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Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations., , , and . Int. J. Appl. Earth Obs. Geoinformation, (2013)A review of earth observation using mobile personal communication devices., and . Comput. Geosci., (2013)Vegetation Phenology Driving Error Variation in Digital Aerial Photogrammetrically Derived Terrain Models., , , , and . Remote Sensing, 10 (10): 1554 (2018)Prediction of eucalypt foliage nitrogen content from satellite-derived hyperspectral data., , , and . IEEE Trans. Geosci. Remote. Sens., 41 (6): 1338-1346 (2003)Satellite-observed changes in terrestrial vegetation growth trends across the Asia-Pacific region associated with land cover and climate from 1982 to 2011., , , , and . Int. J. Digit. Earth, 9 (11): 1055-1076 (2016)Normalization method for multi-sensor high spatial and temporal resolution satellite imagery with radiometric inconsistencies., , and . Comput. Electron. Agric., (2019)Maintaining accurate, current, rural road network data: An extraction and updating routine using RapidEye, participatory GIS and deep learning., , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)Correction, update, and enhancement of vectorial forestry road maps using ALS data, a pathfinder, and seven metrics., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2022)Towards analysis ready data of optical CubeSat images: Demonstrating a hierarchical normalization framework at a wetland site., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)Quantifying local fire regimes using the Landsat data-archive: a conceptual framework to derive detailed fire pattern metrics from pixel-level information., , and . Int. J. Digit. Earth, 12 (5): 544-565 (2019)