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Arch. Photogram., Rem. Sens. Spatial Inform. Sci., 559, 10.5194\u002Fisprsarchives-XXXIX-B3-559-2012\nd’Angelo, 2010, Image matching and outlier removal for large scale DSM generation\nd’Angelo, 2012, Dense multi-view stereo from satellite imagery, IEEE Int. Geosci. Rem. Sens. Symp., 6944\nDenis, 2007, ATSR-2 camera models for the automated stereo photogrammetric retrieval of cloud-top heights—initial assessments, Int. J. Rem. Sens., 28, 1939, 10.1080\u002F01431160600641723\nDerrien, 2010, Improvement of cloud detection near sunrise and sunset by temporal-differencing and region-growing techniques with real-time SEVIRI, Int. J. Rem. Sens., 31, 1765, 10.1080\u002F01431160902926632\nDinchang, 2008, Automatic cloud removal from multi-temporal SPOT images, Appl. Math. Comput., 205, 584, 10.1016\u002Fj.amc.2008.05.050\nGabarda, 2007, Cloud covering denoising through image fusion, Image Vis. 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Sci., 607\nHirschmuller, 2005, Accurate and efficient stereo processing by semi-global matching and mutual information, IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE, 807\nHirschmuller, 2008, Stereo processing by semiglobal matching and mutual information, IEEE Trans. Pattern Anal. Mach. Intell., 30, 328, 10.1109\u002FTPAMI.2007.1166\nHughes, 2014, Automated detection of cloud and cloud shadow in single-date Landsat imagery using neural networks and spatial post-processing, Rem. Sens., 6, 4907, 10.3390\u002Frs6064907\nIrish, 2000, Landsat 7 automatic cloud cover assessment, 348\nJang, 2006, Neural network application for cloud detection in SPOT VEGETATION images, Int. J. Rem. Sens., 27, 719, 10.1080\u002F01431160500106892\nJedlovec, 2009\nJin, 2013, Automated cloud and shadow detection and filling using two-date Landsat imagery in the USA, Int. J. Rem. Sens., 34, 1540, 10.1080\u002F01431161.2012.720045\nKrauß, 2005, DEM generation from very high resolution stereo data in urban areas, Int. Arch. Photogram., Rem. Sens. Spatial Inform. Sci.\nKrauß, 2005, DEM generation from very high resolution stereo satellite data in urban areas using dynamic programming, Int. Arch. Photogram., Rem. Sens. Spatial Inform. Sci.\nKubo, 2001, Extraction of clouds from satellite imagery in the Antarctic using wavelet transform and Mahalanobis classifier, IEEE Int. Geosci. Rem. Sens. Symp., 2158\nLaban, 2012, Spatial cloud detection and retrieval system for satellite images, Int. J. Adv. Comput. Sci. Appl., 3, 212\nLe Hégarat-Mascle, 2009, Use of Markov random fields for automatic cloud\u002Fshadow detection on high resolution optical images, ISPRS J. Photogram. Rem. Sens., 64, 351, 10.1016\u002Fj.isprsjprs.2008.12.007\nLiang, 2001, Atmospheric correction of Landsat ETM+ land surface imagery. I. Methods, IEEE Trans. Geosci. Rem. Sens., 39, 2490, 10.1109\u002F36.964986\nLiang, 2002, Atmospheric correction of Landsat ETM+ land surface imagery. II. Validation and applications, IEEE Trans. Geosci. Rem. Sens., 40, 2736, 10.1109\u002FTGRS.2002.807579\nLiew, 1998, “Cloud-free” multi-scene mosaics of SPOT images, 1083\nLiu, 2013, Verification and analysis of positioning accuracy of RPC model of TH-1 three-line imagery\nLu, 2013, Estimation of transformation parameters between centre-line vector road maps and high resolution satellite images, Photogram. Rec., 28, 130, 10.1111\u002Fphor.12015\nManizade, 2006, Stereo cloud heights from