and indices, there were no significant differences (α = 0.05) in the errors of prediction between the two new generational sensors across all fertilizer treatments. The findings of this study portrays Sentinel 2 MSI and Landsat 8 OLI as promising remotely sensed datasets for regional scale biomass estimation, particularly in resource scarce areas. Numéro de notice : A2015-892 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.005 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79442 [article]

Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories / Shengli Tao in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 66 – 76 Titre : Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Fangfang Wu, Auteur ; Qinghua Guo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 66 – 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] croissance des arbres [Termes IGN] données lidar [Termes IGN] écologie forestière [Termes IGN] segmentation d'image [Termes IGN] télémétrie laser terrestre Résumé : (auteur) The rapid development of light detection and ranging (LiDAR) techniques is advancing ecological and forest research. During the last decade, numerous single tree segmentation techniques have been developed using airborne LiDAR data. However, accurate crown segmentation using terrestrial or mobile LiDAR data, which is an essential prerequisite for extracting branch level forest characteristics, is still challenging mainly because of the difficulties posed by tree crown intersection and irregular crown shape. In the current work, we developed a comparative shortest-path algorithm (CSP) for segmenting tree crowns scanned using terrestrial (T)-LiDAR and mobile LiDAR. The algorithm consists of two steps, namely trunk detection and subsequent crown segmentation, with the latter inspired by the well-proved metabolic ecology theory and the ecological fact that vascular plants tend to minimize the transferring distance to the root. We tested the algorithm on mobile-LiDAR-scanned roadside trees and T-LiDAR-scanned broadleaved and coniferous forests in China. Point-level quantitative assessments of the segmentation results showed that for mobile-LiDAR-scanned roadside trees, all the points were classified to their corresponding trees correctly, and for T-LiDAR-scanned broadleaved and coniferous forests, kappa coefficients ranging from 0.83 to 0.93 were obtained. We believe that our algorithm will make a contribution to solving the problem of crown segmentation in T-LiDAR scanned-forests, and might be of interest to researchers in LiDAR data processing and to forest ecologists. In addition, our research highlights the advantages of using ecological theories as guidelines for processing LiDAR data. Numéro de notice : A2015-893 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79444 [article]

Semi-supervised SVM for individual tree crown species classification / Michele Dalponte in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 77 – 87 Titre : Semi-supervised SVM for individual tree crown species classification Type de document : Article/Communication Auteurs : Michele Dalponte, Auteur ; Levi Theodor Ene, Auteur ; Mattia Marconcini, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 77 – 87 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification dirigée [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données laser [Termes IGN] forêt boréale [Termes IGN] image hyperspectrale [Termes IGN] inventaire forestier local Résumé : (auteur) In this paper a novel semi-supervised SVM classifier is presented, specifically developed for tree species classification at individual tree crown (ITC) level. In ITC tree species classification, all the pixels belonging to an ITC should have the same label. This assumption is used in the learning of the proposed semi-supervised SVM classifier (ITC-S3VM). This method exploits the information contained in the unlabeled ITC samples in order to improve the classification accuracy of a standard SVM. The ITC-S3VM method can be easily implemented using freely available software libraries. The datasets used in this study include hyperspectral imagery and laser scanning data acquired over two boreal forest areas characterized by the presence of three information classes (Pine, Spruce, and Broadleaves). The experimental results quantify the effectiveness of the proposed approach, which provides classification accuracies significantly higher (from 2% to above 27%) than those obtained by the standard supervised SVM and by a state-of-the-art semi-supervised SVM (S3VM). Particularly, by reducing the number of training samples (i.e. from 100% to 25%, and from 100% to 5% for the two datasets, respectively) the proposed method still exhibits results comparable to the ones of a supervised SVM trained with the full available training set. This property of the method makes it particularly suitable for practical forest inventory applications in which collection of in situ information can be very expensive both in terms of cost and time. Numéro de notice : A2015-894 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.010 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79445 [article]