Brandon Heung

Department of Plant, Food, and Environmental Sciences

Faculty of Agriculture

Brandon Heung

Associate Professor, Soil Science and Pedometrics

Department of Plant, Food, and Environmental Sciences

Email: brandon.heung@dal.ca
Phone: 902.893.3605
Mailing Address:

Faculty of Agriculture, 鲍鱼tv University
Rm 233-C Cox Institute Building
50 Pictou Rd. PO Box 550
Truro, NS, B2N 5E3

Research Topics:

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鈥攁 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 鈥� 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 聽

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.

Dr. Esther Ayito (Postdoctoral Fellow; Co-Supervised with Drs. Gordon Price and Derek Lynch, 鲍鱼tv University): Development of MIR spectral library.

Travis Pennell (PhD Student): Mapping soil biodiversity and health indices for Atlantic Canada.

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.

Jin Zhang (PhD Student): Predictive digital soil mapping and digital soil data management.

Vijeta Chatterjee (MSc Student; Co-Supervised with Dr. Judith Nyiraneza, Agriculture and Agri-Food Canada)

Past Lab Members:

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.

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, 鲍鱼tv University): Farm-scale soil carbon assessments using digital soil mapping techniques.

Wenjie Xu (MSc Student; Co-Supervised with Dr. Andrew Hammermeister, 鲍鱼tv 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, , Canadian Society of Soil Science
Co-Chair, Canadian Digital Soil Mapping Working Group, Canadian Society of Soil Science
Founding Member, 鲍鱼tv University
Associate Editor, Associate Editor, Guest Editor, 鈥溾€�, Canadian Journal of Soil Science

Publications (Last 5-years)

You can find me on and .

Antora, S.S., Alahe, M.A., Chang, Y.K., Nguyen-Quang, T., Heung, B. Application of real-time FPGA-based image processing system for crop monitoring in precision agriculture. AgriEngineering. agriengineering-3101534.

France, R.W., Heung, B. 2024. Determinants of COVID-19 face mask litter in coastal urban parking lots: Implications for source modelling of potential microplastic pollution. Journal of Environmental Protection 15: 874-886.

Pennell, T.*., Comeau, L.-P., MacKinley, K., Hann, S., Heung, B., Kiely, B. 2024. Sampling variability and controlling factors in the emissions of carbon dioxide from windrow composting. Frontiers in Environmental Science 12: 1453306.

Kebonye, N.M., John, K.*, Delgado-Baquerizo, M., Zhou, Y., Agyeman, P.C., Seletlo, Z., Heung, B., Scholten, T. 2024. Major overlap in plant and soil carbon hotspots across Africa. Science of the Total Environment 951: 175476.

Arbor, A.*, Schmidt, M.G., Zhang, J.*, Bulmer, C.E., Filatow, D.S., Kasraei, B., Smukler, S.M., Heung, B. 2024. Filling the gaps: A multi-model framework for addressing data sparsity using pedotransfer functions and machine-learning with uncertainty estimates to predict bulk density. Catena 245: 108310.

Su, L., Heydari, M., Jaafarzadeh., M.S., Mousavi, S.R., Rezaei, M., Fathizad, H., Heung, B. 2024. Land use legacies on semi-arid oak forest: Soil organic carbon predictions using environmental covariates and incorporating canopy openness. Soil & Tillage Research 244: 106220.

Ayito, E.O., John, K.*, Iren, O.B., John, N.M., Mngadi, S., Moodley, R., Heung, B. 2024. Effect of biochar treatment on soil pH and cucumber fruit: A demonstration of the importance of biochar amendment on tropical soils of Nigeria. Journal of Soil and Water Conservation. JSWC.2024.00059

Laurence, L.*, Heung, B., Zhang, J.*, Pennell, T.*, Nyiraneza, J., Strom, H., Stiles, K., Burton, D.L. 2024. Integrating multi-year crop inventories as a proxy for historical soil management practices within a digital soil mapping framework for predicting nitrogen indices. Geoderma 448: 116944.

