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2016 | 20 | 1 |

Article title

The application of APEX images in the assessment of the state of non-forest vegetation in the Karkonosze Mountains

Content

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Abstracts

EN
Information about vegetation condition is needed for the effective management of natural resources and the estimation of the effectiveness of nature conservation. The aim of the study was to analyse the condition of non-forest mountain communities: synanthropic communities and natural grasslands. UNESCO’s M&B Karkonosze Transboundary Biosphere Reserve was selected as the research area. The analysis was based on 40 field test polygons and APEX hyperspectral images. The field measurements allowed the collection of biophysical parameters - Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and chlorophyll content - which were correlated with vegetation indices calculated using the APEX images. Correlations were observed between the vegetation indices (general condition, plant structure) and total area of leaves (LAI), as well as fraction of Absorbed Photosynthetically Active Radiation (fAPAR). The outcomes show that the non-forest communities in the Karkonosze are in good condition, with the synanthropic communities characterised by better condition compared to the natural communities.

Contributors

  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
  • University of Warsaw, College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, Poland
  • Department of Geoinformatics, Cartography and Remote Sensing, Faculty of Geography and Regional Studies, University of Warsaw, Poland
author
  • VITO – Centre for Remote Sensing and Earth Observation Processes, Belgium

References

  • Cho, MA & Skidmore, AK 2009, ‘Hyperspectral predictors for monitoring biomass production in Mediterranean mountain grasslands: Majella National Park, Italy’, International Journal of Remote Sensing, vol. 30(2), pp. 499-515.[WoS]
  • Darvishzadeh, R, Atzberger, C & Skidmore, AK 2006, ‘Hyperspectral vegetation indices for estimation of leaf area index’, ISPRS Commission VII Mid-term Symposium, Enschede, the Netherlands, pp. 391-396. Available from: Purdue University: <ftp://ftp.ecn.purdue.edu/jshan/proceedings/ISPRS_Comm7_2006/PDF%20FIles/233%20Darvishzadeh/isprs2006-darvish.pdf>. [5 August 2015].
  • di Bella, CM, Paruelos, JM, Becerra, JE, Bacour, C & Baret, F 2004, ‘Effect of senescent leaves on NDVI-based estimates of fAPAR: experimental and modelling evidences’, International Journal of Remote Sensing, vol. 25, no. 23, pp. 5415-5427.
  • Fourty, T, Baret, F, Jacquemoud, S, Schmuck, G & Verdebout, J 1996, ‘Leaf Optical Properties with Explicit Description of Its Biochemical Composition: Direct and Inverse Problems’, Remote Sensing of Environment, vol. 56, pp. 104-117.[Crossref]
  • Gamon, J, Penuelas, J & Field, C 1992, ‘A Narrow-Waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efficiency’, Remote Sensing of Environment, vol. 41, pp. 35-44.[Crossref]
  • He, Y, Guo, X & Wilmshurst, J 2006, ‘Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices’, Journal of Remote Sensing, vol. 23, no. 2, pp. 98-107.
  • Hsu, CW, Chang, CC & Lin, CJ 2010, A practical guide to support vector classification. National Taiwan University. Taiwan. Available from: http://ntu.csie.org/~cjlin/papers/guide/guide.pdf. [5 August 2015].
  • Hunt, ER & Rock, BN 1989, ‘Detection of changes in leaf water content using near- and middle-infrared reflectances’, Remote Sensing of Environment, vol. 30, pp. 43-54.[Crossref]
