Abstract
Tree cover maps are used for many purposes, such as vegetation mapping, habitat connectivity and fragmentation studies. Small remnant patches of native vegetation are recognised as ecologically important, yet they are underestimated in remote sensing products derived from Landsat. High spatial resolution sensors are capable of mapping small patches of trees, but their use in large-area mapping has been limited. In this study, multi-temporal Satellite pour l’Observation de la Terre 5 (SPOT5) High Resolution Geometrical data was pan-sharpened to 5 m resolution and used to map tree cover for the Australian state of New South Wales (NSW), an area of over 800,000 km2. Complete coverages of SPOT5 panchromatic and multispectral data over NSW were acquired during four consecutive summers (2008–2011) for a total of 1256 images. After pre-processing, the imagery was used to model foliage projective cover (FPC), a measure of tree canopy density commonly used in Australia. The multi-temporal imagery, FPC models and 26,579 training pixels were used in a binomial logistic regression model to estimate the probability of each pixel containing trees. The probability images were classified into a binary map of tree cover using local thresholds, and then visually edited to reduce errors. The final tree map was then attributed with the mean FPC value from the multi-temporal imagery. Validation of the binary map based on visually assessed high resolution reference imagery revealed an overall accuracy of 88% (±0.51% standard error), while comparison against airborne lidar derived data also resulted in an overall accuracy of 88%. A preliminary assessment of the FPC map by comparing against 76 field measurements showed a very good agreement (r2 = 0.90) with a root mean square error of 8.57%, although this may not be representative due to the opportunistic sampling design. The map represents a regionally consistent and locally relevant record of tree cover for NSW, and is already widely used for natural resource management in the state.
Highlights
Human activity has modified much of the world’s forests, converting large areas of continuous forest into small, fragmented patches, such that 70% of remaining forest is within 1 km of an edge [1].Remote Sens. 2016, 8, 515; doi:10.3390/rs8060515 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 515Fragmentation degrades ecosystems, reducing biodiversity especially in the smallest and most isolated fragments [2,3,4,5,6]
To determine how the new Satellite pour l’Observation de la Terre 5 (SPOT5) foliage projective cover (FPC) map compared to the previous Landsat FPC map, both determine how
The high resolution binary tree cover map was found to have an accuracy of 88%, compared to lidar derived products and visually interpreted high resolution imagery
Summary
Human activity has modified much of the world’s forests, converting large areas of continuous forest into small, fragmented patches, such that 70% of remaining forest is within 1 km of an edge [1].Remote Sens. 2016, 8, 515; doi:10.3390/rs8060515 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 515Fragmentation degrades ecosystems, reducing biodiversity especially in the smallest and most isolated fragments [2,3,4,5,6]. Human activity has modified much of the world’s forests, converting large areas of continuous forest into small, fragmented patches, such that 70% of remaining forest is within 1 km of an edge [1]. Some declines in biodiversity are evident almost immediately after fragmentation, whereas others increase over time, with extinctions occurring decades or more after disturbances [7]. High spatial resolution imagery can allow small fragments such as thin corridors of trees, and scattered individual trees, to be mapped. Such detailed maps, are usually only produced for small regions [8], and it remains a challenge to create consistent high resolution maps over large areas
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