An improved semiautomatic segmentation approach to land cover mapping for identification of land cover change and trend|
Shubho, M. T. H.; Islam, S. R.; Ayon, B. D. & Islam, I.
Worldwide, land cover change is monitored by
conventional land cover mapping techniques using satellite
imagery. Index method ends with assigning positive values
to indicate vegetation, wetland and built-up area. However,
not all positive values up to a certain threshold specify
desired land cover and might indicate other covers erroneously.
Therefore, a threshold value must be determined
above which land covers are mapped more accurately. In
this research, we employed an improved land cover mapping
technique to extract vegetation, wetland and built-up
area using semiautomatic segmentation approach. We used
double-window flexible pace search technique not only for
built-up features but also for vegetation and wetland
mapping to increase the accuracy. Study is based on
Landsat Thematic Mapper images of 1989, 1999 and 2010
with spatial resolution of 30 m. Integration of simple recoding
of derived index images prior to threshold identi-
fication entails increased accuracy. Accuracy assessment of
land cover mapping is done using high-resolution Google
Earth satellite image which substitutes expensive aerial
photography and time-consuming ground data collection.
Error matrix presents 82.46, 96.83 and 90 % user’s accuracy
of mapping built-up area, vegetation and wetland,
respectively. Trend analysis discloses an average loss of
vegetation and wetland by 2,664.6 and 5,328.8 acres per
year, respectively, in study area from 1989 to 2010.
Expectantly, future land cover mapping in similar researches
will be greatly assisted with the diligent technique
used in this study.
Accuracy assessment; Double-window flexible pace search; Error matrix; Geographic information system; Land cover mapping; Remote sensing; Semiautomatic segmentation approach