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Integration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping / Guoyuan Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 9 (September 2018) . - pp 569 - 578 Titre : Integration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping Type de document : Article/Communication Auteurs : Guoyuan Li, Auteur ; Xinming Tang, Auteur ; Xiaoming Gao, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 569 - 578 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] Chine [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] données IceSat-Glas [Termes descripteurs IGN] image ZiYuan-3 [Termes descripteurs IGN] modèle par fonctions rationnelles [Termes descripteurs IGN] ZiYuan-3 Résumé : (Auteur) Integration of satellite laser altimetry data and stereo images without ground control points (GCPs) is an attractive method for global mapping. In this paper, we propose a new strategy of integrating Ziyuan3-02 (ZY3-02) satellite stereo images and laser altimetry data using a rigorous sensor model (RSM) with laser ranging constraint under the synchronized and rational function model (RFM) with laser elevation constraint under the non-synchronized capture for high-accuracy mapping without GCPs. Four experimental regions in China are selected to validate the method. The results show that the ZY3-02 satellite laser altimetry data can be used to improve the elevation accuracy of stereo images to better than 3.0 m without GCPs. All of the conclusions are valuable for the development of China's next generation of surveying and mapping satellites. Numéro de notice : A2018-362 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.9.569 date de publication en ligne : 01/09/2018 En ligne : https://doi.org/10.14358/PERS.84.9.569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90673 [article]

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Forest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India / S.M. Ghosh in Applied geomatics, vol 9 n° 3 (September 2017)  

Public [article]  inApplied geomatics > vol 9 n° 3 (September 2017) . - pp 159 - 166 Titre : Forest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India Type de document : Article/Communication Auteurs : S.M. Ghosh, Auteur ; M. Dev Behera, Auteur Année de publication : 2017 Article en page(s) : pp 159 - 166 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] altimétrie satellitaire par laser [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] données IceSat-Glas [Termes descripteurs IGN] données laser [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] Ghats occidentaux [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] Inde [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] pente Résumé : (Auteur) Canopy height is a crucial metric required to quantify the aboveground plant biomass accurately. The study explores the data derived using Light Detection and Ranging (LiDAR) technology from GeoScience Laser Altimeter System (GLAS) aboard Ice, Cloud, and Land Elevation satellite (ICESat) to derive canopy height estimate equations in the tropical forests of the Western Ghats, India. The interpretation of LiDAR waveforms for the purpose of estimating canopy heights is not straightforward, especially over sloping terrain where vegetation and ground are found at comparable heights. Canopy height models are developed using GLAS waveform extent and terrain index, derived from ASTER digital elevation, to counter the effect of topographic relief effects in canopy height estimates over steep terrain. The model was applied to calculate tree heights for whole of the Western Ghats. Results showed that the model can estimate tree heights within the specified height range with an accuracy of more than 90% while using percent overestimation/underestimation method of validation. This shows the effectiveness of the model, especially over steep slopes, also revealing that the models were able to successfully account for the pulse broadening effect. The study highlights the development of a LiDAR-based canopy height model for tropical forest and its ability to yield better canopy height estimates especially over steep slopes. Numéro de notice : A2017-597 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s12518-017-0190-2 En ligne : https://doi.org/10.1007/s12518-017-0190-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86815 [article]

Hybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar / Sören Holm in Remote sensing of environment, vol 197 (August 2017)  

Public [article]  inRemote sensing of environment > vol 197 (August 2017) . - pp 85 - 97 Titre : Hybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar Type de document : Article/Communication Auteurs : Sören Holm, Auteur ; Ross Nelson, Auteur ; Göran Stahl, Auteur Année de publication : 2017 Article en page(s) : pp 85 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] données IceSat-Glas [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] estimation statistique [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] variance [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Previous studies have utilized ground plots, airborne lidar scanning or profiling data, and space lidar profiling data to estimate biomass across large regions, but these studies have failed to take into account the variance components associated with multiple models because the proper variance equations were not available. Previous large-domain studies estimated the variances of their biomass density estimates as the sum of the GLAS sampling variability plus the model variability associated with the models that predict airborne lidar estimates of biomass density (Y) as a function of satellite lidar measurements (X). This approach ignores the additional variability associated with the predictive models used to estimate ground biomass density as a function of airborne lidar measurements. This paper addresses that shortcoming. Analytic variance expressions are provided that include sampling variability and model variability in situations where multiple models are employed to generate estimates of biomass. As an example, the forest biomass of the continental US is estimated, by forest stratum within state, using a space lidar system (ICESat/GLAS). An airborne laser system (ALS) is used as an intermediary to tie the GLAS measurements of forest height to a small subset of US Forest Service (USFS) ground plots by flying the ALS over the ground plots and, independently, over individual GLAS footprints. Two sets of models are employed to relate satellite measurements to the ground plots. The first set of equations relates USFS ground plot estimates of total aboveground dry biomass density (Y1) to spatially coincident ALS forest canopy measurements (X1). The second set of models predicts those ALS canopy height measurements (X1) used in the first set of models to GLAS waveform measurements (X2). The following important conclusions are noted. (1) The variability associated with estimation of the plot-ALS model coefficients is significant and should be included in the overall estimate of biomass density variance. In the continental US, the total variance of mean forest biomass density (98.06 t/ha) increases by a factor of 3.6 ×, i.e., from 1.91 to 6.94 t2/ha2, when plot-ALS model variance is included in the calculation of total variance. (2) State-level results are more variable, but on average, the percent model variance at the state level, i.e., (model variance / total variance) ∗ 100, increases from 16% to 59% when plot-ALS model variance is included. (3) The overall model variance is driven in large part by the number of plots overflown by the ALS and the number of GLAS pulses overflown by the ALS. Given a choice of improving precision by either increasing the number of plot-ALS observations or increasing ALS-GLAS observations, there is no obvious benefit to selecting one over the other. However, typically the number of ground plots overflown is the limiting factor. (4) If heteroskedasticity is evident in either the ground-air or air-satellite models, it can modeled using weighted regression techniques and incorporated into these model variance formulas in straightforward fashion. The results are unambiguous; in a hybrid three-phase sampling framework, both the ground-air and air-satellite model variance components are significant and should be taken into account. Numéro de notice : A2017-655 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.04.004 En ligne : https://doi.org/10.1016/j.rse.2017.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87050 [article]

