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

• Authors: Michał T. Chiliński , Marek Ostrowski

Abstracts

EN

Remote sensing from unmanned aerial systems (UAS) has been gaining popularity in the last few years. In the field of vegetation mapping, digital cameras converted to calculate vegetation index (DCVI) are one of the most popular sensors. This paper presents simulations using a radiative transfer model (libRadtran) of DCVI and NDVI results in an environment of possible UAS flight scenarios. The analysis of the results is focused on the comparison of atmosphere influence on both indices. The results revealed uncertainties in uncorrected DCVI measurements up to 25% at the altitude of 5 km, 5% at 1 km and around 1% at 0.15 km, which suggests that DCVI can be widely used on small UAS operating below 0.2 km.

Keywords

EN

Remote sensing; vegetation index; digital camera; UAS; atmospheric correction

• Publisher: Wydział Geografii i Studiów Regionalnych Uniwersytetu Warszawskiego
• Journal: Miscellanea Geographica. Regional Studies on Development
• Year: 2014
• Volume: 18
• Issue: 2
• Pages: 35-45

Dates

published

2014

Contributors

author

Michał T. Chiliński

• Department of Geoinformation and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Institute of Geophysics University of Warsaw

author

Marek Ostrowski

• Laboratory of Image-based Information and Modelling, Faculty of Biology, University of Warsaw

References

• Anderson, G, Clough, S, Kneizys, F, Chetwynd, J & Shettle, E 1986, ‘AFGL atmospheric constituent profiles (0-120 km)’, Tech. Rep. AFGL-TR-86-0110, Air Force Geophys. Lab., Hanscom Air Force Base, Bedford, Mass.
• Burgheimer, J, Wilske, B, Maseyk, K, Karnieli, A, Zaady, E, Yakir, D & Kesselmeier, J 2006, ‘Relationships between Normalized Difference Vegetation Index (NDVI) and carbon fluxes of biologic soil crusts assessed by ground measurements’, J. Arid Environ, vol. 64, pp. 651-669.
• Chiliński, M 2010, 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 Sensing, vol. 31, no. 24, pp. 6347-6385.
• Fischer, T, Veste, M, Eisele, A, Bens, O, Spyra, W & Hüttl, RF 2012, ‘Small scale spatial heterogeneity of Normalized Difference Vegetation Indices (NDVIs) and hot spots of photosynthesis in biological soil crusts’, Flora, vol. 207, pp. 159-167.[WoS]
• Hardin, PJ & Hardin, TJ 2010, ‘Small-scale remotely piloted vehicles in environmental research’, Geography Compass, vol. 4, pp. 1297-1311.
• Hess, M, Koepke, P & Schult, I 1998, ‘Optical Properties of Aerosols and Clouds: The Software Package OPAC’, Bulletin of the American Meteorological Society, vol. 79, pp. 831-844. The HITRAN Database 2012. Available from: <http://www.cfa. harvard.edu/hitran/>. [11 October 2013].
• Holben, BN, Eck, TF, Slutsker, I, Tanré, D, Buis, JP, Setzer, A, Vermote, E, Reagan, JA, Kaufman, YJ, Nakajima, T, Lavenu, F, Jankowiak, I & Smirnov, A 1998, ‘AERONET A federated instrument network and data archive for aerosol characterization’, Remote Sensing of Environment, vol. 66, pp. 1-16.
• Hunt, ER, Cavigelli, M, Daughtry, CST, McMurtrey, JE & Walthall, CL 2005, ‘Evaluation of digital photography from model aircraft for remote sensing of crop biomass and nitrogen status’, Precision Agriculture, vol. 6, pp. 359-37.
• Ichii, K, Matsui, Y, Yamaguchi, Y & Ogawa, K 2001, ‘Comparison of global net primary production trends obtained from satellite based normalized difference vegetation index and carbon cycle model’, Global Biogeochem, Cycles, vol. 15, pp. 351-364.
• Kylling, A & Stamnes, K 1992, ‘Effcient yet accurate solution of the linear transport equation in the presence of internal sources: the exponential-linear-in-depth approximation’, J. Com. Phys., vol. 102, pp. 265-276.
• Lelong, CCD, Burger, P, Jubelin, G, Roux, B, Labbe, S & Barett, F 2008, ‘Assessment of unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots’, Sensors, vol. 8, pp. 3557-3585. libRatran, 2013. Available from: < http://www.libradtran.org>.[WoS]
• Markowicz, KM, Zielinski, T, Blindheim, D, Gausa, M, Jagodnicka, AK, Kardas, A, Kumala, W, Malinowski, SP, Posyniak, M, Petelski, T & Stacewicz, T 2012, ‘Study of vertical structure of aerosol optical properties by sun photometers and ceilometer during macron campaign in 2007’, Acta Geophys., vol. 60, no. 5, pp. 1308-1337.[WoS]
• Myneni, RB, Keeling, CD, Tucker, CJ, Asrar, G & Nemani, RR 1997, ‘Increased plant growth in the northern high latitudes from 1981 to 1991’, Nature, vol. 386, pp. 698-702.
• Nebiker, S, Annen, A, Scherrer, M & Oesch, D 2008, ‘A lightweight multispectral sensor for micro UAV. Opportunities for very high resolution airborne remote sensing. The International Archives of the Photogrammetry’, Remote Sensing and Spatial Information Sciences, vol. XXXVII Part B1, pp. 1193-120.
• Rango, A, Laliberte, AS, Herrick, JE, Winters, C, Havstad, K, Steele, C & Browning, D 2009, ‘Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management’, Journal of Applied Remote Sensing, vol. 3.
• Rouse, J, Haas, R, Well, J & Deering, D 1973, ‘Monitoring vegetation systems in the great plains with erts’, In Third Earth Resources Technology Satellite-1 Symposium, vol. I, Technical Presentations Section A, pp. 309-317.
• Running, SW 1990, ‘Estimating terrestrial primary productivity by combining remote sensing and ecosystem simulation’, Remote Sensing of Biosphere Functioning. Ecol. Stud., vol. 79, pp. 65-86.
• Stamnes, K, S-Chee, T, Wiscombe, W & Kolf, J 1988, ‘Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media’, Applied Optics, vol. 27, pp. 2502-2509.
• Tucker, CJ, Fung, IY, Keeling, CD & Gammon, RH 1986, ‘Relationship between atmospheric CO2 variations and a satellite-derived vegetation index’, Nature, vol. 319, pp. 195-199.
• Xiang, H & Tian, L 2011, ‘Method for automatic georeferencing aerial remote sensing (RS) images from an unmanned aerial vehicle (UAV) platform’, Biosystems Engineering, vol. 108, pp. 104-111.[WoS]
• Wanner, W, Strahler, A, Hu, B, Lewis, P, Muller, JP, Li, X, Barker Schaaf, C & Barnsley, M 1997, ‘Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data. Theory and algorithm’, J. Geophys. Res., vol. 102, pp. 17143-17161.
• Zawadzka, O, Markowicz, KM, Pietruczuk, A, Zielinski, T & Jarosławski, J 2013, ‘Impact of urban pollution emitted in Warsaw on aerosol properties’, Atmospheric Environment, vol. 69, pp. 1528.[WoS]
• Zhang, C & Kovacs, J 2012, ‘The application of small unmanned aerial systems for precision agriculture: a review’, Precision Agriculture, vol. 13, pp. 693-712.

Identifiers

Biblioteka Nauki

2037392