multispectral IR imagery via region-of-interest segmentation, Geosci. Rem. Sens., IEEE Trans. on, 44, 2481, 10.1109\u002FTGRS.2006.873339\nMarais, 2011, An optimal image transform for threshold-based cloud detection using heteroscedastic discriminant analysis, Int. J. Rem. Sens., 32, 1713, 10.1080\u002F01431161003621619\nMarchand, 2010, A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS, J. Geophys. Res.: Atmos., 1984–2012, 115\nMarchand, 2007, An assessment of Multiangle Imaging Spectroradiometer (MISR) stereo-derived cloud top heights and cloud top winds using ground-based radar, lidar, and microwave radiometers, J. Geophys. Res.: Atmos., 1984–2012, 112\nMartz, 1992, Numerical definition of drainage network and subcatchment areas from Digital Elevation Models, Comput. Geosci., 18, 747, 10.1016\u002F0098-3004(92)90007-E\nMuller, 2007, Stereo cloud-top heights and cloud fraction retrieval from ATSR-2, Int. J. Rem. Sens., 28, 1921, 10.1080\u002F01431160601030975\nNagashima, 2006, A subpixel image matching technique using phase-only correlation, Int. Symp. Intell. Signal Process. Commun., IEEE, 701\nNaud, 2006, Assessment of multispectral ATSR2 stereo cloud-top height retrievals, Rem. Sens. Environ., 104, 337, 10.1016\u002Fj.rse.2006.05.008\nNaud, 2002, Comparison of cloud top heights derived from MISR stereo and MODIS CO2‐slicing, Geophys. Res. Lett., 29, 10.1029\u002F2002GL015460\nNing, 2012, Development and research comprehensive report of 2011–2012 Surveying and Mapping, Sci. Survey. Mapping, 37, 1\nO’Callaghan, 1984, The extraction of drainage networks from digital elevation data, Comput. Vision, Graphics, Image Process., 28, 323, 10.1016\u002FS0734-189X(84)80011-0\nOtsu, 1975, A threshold selection method from gray-level histograms, Automatica, 11, 23\nPanem, 2005, Automatic cloud detection on high resolution images, IEEE Int. Geosc. Rem. Sens. Symp., 506\nSeiz, 2003\nSoille, 2008, IMAGE-2006 Mosaic: SPOT-HRVIR and IRS-LISSIII Cloud Detection\nToutin, 2004, DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling, Int. J. Rem. Sens., 25, 5181, 10.1080\u002F01431160410001726030\nWang, Y., Wang, W., Yang, L., Liang, H., 2013. Two-stage algorithm for cloud detection with ZY-1 02C multi-spectral measurements. In: Proc. SPIE 8890, Remote Sensing of Clouds and the Atmosphere XVIII; and Optics in Atmospheric Propagation and Adaptive Systems XVI, pp. 889012–889011.\nWang, Z., Jin, J., Liang, J., Yan, K., Peng, Q., 2005. A new cloud removal algorithm for multi-spectral images, Proc. SPIE 6043, MIPPR 2005: SAR and Multispectral Image Processing. International Society for Optics and Photonics, pp. 60430W–60430W-60411.\nWatmough, 2011, A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+, Int. J. Appl. Earth Obs. Geoinf., 13, 220, 10.1016\u002Fj.jag.2010.11.006\nXu, 2013, Generating DEM of very narrow baseline stereo using multispectral images\nZhang, 2009, An improved approach for DSM generation from high-resolution satellite imagery, J. 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Ecol., 17, 711, 10.1111\u002Fj.1365-2435.2003.00790.x\nSantos, 2004, High rates of net ecosystem carbono assimilation by Brachiaria pasture in the Brazilian Cerrado, Glob. Change Biol., 10, 877, 10.1111\u002Fj.1529-8817.2003.00777.x\nSilva, 2004, Carbon storage in clayey Oxisol cultivated pastures in the “Cerrado” region, Brazil, Agric. Ecosyst. Environ., 103, 357, 10.1016\u002Fj.agee.2003.12.007\nSilva, E.B., Ferreira, L.G., Rocha, G.F., Couto, M.S.D.S., 2009. Taxas de desmatamento em Otto bacias do bioma Cerrado obtidas através de imagens índice de vegetação MODIS. In: XIV Brazilian Remote Sensing Symposium, Natal, Brazil, pp. 6241–6248.