The weight matrix determination of systematic bias calibration for a laser altimeter / Ma Yue in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 11 (November 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 11 (November 2016) . - pp 847 - 852 Titre : The weight matrix determination of systematic bias calibration for a laser altimeter Type de document : Article/Communication Auteurs : Ma Yue, Auteur ; Li Song, Auteur ; Lu Xiushan, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 847 - 852 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données IceSat-Glas [Termes descripteurs IGN] erreur de mesure [Termes descripteurs IGN] étalonnage [Termes descripteurs IGN] géolocalisation [Termes descripteurs IGN] incertitude de mesurage [Termes descripteurs IGN] matrice [Termes descripteurs IGN] matrice d'erreur Résumé : (Auteur) The geolocation accuracy of satellite laser altimeters is significantly influenced by on-orbit misalignment and ranging biases. Few researchers have investigated the weight matrix determination method, which plays a critical role in bias estimation. In this article, a systematic misalignment and ranging bias model was deduced. Based on the least squares criterion, a bias calibration method was designed for use with solid natural surfaces; and the weight matrix was defined according to the ranging uncertainty theory. Referring to the Geoscience Laser Altimeter System (glas) parameters, the established model and method were verified using programming simulations, which indicated with a misalignment of tens of arc-seconds in the pitch and roll directions and a ranging bias of several centimeters, by using the weight matrix, the estimation accuracies of the misalignment and ranging bias increased by 0.22 and 2 cm, respectively. Consequently, the geolocation accuracy increased by approximately 0.64 m horizontally and 3 cm vertically for a 1° sloping surface. Numéro de notice : A2016-944 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article En ligne : http://dx.doi.org/10.14358/PERS.82.11.847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83436 [article]

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Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data / Ibrahim Fayad in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 52 (October 2016) . - pp 502 - 514 Titre : Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Nicolas Baghdadi, Auteur ; Stéphane Guitet , Auteur ; Jean-Stéphane Bailly, Auteur ; Bruno Hérault, Auteur ; Valéry Gond, Auteur ; Mahmoud El-Hajj, Auteur ; Ho Tong Minh Dinh, Auteur Année de publication : 2016 Article en page(s) : pp 502 - 514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] données IceSat-Glas [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] Guyane (département français) [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] régression Résumé : (auteur) Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain “wall-to-wall” AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values. Numéro de notice : A2016--202 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2016.07.015 date de publication en ligne : 01/08/2016 En ligne : https://doi.org/10.1016/j.jag.2016.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96037 [article]

The influence of elliptical Gaussian laser beam on inversion of terrain information for satellite laser altimeter / Zhou Hui in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)  

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ICESat/GLAS canopy height sensitivity inferred from Airborne Lidar / Craig Mahoney in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)  

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Forest above ground biomass inversion by fusing GLAS with optical remote sensing data / Xiaohuan Xi in ISPRS International journal of geo-information, vol 5 n° 4 (April 2016)  

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Regional scale rain-forest height mapping using regression-kriging of spaceborne and airborne Lidar data: application on French Guiana / Ibrahim Fayad in Remote sensing, vol 8 n° 3 (March 2016)  

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ZY-3 block adjustment supported by GLAS laser altimetry data / Guoyuan Li in Photogrammetric record, vol 31 n° 153 (March - May 2016)  

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A multi-scale approach to mapping canopy height / Gordon M. Green in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 2 (February 2013)  

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