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Remote Sensing in Forest Management

References [1] Badgley, G.; Field, C.B.; Berry, J.A. Canopy near-infrared reflectance and terrestrial photosynthesis. Sci. Adv. 2017, 3, e1602244 [2] C. B. Field, J. T. Randerson, C. M. Malmstrom, Global net primary production: Combiningecology and remote sensing.Remote Sens. Environ.51,74–88 (1995) [3] Ciubotaru, A., Exploatareapădurilor , ed. Lux Libris, 1998 [4] C. S. Potter, J. T. Randerson, C. B. Field, P. A. Matson, P. M. Vitousek, H. A. Mooney,S. A. Klooster, Terrestrial ecosystem production: A process model based on global

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Remote Sensing Using Unmanned Aerial Vehicles for Tourist-Recreation Lake Evaluation and Development

Introduction The development of new technologies has made it possible to carry out both field and chamber scientific research in a way that until recently seemed impossible, as well as provide measurement methods to assess the geographical environment from an entirely different perspective. This revolution in remote sensing research is especially enabled by the relatively new ability to perform measurements using unmanned aerial vehicles. Unmanned Aerial Vehicles (UAVs), commonly known as drones and according to the European Commission recommendations

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Biotope mapping of extensive/intensive grassland supported by Remote Sensing and Mobile GIS in Eastern Styria (Austria)

References Amt der Steiermärkischen Landesregierung (2008). Biotoptypen - Katalog der Steiermark. Amt der Steiermärkischen Landesregierung Fachabteilung 13C Naturschutz. Angold, P.G., Gurnell, A.M. & Edwards P.J. (1996). Locational errors in maps from environmental surveys and their implications for information extraction. J.Environ. Manag., 47, 341−354. Bock, M. (2003). Remote sensing and GIS-based techniques for the classification and monitoring of biotopes. J. Nat.Conserv., 11, 145-155. http

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ICA-ASIFT-Based Multi-Temporal Matching of High-Resolution Remote Sensing Urban Images

References 1. Yin, S. W. A Linear Feature-Based Image Rectification Method for HD Remote Sensing Images. - Geomatics Technology and Equipment, Vol. 9, 2007, No 2, pp. 3-5. 2. Smith, S. M., J. M. Brady. SUSAN-A New Approach to Low Level Image Processing. - International Journal of Computer Vision, Vol. 23, 1997, No 1, pp. 45-78. 3. Harris, C. J., M. Stephen. A Combined Corner and Edge Detector. - In: Proc. of 4th Alvey Vision Conference, Manchester, United Kingdom, 1988. 4. Bay, H., A. Ess, T

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Possibilities of the Practical Application of Remote Sensing Data in Real Property Appraisal

References BENDIG J., BOLTEN A., BARETH G., 2012, Introducing a low-cost mini-UAV For thermal- and multispectralimaging”, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v.XXXIX-B1. CHUVIECO E., 1989, Application of remote sensing and geographic information systems to forest fire hazard mapping, Remote Sensing of Environment, v.29(2), pp.147-159. DĄBROWSKI R., ORYCH A., WALCZYKOWSKI P., 2010 Ocena możliwości wykorzystania wysokorozdzielczych zobrazowań satelitarnych

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Spatio-temporal dynamics of vegetation cover in North-West Algeria using remote sensing data

Tell Oranie . “Revue de Géographie de Lyon” Vol. 41, no. 4, pp. 303−338. Bernstein L.S., Adler-Golden S,. M. Sundberg R.L., 2005, Validation of the QUick Atmospheric Correction (QUAC) algorithm for VNIR-SWIR multi-and hyperspectral imagery . “SPIE Proceedings, ATMHUI” XI, Vol. 5806, pp. 668−678. Bernstein L.S., Adler-Golden S.M., Sundberg R.L., Ratkowski A., 2006, Improved reflectance retrieval from hyper- and multispectral imagery without prior scene or sensor information . “SPIE Proceedings, Remote Sensing of Clouds and the Atmosphere” XI, Vol. 6362

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The Remote Sensing Method of Forest Fire Danger Rating Categorization

made by the Polish Minister of Environmental Protection, Natural Resources and Forestry, regarding detailed guidelines for forest fire prevention, Dziennik Ustaw [Daily Regulations Report] no. 73 [entry 824; in Polish]. [5] Polish State Forests, Yearly Report 2002 ( ). [6] Zawiła-Niedźwiecki T., 1999, The use of remote sensing in forest fire protection in Poland, Proceedings of Conference on Remote Sensing and Forest Monitoring , Rogów.

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Error simulations of uncorrected NDVI and DCVI during remote sensing measurements from UAS

, Fundamentals of imaging, remote sensing method for assessing the state of vegetation and verification of its usefulness in environmental studies, Bachelor thesis on University of Warsaw. Chiliński, M 2012, Improvement of Data Acquiring in LNDVI Method and Comparison of it’s Results with Hyperspectral Spectrometer Measurements, Master thesis on University of Warsaw. Chrysoulakis, N, Abrams, M, Feidas, H & Arai, K 2010, ‘Comparison of atmospheric correction methods using ASTER data for the area of Crete, Greece’, International Journal Of Remote

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Application of remote sensing techniques for the identification of biotic stress in plum trees caused by the Plum pox virus

-483. D unez J., S utic D., 1988. Plum pox virus. In: European Handbook of Plant Diseases. I.M. Smith, J. Dunez, R.A. Eliot, D.H. Phillips and S.A. Arches (eds), Blackwell, Oxford, UK: 44-46. K rezhova D., 2011. Spectral remote sensing of the responses of soybean plants to environmental stresses, In: Soybean – Genetics and Novel Techniques for Yield Enhancement, Chapter 11. D. Krezhova (ed), Tech Publisher: 215-256. K rezhova D.D., P etrov N.M., M aneva S.N., 2012. Hyperspectral remote sensing applications for monitoring and stress detection in

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