The Suitablity of Decadal Image Data Sets for Mapping Tropical Forest Cover Change in the Democratic Republic of Congo: Implications for the Global Land Survey

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Landsat remote sensing of the central African humid tropics is confounded by

persistent cloud cover and, since 2003, missing data due to the Landsat-7

Enhanced Thematic Mapper Plus (ETM + ) scan line corrector (SLC) malfunction.

To quantify these limitations and their effects on contemporary forest cover

and change characterization, a comparison was made of multiple Landsat-7

image mosaics generated for a six Landsat path/row study site in central Africa

for 2000 and 2005. Epoch 2000 mosaics were generated by compositing (i) two to

three Landsat acquisitions per path/row, (ii) using the best single GeoCover 2000

acquisition for each path/row. Epoch 2005 composites were generated by

compositing SLC-off data using (iii) five to seven acquisitions per path/row, (iv)

three acquisitions per path/row. Eighty per cent of pixels were of suitable quality

for change detection between (ii) and (iv), emulating that which is possible with

current GeoCover and planned Global Land Survey (GLS) inputs. In a more

data intensive change detection analysis using mosaics (i) and (iii), 96% of pixels

had suitable quality. Compositing more acquisitions per path/row for the study

area systematically reduced the percentage of SLC-off gaps and, when more than

three acquisitions were composited, reduced the percentage of pixels with high

likelihood of cloud, haze or shadow. The results indicate that additional input

imagery to augment both the Geocover and GLS data may be required to enable

forest cover and change analyses for regions of the humid tropics.

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International Journal of Remote Sensing





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© 2008 Taylor & Francis