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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)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 767 - 773 Titre : The influence of elliptical Gaussian laser beam on inversion of terrain information for satellite laser altimeter Type de document : Article/Communication Auteurs : Zhou Hui, Auteur ; Li Song, Auteur ; Yang Chi, Auteur Année de publication : 2016 Article en page(s) : pp 767 - 773 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] données ICEsat [Termes IGN] erreur de positionnement [Termes IGN] fonction inverse [Termes IGN] modèle mathématique [Termes IGN] récepteur radar [Termes IGN] signal Résumé : (Auteur) The transmitted laser mode of Geosciences Laser Altimeter System (GLAS) is a significant factor in determining the received pulse waveforms, which are used for inversing target information. The inversion algorithms in the scientific literature are based on the assumption that the transmitted laser is circular Gaussian. The practical laser pattern of GLAS is not circularly symmetric, but elliptical Gaussian. The received pulse shape will contain a bias, which would cause an error in the inversion information. In this paper, we describe new theoretical models about received pulse signal and inversion errors of range, surface slope and roughness. We present the results of waveforms shape and inversion errors for three representative terrains with different surface slope and roughness. The results show that the maximal inversion errors of range, surface slope, and roughness will reach 24.25 cm, 8.82° and 4.58 m, respectively, which cannot be negligible. Therefore, the inversion information should be reevaluated and amended depending on the type of terrain. Numéro de notice : A2016-933 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.82.10.767 En ligne : http://dx.doi.org/10.14358/PERS.82.10.767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83347 [article]

Modeling the effects of horizontal positional error on classification accuracy statistics / Henry B. Glick in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 789 - 802 Titre : Modeling the effects of horizontal positional error on classification accuracy statistics Type de document : Article/Communication Auteurs : Henry B. Glick, Auteur ; Devin Routh, Auteur ; Charlie Bettigole, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 789 - 802 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification [Termes IGN] erreur de positionnement [Termes IGN] méthode de Monte-Carlo [Termes IGN] simulation Résumé : (Auteur) Using a concept proposed by Stehman and Czaplewski (1997), we implemented spatially-explicit Monte Carlo simulations to test the effects of manually introduced horizontal positional error on standard inter-rater statistics derived from twelve classified high-resolution images. Through simulations we found that both overall and kappa accuracies decrease markedly with increasing error distance, varying greatly across distances relevant to practical application. The use of ground reference sites falling solely in homogeneous patches significantly improves inter-rater statistics and calls into question the use of kernel-smoothed data in one-time accuracy assessments. Our simulations offer insight into the scale of both structural and cover type heterogeneity across our landscapes, and support a new method for minimizing the effects of positional error on map accuracy. We recommend that analysts use caution when applying traditional accuracy assessment strategies to categorical maps, particularly when working with high-resolution imagery. Numéro de notice : A2016-934 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.10.789 En ligne : http://dx.doi.org/10.14358/PERS.82.10.789 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83348 [article]

Vegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 803 - 810 Titre : Vegetation effects modeling in soil moisture retrieval using MSVI Type de document : Article/Communication Auteurs : Mina Moradizadeh, Auteur ; Mohammad R. Saradjian, Auteur Année de publication : 2016 Article en page(s) : pp 803 - 810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] humidité du sol [Termes IGN] image multicapteur [Termes IGN] indice de végétation [Termes IGN] itération [Termes IGN] température au sol [Termes IGN] température de luminance Résumé : (Auteur) Brightness temperature (BT) measured by passive microwave sensors is usually affected by soil moisture, vegetation cover, and soil roughness. Soil moisture estimates have been limited to regions that had either bare soil or low to moderate amounts of vegetation cover. In this study, Simultaneous Land Parameters Retrieval Model (SLPRM) as an iterative least-squares minimization method has been used. This algorithm retrieves surface soil moisture, land surface temperature, and canopy temperature simultaneously using brightness temperature data in bare soil, low to moderate and higher amounts of vegetation cover. Furthermore, a new index called MSVI (Multi Sensor Vegetation Index) has been introduced to approximate vegetation effects on properly observed brightness temperatures. The algorithm includes model construction, calibration, and validation using observations carried out for the SMEX03 (Soil Moisture Experiment 2003) region in the South and North of Oklahoma. The results indicated about 0.9 percent improvement on soil moisture estimation accuracy using the MSVI. Numéro de notice : A2016-935 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.10.803 En ligne : http://dx.doi.org/10.14358/PERS.82.10.803 Format de la ressource électronique : URL artilce Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83349 [article]