Since Spanish colonial times, the Canary Islands and especially Tenerife have always been used for intensive agriculture.
Today almost 1/4 of the total area of Tenerife are agriculturally affected, whereas especially mountainous areas with
suitable climate conditions are drastically transformed for agricultural use by building of large terraces. In recent years,
political and economical developments lead to a further transformation process, especially inducted by an expansive
tourism, which caused concentration- and intensification-tendencies of agricultural land use in lower altitudes as well as
agricultural set-aside and rural exodus in the hinterland. The overall aim of the research at hand is to address the
agricultural land use dynamics of the past decades, to statistically assess the causal reasons for those changes and to
model the future agricultural land use dynamics on Tenerife. Therefore, an object-based classification procedure for
recent RapidEye data (2010), Spot 4 (1998) as well as SPOT 1 (1986-88) imagery was developed, followed by a post
classification comparison (PCC). Older agricultural fallow land or agricultural set-aside with a higher level of natural
succession can hardly be acquired in the used medium satellite imagery. Hence, a second detection technique was
generated, which allows an exact identification of the total agriculturally affected area on Tenerife, also containing older
agricultural fallow land or agricultural set-aside. The method consists of an automatic texture-oriented detection and
area-wide extraction of linear agricultural structures (plough furrows and field boundaries of arable land, utilised and
non-utilised agricultural terraces) in current orthophotos of Tenerife. Once the change detection analysis is realised, it is
necessary to identify the different driving forces which are responsible for the agricultural land use dynamics. The
statistical connections between agricultural land use changes and these driving forces are identified by the use of
correlation and regression analyses.
The island Tenerife has always been used for intensive agriculture, whereby the natural landscape was continuously
altered. Especially mountainous areas with suitable climate conditions have been drastically transformed for agricultural
use by building of large terraces to get flat surfaces. In recent decades political and economic developments lead to a
transformation process (especially inducted by an expansive tourism), which caused concentration- and intensificationtendencies
of agricultural land use as well as agricultural set-aside and rural exodus.
In order to get information about the land use and land cover (LULC) patterns and especially the agricultural dynamics
on Tenerife, a multi-scale, knowledge-based classification procedure for recent RapidEye data was developed.
Furthermore, a second detection technique was generated, which allows an exact identification of the total ever utilised
agricultural area on Tenerife, also containing older agricultural fallow land or agricultural set-aside with a higher level of
natural succession (under the assumption that long-term fallow areas can be detected mainly together with old agricultural
terraces and its specific linear texture). These areas can hardly be acquired in the used satellite imagery. The method
consists of an automatic texture-oriented detection and area-wide extraction of linear agricultural structures (plough
furrows and field boundaries of arable land, utilised and non-utilised agricultural terraces) in current orthophotos of
Tenerife. Through the detection of recent agricultural land use in the satellite imagery and total ever utilised agricultural
area in the orthophotos, it is possible to define the total non-active agricultural land as well as hot spots of agricultural
decrease.
The island Tenerife is a popular destination for tourists, especially from European countries. From the middle
of the 1970s, the mass tourism increased from about 1.3 million to 6 million tourists nowadays (2008).1 This
development lead not only to an increasing expansion of infrastructure but also to a spatial concentration of
settlements.2 Moreover, the Canary Islands and especially Tenerife are a hotspot of climate change with possible
reorientation of atmospheric circulation. The presented research project follows the question how sensitive
ecosystems (e.g. laurel forest or pinewood) on Tenerife will be affected by, on the one hand, global impacts
of climate change and on the other hand by local socioeconomic effects in future. For this purpose existing
time series of land cover and land use change, derived from medium spatial scaled remotely sensed data, will be
upgraded with regard to the spatial and temporal resolution. Therefore an object-based classification of high
spatial scaled satellite scenes has to be done followed by a change detection analysis. Taking into account the
different local and global driving forces for these changes the spatial future development of the most important
land use processes like e.g. increase of agricultural land (monocultures) and fallow land will then be simulated
and visualised. Based on these results the impacts for different sensitive ecosystems can finally be analysed and
valuated.
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