Bilodeau, M.J.F.*, Esau, T.J., Farooque, A.A., Heung, B., Zaman, Q.U. 2024. Enhancing surface drainage mapping in eastern Canada with deep learning applied to LiDAR-derived elevation data. Scientific Reports 14: 10016.

Kasraei, B.*, Schmidt, M.G., Zhang, J.*, Bulmer, C.E., Filatow, D., Arbor, A.*, Heung, B. 2024. A framework for optimizing environmental covariates to support model interpretability in digital soil mapping. Geoderma 445: 116873.

Taghizadeh-Mehrjardi, R., Nabiollahi, K., Kebonye, N.M., Kakhani, N., Ghebleh-Goydaragh, M., Heung, B., Amirian-Chakan, A., Hossaini, S.M.T., Scholten, T. 2024. High-performance soil class delineation via UMAP coupled with machine learning in Kurdistan Province, Iran. Geoderma Regional 36: e00754.

Nozari, S.*, Pahlavan Rad, M.R., Brungard, C.W., Heung, B., Bor暖vka, L. 2024. Comparing of digital soil organic carbon mapping using Random Forest and Cubist models in Liberec and Doma啪lice districts in the Czech Republic. Soil and Water Research. 119/2023-SWR.

Mosaid, H., Barakat, A., John, K.*, Faouzi, E., Bustillo, V., El Garnaoui, M., Heung, B. 2024. Improved soil carbon stock spatial prediction in a Mediterranean soil erosion site through robust machine learning techniques. Environmental Monitoring and Assessment 196: 130.

Ayito, E.O., John, K.*, Iren, O.B., John, N.M., Mngadi, S., Heung, B., Abbey, L., Agyeman, P.C., Moodley, R. 2023. Synergistic effects of biochar and poultry manure on soil and cucumber (Cucumis sativus) performance: A case study from the southeastern region of Nigeria. Soil Science Annual 74: 183903.

Easher, T.H.*, Saurette, D.D., Heung, B., Gillespie, A., Heck, R.J., Biswas, A. 2023. Disaggregating soil series maps of Middlesex County, Ontario: A comparison between DSMART and pure polygon disaggregation approach. Pedosphere. PEDSPH-2023-12-004.

Deragon, R.*, Heung, B., Lefebvre, N., John, K.*, Cambouris, A., Caron, J. 2023. Improving a regional peat thickness map using electrical conductivity measurements at the field-scale. Frontiers in Soil Science 3: 1305105.

Laurence, L*. Heung, B., Strom, H., Stiles, K., Burton, D.L. 2023. Towards a cost-effective framework for estimating soil nitrogen pools using pedotransfer functions and machine learning. Geoderma 440: 116692.

Arbor, A.*, Schmidt, M.G., Saurette, D.D., Zhang, J.*, Bulmer, C.E., Filatow, D., Kasraei, B.*, Smukler, S.M., Heung, B. 2023. A framework for recalibrating predotransfer functions using nonlinear least squares and estimating uncertainty using quantile regression. Geoderma 439: 116674

John, K.*, Ofem, K.I., Isong, I.A., Umeobi, E.C., Heung, B. 2023. Detailed investigation of soil properties and elemental concentration variation along a hillslope landscape using multivariate approaches. Journal of Earth System Science 132: 113.

Mirhashemi, H., Heydari, M., Ahmadi, K., Karami, O., Kavgaci., Matsui, T., Heung, B. 2023. Species distribution models of Brant鈥檚 oak (Quercus brantii Lindl.): The impact of spatial database on predicting the impacts of climate change. Ecological Engineering 194: 107038.

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., Monta帽o-L贸pez, 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 鈥� A case study of strawberry powdery mildew detection. Biosystems Engineering 194: 49-60.