temporal scales ranging from the individual habitat level to entire landscapes and
involving varying temporal revisit frequencies up to daily observations.
Habitat mapping is developing at a fast rate within the two basic approaches of field
mapping and remote sensing. The latest technologies are quickly incorporated into
habitat monitoring (Lengyel et al. 2008; Turner et al. 2003). Field mapping, for
example, is facilitated by the use of object-oriented methods or wireless sensor
systems (e.g. Polastre et al. 2004; Bock et al. 2005). Additionally, advances in remote
sensing methods have resulted in the widespread production and use of spatial
information on biodiversity (Duro et al. 2007; Papastergiadou et al. 2007; Fo ¨rster
et al. 2008). In fact, earth observation data is becoming more and more accepted as an
appropriate data source to supplement, and in some cases even replace, field-based
surveys in biodiversity science and conservation, as well as in ecology. Objectivity
and transparency in the process of integrity assessments of Natura 2000 sites can be
supported by quantitative methods, if applied cautiously (Lang and Langanke 2005).
However, it should be kept in mind that there are various sources of uncertainty in
remote sensing-based monitoring of vegetation (Rocchini et al. 2013).
Despite all the advantages mentioned above, the monitoring of habitats using fieldbased and remote sensing approaches has a very short history. Landsat-4, the first
non-military optical sensor with the potential to monitor habitats at a suitable spatial
resolution, was initiated only in 1982. Even within this time period the story of image
acquisition and interpretation is not free of interruptions due to sensor faults and a lack
of financial support for continuity missions (Wulder et al. 2011). Recently, the sensor
series RapidEye and the planned mission Sentinel-2, which employ a constellation of
multiple identical satellites, have been supplying data with a higher temporal frequency (Berger et al. 2012). However, this time-span is still not long enough to allow
reliable statements about modifications of habitats dependent on climate change.
This study focuses on the potential of remote sensing to detect indicators related
to climate change in three focus areas. The case studies presented use the Natura
2000 habitat nomenclature and descriptions of the conservation status of the
protected habitats as a basis for their evaluation. For all studies within this chapter,
RapidEye products acquired between 2009 and 2011 were used as basic imagery for
the subsequent investigations due to their frequent availability and suitable spectral
as well as spatial resolution. The acquired images were always used in combination
for a single mapping step. The necessary time-frame for monitoring with repeated
image acquisition (e.g. a 6-year cycle as proposed in the EC Habitats Directive) was
not available within the HABIT-CHANGE project.
Within the general framework described (Natura 2000-related indicators,
RapidEye data from 2009 to 2011), methods for various habitats in three different
biogeographic regions (Continental, Alpine, Pannonian) were applied. The techniques, which are described in the following subchapters, are intended to demonstrate
their potential for indicating likely climate change impacts. In the Vessertal, a
forested area in Germany, the immigration of beech into a spruce dominated region –
a potential effect of climate change – was investigated (Sect. 7.2). In the Lake
Neusiedl area in Austria potential climate-induced changes in Pannonic inland
marshes are shown (Sect. 7.3). In Rieserferner Ahrn, an Alpine region in Italy, the
potential of detecting shrub encroachment – an indicator for climate-related change to
the treeline – was explored (Sect. 7.4).
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M. Fo ¨rster et al.
involving varying temporal revisit frequencies up to daily observations.
Habitat mapping is developing at a fast rate within the two basic approaches of field
mapping and remote sensing. The latest technologies are quickly incorporated into
habitat monitoring (Lengyel et al. 2008; Turner et al. 2003). Field mapping, for
example, is facilitated by the use of object-oriented methods or wireless sensor
systems (e.g. Polastre et al. 2004; Bock et al. 2005). Additionally, advances in remote
sensing methods have resulted in the widespread production and use of spatial
information on biodiversity (Duro et al. 2007; Papastergiadou et al. 2007; Fo ¨rster
et al. 2008). In fact, earth observation data is becoming more and more accepted as an
appropriate data source to supplement, and in some cases even replace, field-based
surveys in biodiversity science and conservation, as well as in ecology. Objectivity
and transparency in the process of integrity assessments of Natura 2000 sites can be
supported by quantitative methods, if applied cautiously (Lang and Langanke 2005).
However, it should be kept in mind that there are various sources of uncertainty in
remote sensing-based monitoring of vegetation (Rocchini et al. 2013).
Despite all the advantages mentioned above, the monitoring of habitats using fieldbased and remote sensing approaches has a very short history. Landsat-4, the first
non-military optical sensor with the potential to monitor habitats at a suitable spatial
resolution, was initiated only in 1982. Even within this time period the story of image
acquisition and interpretation is not free of interruptions due to sensor faults and a lack
of financial support for continuity missions (Wulder et al. 2011). Recently, the sensor
series RapidEye and the planned mission Sentinel-2, which employ a constellation of
multiple identical satellites, have been supplying data with a higher temporal frequency (Berger et al. 2012). However, this time-span is still not long enough to allow
reliable statements about modifications of habitats dependent on climate change.
This study focuses on the potential of remote sensing to detect indicators related
to climate change in three focus areas. The case studies presented use the Natura
2000 habitat nomenclature and descriptions of the conservation status of the
protected habitats as a basis for their evaluation. For all studies within this chapter,
RapidEye products acquired between 2009 and 2011 were used as basic imagery for
the subsequent investigations due to their frequent availability and suitable spectral
as well as spatial resolution. The acquired images were always used in combination
for a single mapping step. The necessary time-frame for monitoring with repeated
image acquisition (e.g. a 6-year cycle as proposed in the EC Habitats Directive) was
not available within the HABIT-CHANGE project.
Within the general framework described (Natura 2000-related indicators,
RapidEye data from 2009 to 2011), methods for various habitats in three different
biogeographic regions (Continental, Alpine, Pannonian) were applied. The techniques, which are described in the following subchapters, are intended to demonstrate
their potential for indicating likely climate change impacts. In the Vessertal, a
forested area in Germany, the immigration of beech into a spruce dominated region –
a potential effect of climate change – was investigated (Sect. 7.2). In the Lake
Neusiedl area in Austria potential climate-induced changes in Pannonic inland
marshes are shown (Sect. 7.3). In Rieserferner Ahrn, an Alpine region in Italy, the
potential of detecting shrub encroachment – an indicator for climate-related change to
the treeline – was explored (Sect. 7.4).
96
M. Fo ¨rster et al.