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Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing / Shangharsha Thapa in Remote sensing, vol 13 n° 8 (April-2 2021)
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Titre : Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing Type de document : Article/Communication Auteurs : Shangharsha Thapa, Auteur ; Virginia Garcia Millan, Auteur ; Lars Eklundh, Auteur Année de publication : 2021 Article en page(s) : n° 1597 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multiéchelle
[Termes IGN] capteur multibande
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] phénologie
[Termes IGN] réflectance spectrale
[Termes IGN] série temporelle
[Termes IGN] Suède
[Termes IGN] surveillance forestière
[Termes IGN] variation saisonnièreRésumé : (auteur) The monitoring of forest phenology based on observations from near-surface sensors such as Unmanned Aerial Vehicles (UAVs), PhenoCams, and Spectral Reflectance Sensors (SRS) over satellite sensors has recently gained significant attention in the field of remote sensing and vegetation phenology. However, exploring different aspects of forest phenology based on observations from these sensors and drawing comparatives from the time series of vegetation indices (VIs) still remains a challenge. Accordingly, this research explores the potential of near-surface sensors to track the temporal dynamics of phenology, cross-compare their results against satellite observations (MODIS, Sentinel-2), and validate satellite-derived phenology. A time series of Normalized Difference Vegetation Index (NDVI), Green Chromatic Coordinate (GCC), and Normalized Difference of Green & Red (VIgreen) indices were extracted from both near-surface and satellite sensor platforms. The regression analysis between time series of NDVI data from different sensors shows the high Pearson’s correlation coefficients (r > 0.75). Despite the good correlations, there was a remarkable offset and significant differences in slope during green-up and senescence periods. SRS showed the most distinctive NDVI profile and was different to other sensors. PhenoCamGCC tracked green-up of the canopy better than the other indices, with a well-defined start, end, and peak of the season, and was most closely correlated (r > 0.93) with the satellites, while SRS-based VIgreen accounted for the least correlation (r = 0.58) against Sentinel-2. Phenophase transition dates were estimated and validated against visual inspection of the PhenoCam data. The Start of Spring (SOS) and End of Spring (EOS) could be predicted with an accuracy of Numéro de notice : A2021-382 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13081597 Date de publication en ligne : 20/04/2021 En ligne : https://doi.org/10.3390/rs13081597 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97633
in Remote sensing > vol 13 n° 8 (April-2 2021) . - n° 1597[article]The delineation of tea gardens from high resolution digital orthoimages using mean-shift and supervised machine learning methods / Akhtar Jamil in Geocarto international, vol 36 n° 7 ([15/04/2021])
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Titre : The delineation of tea gardens from high resolution digital orthoimages using mean-shift and supervised machine learning methods Type de document : Article/Communication Auteurs : Akhtar Jamil, Auteur ; Bulent Bayram, Auteur Année de publication : 2021 Article en page(s) : pp 758 - 772 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de décalage moyen
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage automatique
[Termes IGN] arbre de décision
[Termes IGN] Camellia sinensis
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] exploitation agricole
[Termes IGN] extraction de la végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] orthoimage
[Termes IGN] segmentation hiérarchique
[Termes IGN] TurquieRésumé : (Auteur) Rize district is an important tea production site in Turkey, which is known for high quality tea. Determining the temporal changes is very crucial from the viewpoint of agricultural management and protection of tea areas. In addition, delineation of tea gardens using photogrammetric evaluation techniques for a single orthoimage takes approximately 8 h of labour work, which is both costly and time-consuming process. To overcome these issues, a method is proposed for demarcation of tea gardens from high-resolution orthoimages. In this article, a hierarchical object-based segmentation using mean-shift (MS) and supervised machine learning (ML) methods are investigated for delineation of tea gardens. First, the MS algorithm was applied to partition the images into homogeneous segments (objects) and then from each segment, various spectral, spatial and textural features were extracted. Finally, four most widely used supervised ML classifiers, support vector machine (SVM), artificial neural network (ANN), random forest (RF), and decision trees (DTs), were selected for classification of objects into tea gardens and other types of trees. Photogrammetrically evaluated tea garden borders were taken as reference data to evaluate the performance of the proposed methods. The experiments showed that all selected supervised classifiers were effective for delineation of the tea gardens from high-resolution images. Numéro de notice : A2021-293 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1622597 Date de publication en ligne : 19/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1622597 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97349
in Geocarto international > vol 36 n° 7 [15/04/2021] . - pp 758 - 772[article]An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)
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Titre : An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects Type de document : Article/Communication Auteurs : Linyuan Li, Auteur ; Xihan Mu, Auteur ; Maxime Soma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3547 - 3566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de partie cachée
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] itération
[Termes IGN] semis de pointsRésumé : (auteur) Occlusion effect, an inherent problem of terrestrial laser scanning (TLS) measurements, limits the potential of TLS data in tree attribute estimation. Multiple scans seek to mitigate this effect to provide enhanced scan completeness. However, the numbers and locations of the scans (i.e., the scan design) are usually determined via a subjective assessment of the tree density, spatial patterns of trees, and attributes to be derived. These could cause suboptimal scan completeness and limit tree attribute estimation. This study proposed an iterative-mode scan design to minimize the occlusion effect. First, we introduced a PoTo index based on visibility analysis to evaluate how many trees can be scanned from a location and to select effective candidates for the optimal TLS location. Second, we introduced a cumulative degree of ring closure (CDRC) to quantify the scan completeness for each candidate and determine the optimal TLS location. The TLS data sets of virtual forests with field-measured and synthetic plot parameter settings were simulated according to iterative- and regular-mode designs by using a Heidelberg light detection and ranging (LiDAR) Operations Simulator (HELIOS). The results demonstrated that an iterative-mode design can improve the scan completeness of trees compared to the regular-mode design. The tree attribute (diameter at breast height (DBH), tree height, stem curve, and crown volume) estimates of the iterative-mode design were less erroneous than those of the regular-mode design (e.g., the root-mean-square error (RMSE) could decrease the stem curve estimation by 38% and the crown volume estimation by 15%). This study suggests that the iterative-mode design can obtain an improved quality of the TLS data, especially for dense stands. Numéro de notice : A2021-288 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3018643 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018643 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97397
