Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 2. Classification
AbstractMapping landscape dynamics is necessary to assess cumulative impacts due to climate change and development in Arctic regions. Landscape changes produce a range of temporal reflectance trajectories that can be obtained from remote sensing image time-series. Mapping these changes assumes that their trajectories are unique and can be characterized by magnitude and shape. A companion paper in this issue describes a trajectory visualization method for assessing a range of landscape disturbances. This paper focusses on generating a change map using a time-series of calibrated Landsat Tasseled Cap indices from 1985 to 2011. A reference change database covering the Mackenzie Delta region was created using a number of ancillary datasets to delineate polygons describing 21 natural and human-induced disturbances. Two approaches were tested to classify the Landsat time-series and generate change maps. The first involved profile matching based on trajectory shape and distance, while the second quantified profile shape with regression coefficients that were input to a decision tree classifier. Results indicate that classification of robust linear trend coefficients performed best. A final change map was assessed using bootstrapping and cross-validation, producing an overall accuracy of 82.8% at the level of 21 change classes and 87.3% when collapsed to eight underlying change processes. View Full-Text
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Olthof, I.; Fraser, R.H. Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 2. Classification. Remote Sens. 2014, 6, 11558-11578.
Olthof I, Fraser RH. Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 2. Classification. Remote Sensing. 2014; 6(11):11558-11578.Chicago/Turabian Style
Olthof, Ian; Fraser, Robert H. 2014. "Detecting Landscape Changes in High Latitude Environments Using Landsat Trend Analysis: 2. Classification." Remote Sens. 6, no. 11: 11558-11578.