Multispectral aerial monitoring of a patchy vegetation oasis composed of different vegetation classes. UAV-based study exploiting spectral reflectance indices

Vol.12,No.1(2022)

Abstract
The study brings data on monitoring of spectral refectance signatures of different components of Antarctic terrestrial vegetation by using a high-resolution multispectral images. The aim of the study was to compare several spots of a vegetation oasis by mapping vegetation cover using an UAV approach. This study provides data on vegetation distribution within a long-term research plot (LTRP) located at the northern coast of James Ross Island (Antarctica). Apart from normalized difference vegetation index (NDVI), 10 spectral reflectance indices (NDVI, NDVIRed-edge, RGBVI, NGRDI, ExG, TGI MSR, MSRRed-edge, Clgreen, ClRed-edge, GLI) were evaluated for different spots representing vegetation classes dominated by different Antarctic autotrophs. The UAV application and spectral reflectance indices proved their capability to detect and map small-area vegetated patches (with the smallest area of 10 cm2) dominated by different Antarctic autotrophs, and identify their classes (moss / lichens / biological soil crusts / microbiological mats / stream bottom microbiological mats). The methods used in our study revealed sufficiently high resolution of particular vegetation-covered surfaces and the spectral indices provided important indicators for environmental characteristics of the long-term research plot at the James Ross Island, Antarctica.

Keywords:
remote sensing; UAV; James Ross Island; vegetation mapping; spectral reflectance; functional substrate types
References

Barták, M., Hájek, J., Morkusová, J., Skácelová, K. and Košuthová, A. (2018): Dehydration-induced changes in spectral reflectance indices and chlorophyll fluorescence of Antarctic lichens with different thallus color, and intrathalline photobiont. Acta Physiologiae Plantrum, 40: 177. doi: 10.1007/s11738-018-2751-3

Barták, M., Váczi, P., Stachoň, Z. and Kubešová, S. (2015): Vegetation mapping of moss-dominated areas of northern part of James Ross Island (Antarctica) and a suggestion of protective measures. Czech Polar Reports, 5: 75-87.

Beamish, A., Raynolds, M. K., Epstein, H., Frost, G. V., Macander, M. J., Bergstedt, H., Bartsch, A., Kruse, S., Miles, V., Tanis, C. M., Heim, B., Fuchs, M., Chabrillat, S., Shevtsova, I., Verdonen, M. and Wagner, J. (2020): Recent trends and remaining challenges for optical remote sensing of Arctic tundra vegetation: A review and outlook. Remote Sensing of Environment, 246: 111872.

Bendig, J., Yu, K., Aasen, H., Bolten, A., Bennertz, S., Broscheit, J., Gnyp, M. L. and Bareth, G. (2015): Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley. International Journal of Applied Earth Observation and Geoinformation, 39: 79-87.

Calviño-Cancela, M., Martín-Herrero, J. (2016): Spectral discrimination of vegetation classes in ice-free areas of Antarctica. Remote Sensing, 8: 856. doi: 10.3390/rs8100856

Chen, J. M. (1996): Evaluation of vegetation indices and a modified simple ratio for boreal applications. Canadian Journal of Remote Sensing, 22: 229-242. doi: 10.1080/07038992.1996. 10855178

Chi, J., Lee, H., Hong, S.G. and Kim, H.-C. (2021): Spectral characteristics of the Antarctic vegetation: A case study of Barton Peninsula. Remote Sensing, 13(13): 2470. doi: 10.3390/ rs13132470

da Rosa, C., Pereira Filho, W., Bremer, U., Andrade, A., Kramer, G., Hillebrand, F. and Jesus, J. (2021): The limnology and spectral behaviour of a freshwater lake at Harmony Point, Nelson Island, Antarctica. Antarctic Science, 33(5): 479-492. doi:10.1017/S0954102021000304

da Rosa, C. N., Pereira Filho, W., Bremer, U. F., Putzke, J., de Andrade, A. M., Kramer, G., Hillebrand, F. and de Jesus, J. B. (2022): Spectral behavior of vegetation in Harmony Point, Nelson Island, Antarctica. Biodiversity and Conservation, 31(7): 1-19. doi: 10.1007/s10531-022-02408-7.

