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Detecting and evaluating land cover change in the eastern half of East Timor (1972-2011)
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Resumo(s)
Land use / land cover (LULC) change detection based on remote sensing (RS) data
is an important source of information for various decision support systems. In East
Timor where forest plays a key role in sustaining communities’ livelihoods the
information derived from LULC change detection is invaluable to the conservation,
sustainable development and management of forest resources.
To assess the patterns of land cover change, as a result of complex socio-economic
factors, satellite imagery and image processing techniques can be useful. This study
is concerned with identifying change in land use and land cover types in East Timor
between 1972 and 2011, using satellite images from Landsat MSS, TM and ETM+
sensors. Seven major cover types were identified in this study including forest,
mixed rangeland, grassland, farmland, built-up areas, bare soil and water. A
combination of NDVI differencing, supervised and unsupervised classification was
used to derive final classification maps. Due to the lack of ground truth data, further
processing were performed to improve the final classification maps by applying
rationality change test.
Post-classification comparison change detection technique was used to assess
categorical changes between 1972 and 2011. The results highlight a significant
level of deforestation due to uncontrolled illegal logging and increase in farmland,
built-up areas, as well as bare soil. This decline has had considerable impact on the
livelihoods of rural communities. As the new nation of Timor-Leste establishes
itself, it must consider its current stock and distribution of natural resources to
ensure that development efforts are geared towards sustainable outcomes. Without
this information historical patterns of resource consumption, development efforts
may, unwittingly, lead to continuing decline in forest resources.
Descrição
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Palavras-chave
Change Detection Change Rationality Test Landsat Land Use Land Cover NDVI Differencing