| Reframing landscape fragmentation’s effects on ecosystem services RJ Matthew Mitchell, Andres Suarez-Castro, Maria Martinez-Harms, Martine ... Trends in Ecology and Evolution 30 (4), 190-198, 2015 | 546 | 2015 |
| Application of high spatial resolution satellite imagery for riparian and forest ecosystem classification K Johansen, NC Coops, SE Gergel, Y Stange Remote sensing of Environment 110 (1), 29-44, 2007 | 334 | 2007 |
| Current practices in UAS-based environmental monitoring G Tmušić, S Manfreda, H Aasen, MR James, G Gonçalves, E Ben-Dor, ... Remote Sensing 12 (6), 1001, 2020 | 239 | 2020 |
| Object-based approach for multi-scale mangrove composition mapping using multi-resolution image datasets M Kamal, S Phinn, K Johansen Remote Sensing 7 (4), 4753-4783, 2015 | 202 | 2015 |
| Mapping woody vegetation clearing in Queensland, Australia from Landsat imagery using the Google Earth Engine K Johansen, S Phinn, M Taylor Remote Sensing Applications: Society and Environment 1, 36-49, 2015 | 180 | 2015 |
| Mapping structural parameters and species composition of riparian vegetation using IKONOS and Landsat ETM+ data in Australian tropical savannahs K Johansen, S Phinn Photogrammetric Engineering & Remote Sensing 72 (1), 71-80, 2006 | 168 | 2006 |
| Blending Landsat and MODIS data to generate multispectral indices: A comparison of “Index-then-Blend” and “Blend-then-Index” approaches AA Jarihani, TR McVicar, TG Van Niel, IV Emelyanova, JN Callow, ... Remote Sensing 6 (10), 9213-9238, 2014 | 160 | 2014 |
| The relationship of spatial–temporal changes in fringe mangrove extent and adjacent land-use: Case study of Kien Giang coast, Vietnam HH Nguyen, C McAlpine, D Pullar, K Johansen, NC Duke Ocean & coastal management 76, 12-22, 2013 | 152 | 2013 |
| Evaluation of multiple satellite altimetry data for studying inland water bodies and river floods AA Jarihani, JN Callow, K Johansen, B Gouweleeuw Journal of Hydrology 505, 78-90, 2013 | 146 | 2013 |
| Integration of LiDAR and QuickBird imagery for mapping riparian biophysical parameters and land cover types in Australian tropical savannas LA Arroyo, K Johansen, J Armston, S Phinn Forest Ecology and Management 259 (3), 598-606, 2010 | 139 | 2010 |
| Using multi-spectral UAV imagery to extract tree crop structural properties and assess pruning effects K Johansen, T Raharjo, MF McCabe Remote Sensing 10 (6), 854, 2018 | 135 | 2018 |
| Mapping of riparian zone attributes using discrete return LiDAR, QuickBird and SPOT-5 imagery: Assessing accuracy and costs K Johansen, S Phinn, C Witte Remote Sensing of Environment 114 (11), 2679-2691, 2010 | 135 | 2010 |
| Comparison of geo-object based and pixel-based change detection of riparian environments using high spatial resolution multi-spectral imagery K Johansen, LA Arroyo, S Phinn, C Witte Photogrammetric Engineering & Remote Sensing 76 (2), 123-136, 2010 | 122 | 2010 |
| Optimising drone flight planning for measuring horticultural tree crop structure YH Tu, S Phinn, K Johansen, A Robson, D Wu ISPRS Journal of Photogrammetry and Remote Sensing 160, 83-96, 2020 | 115 | 2020 |
| A new source for high spatial resolution night time images—The EROS-B commercial satellite N Levin, K Johansen, JM Hacker, S Phinn Remote Sensing of Environment 149, 1-12, 2014 | 115 | 2014 |
| Assessment of multi-resolution image data for mangrove leaf area index mapping M Kamal, S Phinn, K Johansen Remote Sensing of Environment 176, 242-254, 2016 | 110 | 2016 |
| Assessing radiometric correction approaches for multi-spectral UAS imagery for horticultural applications YH Tu, S Phinn, K Johansen, A Robson Remote Sensing 10 (11), 1684, 2018 | 95 | 2018 |
| Mapping riparian condition indicators in a sub-tropical savanna environment from discrete return LiDAR data using object-based image analysis K Johansen, LA Arroyo, J Armston, S Phinn, C Witte Ecological Indicators 10 (4), 796-807, 2010 | 90 | 2010 |
| What is the value of a good map? An example using high spatial resolution imagery to aid riparian restoration SE Gergel, Y Stange, NC Coops, K Johansen, KR Kirby Ecosystems 10, 688-702, 2007 | 88 | 2007 |
| Predicting biomass and yield in a tomato phenotyping experiment using UAV imagery and random forest K Johansen, MJL Morton, Y Malbeteau, B Aragon, S Al-Mashharawi, ... Frontiers in Artificial Intelligence 3, 28, 2020 | 85 | 2020 |
Stuart PhinnProfessor of Geography, School of the Environment, University of QueenslandBestätigte E-Mail-Adresse bei uq.edu.au