GOOGLE SCHOLAR
BOOK EDITED
He, Y., and Q., Weng. 2018. High Spatial Resolution Remote Sensing: Data, Analysis, and Applications. Boca Raton, FL: CRC Press/Taylor and Francis, pp. 381.
REFEREED JOURNAL ARTICLES (Student’s names in bold)
2023
Lee, H., Y. He, M. E. Isaac, A. Roberto. 2023. Investigating Crop Performance on Urban Green Roofs Using Hyperspectral Data. Ecological Informatics. 2024, 102599, https://doi.org/10.1016/j.ecoinf.2024.102599 (IF: 5.1).
Li, W., Q. Liu, Y. Zhang, Y. Wang, Y. Yuan, Y. Jia, and Y. He. 2023. Few-Shot Hyperspectral Image Classification Using Meta Learning and Regularized Finetuning. IEEE Transactions on Geoscience and Remote Sensing. doi: 10.1109/TGRS.2023.3328263.(IF: 8.2)
Guo, Y., Y. Xiao, F. Hao, X. Zhang, J. Chen, K.Beurs, Y. He , and Y. Fu. 2023. Comparison of different machine learning algorithms for predicting maize grain yield using UAV-based hyperspectral images. International Journal of Applied Earth Observation and Geoinformation. 124, 103528, https://doi.org/10.1016/j.jag.2023.103528. (IF: 7.5)
Lyu, M., X. Lu, Y. Shen, Y. Tan, L. Wan, Q. Shu, Y. He, Y. He. 2023. UAV time-series imagery with novel machine learning to estimate heading dates of rice accessions for breeding. Agricultural and Forest Meteorology. 341, 109646, https://doi.org/10.1016/j.agrformet.2023.109646. (IF: 6.2)
Cherifa, E., Feilhauer, H., Berger, K., Dao, P.D., Ewald, M., Hank, T.B., He., Y., Kovachi, K.R., Lu, B., Townsend, P.A., and T., Kattenborn. 2023. From spectra to plant functional traits: Transferable multi-trait models from heterogeneous and sparse data. Remote Sensing of Environment. 292. https://doi.org/10.1016/j.rse.2023.113580. (IF: 13.85).
Qiang, C., J. Leydon, and Y. He. 2023. Impact of COVID-19 Restrictions on the Urban Thermal Environment of Edmonton, Canada. Environment Management. 72, 862–882, https://link.springer.com/article/10.1007/s00267-023-01813-0. (IF: 3.644).
Wang, Y., Z. Ma, Y. He, W. Yu, J. Chang, D. Peng, X. Min, H. Guo, Y. Xiao, L. Gao, and Z. Shi. 2023. Vegetation disturbances characterization in the Tibetan Plateau from 1986 to 2018 using Landsat time series and field observations. Environmental Research Letters. 18, 014016. DOI 10.1088/1748-9326/acab1b (IF: 6.973).
2022
Xu. M., R. Liu, J. M. Chen, Y. Liu, A. Wolanin, H. Croft, L. He, R. Shang, W. Ju, Y. Zhang, Y. He, R. Wang. 2022. A 20 year time-series of global leaf chlorophyll content maps from MODIS imagery. IEEE Transactions on Geoscience and Remote Sensing. 60:1-13. DOI: 10.1109/TGRS.2022.3204185 (IF: 6.870).
Guo, Y., Y. Xiao, M. Li, F. Hao, X. Zhang, H. Sun, K.Beurs, Y.H. Fu, and Y. He. 2022. Identifying crop phenology using maize height constructed from multi-sources images. International Journal of Applied Earth Observation and Geoinformation. 115, 103121, https://doi.org/10.1016/j.jag.2022.103121.
