Land cover dynamics monitoring with Landsat data in Kunming,China: a cost-effective sampling and modelling scheme using Google Earth imagery and random forests |
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| Authors: | Ning Lu Alexander J Hernandez R Douglas Ramsey |
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| Institution: | 1. Computer and Information Science College, Southwest Forestry University, Kunming, China;2. Researcher RS/GIS Laboratories, Wildland Resources Department, Utah State University, Logan, UT, USA;3. Wildland Resources Department, Utah State University, Logan, UT, USA |
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| Abstract: | Changes in forest composition impact ecological services, and are considered important factors driving global climate change. A hybrid sampling method along with a modelling approach to map current and past land cover in Kunming, China is reported. MODIS land cover (2001–2011) data-sets were used to detect pixels with no apparent change. Around 3000 ‘no change points’ were systematically selected and sampled using Google Earth’s high-resolution imagery. Thirty-five per cent of these points were verified and used for training and validation. We used Random forests to classify multi-temporal Landsat imagery. Results show that forest cover has had a net decrease of 14385?ha (1.3% of forest area), which was primary converted to shrublands (11%), urban and barren land (2.7%) and agriculture (2.5%). Our validation indicates an overall accuracy (Kappa) of 82%. Our methodology can be used to consistently map the dynamics of land cover change in similar areas with minimum costs. |
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| Keywords: | systematic sampling random forests change detection forest cover Landsat |
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