\nSilva, 2013, An spatial distribution of cultivated pastures in the Brazilidas no bioma Cerrado entre 1970 e 2006, Revista IDeAs, 7, 174\nSoares-Filho, 2014, Cracking Brazil’s forest code, Science, 344, 363, 10.1126\u002Fscience.1246663\nSolano, R., Didan, K., Jacobson, A., Huete, A.R., 2010. MODIS vegetation indices (MOD13) user ́s guide. \u003Chttp:\u002F\u002Ftbrs.arizona.edu\u002Fproject\u002FMODIS\u002FMOD13.C5-UsersGuide-HTML-v1.00> (accessed on 25.02.11).\nSolórzano, 2012, Perfil florístico e estrutural do componente lenhoso em seis áreas de cerradão ao longo do bioma Cerrado, Acta Botanica Brasilica, 26, 328, 10.1590\u002FS0102-33062012000200009\nSpracklen, 2012, Observations of increased tropical rainfall preceded by air passage over forests, Nature, 489, 10.1038\u002Fnature11390\nStickler, 2013, The Dependence of hydropower energy generation on forests in the Amazon Basin at local and regional scales, Proc. Nat. Acad. Sci., 13\nTan, B., Morisette, J.T., Wolfe, E., Gao, F., Ederer, G.A., Nightingale, J., Pedelty, J.A., 2008. Vegetation phenology metrics derived from temporally smoothed and gap-filled MODIS data. 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Eng. Remote Sens., 73, 1321, 10.14358\u002FPERS.73.12.1321\nAguilar, 2008, Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for common agricultural policy purposes, Int. J. Remote Sens., 29, 7181, 10.1080\u002F01431160802238393\nAguilar, 2013, Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images, Int. J. Appl. Earth Obs. Geoinf., 21, 427, 10.1016\u002Fj.jag.2012.06.004\nDial, G., Grodecki, J., 2002. Block adjustment with rational polynomial camera models. In: Proceedings of APSRS 2002 Annual Conference, Washington DC, 22–26 April (on CDROM).\nDowman, I., Dolloff, J.T., 2000. An evaluation of rational functions for photogram-metric restitution. In: The International Archives of Photogrammetry and Remote Sensing, Amsterdam, The Netherlands, Vol. XXXIII, PartB3\u002F1, pp. 252–266.\nFraser, 2003, Bias compensation in rational functions for IKONOS satellite imagery, Photogram. Eng. Remote Sens., 69, 53, 10.14358\u002FPERS.69.1.53\nFraser, 2005, Bias compensated RPCs for sensor orientation of high-resolution satellite imagery, Photogram. Eng. Remote Sens., 71, 909, 10.14358\u002FPERS.71.8.909\nFraser, 2002, Processing of IKONOS imagery for submetre 3D positioning and building extraction, ISPRS J. Photogram. Remote Sens., 56, 177, 10.1016\u002FS0924-2716(02)00045-X\nFraser, 2006, Sensor orientation via RPCs, ISPRS J. Photogram. Remote Sens., 60, 182, 10.1016\u002Fj.isprsjprs.2005.11.001\nGrodecki, J., Dial, G., 2001. IKONOS geometric accuracy. In: Proceedings of Joint International Workshop on High Resolution Mapping from Space. Hannover, Germany, 19–21 September, pp. 234–251 (CD-ROM).\nGrodecki, 2003, Block adjustment of high-resolution satellite images described by rational polynomials, Photogram. Eng. Remote Sens., 69, 59, 10.14358\u002FPERS.69.1.59\nKoch, 1977, Least squares adjustment and collocation, Bulletin Géulletine, 51, 127\nLi, 2007, Integration of Ikonos and QuickBird imagery for geopositioning accuracy analysis, Photogram. Eng. Remote Sens., 73, 1067\nLi, 2011, Efficient estimation of variance and covariance components: a case study for GPS stochastic model evaluation, IEEE Trans. Geosci. Remote Sens., 49, 203, 10.1109\u002FTGRS.2010.2054100\nMadani, M., 1999. Real-time sensor-independent positioning by rational functions. In: Proc. of ISPRS Workshop on Direct versus Indirect Methods of Sensor Orientation, Barcelona, Spain, 25–26, November, pp. 64–75.