However, the compatibility and transferability of such classification results
depends on a variety of factors, including:
• comparable and high sampling intensity in space (all necessary classes equally
covered) and time (seasonally and/or according to phenological changes of the
habitat types),
• comparable sensors and spectral resolution, similar conditions for input imagery
(acquisition date/frequency, cloud cover etc.),
• comparable mapping scale or spatial precision: the minimum mapping unit (for
vector maps) or the spatial resolution (for raster maps) should be similar,
• comparable mapping accuracy, consisting of thematic accuracy (percentage of
correctly classified habitats), and spatial accuracy (habitat delineation errors),
• compatibility of habitat nomenclatures (habitat classification systems).
Summarising the experiences from the HABIT-CHANGE project, a set of key
points has to be kept in mind when considering remote sensing techniques for
habitat monitoring. In order to fulfil the goal of a focused habitat monitoring
integrating remote sensing technique, a clear vision of the outcome (objective)
has to be defined. A selection of possible questions is compiled in Table 7.4 for
consideration in further studies, for service providers as well as (or together with)
users and practitioners of the mapping or monitoring of results.
Table 7.4 List of key issues to be considered for remote sensing-based habitat monitoring
(Adapted from Fo ¨rster et al. 2010). Note that this list is not exhaustive and can be extended
(e.g. use of additional data or post-processing)
Objective(s)
Which is/are your objective(s)?
Mapping, indicator assessment, monitoring,
change detection, phenology, others
Image data
Which imagery should be acquired?
Multispectral, imaging spectroscopy, very high
spatial resolution data, LiDAR, others
What is the image size or path width?
Spatial coverage (geographic extent of the image)
Which spatial resolution is necessary to fulfil
the objective?
The ground sampling distance (GSD) of an image
What is the number of bands and wavelengths necessary to fulfil the objective?
Specific wavelengths (e.g. short wave infrared,
thermal)
Which frequency of image acquisition is
necessary to fulfil the objective?
Mono vs. multi-temporal images (indicate required
acquisition time(s))
Sampling
What is the sampling strategy?
Selected (non-random selection of representative
plots of predefined classes)
Systematic (e.g. regular grid)
Simple random
Stratified random
Which type of ground-truth data
should be collected?
Plant species releve ´s
Vegetation structure releve ´s
Natura 2000 habitat type
Spectral signature
(continued)
110
M. Fo ¨rster et al.
depends on a variety of factors, including:
• comparable and high sampling intensity in space (all necessary classes equally
covered) and time (seasonally and/or according to phenological changes of the
habitat types),
• comparable sensors and spectral resolution, similar conditions for input imagery
(acquisition date/frequency, cloud cover etc.),
• comparable mapping scale or spatial precision: the minimum mapping unit (for
vector maps) or the spatial resolution (for raster maps) should be similar,
• comparable mapping accuracy, consisting of thematic accuracy (percentage of
correctly classified habitats), and spatial accuracy (habitat delineation errors),
• compatibility of habitat nomenclatures (habitat classification systems).
Summarising the experiences from the HABIT-CHANGE project, a set of key
points has to be kept in mind when considering remote sensing techniques for
habitat monitoring. In order to fulfil the goal of a focused habitat monitoring
integrating remote sensing technique, a clear vision of the outcome (objective)
has to be defined. A selection of possible questions is compiled in Table 7.4 for
consideration in further studies, for service providers as well as (or together with)
users and practitioners of the mapping or monitoring of results.
Table 7.4 List of key issues to be considered for remote sensing-based habitat monitoring
(Adapted from Fo ¨rster et al. 2010). Note that this list is not exhaustive and can be extended
(e.g. use of additional data or post-processing)
Objective(s)
Which is/are your objective(s)?
Mapping, indicator assessment, monitoring,
change detection, phenology, others
Image data
Which imagery should be acquired?
Multispectral, imaging spectroscopy, very high
spatial resolution data, LiDAR, others
What is the image size or path width?
Spatial coverage (geographic extent of the image)
Which spatial resolution is necessary to fulfil
the objective?
The ground sampling distance (GSD) of an image
What is the number of bands and wavelengths necessary to fulfil the objective?
Specific wavelengths (e.g. short wave infrared,
thermal)
Which frequency of image acquisition is
necessary to fulfil the objective?
Mono vs. multi-temporal images (indicate required
acquisition time(s))
Sampling
What is the sampling strategy?
Selected (non-random selection of representative
plots of predefined classes)
Systematic (e.g. regular grid)
Simple random
Stratified random
Which type of ground-truth data
should be collected?
Plant species releve ´s
Vegetation structure releve ´s
Natura 2000 habitat type
Spectral signature
(continued)
110
M. Fo ¨rster et al.