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GNSS best integer equivariant estimation combining with integer least squares estimation: an integrated ambiguity resolution method with optimal integer aperture test / Liye Ma in GPS solutions, vol 26 n° 4 (October 2022)
[article]
Titre : GNSS best integer equivariant estimation combining with integer least squares estimation: an integrated ambiguity resolution method with optimal integer aperture test Type de document : Article/Communication Auteurs : Liye Ma, Auteur ; Yidong Lou, Auteur ; Liguo Lu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse comparative
[Termes IGN] méthode des moindres carrés
[Termes IGN] phase GNSS
[Termes IGN] positionnement par GNSS
[Termes IGN] précision du positionnement
[Termes IGN] résolution d'ambiguïtéRésumé : (auteur) Accurate and reliable carrier phase ambiguity resolution (AR) is the key to global navigation satellite system (GNSS) high-precision navigation and positioning applications. The integer least squares (ILS) estimation and the best integer equivariant (BIE) estimation are two widely used AR method, with the former considered to have the highest success rate and the latter to be optimal in the minimum mean squared error (MSE) sense. We analyzed three key issues of applying the BIE method in detail, including the use boundary of BIE, the number of candidates to be involved, and the weight determination among ambiguity candidates. It has been demonstrated that the BIE estimator is superior to ILS estimator from an overall perspective, but not always the best in each specific epoch. Therefore, we recommend constructing an integrated ambiguity resolution scheme that combines BIE with ILS, and we propose to adopt the optimal integer aperture (OIA) test as a criterion to distinguish the two. Moreover, a new criterion referred to the OIA test is proposed to determine the number of candidates involved in the BIE estimator. We also attempt to add the quadratic forms of baseline residuals into the weight function of BIE, aiming to reach a more accurate estimator. Finally, an integrated AR method that combines ILS with BIE and distinguished by the OIA test is proposed, named OIA-BIE. A set of real-measured vehicle data are tested to evaluate its performance, compared to least squares (LS), ILS, and the original BIE. The results show that the positioning accuracy of OIA-BIE is a little better than BIE, better than ILS, and significantly better than LS. Moreover, the average time consumption of ILS, BIE, and OIA-BIE are also evaluated, with 1.15, 14.62, and 3.71 ms, respectively, and OIA-BIE is four times more efficient than BIE. Numéro de notice : A2022-542 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01285-5 Date de publication en ligne : 03/07/2022 En ligne : https://doi.org/10.1007/s10291-022-01285-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101107
in GPS solutions > vol 26 n° 4 (October 2022) . - n° 100[article]The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)
[article]
Titre : The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Tianyu Guo, Auteur ; Chengye Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 665 - 671 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] Chine
[Termes IGN] couvert végétal
[Termes IGN] Google Earth Engine
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] industrie minière
[Termes IGN] mine
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression géographiquement pondérée
[Termes IGN] régression multiple
[Termes IGN] réseau neuronal artificielRésumé : (auteur) To determine the fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas, six types of data were used as driving factors and three methods —multi-linear regression (MLR), geographically weighted regression (GWR), and geographically weighted artificial neural network (GWANN)— were adopted in the modeling. The experiments, conducted in Shengli mining areas located in Xilinhot city, China, show that the MLR model without consideration of spatial heterogeneity and spatial non-stationarity performs the worst and that the GWR model presents obvious location differences, since it predefines a linear relationship which is unable to describe FVC for some locations. The GWANN model, improving on these defects, is the most suitable model for the FVC driving process in mining areas; it outperforms the other two models, with root-mean-square error (RMSE) and mean absolute percentage error (MAPE) reaching 0.16 and 0.20. It has improvements of approximately 24% in RMSE and 33% in MAPE compared to the MLR model, and those values grow to 59% and 71% when compared with the GWR model. Numéro de notice : A2022-813 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00070R3 Date de publication en ligne : 01/10/2022 En ligne : https://doi.org/10.14358/PERS.21-00070R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101973
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 10 (October 2022) . - pp 665 - 671[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2022101 SL Revue Centre de documentation Revues en salle Disponible Comparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska / Jiang Chen in Geocarto international, vol 37 n° 20 ([20/09/2022])
[article]