\nMoritz, 1980, Statistical foundations of collocation, Boll Geod. Sci. 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1988\nBardinet, 1988, Application of Multisatellite data to thematic mapping, Geol. Jahrb., Reihe B, Heft 67, 74\nBerger, 1978\nBerger, 1988\nBonnefoy, 1986, Télédétection, discrimination d'objets géologiques et miniers; analyse multitemporelle et multispectrale des données spatiales et de leurs relations avec les données géochimiques, 2ème partie: Tunisie (zone des dômes), 74\nBrosse, 1975, La télédétection en géologie structurale. Deux exemples: le massif anitique de Villefranche-de-Rouergue (Aveyron) et le système filonien de de Vialas (Lozère) (Massif Central, France), Thesis, 132\nChorowicz, 1984, Intérêt de la cartographie géologique à petite échelle à partir d'images spatiales dans le sud-est de la France, Bull. Centre Géomorph., CNRS, Caen, 28, 83\nConradsen, 1986, A geological example of improving classification of remotely sensed data using additional variables and a hierarchical structure, Photogramm. Eng. Remote Sensing, 52, 1181\nDeroin, 1988, Fracturation comparée d'un secteur du Bas-Languedoc à l'aide de données multisources, 45\nDeroin, 1988, Cartographie géologique télé-analytique du couple de scènes stéréoscopique SPOT 1-HRV - K.J. 047.261 Alès-Mont Lozère, 75\nDewolf, 1987, Interprétations et perceptions de la morphologique du Bassin Parisien, Bull. Inf. Géol. Bassin Paris, Mém. Hors. Sér., 19\nDupias, 1973\nDutartre, 1986, Structural and geobotanical contribution of remote sensing to exploration of ore deposits in Rhodope (Greece), 85\nEosat, 1988, Mineral Exploration in Central Spain, Landsat Application Notes, 3, 4\nFontanel, 1976, Comparaison des images et des classifications multispectrales obtenues à partir des satellites Landsat, Skylab et du scanner aéroporté Daedalus, Journées Télédétection, Toulouse, II, 499\nFrench, 1960, The chlorophylls in vivo and in vitro, vol. 1, 252\nGess, 1987, Methodology for the use of Spot imagery in petroleum exploration (PEPS 104), 811\nHill, 1988, Regional land cover and agricultural area statistics and mapping in The Déparment Ardèche, France, by use of Thematic Mapper data, Int. J. Remote Sensing, 10–11, 1573, 10.1080\u002F01431168808954962\nJaskolla, 1988, Evaluation and digital processing of multispectral SPOT data, Int. J. Remote Sensing, 10\u002F11, 1629, 10.1080\u002F01431168808954965\nKaufmann, 1988, Image optimization versus classification — An application oriented comparison of different methods by use of Thematic Mapper data, Photogrammetria, 42, 311, 10.1016\u002F0031-8663(88)90008-7\nKing, 1967, Geomorphology about the Central Plateau of France, 382\nLetalenet, 1979, Prospection géochimique Génolhac-Bessèges, division Sud-Ouest-Zone 54. Interprétation des résultats analytiques, 11\nLetouzey, 1980, Etude géologique comparative des enregistrements radar Goodyear (bande X) et J.P.L. (band L) sur le site-test des Vans, Bull. Soc. Fr. Photogramm. Télédét., 79–80, 49\nMalon, 1984, Principaux traitements des images satellitaires et associées, 46\nNultsch, 1982, Allgemeine Botanik, 516\nScanvic, 1983, Expérience SAR 580 sur Les Vans, 107\nScanvic, 1985, Structural and geobotanical contribution of remote sensing to exploration of hidden deposits in Brittany (France), 128\nVergely, 1988, Etude par photo-interprétation comparée de la région de Largentière-Les Vans (Languedoc septentrional, France): utilisation des photographies aèriennes, des images par satellites et des images radar, Bull. Soc. Géol. 