Brandon Heung
Associate Professor
Email: brandon.heung@dal.ca
Phone: 902.893.3605
Mailing Address:
Rm 233-C Cox Institute Building
50 Pictou Rd. PO Box 550
Truro, NS, B2N 5E3
- Soil Science and Soil Surveying
- Digital Soil Mapping and Assessments
- Geospatial Information Systems
- Spatial Analysis and Modelling
- Data-Mining and Machine-Learning
Research Vision & Interests:
My area of research is in pedometrics—a branch of soil science that aims to develop accurate and precise high resolution digital soil maps and predictive models that provide knowledge of soil variability over space and time. This discipline is the convergence of soil science, applied computing science, and remote sensing by leveraging the advances in geographical information systems, machine-learning, artificial intelligence, and Big Data analytics. At the Soil-Landscapes Analysis and Modelling Lab, my team focusses on the modeling and monitoring of soil properties and health, assessment of soil functions, and the transformation of soil data into knowledge to support decision making processes across diverse spatial scales. Spatial soil information and estimates of uncertainty are critical towards informing sustainable soil resource management practices and successfully implementing nature-based solutions to climate change. At the local-scale, I contribute data for precision agriculture, on-farm carbon sequestration programs and enhanced forest resource inventory activities. At the national-scale, my team supports the reporting of greenhouse gas emissions by providing baseline soil data for informing national- and global climate change models, ensuring that our international commitments to monitor, verify, and report on the state of our soil resources are met.
Lab: Soil-Landscapes Analysis & Modelling Lab
Research Topics:
- Soil Science and Soil Surveying
- Digital Soil Mapping and Assessments
- Geospatial Information Systems
- Spatial Analysis and Modelling
- Data Mining and Machine-Learning
Teaching:
ENVA 3005: Geographical Information Systems (GIS) (A)
AGRI 5700: Communication Skills & Graduate Seminar
AGRI 6800: Advanced Graduate Seminar
Adjunct Status:
Adjunct Professor (2018 – Current), Department of Geography, Faculty of Environment, Simon Fraser University
Major Sources of Research Funding:
Natural Sciences and Engineering Research Council
Canadian Foundation for Innovation
Agriculture and Agri-Food Canada
Canadian Forest Service, Natural Resources Canada
Research Nova Scotia Trust
Nova Scotia Department of Natural Resources & Renewables
Nova Scotia Department of Agriculture
Ontario Ministry of Agriculture, Food, and Rural Affairs
British Columbia Ministry of Forests, Lands, Natural Resource Operations, and Rural Development Â
Current Lab Members:
Dr. Kingsley John (McCain Postdoctoral Fellow): Integrating process-based modelling and digital soil mapping for estimating soil organic carbon sequestration potential in Canada.
Travis Pennell (PhD Student): Mapping soil biodiversity and health indices for Atlantic Canada.
Jay Woodworth (PhD Student): Supporting Christmas tree cultivation in Nova Scotia using digital soil mapping.
Babak Kasraei (PhD Student; Co-Supervised with Dr. Margaret Schmidt, Simon Fraser University): Evaluation of soil organic carbon sequestration potential, and stocks in British Columbia and comparison of uncertainty estimation approaches in predictive soil mapping.
Adrienne Arbor (MSc Student; NSERC CGS-M; Co-Supervised with Dr. Margaret Schmidt, Simon Fraser University): Comparing the performance of existing pedotransfer functions with machine learning approaches.
Jin Zhang (Research Associate): Predictive digital soil mapping and digital soil data management.
Past Lab Members:
Dr. Shane Furze (Postdoctoral Fellow; Co-Supervised with Dr. Kara Webster, Natural Resources Canada): Developing a digital soil mapping framework to support enhanced forest resource inventory activities in northern Ontario.
Dr. Siddhartho Paul (Postdoctoral Fellow; Co-Supervised with Dr. Derek Lynch, ±«Óătv University): Farm-scale soil carbon assessments using digital soil mapping techniques.
Wenjie Xu (MSc Student; Co-Supervised with Dr. Andrew Hammermeister, ±«Óătv University): Impact of organic management on landscape heterogeneity.
William Bethel (MSc Student; Co-Supervised with Dr. Margaret Schmidt, Simon Fraser University): Use of LiDAR and machine-learning to predict soil attributes of managed forests.
Babak Kasraei (MSc Student; Co-Supervised with Dr. Margaret Schmidt, Simon Fraser University): High-resolution digital soil mapping for managed forests using airborne LiDAR Data.
Christopher Blackford (Research Associate; Co-Supervised with Dr. Kara Webster, Natural Resources Canada): Developing a digital soil mapping framework to support enhanced forest resource inventory activities in northern Ontario.