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 3547 - 3566[article]Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters / Quinten Vanhellemont in Remote sensing of environment, Vol 256 (April 2020)
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Titre : Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters Type de document : Article/Communication Auteurs : Quinten Vanhellemont, Auteur ; Kevin Ruddick, Auteur Année de publication : 2021 Article en page(s) : n° 112284 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Belgique
[Termes IGN] chlorophylle
[Termes IGN] correction atmosphérique
[Termes IGN] eaux côtières
[Termes IGN] image Sentinel-OLCI
[Termes IGN] particule
[Termes IGN] rayonnement infrarouge
[Termes IGN] réflectance
[Termes IGN] turbidité des eauxRésumé : (auteur) The performance of different atmospheric correction algorithms for the Ocean and Land Colour Instrument (OLCI) on board of Sentinel-3 (S3) is evaluated for retrieval of water-leaving radiance reflectance, and derived parameters chlorophyll-a concentration and turbidity in turbid coastal waters in the Belgian Coastal Zone (BCZ). This is performed using in situ measurements from an autonomous pan-and-tilt hyperspectral radiometer system (PANTHYR). The PANTHYR provides validation data for any satellite band between 400 and 900 nm, with the deployment in the BCZ of particular interest due to the wide range of observed Near-InfraRed (NIR) reflectance. The Dark Spectrum Fitting (DSF) atmospheric correction algorithm is adapted for S3/OLCI processing in ACOLITE, and its performance and that of 5 other processing algorithms (L2-WFR, POLYMER, C2RCC, SeaDAS, and SeaDAS-ALT) is compared to the in situ measured reflectances. Water turbidities across the matchups in the Belgian Coastal Zone are about 20–100 FNU, and the overall performance is best for ACOLITE and L2-WFR, with the former providing lowest relative (Mean Absolute Relative Difference, MARD 7–27%) and absolute errors (Mean Average Difference, MAD -0.002, Root Mean Squared Difference, RMSD 0.01–0.016) in the bands between 442 and 681 nm. L2-WFR provides the lowest errors at longer NIR wavelengths (754–885 nm). The algorithms that assume a water reflectance model, i.e. POLYMER and C2RCC, are at present not very suitable for processing imagery over the turbid Belgian coastal waters, with especially the latter introducing problems in the 665 and 709 nm bands, and hence the chlorophyll-a and turbidity retrievals. This may be caused by their internal model and/or training dataset not being well adapted to the waters encountered in the BCZ. The 1020 nm band is used most frequently by ACOLITE/DSF for the estimation of the atmospheric path reflectance (67% of matchups), indicating its usefulness for turbid water atmospheric correction. Turbidity retrieval using a single band algorithm showed good performance for L2-WFR and ACOLITE compared to PANTHYR for e.g. the 709 nm band (MARD 15 and 17%), where their reflectances were also very close to the in situ observations (MARD 11%). For the retrieval of chlorophyll-a, all methods except C2RCC gave similar performance, due to the RedEdge band-ratio algorithm being robust to typical spectrally flat atmospheric correction errors. C2RCC does not retain the spectral relationship in the Red and RedEdge bands, and hence its chlorophyll-a concentration retrieval is not at all reliable in Belgian coastal waters. L2-WFR and ACOLITE show similar performance compared to in situ radiometry, but due to the assumption of spatially consistent aerosols, ACOLITE provides less noisy products. With the superior performance of ACOLITE in the 490–681 nm wavelength range, and smoother output products, it can be recommended for processing of S3/OLCI data in turbid waters similar to those encountered in the BCZ. The ACOLITE processor for OLCI and the in situ matchup dataset used here are made available under an open source license. Numéro de notice : A2021-476 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112284 Date de publication en ligne : 12/02/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97116
in Remote sensing of environment > Vol 256 (April 2020) . - n° 112284[article]Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
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Titre : Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours Type de document : Article/Communication Auteurs : Amir Hossein Safaie, Auteur ; Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre remarquable
[Termes IGN] arbre urbain
[Termes IGN] détection d'arbres
[Termes IGN] détection de contours
[Termes IGN] diagramme de Voronoï
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] sécurité routière
[Termes IGN] semis de points
[Termes IGN] transformation de HoughRésumé : (auteur) Trees are important road-side objects, and their geometric information plays an essential role in road studies and safety analyses. This paper proposes an efficient method for the automated creation of a road-side tree inventory using Mobile Terrestrial Lidar System (MTLS) point clouds. In the proposed method ground points are filtered through preprocessing to reduce processing time. Next, tree trunks are detected by performing a Hough Transform (HT) algorithm on several generated raster images from the point clouds. By initiating an approximate area of a tree’s foliage through a Voronoi Tessellation (VT) algorithm, the accurate boundary of the foliage is identified by applying Active Contour (AC) models. By extracting the points within this foliage boundary the geometric characteristics of each tree are obtained. This method was evaluated with two sample point clouds from different MTLS systems, and the algorithm correctly extracted all of the trees from both datasets. Additionally, comparing the calculated parameters with manually observed measures, the accuracy of the obtained geometric parameters were promising. Numéro de notice : A2021-206 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.026 Date de publication en ligne : 14/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.026 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97183
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 19 - 34[article]Réservation
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