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2010\nAllouis, 2010, Comparison of LiDAR waveform processing methods for very shallow water bathymetry using Raman, near infrared and green signals, Earth Surf. 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ASPRS Ten-Year Remote Sensing Industry Forecast. \u003Chttp:\u002F\u002Fwww.asprs.org\u002F10-Year-Industry-Forecast\u002FTen-Year-Industry-Forecast.html> (accessed 16.09.2015).\nBo, 2011, A multi-wavelength canopy LiDAR for vegetation monitoring: system implementation and laboratory-based tests, Proc. Environ. Sci., 10, 2775, 10.1016\u002Fj.proenv.2011.09.430\nBonin-Font, 2008, Visual navigation for mobile robots: a survey, J. Intell. Rob. Syst., 53, 263, 10.1007\u002Fs10846-008-9235-4\nBrock, 2009, The emerging role of lidar remote sensing in coastal research and resource management, J. Coastal Res., 1, 10.2112\u002FSI53-001.1\nCaballero, 2009, Vision-based odometry and SLAM for medium and high altitude flying UAVs, J. Intell. Rob. Syst., 54, 137, 10.1007\u002Fs10846-008-9257-y\nCampbell, 2002\nChauve, A., Mallet, C., Bretar, F., Durrieu, S., Deseilligny, M.P., Puech, W., 2007. Processing full-waveform lidar data: modelling raw signals. In: International archives of photogrammetry remote sensing and spatial information sciences. XXXVI-3\u002FW52, pp. 102–107.\nChen, 2010, Two-channel hyperspectral LiDAR with a supercontinuum laser source, Sensors, 10, 7057, 10.3390\u002Fs100707057\nColomb, 2004, SAC-C mission, an example of international cooperation, Adv. Space Res., 34, 2194, 10.1016\u002Fj.asr.2003.10.039\nColomina, I., 2015. On trajectory determination for photogrammetry and remote sensing: sensors, models and exploitation. In: Fritsch, D. (Ed.), Photogrammetric Week 2015.\nColomina, 2014, Unmanned aerial systems for photogrammetry and remote sensing: a review, ISPRS J. Photogramm. Remote Sens., 92, 79, 10.1016\u002Fj.isprsjprs.2014.02.013\nConte, 2008, An integrated UAV navigation system based on aerial image matching\nCramer, M., 2004. The EuroSDR network on digital camera calibration. Report Phase 1, 53 p. \u003Chttp:\u002F\u002Fwww.ifp.uni-stuttgart.de\u002Feurosdr\u002FEuroDAC\u002Findex.en.html>.\nd’Angelo, 2014, Evaluation of skybox video and still image products, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 95, 10.5194\u002Fisprsarchives-XL-1-95-2014\nDunn, 2003, APPLICATION CHALLENGE-instrument of grace-GPS augments gravity measurements, GPS World, 14, 16\nEbner, 1988, Combined point determination using digital terrain models as control information, Int. Arch. Photogramm. Remote Sens., 27, 578\nEisenberg, 2013\nEuropean GNSS Agency (GSA), 2015. GNSS Market Report, Issue 4. \u003Chttp:\u002F\u002Fwww.gsa.europa.eu\u002Fsystem\u002Ffiles\u002Freports\u002FGNSS-Market-Report-2015-issue4_0.pdf> (accessed 16.09.2015).\nFraser, 2005, Hyper redundancy for accuracy enhancement in automated close range photogrammetry, Photogram. 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