Titre : Comparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska Type de document : Article/Communication Auteurs : Jiang Chen, Auteur ; Weining Zhu, Auteur Année de publication : 2022 Article en page(s) : pp 6052 - 6071 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] analyse comparative
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-8
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] latitude
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] observation de la Terre
[Termes IGN] réflectance de surfaceRésumé : (auteur) Combining Landsat-8 and Sentinel-2 images is an effective approach to obtain high spatiotemporal resolution data for Earth observation and remote sensing modeling. The differences between Landsat-8 and Sentinel-2 products, such as the reflectance at the top of atmosphere (TOA) and land surface, should be compared and evaluated to make sure they are spectrally consistent. Their consistency has been evaluated and the differences have been empirically corrected at mid-low latitudes, but in high latitude areas with a higher solar zenith angle (SZA), the similar work has not been explored. In this study, Landsat-8 and Sentinel-2 TOA and surface reflectance in Alaska as well as some surface parameters, such as the normalized difference vegetation index (NDVI) and normalized difference snow index (NDSI), were compared using the massive data distributed on Google earth engine (GEE) online platform, and their consistency was evaluated and the uncertainty was analyzed. Some empirical models were suggested to convert Sentinel-2 products to be consistent with Landsat-8 products at all bands. The results show that TOA reflectance is more consistent than surface reflectance in Alaska. This study suggests that the consistency between Landsat-8 and Sentinel-2 at high latitudes should be paid more attention because their consistency is lower than that at mid-low latitudes. Numéro de notice : A2022-717 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/10106049.2021.1924295 Date de publication en ligne : 17/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1924295 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101642
in Geocarto international > vol 37 n° 20 [20/09/2022] . - pp 6052 - 6071[article]Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)
[article]
Titre : Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics Type de document : Article/Communication Auteurs : Jakob Wernicke, Auteur ; Christian Torsten Seltmann, Auteur ; Ralf Wenzel, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113134 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] analyse comparative
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] semis de points
[Termes IGN] stratificationRésumé : (auteur) Knowledge about the forest canopy stratification is of essential importance for forest management and planning. Collecting structural information (e.g. natural regeneration) still depends on cost and labour intensive forest inventories with a coarse spatio-temporal resolution. Remote sensing partly overcomes these limitations and particularly active sensors of type light detection and ranging (LiDAR) have proven their great potential of separating forest strata. The applicability of LiDAR metrics for the differentiation of the spruce dominated forest strata in Central Germany has not been tested yet. Additionally, studying the potential of Sentinel-2 metrics for the classification of forest strata is lacking too. In this study, we investigated the capabilities of six different classification approaches for the differentiation of five forest strata that are typical for the study region. Reference data were derived from forest inventory measurements surveyed on a dense 200 × 200 m grid. The six classification approaches were trained with fused and un-fused LiDAR and Sentinel-2 inferred metrics. The classification results were compared using the overall mean accuracy, sensitivity and specificity via receivers operating characteristics of multi-class problems. We were interested in the classification abilities of Sentinel-2 metrics due to the obvious advantages of Sentinel-2 based metrics (free of charge, high spatio-temporal coverage). We assumed that the canopy structure determines the reflection on stand level and thus might facilitate the classification of different canopy strata. Beforehand, it was important to examine the influence of distinctly imbalanced and collinear reference data on the classification results. We found that the Random Forest classifier most accurately separated the five forest strata with a mean overall accuracy of 83.3% (Kappa = 76.2%). These values were achieved from balanced training data and the classification capability was confirmed by classification results from an independent test data set. Fused predictors of active (LiDAR) and passive (Sentinel-2) remote sensing revealed no substantial improvement in the classification accuracy due to the dominant role of LiDAR metrics. Herein, we identified that especially the height variability, top height, portion of LiDAR-returns between 2 m and 10 m and the standard deviation of the return number between the 25th and 50th height percentile, predominately contributed to the classification accuracy. Classification results purely based on Sentinel-2 metrics revealed a rather small overall mean accuracy of 54.7%. The metrics (e.g. median, variance, entropy) were derived from Sentinel-2 indices, covering the visible and near to short infrared spectrum. Variable importance computations unraveled a detectable but minor contribution of MSI, TCG, NDVI to the classification result. Finally, our data driven observations illustrated serious drawbacks associated to data imbalance, collinearity and autocorrelation and presented practical guidance to cope with these issues. Numéro de notice : A2022-510 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113134 Date de publication en ligne : 28/06/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101047
