Dr. Chunhua Zhang

Associate Professor
Department of Biology
Algoma University

1520 Queen Street East
Sault Ste. Marie, Ontario P6A 2G4 Canada
Office: CC 3035
Email: chunhua.zhang@algomau.ca
Phone: 705-949-2301 ext 1090

As a faculty member in the Department of Biology, I am responsible for teaching courses on geospatial/geomatics techniques such as Digital Earth, Geographic Information Systems, and Remote Sensing of the Environment, as well as environmental management courses like Geomorphology, Climatology, and Impact Assessment. 

My research interests center around  the integration of geomatics techniques, spatial statistics, and geospatial big data to monitor/model environmental changes.  Specifically, I examine how impacts of global climate change on various environmental processes at the landscape level affect ecosystems and natural resources.

About me image

Ph.D., University of Saskatchewan, Canada

M.Sc., Southwest China Normal University, China

B.Sc., Hunan Normal University, China

GEOG1026--Introduction to the Physical Environment 

GEOG 2016--Digital Earth 

GEOG 2996--The Great Lakes: Resources, People, and the Environment

GEOG 3037--Remote Sensing of the Environment 

GEOG 3076--Advanced Geographic Information Systems 

GEOG 3106-- Climatology: The Context for Climate Change 

GEOG 4006--Geographic Information System Research Project 

GEOG 4296--Impact Assessment and Environmental Management

Applications of Geographic Information Systems and geospatial big data in environmental monitoring

Applications of Geographic Information Systems and geospatial big data in environmental monitoring

Geomatics, which includes geographic information systems and remote sensing, has the potential to identify and analyze spatial patterns and processes of various environmental issues. For example, it can be used to monitor crop conditions, track deforestation and desertification, and assess eutrophication. Picture source: https://www.frontiersin.org/research-topics/8127/big-spatial-data

Applications of drone images in precision farming

Applications of drone images in precision farming

Drone technology, also known as unmanned aerial systems (UAS), has found significant use in precision agriculture due to its cost-effectiveness and ability to acquire data with flexibility. The picture on the right is a mosaicked image map based on UAS images of a soybean field in Sturgeon Falls, ON, Canada taken on July 12, 2013. The A, B, and C represent treatment areas of organic only, organic and chemical fertilizer and chemical fertilizer only applications, respectively. The final yields for the treatment areas A, B and C were calculated at 1.73, 2.27 and 2.97 tons/ha, respectively.

Landscape Science

Landscape Science

Landscape science is a discipline that incorporates field studies, remotely sensed imagery, and modeling to analyze past landscape changes, forecast future changes, and assess their impact on ecosystem services. Images on the left show typical karst landscapes. (a) A desertified slope in Huanjiang, Guangxi (Imaging date: January 15, 2002), (b) a typical Maolan (minority) village in Huanjiang, Guangxi (Imaging date: March 25, 2003), (c) typical land use pattern in a peak-cluster (fengcong) depression (Imaging date: January 24, 2018), (d) Mulun National Reserve (Guangxi) (Imaging date: November 9, 2007)

Landscape Science

Landscape Science

Land cover change is an important proxy for environmental changes. The picture on the right shows land cover changes (recovery) in a karst depression, Southwest China between 2004 (left) and 2019 (right)

Environmental Degradation

Environmental Degradation

Multiple ecosystems are experiencing degradation due to various stressors.The picture features mangrove forests with different conditions. (a) healthy black mangrove (Avicennia germinans), (b) dwarf black mangrove, (c) poor condition black mangrove.

Environmental Dynamics

Environmental Dynamics

Utilizing historical geospatial big data can help identify environmental dynamics. This animation indicates dynamics of the channels of Ucayali River, Peru between 1984 and 2022 (Landsat images)

Zhang, C., Wang, K., Yue, Y., Qi, X., Zhang, M. 2023. Assessing Regional Ecosystem Conditions Using Geospatial Techniques—A Review. Sensors, 23(8):4101. (https://doi.org/10.3390/s23084101)

Chang, J., Yue, Y., Tong, X., Brandt, M., Zhang, C., Zhang, X., Qi, X., Wang, K. 2023. Rural outmigration generates a carbon sink in South China karst. Progress in Physical Geography: Earth and Environment (10.1177/03091333231154177)

Zhang, M., Liu, H., Wang, K., Chen, Y., Ren, Y., Yue, Y., Deng, Z., Zhang, C. (2023). Nonlinear trends of vegetation changes in different geomorphologic zones and land use types of the Yangtze River basin, China. Land Degradation & Development, 34: 2548–2559. (https://doi.org/10.1002/ldr.4627)

Qi, X., Li, Q., Yue, Y., Liao, C., Zhai, L., Zhang, X., Wang, K., Zhang, C., Zhang, M., Xiong, Y. 2021. Rural–urban migration and conservation drive the ecosystem services improvement in China Karst: A case study of HuanJiang County, Guangxi. Remote Sensing, 13, 566 (https://doi.org/10.3390/rs13040566 )

