## 5 Conclusions  
The objective of this work was to develop a method to map the heterogeneous patterns of fragmented forest and open woodland across the Australian state of NSW. This was achieved through combining multi-temporal high spatial resolution data from the SPOT5 satellite, automated image processing methods developed for continental scale Landsat projects, and manual image processing methods developed for regional scale vegetation mapping. The result is a tree cover map with 5 m pixels, which will be used for natural resource management at a variety of scales, from state-wide reports to local planning. Overall accuracy for the binary tree cover map was 88%, determined through comparison with high resolution imagery and airborne lidar data. Errors were not uniformly distributed, with omission of trees more common in the arid and semi-arid regions, and commission of false positive trees more common in areas of tall shrubs, such as heathlands and wetlands. Although the use of multi-temporal imagery allowed the classification to separate persistent tree cover from temporary fluctuations in ground cover, it proved too difficult in some areas. A preliminary assessment of the FPC tree cover map using a sample of 76 non-randomly selected field plots resulted in an RMSE of around 9%. Future work will examine methods of deriving FPC from airborne lidar data, to allow a larger validation sample. The validation of the map products, using field data, high resolution imagery and airborne lidar, was as thorough as possible, and provides extra information to map users who can determine practical limitations based on their knowledge of local vegetation. The lidar products were particularly informative, providing quantitative data on vegetation cover, height, and fragmentation. As expected, the use of multi-temporal SPOT5 data over such a large area proved more computationally intensive than previous Landsat based projects. The fewer spectral bands that were available in the SPOT5 data proved capable of modelling FPC, and the smaller pixel size allowed much better depiction of the fragmented nature of the vegetation. Comparison of the SPOT5 and Landsat FPC maps showed excellent agreement, when both were degraded to 100 m pixels. Future tree cover maps based on 10 m multi-spectral Sentinel-2 data may provide greater accuracy due to the increased spectral and temporal resolution, and will hopefully require less manual editing to reduce the commission of false positives due to persistent understorey vegetation. The high degree to which Australian forests have been cleared and fragmented has created an imperative for the conservation of existing primary forest patches. It also highlights the importance of possible regeneration of areas between fragments to increase native habitat area, connectivity and ecosystem functions [7]. The SPOT5 tree cover map presented here will facilitate better management and conservation across the fragmented vegetation of NSW. **Supplementary Materials:** The following are available online at www.mdpi.com/2072-4292/8/6/515/s1 in a supplementary document: Figure S1: Predicted SPOT5 FPC compared with the predicted Landsat FPC, for the 17 vegetation formation classes listed in Table S1, Table S1: Tree cover area for NSW grouped by vegetation formation, Table S2: Specifications of the lidar surveys sampled as part of the tree cover validation, Table S3: SPOT5 tree cover accuracy statistics using visually interpreted data as reference, grouped by catchment, Table S4: SPOT5 tree cover accuracy statistics using lidar products as reference, grouped by vegetation formation. **Acknowledgments:** SPOT5 data were acquired from Airbus Defence and Space. Lidar data were supplied by NSW Land and Property Information and a number of commercial vendors funded from various sources. We owe a debt of gratitude to the staff, volunteers and students who edited the maps, including [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON].