The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the global land survey

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.