Wang, K., Zhang, C., Chen, H., Yue, Y., Zhang, W., Zhang, M., Qi, X., Fu, Z. 2019. Karst landscapes of China: pattern, ecosystem processes, and ecosystem services. Landscape Ecology, 34(3): 2743–2763 (https://doi.org/10.1007/s10980-019-00912-w)  

Zhang, C., Walters, D, & Kovacs, J.M. In press. 2019. The use of small unmanned aerial systems (UASs) in precision agriculture. In Stafford, J. Precision Agriculture for Sustainability. Cambridge, UK: Burleigh Dodds Science Publishing , pp 107-128 Link

Qi, X., Zhang, C., He, Y., & Wang, K. (2018). Fraction Vegetation Cover Extraction Using High Spatial Resolution Imagery in Karst Areas. In He, Y. & Weng, Q. High Spatial Resolution Remote Sensing. Boca Raton, Florida, United States: CRC Press, pp. 347-359 Link

 Qi, X., Zhang, C., Wang, K. 2017. Comparing remote sensing methods for rocky desertification monitoring at sub-pixel level in a highly heterogeneous karst region. Scientific Reports 9: 13368 Link 

Zhang, C., Qi, X., Wang, K., Zhang, M., Yue, Y. 2017. The application of geospatial techniques in monitoring karst vegetation recovery in southwest China - a review. Progress in Physical Geography, 41: 450-477 (doi: 10.1177/0309133317714246)  

Tong, X., Wang, K., Yue, Y., Brandt, M., Liu, B., Zhang, C., Liao, C., Fensholt, R. 2017. Quantifying the effectiveness of ecological restoration projects on long term vegetation dynamics in the karst regions of Southwest China. International Journal of Applied Earth Observation & Geoinformation, 54: 105–113 (doi: 10.1016/j.jag.2016.09.013)

 Flores-de-Santiago, F., Kovacs, J.M., Wang, J., Flores-Verdugo, F., Zhang, C., & González-Farías, F. 2016. Examining the influence of seasonality,
condition, and species composition on mangrove leaf pigment contents and laboratory based spectroscopy data. Remote Sensing, 8: 226.
(doi: 10.3390/rs8030226)

Wang, J., Wang, K., Zhang, M., Zhang, C. 2015. Impacts of climate change and human activities on vegetation cover in hilly southern China. Ecological
, 81:451-461. (doi: 10.1016/j.ecoleng.2015.04.022)

 Zhang, C., Kovacs, J.M., Liu, Y., Flores-Verdugo, F., & Flores-de-Santiago, F. 2014. Separating mangrove species and conditions using laboratory hyperspectral data: a case study of a degraded mangrove forest of the Mexican Pacific. Remote Sensing, 6: 11673-11688 (doi: 10.3390/rs61211673)  

Zhang, C., Walters, D, & Kovacs, J.M. 2014. Applications of low altitude remote sensing in agriculture upon farmers' requests - a case study in Northeastern Ontario, Canada. PLoS ONE, 9: e112894 (doi: 10.1371/journal.pone.0112894

Qi, X., Wang, K., Zhang, C., Chen, H., & Zhang, W. 2014. Effects of the implementation of ecological restoration policies on soil organic carbon storage in a discontinuous soil region. Acta Agriculture Scandinavica, Section B – Plant Soil Science, 64: 97-108 (doi: 10.1080/09064710.2013.865780

Wilson, J.H., Zhang, C., & Kovacs, J.M. 2014. Separating crop species in Northeastern Ontario using hyperspectral data. Remote Sensing, 6: 925-945 (doi: 10.3390/rs6020925

Kovacs, J.M., Jia, X., Flores-de-Santiago, F., Zhang, C., & Flores-Verdugo, F. 2013. Assessing relationships between Radarsat-2 C-band and structural parameters of a degraded mangrove forest. International Journal of Remote Sensing, 34: 7002-7019 (doi: 10.1080/01431161.2013.813090

Quan, C., Han, S., Utescher, T., Zhang, C., & Liu, Y.S. 2013. Validation of temperature–precipitation based aridity index: Paleoclimatic implications. Palaeogeography, Palaeoclimatology, Palaeoecology, 386: 86-95 (doi:10.1016/j.palaeo.2013.05.008

Kovacs, J.M., Lu, X.X., Flores-de-Santiago, F., Zhang, C., Flores-Verdugo, F., & Jiao, X. 2013. Applications of ALOS PALSAR for monitoring biophysical parameters of a degraded black mangrove (Avicennia germinans) forest. ISPRS Journal of Photogrammetry and Remote Sensing, 82: 102-111 (doi:10.1016/j.isprsjprs.2013.05.004

