<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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&amp;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.</p></abstract>

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.

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

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

VITO – Centre for Remote Sensing and Earth Observation Processes, Belgium

Miscellanea Geographica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Information about vegetation condition is needed for the effective management of natural resources and the estimation of the effectiveness of nature...

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

Online veröffentlicht: 20. Apr. 2016

Seitenbereich: 21 - 27

Eingereicht: 20. Juli 2015

Akzeptiert: 10. Feb. 2016

DOI: https://doi.org/10.1515/mgrsd-2016-0009

Schlüsselwörter
Mountain meadows, vegetation condition, APEX, hyperspectal remote sensing, vegetation indices, biophysical parameters

© by Anna M. Jarocińska

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Online veröffentlicht: 20. Apr. 2016

Seitenbereich: 21 - 27

Eingereicht: 20. Juli 2015

Akzeptiert: 10. Feb. 2016

DOI: https://doi.org/10.1515/mgrsd-2016-0009

SchlüsselwörterMountain meadows, vegetation condition, APEX, hyperspectal remote sensing, vegetation indices, biophysical parameters

© by Anna M. Jarocińska

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Mountain meadows, vegetation condition, APEX, hyperspectal remote sensing, vegetation indices, biophysical parameters