Xu. M., R. Liu, J. M. Chen, R. Shang, Y. Liu, L. Qi, H. Croft, W. Ju, Y. Zhang, Y. He, F. Qiu, J. Li, Q. Lin. 2022. Retrieving global leaf chlorophyll content from MERIS data using a neural network method. ISPRS P&RS. 192: 66-82. DOI: https://doi.org/10.1016/j.isprsjprs.2022.08.003 (IF: 8.979).
Mantripragada, K., P.D. Dao, Y. He and F.Z. Qureshi. 2022. The Effects of spectral dimensionality reduction on hyperspectral pixel classification: a case study. PLOS ONE. 14:17(7):e0269174. DOI: 10.1371/journal.pone.0269174 (IF: 3.240).
Zhu, T., F. Hisey, and Y. He. 2022. Use of interactive storytelling trailers to engage students in an online learning environment. Active Learning in Higher Education. https://doi.org/10.1177/14697874221107574 (IF: 4.765).
He, Y., Dosanjh, M., Shang, J., Liu, J., Drury, C., Yang, X., Yang, J., Dao, P.D., Axiotis, A., and C. Proctor. 2022. Mapping crop fractional green canopy cover using high spatial resolution thermal and optical remote sensing in Southern Ontario, Canada. Geomatica. https://doi.org/10.1139/geomat-2021-0016.
Marajh, L., and Y. He. 2022. Temperature variation and climate resilience action within a changing landscape. Remote Sensing. 2022, 14(3), 701; https://doi.org/10.3390/rs14030701 (IF: 4.848).
Proctor, C., Pereira, C., Jin, T., Lim, G., and Y. He. 2022. Linking the spectra of decomposing litter to ecosystem processes: tandem close range hyperspectral imagery and decomposition metrics. Remote Sensing. 14(2), 370; https://doi.org/10.3390/rs14020370 (IF: 4.848)
2021
Lu, B., and Y. He. 2021. Assessing the impacts of species composition on the accuracy of mapping chlorophyll content in heterogeneous ecosystems. Remote Sensing. 13(22), 4671. https://doi.org/10.3390/rs13224671 (IF: 4.848).
Dao, P.D., A. Axiotis, and Y. He. 2021. Mapping native and invasive grassland species and characterizing topography-driven species dynamics using high spatial resolution hyperspectral imagery. International Journal of Applied Earth Observations and Geoinformation. 104: 102542. https://doi.org/10.1016/j.jag.2021.102542. (IF: 5.993).
Bonney, M. T., and Y. He, 2021. Temporal connections between long-term Landsat time-series and tree rings in an urban-rural temperate forest. International Journal of Applied Earth Observations and Geoinformation. 103: 102523, https://doi.org/10.1016/j.jag.2021.102523 (IF: 5.933).
Dao, P.D., Y. He, and C. Proctor. 2021. Plant drought impact detection using ultra high resolution hyperspectral images and machine learning. International Journal of Applied Earth Observations and Geoinformation. 102: 102364. https://doi.org/10.1016/j.jag.2021.102364 (IF: 5.933).
Proctor, C., P.D. Dao, and Y. He. 2021. Close-range, heavy-duty hyperspectral imaging for tracking drought impacts using the PROCOSINE model. Journal of Quantitative Spectroscopy and Radiative Transfer. https://doi.org/10.1016/j.jqsrt.2021.107528 (IF: 3.047).
Lu, B., C. Proctor, and Y. He. 2021. Different Versions of PROSPECT and PROSAIL for Estimating Properties of Photosynthetic and Non-photosynthetic Vegetation. GIScience & Remote Sensing. https://doi.org/10.1080/15481603.2021.1877435 (IF: 5.965).
Proctor, C., and Y. He. 2021. Modelling Root Exudate Accumulation Gradients to Estimate Net Exudation Rates by Peatland Soil Depth. Plants. https://doi.org/10.3390/plants10010106 (IF: 2.762).