Qi, X., Wang, K., & Zhang, C. 2013. Effectiveness of ecological restoration projects in a karst region of southwest China assessed using vegetation succession mapping. Ecological Engineering, 54: 245-253 (doi: 10.1016/j.ecoleng.2013.01.002)

 Zhang, C., Kovacs, J.M., Wachowiak, M.P., & Flores-Verdugo, F. 2013. Relationship between hyperspectral measurements and mangrove leaf nitrogen concentrations. Remote Sensing, 5: 891-908 (doi: 10.3390/rs5020891)  

Zhang, C. & Kovacs, J.M. 2012. The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture, 13: 693-712 (doi: 10.1007/s11119-012-9274-5)  

Zhang, C., Liu, Y., Kovacs, J.M., Flores-Verdugo, F., Flores-Santiago, F., & Chen, K. 2012. Spectral response to varying levels of leaf pigments collected from a degraded mangrove forest. Journal of Applied Remote Sensing, 6 (063501): 1-14 (doi: 10.1117/1.JRS.6.063501)

Chen, K., Gunter, C., & Zhang, C. 2012. How global is U.S. Major League Baseball? A geographic perspective. GeoJournal, 77: 429-444 (doi: 10.1007/s10708-011-9406-x)

 Kovacs, J. M., Liu, Y., Zhang, C., Flores-Verdugo., F., & Flores-Sandiago, F. 2011. A field based statistical approach for validating a remotely sensed mangrove forest classification scheme of Isla La Palma, Sinaloa, Mexico. Wetlands Ecology and Management, 19: 409-421 (doi: 10.1007/s11273-011-9225-3

Zhang, M., Zhang, C., Wang, K., Liu, H., Yue, Y., Qi, X., & Fan, F. 2011. Spatiotemporal variations of Karst ecosystem service values in Northwest Guangxi, China. Environmental Management, 49: 933-944 (doi: 10.1007/s00267-011-9735-z

Yang, Q., Wang, K., Zhang, C., Yue, Y., Tian, R., & Fan, F. 2011. Spatio-temporal evolution of rocky desertification and its driving forces in karst area of Northwest Guangxi, China. Environmental Earth Science, 64: 383-393 (doi: 10.1007/s12665-010-0861-3

Zhang, M., Wang, K., Zhang, C., Chen, H., Liu, H., Luffman, I., & Qi, X. 2011. Using the radial basis function network model to assess rocky desertification in Northwest Guangxi, China. Environmental Earth Science, 64: 69-76 (doi: 10.1007/s12665-010- 0498-2

Kovacs, J.M., Zhang, C., & Flores, F. 2008. Mapping coastal wetland using C-band ENVISAT ASAR and Landsat optical data. Ciencias Marina, 34: 407-418  

Zhang, C. & Guo, X. 2008. Monitoring northern mixed grassland health using broadband satellite imagery. International Journal of Remote Sensing, 29: 2257-2271 (doi: 10.1080/01431160701408378)  

Zhang, C., Guo, X., & Wilmshurst, J. 2008. Monitoring temporal heterogeneity in a protected mixed grassland ecosystem using 10-day NDVI composite. Prairie Forum, 33: 145-166 

Chen, K., Kennedy, J.,Kovacs, J.M., & Zhang, C. 2007. A spatial perspective for predicting enrollment in a regional pharmacy school. GeoJournal, 70:133-143 Link  

Zhang, C. & Guo, X. 2007. Measuring biological heterogeneity in the northern mixed grassland: A remote sensing approach. The Canadian  Geographer, 51: 462-474 Link  

Zhang, C., Guo, X., Wilmshurst, J., & Sissons, R. 2006. Application of Radarsat imagery to grassland biophysical heterogeneity assessment. Canadian Journal of Remote Sensing, 32: 281-287. Link

Journal referee: Agriculture, Agriculture and Forest Meteorology, Applied Geography, Biological Engineering, Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Canadian Journal of Remote Sensing, Canadian Water Resources Journal, Catena, Computers and Electronics in Agriculture, Computers and Geosciences, Digital Earth, Diversity, Environmental Management, Ecological Engineering, Environmental Challenges, Environmental Monitoring and Assessment, Frontiers in Public Health, Geocarto International, Geoforum, Geoinformatics & Geostatistics, Hydrology and Earth System Sciences, IEEE Transactions on Geoscience and Remote Sensing, ISPRS Photogrammetry and Remote Sensing, International Journal of Remote Sensing and Remote Sensing Letters,  Journal of Applied Remote Sensing, Journal of Environmental Management, Journal of Mountain Science, Journal of Unmanned Vehicle Systems, Landscape and Urban Planning, Marine Geodesy, Photogrammetric Engineering and Remote Sensing, PLOS ONE, Precision Agriculture, Remote Sensing, Remote sensing applications: Society and Environment, Remote Sensing of Environment, Sensors, Science of the Total Environment, Trees, Wetlands.