Eischeid, I., Soininen, E. M., Assmann, J. J., Ims, R.A., Madsen, J., Pedersen, Å. Ø., Pirotti, F., Yoccoz, N. G. and Ravolainen, V. T. (2021): Disturbance mapping in Arctic tundra improved by a planning workflow for drone studies: Advancing tools for future ecosystem monitoring. Remote Sensing, 13(21): 4466. doi: 10.3390/rs13214466

Fonseca, E. L., Santos, E., Figueiredo, A. R. and Simões, J. C. (2022): Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images. Anais da Academia Brasileira de Ciencias [Annals of the Brazilian Academy of Sciences], 94(suppl 1): e20210596. doi: 10.1590/0001-3765202220210596

Fraser, R.H., Olthof, I., Lantz, T.C. and Schitt, C. (2016): UAV photogrammetry for mapping vegetation in the low-Arctic. Arctic Science, 2(3): 79-102. doi: 10.1139/as-2016-0008.

Gatzouras, M. (2015): Assessment of trampling impact in Icelandic natural areas in experimental plots with focus on image analysis of digital photographs. Thesis, No. 351, Department of Physical Geography and Ecosystem Science, Lund University, Sweden, 45 p.

Gitelson, A. A., Gritz, Y. and Merzlyak, M. N. (2003): Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology, 160: 271-282.

Gitelson, A. A., Viña, A., Ciganda, V., Rundquist, D. C. and Arkebauer, T. J. (2005): Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters, 32(8): 1-4. doi: 10.1029/2005GL022688

Gitelson, A., Merzlyak, M. N. (1994): Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation. Journal of Plant Physiology, 143: 286-292. doi: 10.1016/S0176-1617(11)81633-0

Gray, A., Krolikowski, M., Fretwell, P., Convey, P., Peck, L. S., Mendelova, M., Smith, A. G. and Davey, M. P. (2020): Remote sensing reveals Antarctic green snow algae as important terrestrial carbon sink. Nature Communications, 11: 2527.

Hunt, E. R., Doraiswamy, P. C., McMurtrey, J. E., Daughtry, C. S., Perry, E. M. and Akhmedov, B. (2013): A visible band index for remote sensing leaf chlorophyll content at the canopy scale. International Journal of Applied Earth Observation and Geoinformation, 21: 103-112. doi: 10.1016/j.jag.2012.07.020

Jawak, S. D., Luis, A. J., Fretwell, P. T., Convey, P. and Durairajan, U. A. (2019): Semiautomated detection and mapping of vegetation distribution in the Antarctic environment using spatial-spectral characteristics of WorldView-2 Imagery. Remote Sensing, 11(16): 1909. doi: 10.3390/rs11161909

Komárek, J. (2013): Phenotypic and ecological diversity of freshwater coccoid cyanobacteria from maritime Antarctica and islands of NW Weddell Sea. I. Synechococcales. Czech Polar Reports, 3(2): 130-143.

Komárek, J., Genuário, D. B., Fiore, M. F. and Elster, J. (2015): Heterocytous cyanobacteria of the Ulu Peninsula, James Ross Island, Antarctica. Polar Biology, 38: 475-492. doi: 10.1007/s00300-014-1609-4.

Kopalová, K., Nedbalová, L., Nývlt, D., Elster, J. and Van de Vijver, B. (2013): Diversity, ecology and biogeography of the freshwater diatom communities from Ulu Peninsula (James Ross Island, NE Antarctic Peninsula). Polar Biology, 36: 933-948. doi: 10.1007/s00300-013-1317-5

Lee, G., Hwang, J. and Cho, S. (2021): A novel index to detect vegetation in urban areas using uav-based multispectral images. Applied Science, 11: 3472. doi: 10.3390/app11083472

Levy, J., Cary, S., Joy, K. and Lee, C. (2020): Detection and community-level identification of microbial mats in the McMurdo Dry Valleys using drone-based hyperspectral reflectance imaging. Antarctic Science, 32(5): 367-381. doi:10.1017/S0954102020000243

Louhaichi, M., Borman, M. M. and Johnson, D. E. (2001): Spatially located platform and aerial photography for documentation of grazing impacts on wheat. Geocarto International, 16: 65-70

Lucieer, A., Robinson, S., Turner, D., Harwin, S. and Kelcey, J. (2012): Using a micro-UAV for ultra-high resolution multi-sensor observations of Antarctic moss beds. 15th Australasian Remote Sensing & Photogrammetry, Conference. Alice Springs. 14-16th Sept 2010. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XXXIX-B1, pp. 429–433. doi: 10.5194/isprsarchives-XXXIX-B1-429-2012.