Dao, P.D., K. Mantripragada, Y. He, F.Z. Qureshi. 2021. Improving Hyperspectral Image Segmentation by Applying Inverse Noise Weighting and Outlier Removal for Optimal Scale Selection. ISPRS Journal of Photogrammetry and Remote Sensing. 171: 348-366. https://doi.org/10.1016/j.isprsjprs.2020.11.013 (IF: 7.319).
2020
Bonney, M. T., Y. He, and S. Myint. 2020. Contextualizing the 2019-20 Australian bushfires: Quantifying landscape-level influences on past severity and recovery with Landsat and Google Earth Engine. Remote Sensing. 12(23), 3942. https://doi.org/10.3390/rs12233942 (IF: 4.509).
He, Y., J. Yang, and X. Guo. 2020. Green Vegetation Cover Dynamics in a Heterogeneous Grassland: Spectral Unmixing of Landsat Time Series from 1999 to 2014. Remote Sensing. 12(22), 3826. doi.org/10.3390/rs12223826 (IF: 4.509)
Lu, B., P.D. Dao, J. Liu, Y. He, and J. Shang. 2020. Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture. Remote Sensing. 12: 2659. doi.org/10.3390/rs12162659 (IF: 4.509)
Croft, H., J.M. Chen, G. Mo, S Luo, X. Luo, L. He, A. Gonsamo, J. Arabian, Y. Zhang, A. Simic, T.L. Noland, Y. He, L. Homolová, Z. Malenovský, Q. Yi, J. Beringer, R. Amiri, L. Hutley, P. Arellano, C. Stahl, and D. Bonal. 2020. The global distribution of leaf chlorophyll content. Remote Sensing of Environment. 236: 111479. https://doi.org/10.1016/j.rse.2019.111479 (IF: 8.218)
2019
Kaluskar, S., A. Richards, C. Johnson, A. Langlois, Y. He, D. Kim, and G. Arhonditsis. 2019. Development of a model ensemble to predict Peary caribou populations in the Canadian Arctic Archipelago. Ecosphere. 10(12): e02976. https://doi.org/10.1002/ecs2.2976 (IF: 5.273)
Bonney, M. T., and Y. He. 2019. Attributing drivers to spatio-temporal changes in tree density across a suburbanizing landscape since 1944. Landscape and Urban Planning. 192, 103652, https://doi.org/10.1016/j.landurbplan.2019.103652 (IF: 5.144)
He Y., J. Yang, J. Caspersen, and T. Jones. 2019. An operational workflow of deciduous-dominated forest species classification: crown delineation, gap elimination, and object-based classification. Remote Sensing. 11(18), 2078. https://doi.org/10.3390/rs11182078. (IF: 3.406)
Lu, B., and Y. He. 2019. Evaluating Empirical Regression, Machine Learning, and Radiative Transfer Modelling for Estimating Vegetation Chlorophyll Content Using Bi-Seasonal Hyperspectral Images. Remote Sensing. 11(17), 1979. doi.org/10.3390/rs11171979 (IF: 4.118)
Lu, B., and Y. He. 2019. Leaf area index estimation in a heterogeneous grassland using optical, SAR, and DEM data. Canadian Journal of Remote Sensing. https://doi.org/10.1080/07038992.2019.1641401(IF: 2.553)
Laamrani, A., A. Berg, P. Voroney, H. Feilhauer, L. Blackburn, M. March, P.D. Dao, Y. He, and R.C. Martin. 2019. Ensemble identification of spectral bands related to soil organic carbon levels over an agricultural field in southern Ontario, Canada. Remote Sensing. 2019, 11(11), 1298; doi.org/10.3390/rs11111298 (IF: 4.118)
Lu, B., Y. He, and Dao, P.D. 2019. Comparing the Performance of Multispectral and Hyperspectral Images for Estimating Vegetation Properties. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2019.2910558. (IF: 2.777)
Proctor, C., and, Y. He. 2019. Quantifying Peatland Plant Vertical Root Distribution for Estimating the Interface with the Anoxic Zone. Plant and Soil, 1-18. doi.org/10.1007/s11104-019-04079-w (IF: 3.306)
