| Abstract: |
A landscape is a large enough contiguous area which is dynamics in space (x, y, z) and in
time (t). Landscape as a unit analysis is defined not independently from the objectives of a study. In assessing a landscape, one needs to cover the continuity over the landscape to understand the landscape configuration and landscape transformation processes. Four main functionalities of SALA are to assess and quantify: (A) the flow
and relationships among elements of the landscape represent landscape transformation processes, (B) the landscape spatial dynamics, i.e., the variation, pattern and composition within the landscape, (C) the landscape temporal dynamics, i.e., the changes in the landscape from time to time, and (D) the spatial autocorrelation (i.e., correlation between nearby areas) due to spatially auto-correlated processes and
characteristics.
Remotely sensed data are used to evaluate land cover
based on the appearance of land surface in one particular time. Specifically designed sensors can generate data that are used to derive elevation maps, hot spots, wind direction etc. The scope of SALA embraces land use/cover change and trajectories
(ALUCT) and spatial planning for sustainable development (I3SPA). Basically for the environmental services for sustainable development application, remotely sensed data are the sources of time-series land cover maps, of which environmental services in the forms of watershed protection, biodiversity maintenance and climate change mitigation are strongly related with. A set of base maps that is aligned with the remotely sensed
data is necessary as additional data to interpret the remotely sensed data, to quantify temporal changes in the same location, and to combine the land cover maps with other factors to quantify and qualify environmental services and livelihood provision. For more specific application, further modeling and analysis are often necessary. SALA produces the main data input for other TULSEA series, i.e., RaBA, RaTA, RaCSA, RHA,
DriLUC. |
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