in Remote sensing of environment > vol 279 (September-15 2022) . - n° 113134[article]The FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation / Shuaijun Liu in Remote sensing of environment, vol 279 (September-15 2022)
[article]
Titre : The FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation Type de document : Article/Communication Auteurs : Shuaijun Liu, Auteur ; Junxiong Zhou, Auteur ; Yuean Qiu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113111 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] autocorrélation
[Termes IGN] bande spectrale
[Termes IGN] détection de changement
[Termes IGN] données spatiotemporelles
[Termes IGN] fusion de données
[Termes IGN] image Landsat-OLI
[Termes IGN] image Terra-MODIS
[Termes IGN] réflectance de surface
[Termes IGN] réflectance spectrale
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] régression multipleRésumé : (auteur) Over the past decade, spatiotemporal fusion has become an indispensable tool for monitoring land surface dynamics due to its promising ability to produce surface reflectance products with both high spatial and temporal resolutions. However, existing fusion methods usually generate multispectral band products by predicting each spectral band separately, so the useful information of spectral autocorrelation within the spectrum has been ignored and waits to be exploited. To address this issue, we propose a novel spatiotemporal fusion method, the spatiotemporal Fusion Incorrporting Spectral autocorrelaTion (FIRST) model, to fully utilize the multiple spectral bands of surface reflectance products. Compared with other fusion methods, the model has three distinct advantages: (1) it utilizes spectral autocorrelation in a many-to-many regression framework that simultaneously inputs and predicts multispectral bands without the collinearity effect; (2) it maintains high fusion accuracy when the spatiotemporal variation is large with acceptable computational efficiency; and (3) it can produce robust results even with input images contaminated by haze and thin clouds. We tested the FIRST model at several experimental sites and compared it with four typical methods, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal DAta Fusion (FSDAF) model, the regression model Fitting, spatial Filtering and residual Compensation (Fit-FC) model and the enhanced STARFM (ESTARFM). The results demonstrate that FIRST yields better overall performance for its simple and effective technical principles. FIRST is thus expected to provide high-quality remotely sensed data with high spatial resolution and frequent observations for various applications. Numéro de notice : A2022-554 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113111 Date de publication en ligne : 16/06/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113111 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101166
in Remote sensing of environment > vol 279 (September-15 2022) . - n° 113111[article]Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method / Juan Vicente Liendro Moncada in Geocarto international, Vol 37 n° 17 ([20/08/2022])PermalinkComparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs / Douglas Stefanello Facco in Geocarto international, vol 37 n° 16 ([15/08/2022])PermalinkAssessing structural complexity of individual scots pine trees by comparing terrestrial laser scanning and photogrammetric point clouds / Noora Tienaho in Forests, Vol 13 n° 8 (August 2022)PermalinkComparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation / Omer Faruk Atiz in Survey review, vol 55 n° 388 (January 2023)PermalinkFull-waveform classification and segmentation-based signal detection of single-wavelength bathymetric LiDAR / Xue Ji in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkPositioning performance of GNSS-PPP and PPP-AR methods for determining the vertical displacements / Burak Akpinar in Survey review, vol 55 n° 388 (January 2023)PermalinkEvaluation of the GSRM2.1 and the NUVEL1-A values in Europe using SLR and VLBI based geodetic velocity fields / Mina Rahmani in Survey review, vol 54 n° 385 (July 2022)PermalinkCombination of Sentinel-1 and Sentinel-2 data for tree species classification in a Central European biosphere reserve / Michael Lechner in Remote sensing, vol 14 n° 11 (June-1 2022)PermalinkManagement or climate and which one has the greatest impact on forest soil’s protective value? A case study in Romanian mountains / Cosmin Cosofret in Forests, vol 13 n° 6 (June 2022)PermalinkOn the consistency of coastal sea-level measurements in the Mediterranean Sea from tide gauges and satellite radar altimetry / Sara Bruni in Journal of geodesy, vol 96 n° 6 (June 2022)Permalink