  • Jarocińska, A, 2014. Radiative Transfer Model parametrization for simulating the reflectance of meadow vegetation. Miscellanea Geographica, 18(2): 5-9.
  • Jarocińska, A & Zagajewski, B 2008, ‘Korelacje naziemnych i lotniczych teledetekcyjnych wskaźników roślinności dla zlewni Bystrzanki’, Teledetekcja Środowiska, vol. 40, pp. 100-125.
  • Jarocińska, A, Zagajewski, B, Ochtyra, A, Marcinkowska, A & Kupkova, L 2014a, ‘PROSAIL model for reflectance simulations of mountainous non-forest communities’, EARSeL eProceedings, vol. 13, no. 1, pp. 18-23.
  • Jarocińska, A, Zagajewski, B, Ochtyra, A, Marcinkowska- Ochtyra, A, Kycko, M & Pabjanek, P 2014b, ‘Przebieg klęski ekologicznej w Karkonoszach i Górach Izerskich na podstawie analizy zdjęć satelitarnych Landsat’, Wydawnictwo pokonferencyjne - konferencja naukowa z okazji 55-lecia Karkonoskiego Parku Narodowego „25 lat po klęsce ekologicznej w Karkonoszach i Górach Izerskich - obawy a rzeczywistość”, pp. 47-61.
  • Jelének, J, Kupková, L, Zagajewski, B, Březina, S, Ochtyra, A & Marcinkowska, A 2014, ‘Laboratory and image spectroscopy for evaluating the biophysical state of meadow vegetation in the Krkonoše National Park’, Miscellanea Geographica - Regional Studies on Development, vol. 18, no. 2, pp. 15-22.
  • Jensen, JR 1983, ‘Biophysical Remote sensing - Review Article’, Annals of the Associations of American Geographers, vol. 73(1), pp. 111-132.
  • Kycko, M, Zagajewski, B & Kozłowska, A 2014, ‘Variability in spectral characteristics of trampled high-mountain grasslands’, Miscellanea Geographica - Regional Studies on Development, vol. 18, no. 2, pp. 10-14.
  • Marcinkowska, A, Zagajewski, B, Ochtyra, A, Jarocińska, E, Raczko, E, Kupková, L, Stych, P & Meuleman, K 2014, ‘Mapping vegetation communities of the Karkonosze National Park using APEX hyperspectral data and Support Vector Machines’, Miscellanea Geographica - Regional Studies on Development, vol. 18, no. 2, pp. 23-29.
  • Myneni, RB & Williams, DL 1994, ‘On the relationship between FAPAR and NDVI’, Remote Sensing of Environment, vol. 49, pp. 200-211.[Crossref]
  • Peñuelas, J, Filella, I, Biel, C, Serrano, L & Save, R 1995, ‘The reflectance at the 950-970 region as an indicator of plant water status’, International Journal of Remote Sensing, vol. 14, pp. 1887-1905.
  • Rapp, M, Schweiger, A & Haller, R 2013, ‘Biomass-mapping of alpine grassland with APEX imaging spectrometry data, Mittersill’, Conference Volume of 5th Symposium for Research in Protected Areas, pp. 631-637. Available from: <http://www.zobodat.at/pdf/NP-Hohe-Tauern-Conference_ 5_0631-0637.pdf>. [5 August 2015].
  • Sims, DA & Gamon, JA 2002, ‘Relationships between leaf pigment content and spectral reflectance cross a wide range of species, leaf structures and developmental stages’, Remote Sensing of Environment, vol. 81, pp. 337-354.[Crossref]
  • Ustin, SL, Roberts, DA, Gamon, JA, Asner, GP, Green, RO 2004, ‘Using Imaging Spectroscopy to Study Ecosystem Processes and Properties’, Bioscience, vol. 54 (6), pp. 523-533.
  • Żołnierz, L & Wojtuń, B 2013, ‘Roślinność subalpejska i alpejska’ in Przyroda Karkonoskiego Parku Narodowego eds R Knapik & A Raj, Karkonoski Park Narodowy, Jelenia Góra, pp. 241-278.
  • Żołnierz, L, Wojtuń, B & Przewoźnik, L 2012, Ekosystemy nieleśne Karkonoskiego Parku Narodowego, Karkonoski Park Narodowy, Jelenia Góra, pp. 100.

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
2096269

YADDA identifier

bwmeta1.element.ojs-doi-10_1515_mgrsd-2016-0009
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