Other Activities
Secretary, Pedology Committee, Canadian Society of Soil Science
Co-Chair, Canadian Digital Soil Mapping Working Group, Canadian Society of Soil Science
Associate Editor, Guest Editor, “”, Canadian Journal of Soil Science
Publications (Last 5-years)
You can find me on and .
Antora, S.S., Chang, Y.K., Nquyen-Quang, T., Heung, B. 2023. Development of a real-time field-programmable gate array (FPGA)-based image processing (RFIP) system for agricultural field monitoring applications. AgriEngineering 5: 886-905.
Karimi, S., Heydari, M., Mirzaei, J., Karami, O., Heung, B., Mosavi, A., 2023. Assessment of post-fire phenological changes using MODIS-derived vegetative indices in the semiarid oak forests. Forests 14: 590.
Easher, T.H., Saurette, D.D., Chappell, E., Montaño-López, F., Gasser, M-.O., Gillespie, A., Heck, R.J., Heung, B., Biswas, A., 2023. Sampling and classifier modifications to DSMART for disaggregating soil polygon maps. Geoderma 431: 116360.
Heung, B., Saurette, D.D., Bulmer, C.E., Bedard-Haughn, A., 2023. Advances in soil survey and classification in Canada. Canadian Journal of Soil Science. CJSS-2023-0002.
Shin, J., Mahmud, M.S., Rehman, T.U., Ravichandran, P., Heung, B., Chang, Y.K., 2023. Trends and prospects of machine vision technology for stresses and diseases detection in precision agriculture. AgriEngineering 5: 20-39.
Mahmoodi, S., Ahmadi, K., Heydari, M., Karami, O., Esmailzadeh, O., Heung, B., 2023. Elevational shift of endangered European Yew under climate change in Hyrcanian mountain forests: Rethinking conservation and restoration strategies. Forest Ecology and Management 529: 120693.
France, R.L., Heung, B., 2023. Density variability of COVID-19 face mask litter: A cautionary tale for PPE waste monitoring. Journal of Hazardous Materials Advances 9: 100220.
Deragon, R., Saurette, D.D., Heung, B., Caron, J., 2023. Mapping the maximum peat thickness of cultivated Organic soils of the southwest plain of Montreal. Canadian Journal of Soil Science 103: 64-80.
Paul, S.S., Heung, B., Lynch, D.H., 2023. Landscape-scale modeling of total and active organic carbon dynamics in agricultural soil using digital soil mapping: A whole-farm based case study from Central Nova Scotia. Canadian Journal of Soil Science 103: 64-80.
Anku, K.E., Percival, D.C., Rajasekaran, L.R., Heung, B., Vankoughnett, M., 2023. Phenological assessment of the wild blueberry field using an unmanned aerial vehicle. Acta Horticulturae 1357: 35-41.
Shahabi, A., Nabiollahi, K., Davari, M., Zeraatpisheh, M., Heung, B., Scholten, T., Taghizadeh-Merhjardi, R., 2022. Spatial prediction of soil properties through hybridized random forest model and combination of reflectance spectroscopy and environmental covariates. Geocarto International 37: 18172-18195.
Blackford, C., Heung, B., Webster, K., 2022. Incorporating spatial uncertainty maps into soil sampling improves digital soil mapping classification accuracy in Ontario, Canada. Geoderma Regional 29: e00495.
Taghipour, K., Heydari, M., Kooch, Y., Fathizad, H., Heung, B., Taghizadeh-Mehrjardi, R., 2022. Investigation and modeling of soil quality using digital soil mapping and geostatistics in protected and degraded semiarid forest ecosystem. CATENA 213: 106204.
Fathizad, H., Taghizadeh-Mehrjardi, R., Ardakani, M.A.H., Zeraatpisheh, M. Heung, B., Scholten, T., 2022. Spatiotemporal assessment of soil organic carbon change using machine-learning in arid regions. Agronomy 12: 628.
Taghizadeh-Mehrjardi, R., Khademi, H., Khayamim, F., Zeraatpisheh, M., Heung, B., Scholten, T., 2022. A comparison of model averaging techniques to improve the prediction of soil properties in digital soil mapping. Remote Sensing 14: 472.
Zhang, J., Schmidt, M.G., Heung, B., Bulmer, C.E., Knudby, A., 2022. Using an ensemble learning approach in digital soil mapping of soil pH for the Thompson-Okanagan region of British Columbia. Canadian Journal of Soil Science 102: 579-596.
Heung, B., Bulmer, C.E., Schmidt, M.G, Zhang, J., 2022. Provincial-scale digital soil mapping using a Random Forest approach for British Columbia, Canada. Canadian Journal of Soil Science 102: 597-620.
