Dr Mark Broich
Research Fellow
Field of Research: 
Large area environmental remote sensing, spatial-temporal dynamics and change
Contact details:
+61 2 9385 8713

Room 633
Biological Sciences Building (D26)
UNSW, Kensington 2052


Geospatial Analysis for Environmental Change Lab


Large area environmental remote sensing, spatial-temporal dynamics and change, forest loss, vegetation dynamics, vegetation response to flooding


A novel approach for assessing environmental flows using satellite data (Australian Research Council Linkage Grant) working with Dr Mirela Tulbure



PhD Students

Iurii Shendryk: Multi-sensor remote sensing data fusion for assessment of River Red Gum health condition. A case study for Barmah-Millewa forest [joint supervisor]

Robbi Bishop-Taylor: Surface water networks: a graph theory approach [joint supervisor]

Valentin Heimhuber: Modelling surface water dynamics on large river basin scale from space [joint supervisor]

Research Assistants

Miles Davitt

Selected Publications - (A complete list of publications is available on the Geospatial Analysis for Environmental Change Lab webpage)

For more information see Google Scholar


Broich M., A. Huete, M. Paget, X. Ma, R. Devadas, N. Restrepo-Coupe, K. Davies, A. Held. (2015). A spatially explicit Land Surface Phenology data product for science, monitoring and natural resources management applications. Environmental Modelling & Software, 64, 191-204.

Xin Q., M. Broich, P. Zhu, P. Gong. (2015). Modelling grassland spring onset across the Western United States using climate variables and MODIS-derived phenology metrics. Remote Sensing of Environment, 161, 63-77.

Xin Q., C. Woodcock, M. Broich, A. Suyker, P. Gong. (2015). Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States. Agricultural and Forest Meteorology, 201, 111-119.

Broich M., A. Huete, M.G. Tulbure, X. Ma, Q. Xin, M. Paget, N. Restrepo-Coupe, K. Davies, R. Devadas, and A. Held. Land surface phenological response to decadal climate variability across Australia using satellite remote sensing (2014). Biogeosciences Special Issue on Climate Extremes and Biogeochemical Cycles in the Terrestrial Biosphere: Impacts and Feedbacks Across Scales, 11 (5), 7685-7719.

Broich, M., A. Huete, M. Paget, X. Ma, R. Devadas, N. Restrepo Coupe, K. Davies, A. Held (2014). Australian Phenology Product Dataset: A spatially explicit vegetation phenology data product for science, monitoring and natural resource management applications across Australia. AusCover TERN Sydney Node. http://www.auscover.org.au/purl/phenology-modis-uts.

Tulbure, M.G., S. Kininmonth, M. Broich. (2014). Spatiotemporal dynamics of surface water networks across a global biodiversity hotspot – implications for conservation.Environmental Research Letters, 9, 114012.

Huete, A., Miura, T., Yoshioka, H., Ratana, P., M. Broich. (2014). Indices of Vegetation Activity. In J. Hanes (Ed.), Biophysical Applications of Satellite Remote Sensing, pp 1-41. Berlin Heidelberg: Springer.

Tulbure M.G. and M. Broich. (2013). Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011. ISPRS Journal of Photogrammetry and Remote Sensing, 79, 44-52.

Tulbure, M.G. and M. Broich. 2013. Data from: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011. Dryad Digital Repository. doi:10.5061/dryad.50003

Xin Q., P. Gong, C. Yu, L. Yu, M. Broich, A.E. Suyker, R. Myneni. (2013). A production efficiency model-based method for satellite estimates of corn and soybean yields in the Midwestern US. Remote Sensing, 5 (11), 5926-5943.

Ma X., A. Huete, Q. Yu, N. Restrepo Coupe, K. Davies, M. Broich, P. Ratana, J. Beringer, L. Hutley, J. Cleverly, N. Boulain, D. Eamus. (2013). Spatial patterns and temporal dynamics in savannah vegetation phenology across the North Australian Tropical Transect. Remote Sensing of Environment, 139, 97-115.

Restrepo Coupe N., A. Huete, M. Broich, K. Davie. (2013).  Phenology validation. In AusCover Good Practice Guidelines: A technical handbook supporting calibration and validation activities of remotely sensed data products, pp 8-28. Brisbane: AusCover / Terrestrial Ecosystem Research Network.

Gaveau D., M. Kshatriya, D. Sheil, S. Sloan, E. Molidena, A. Wijaya, S. Wich, M. Ancrenaz, M.C. Hansen, M. Broich, M. Guariguata, P. Pacheco, P.V. Potapov, S. Turubanova, E. Meijaard. (2013). Reconciling Forest Conservation and Logging in Indonesian Borneo. PLOS ONE, 8 (8), e69887.

Broich M., M.C. Hansen, P.V Potapov, M. Wimberley (2013). Patterns of tree cover loss along the Indonesia-Malaysia border on Borneo. International Journal of Remote Sensing, 34 (16), 5748-5760.

Potapov, P.V., S.A. Turubanova, M.C. Hansen, B. Adusei, M. Broich, A. Altstatt., L. Mane, and C.O. Justice. (2012). Quantifying forest cover loss in Democratic Republic of the Congo, 2000-2010. Remote Sensing of Environment, 122, 106-116.

Broich M., M.C. Hansen, P.V Potapov, B. Adusei, E.J Lindquist, S.V. Stehman. (2011). Time-series analysis of multi-resolution optical remote sensing imagery for quantifying forest cover loss in Sumatra and Kalimantan, Indonesia. International Journal of Applied Earth Observation and Geoinformation, 13 (2), 277-291.

Broich M., M.C. Hansen, F. Stolle, P.V. Potapov, B.A. Margono. (2011). Remotely sensed forest cover loss reveals high spatial and temporal variation across Sumatera and Kalimantan, Indonesia 2000-2008. Environmental Research Letters, 6, 014010

Stehman, S.V., M.C. Hansen, M. Broich, P.V. Potapov. (2011). Adapting a global stratified random sample for regional estimation of forest cover change derived from satellite imagery. Remote Sensing of Environment, 115 (2), 650-658.

Broich, M., Fontaine, J., & Tulbure, M.G. (2011). “A report for Fire and Emergency Services, Bushfire Protection Branch”. In, Bushfire Threat Analysis: Western Australia. Western Australia.

Broich M., S.V. Stehman, M.C. Hansen, P.V. Potapov, Y.E. Shimabukuro. (2009). A comparison of sampling designs for estimating deforestation from Landsat imagery: A case study of the Brazilian Legal Amazon. Remote Sensing of Environment, 113 (11), 2448-2454.

For more information please refer to the Geospatial Analysis for Environmental Change Lab webpage.