Xu, J., Y. Zheng, Y. He, F, Zhu, B. Mai, S. Wang, M. Zhang, X. Zhao, L. Wang, L., Xu, L. Ding, and Z. Guo. 2019. Estimating stomatal conductance and partitioning total ozone uptake over a winter wheat field. Atmospheric Pollution Research, Available online 4 January 2019, https://doi.org/10.1016/j.apr.2018.12.018 (5-year IF: 2.299)
Dao, P.D., Y. He, and B. Lu. 2019. Maximizing the quantitative utility of airborne hyperspectral imagery for studying plant physiology: an optimal sensor exposure setting procedure and empirical line method for atmospheric correction. International Journal of Applied Earth Observations and Geoinformation. 77: 140-150. https://doi.org/10.1016/j.jag.2018.11.010 (IF: 5.933)
2017
Lu, B., and Y. He. 2017. Optimal spatial resolution of UAV imagery for species classification in a heterogeneous ecosystem. GIScience and Remote Sensing. 1-16, https://doi.org/10.1080/15481603.2017.1408930 (IF: 3.049)
Proctor, C., B. Lu, and Y. He. 2017. Determining the absorption coefficients of decaying pigments in decaying monocot leaves. Remote Sensing of Environment. 199: 137-153. https://doi.org/10.1016/j.rse.2017.07.007 (5-year IF: 7.388)
Lu, B., Y. He, and H. Liu. 2017. Mapping vegetation biophysical and biochemical properties using Unmanned Aerial Vehicles (UAV)-acquired imagery. International Journal of Remote Sensing. 1-23. dx.doi.org/10.1080/01431161.2017.1363441 (IF: 1.724)
Proctor, C., and Y. He. 2017. Quantifying root extracts and exudates of sedge and shrub in relation to root morphology. Soil Biology and Biochemistry. 114: 168-180, 2017. https://doi.org/10.1016/j.soilbio.2017.07.006 (5-year IF: 5.041)
Lu, B., and Y. He. 2017. Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland. ISPRS Journal of Photogrammetry and Remote Sensing. 128: 73-85. https://doi.org/10.1016/j.isprsjprs.2017.03.011(5-year IF: 5.062)
Tong, A., and Y. He. 2017. Estimating and mapping chlorophyll content for a heterogeneous grassland: Comparing prediction power of a suite of vegetation indices across scales between years. ISPRS P&RS. 126: 146-167. https://doi.org/10.1016/j.isprsjprs.2017.02.010 (5-year IF: 5.062)
Yang, J., Y. He, and J. Caspersen. 2017. Region merging using local spectral angle thresholds: a more accurate method for hybrid segmentation of remote sensing images. Remote Sensing of Environment. 192: 137-148. https://doi.org/10.1016/j.rse.2016.12.011 (5-year IF: 7.388)
Yang, J. and Y. He. 2017. Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery. International Journal of Applied Earth Observation and Geoinformation; 54: 53-64. (5-Year IF: 3.904)
Mui, A., B. Caverhill, M.J- Fortin, B. Johnson, and Y. He. 2017. Using multiple metrics to estimate seasonal landscape connectivity for Blanding's turtles (Emydoidea blandingii) in a fragmented landscape. Landscape Ecology. doi:10.1007/s10980-016-0456-9 (IF: 3.657)
2016
Yang, J., Y. He, J. Caspersen, and T. Jones. 2016. Delineating individual tree crowns in an uneven-aged, mixed broadleaf forest using multi-spectral watershed segmentation and multi-scale fitting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 99: 1-12. (IF: 2.145)
Murfitt, J., Y. He, J. Yang, A. Mui, and K. Demille. 2016. Ash decline assessment in Emerald Ash Borer infested natural forests using high spatial resolution images. Remote Sensing; 8(3), 256; doi:10.3390/rs8030256. (IF: 3.180)