Heung, B., Saurette, D., Bulmer, C.E., 2021. Chapter 17: Digital Soil Mapping. In Krzic, M., Walley, F.L., Diochon, M.V., Farrell, R.E. (eds), Digging into Canadian Soils: An Introduction to soil science. Canadian Society of Soil Science, Pinawa, MB.
Heung, B., Keys, K., Burton, D.L., Lynch, D.H., 2021. Chapter 13: Soils of the Atlantic Provinces. In Krzic, M., Walley, F.L., Diochon, M.V., Farrell, R.E. (eds), Digging into Canadian Soils: An Introduction to soil science. Canadian Society of Soil Science, Pinawa, MB.
Bilodeau, M.F.J., Esau, T.J., Farooque, A.A., Zaman, Q.U., Heung, B., 2021. Estimation of agricultural dykelands cultivated in Nova Scotia using land property boundaries and crop inventory. ISPRS International Journal of Geo-Information 10: 801.
Ebrahimi-Khusfi, Z., Taghizadeh-Mehrjardi, R., Roustaei, F., Ebrahimi-Khusfi, M., Mosavi, A.H., Heung, B., Soleimani-Sardo, M., Scholten, T., 2021. Determining the contribution of environmental factors in controlling dust pollution during cold and warm months of western Iran using different data mining algorithms and game theory. Ecological Indicators 132: 108287
Kasraei, B., Heung, B., Saurette, D.D., Schmidt, M.G., Bulmer, C.E., Bethel, W., 2021. Quantile regression as a generic approach for estimating uncertainty for machine-learning techniques. Environmental Modelling & Software 144: 105139.
Marshall, C.B., Burton, D.L., Heung, B., Lynch, D.H., 2021. Influence of cropping system and pedogenesis on soil health. Canadian Journal of Soil Science 101: 626-640
Taghizadeh-Mehrjardi, R., Fathizad, H., Ardakani, M.A.H, Sodaiezadeh, H., Kerry, R., Heung, B., Scholten, T., 2021. Spatial-temporal analysis of heavy metals in the arid soils using digital soil assessment and machine learning techniques. Remote Sensing 13: 1698.
Taghizadeh-Mehrjardi, R., Hamzehpour, N., Hassanzadeh, M., Heung, B., Gheble-Goydaragh, M., Schmidt, K., Scholten, T., 2021. Enhancing accuracy and interpretability of machine learning models using super learning and permutation feature importance techniques in digital soil mapping. Geoderma 399: 115108.
Taghizadeh-Mehrjardi, R., Emado, M., Cherati, A., Heung, B., Mosavi, A., Scholten, T., 2021. Bio-inspired hybridization of artificial neural networks to improve the spatial prediction of soil texture fractions. Remote Sensing 13: 1025.
Shin, J., Chang, Y.K., Heung, B., Nguyen-Quang, T., Price, G.W., Al-Mallahi, A., 2021. Deep learning for image-based powdery mildew disease detection on strawberry leaves. Computers and Electronics in Agriculture 183: 106042.
Nabiollahi, K., Taghizadeh-Mehrjardi, R., Aram, S., Heung, B., Amirian-hakan, A., Scholten, T., 2021. 
Assessing agricultural salt-affected land using digital soil mapping and hybridized Random Forests. Geoderma 385: 114858.
Taghizadeh-Mehrjardi, R., Schmidt, K., Toomanian, N., Heung, B., Behrens, T., Mosavi, A., Band, S.S., Amirian-Chakan, A., Fathabadi, A., Scholten, T., 2021. Improving the spatial prediction of soil salinity in arid regions using wavelet transform and support vector regression models. Geoderma 383: 114793.
Blackford, C., Heung, B., Baldwin, K., Fleming, R.L., Hazlett, P.W., Morris, D.M., Uhlig, P.W.C., Kebster, K.L. 2021. Digital soil mapping workflow for forest resource applications: A case study in the Hearst Forest, Ontario. Canadian Journal of Forest Research 51: 59-77.
Fathizad, H., Ardakani, M.A.H., Heung, B., Sodaiezadeh, H., Rahmani, A., Fathabadi, A., Scholten, T., Taghizadeh-Mehrjardi, R., 2020. Spatio-temporal dynamic of soil quality in the Central Iranian desert modeled with machine learning and digital soil assessment techniques. Ecological Indicators 118: 106736.
Shin, J., Chang, Y.K., Heung, B., Nguyen-Quang, T., Price, G.W., Al-Mallahi, A., 2020. Effect of directional augmentation using supervised machine learning technologies – A case study of strawberry powdery mildew detection. Biosystems Engineering 194: 49-60.