Lucieer, A., Turner, D., King, D. and Robinson, S. (2014): Using an Unmanned Aerial Vehicle (UAV) to capture micro-topography of Antarctic moss beds. International Journal of Applied Earth Observation and Geoinformation, 27: 53-62. doi: 10.1016/j.jag.2013.05.011

Miranda, V., Pina, P., Heleno, S., Vieira, G., Mora, C. and Schaefer, C.E.G.R. (2020): Monitoring recent changes of vegetation in Fildes Peninsula (King George Island, Antarctica) through satellite imagery guided by UAV surveys. Science of The Total Environment, 704: 135295.

Pina, P., Vieira, G. (2022): UAVs for science in Antarctica. Remote Sensing, 14(7):1610. doi: 10.3390/rs14071610

Puhovkin, A., Barták, M., Shepeta, Y., Dzhulai, A., Kazantsev, T. and Parnikoza, I. (2022, subm.): Impact of environmental factors on the moss banks interannual development and their spectral/vitality parameters in the Galindez Island (Argentine Islands, West Antarctica). Polar Science

Rouse, J. W., J., Haas, R. H., Schell, J. A. and Deering, D. W. (1974): Monitoring vegetation systems in the Great Plains with ERTS. In: NASA. Goddard Space Flight Center 3d ERTS-1 Symp., Vol. 1, Sect. A. pp. 309–317.

Salvatore, M. R., Borges, S. R., Barrett, J. E., Sokol, E. R., Stanish, L. F., Power, S. N. and Morin, P. (2020): Remote characterization of photosynthetic communities in the Fryxell basin of Taylor Valley, Antarctica. Antarctic Science, 32: 255-270.

Siewert, M. B, Olofsson, J. (2020): Scale-dependency of Arctic ecosystem properties revealed by UAV. Environmental Research Letters, 15: 129601

Skácelová, K., Barták, M., Coufalík, P., Nývlt, D. and Trnková, K. (2013): Biodiversity of freshwater algae and cyanobacteria on deglaciated northern part of James Ross Island, Antarctica. A preliminary study. Czech Polar Reports, 3: 93-106.

Sotille, M. E., Bremer, U. F., Vieira, G., Velho, L. F., Petsch, C., Auger, J. D. and Simões, J. C. (2022): UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest. Ecological Informatics, 71: 101768. doi: 10.1016/j.ecoinf.2022.101768

Tucker, C. J. (1979): Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8: 127-150.

Turner, D., Lucieer, A., Malenovský, Z., King, D. and Robinson, S. (2014): Spatial co-registration of ultra-high resolution visible, multispectral and thermal images acquired with a micro-UAV over Antarctic moss beds. Remote Sensing, 6(5): 4003-4024. doi: 10.3390/ rs6054003

Turner, D., Lucieer, A., Malenovský, Z., King, D. and Robinson, S.A. (2018): Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling. International Journal of Applied Earth Observation and Geoinformation, 68: 168-179.

Váczi. P., Barták, M., Bednaříková, M., Hrbáček, F. and Hájek, J. (2020): Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts. Czech Polar Reports, 10(2): 297-312.

Woebbecke, D. M., Meyer, G. E., Von Bargen, K. and Mortensen, D. A. (1995): Color indices for weed identification under various soil, residue, and lighting conditions. Transactions of the ASAE, 38: 259-269.

Wu, C., Niu, Z., Tang, Q. and Huang, W. (2008): Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation. Agric For Meteorol, 148: 1230-1241. doi: 10.1016/J.AGRFORMET.2008.03.005

Web sources / Other sources

Korea Polar Data Center (https://kpdc.kopri.re.kr)

Metrics

web of science logo


302

Views

249

PDF views