170
that in the first instance, the variables are usable to detect ecological integrity even
without normalization. Normalizations within specific land-use classes have been
used mainly to validate the variables with respect to their capacity to differentiate
natural from anthropogenic land use types. The relative indexes, including the
resulting RIEI, are suitable for comparison between different regions; their interpretation has to take into consideration the specifics and limitations of the aggregation method.
5 Conclusions
Three variables representing three ecological integrity indicators have been designed
based on open-acess remote sensing data and validated using a land-cover layer
(CLE). Valuable areas from the point of view of nature conservation as well as ecosystem management can be highlighted using the proposed variables, along with
areas of low value and disturbed areas. A method of aggregation is proposed, quantifying the relative distance of a land-use class from a regional maximum and minimum to provide a method of land-use integrity evaluation and quantification. A
composite Regional Index of Ecological Integrity (RIEI) has been designed and
quantified to provide an estimation of the overall regional integrity and it’s distance
from a hypothetical top and bottom state.
Acknowledgements We would especially like to thank our colleagues from the Institute of
Natural Resource Conservation of the University in Kiel, namely Felix Müller, Wilhelm Windhorst
and Claus-G. Schimming for consultation and advices on the methodological aspects and results
interpretation. This study was made possible thanks to financial support from the DBU (Deutsche
Bundesstiftung Umwelt) MOE scholarship, GAUK (Charles University Grant Agency [Grant no.
546517]) and Specific University Research [VS 260471] funding.
References
Andreasen JK, O’Neill RV, Noss R, Slosser NC (2001) Considerations for the development
of a terrestrial index of ecological integrity. Ecol Indic 1:21–35. https://doi.org/10.1016/
S1470-160X(01)00007-3
Capmourteres V, Anand M (2016) Assessing ecological integrity: a multi-scale structural and
functional approach using structural equation modeling. Ecol Indic 71:258–269. https://doi.
org/10.1016/j.ecolind.2016.07.006
Castaldi F, Palombo A, Santini F, Pascucci S, Pignatti S, Casa R (2016) Evaluation of the potential
of the current and forthcoming multispectral and hyperspectral imagers to estimate soil texture
and organic carbon. Remote Sens Environ 179:54–65. https://doi.org/10.1016/j.rse.2016.03.025
Chrysafis I, Mallinis G, Siachalou S, Patias P (2017) Assessing the relationships between growing
stock volume and Sentinel-2 imagery in a Mediterranean forest ecosystem. Remote Sens Lett.
8(6):508–517. https://doi.org/10.1080/2150704X.2017.1295479
J. Zelený and D. Mercado-Bettín
that in the first instance, the variables are usable to detect ecological integrity even
without normalization. Normalizations within specific land-use classes have been
used mainly to validate the variables with respect to their capacity to differentiate
natural from anthropogenic land use types. The relative indexes, including the
resulting RIEI, are suitable for comparison between different regions; their interpretation has to take into consideration the specifics and limitations of the aggregation method.
5 Conclusions
Three variables representing three ecological integrity indicators have been designed
based on open-acess remote sensing data and validated using a land-cover layer
(CLE). Valuable areas from the point of view of nature conservation as well as ecosystem management can be highlighted using the proposed variables, along with
areas of low value and disturbed areas. A method of aggregation is proposed, quantifying the relative distance of a land-use class from a regional maximum and minimum to provide a method of land-use integrity evaluation and quantification. A
composite Regional Index of Ecological Integrity (RIEI) has been designed and
quantified to provide an estimation of the overall regional integrity and it’s distance
from a hypothetical top and bottom state.
Acknowledgements We would especially like to thank our colleagues from the Institute of
Natural Resource Conservation of the University in Kiel, namely Felix Müller, Wilhelm Windhorst
and Claus-G. Schimming for consultation and advices on the methodological aspects and results
interpretation. This study was made possible thanks to financial support from the DBU (Deutsche
Bundesstiftung Umwelt) MOE scholarship, GAUK (Charles University Grant Agency [Grant no.
546517]) and Specific University Research [VS 260471] funding.
References
Andreasen JK, O’Neill RV, Noss R, Slosser NC (2001) Considerations for the development
of a terrestrial index of ecological integrity. Ecol Indic 1:21–35. https://doi.org/10.1016/
S1470-160X(01)00007-3
Capmourteres V, Anand M (2016) Assessing ecological integrity: a multi-scale structural and
functional approach using structural equation modeling. Ecol Indic 71:258–269. https://doi.
org/10.1016/j.ecolind.2016.07.006
Castaldi F, Palombo A, Santini F, Pascucci S, Pignatti S, Casa R (2016) Evaluation of the potential
of the current and forthcoming multispectral and hyperspectral imagers to estimate soil texture
and organic carbon. Remote Sens Environ 179:54–65. https://doi.org/10.1016/j.rse.2016.03.025
Chrysafis I, Mallinis G, Siachalou S, Patias P (2017) Assessing the relationships between growing
stock volume and Sentinel-2 imagery in a Mediterranean forest ecosystem. Remote Sens Lett.
8(6):508–517. https://doi.org/10.1080/2150704X.2017.1295479
J. Zelený and D. Mercado-Bettín