Xu, J., Y. Zheng, Y. He, and R. Wu. 2016. The effect of elevated ozone concentrations with varying shading on dry matter loss in a winter wheat-producing region in China. PLOS ONE; 11(1):e0145446. doi: 10.1371/journal.pone.0145446. (IF: 3.234)
2015
Yang, J., T. Jones, J. Caspersen, and Y. He. 2015. Object-based canopy gap segmentation and classification: quantifying the pros and cons of integrating optical and LiDAR data. Remote Sensing; 7 (12): 15917-15932. (IF: 3.180)
Mui, A., C.B. Edge, J. Paterson, B. Caverhill, B. Johnson, J.D. Litzgus, and Y. He. 2015. Nesting sites in agricultural landscapes are potential sinks for turtle populations. Canadian Journal of Zoology; 2016, 94(1): 61-67. 10.1139/cjz-2015-0154. (IF: 1.303)
Lu, B., Y. He, and A. Tong. 2015. Evaluation of spectral indices for estimating burn severity in semi-arid grasslands. International Journal of Wildland Fire; 25(2) 147-157. www.publish.csiro.au/paper/WF15098.htm ( IF: 2.506)
Mui, A., Y. He, and Q. Weng. 2015. An object-based approach to delineate wetlands across landscapes of varied disturbance with high spatial resolution satellite imagery. ISPRS P&RS; 109: 30-46. (5-Year IF: 4.652)
He, Y., Z. Ma, X. Guo. 2015. Grassland productivity simulation: integrating remote sensing and an ecosystem process model. In Li J. and Yang X. (eds): Monitoring and Modeling of Global Changes: A Geomatics Perspective, Springer Remote Sensing/Photogrammetry, DOI 10.1007/978-94-017-9813-6_8.
Yang, J., Y. He, and Q. Weng. 2015. An automated method to parameterize segmentation scale by enhancing intra-segment homogeneity and inter-segment heterogeneity. IEEE Geoscience and Remote Sensing Letters; 12(6): 1282-1286. (5-Year IF: 1.98)
Yang, J., Y. He, J. Caspersen, and T. Jones. 2015. A discrepancy measure for segmentation evaluation from the perspective of object recognition. ISPRS Journal of Photogrammetry and Remote Sensing; 101: 186-192. (5-Year IF: 4.202)
Yang, J., Y. He, and J. Caspersen. 2015. Fully constrained linear spectral unmixing based global shadow compensation for high resolution satellite imagery of urban areas. International Journal of Applied Earth Observation and Geoinformation; 38: 88-98. (5-Year IF: 2.809)
2014
Tong, A., and Y. He. 2014. Remote sensing of grassland chlorophyll content: Assessing the spatial-temporal performance of spectral indices. IGARSS 2014, Quebec, Canada (IEEE: EI).
Yang, J., Y. He, J. Caspersen, and T. Jones. 2014. A multi-band watershed segmentation method for individual tree crown delineation from high spatial resolution multispectral aerial image. IGARSS 2014, Quebec, Canada (IEEE: EI).
Lu, B., and Y. He. 2014. Analyzing a North American prairie wildfire using remote sensing imagery. IGARSS 2014, Quebec, Canada (IEEE: EI).
He, Y. 2014. The effect of precipitation on vegetation cover over three landscape units in a protected semi-arid grassland: temporal dynamics and suitable climatic index. Journal of Arid Environments; 109:74-82. (5-Year IF: 2.120)
He, Y. 2014. The relationship between an invasive shrub and soil moisture: seasonal interactions and spatially covarying relations. ISPRS Int. J. Geo-Inf. 3: 1139-1153.
Yang, J., P. Li, and Y. He. 2014. A multi-band approach to unsupervised scale parameter selection for multi-scale image segmentation. ISPRS Journal of Photogrammetry and Remote Sensing; 94:13-24. (5-Year IF: 4.202)
Yang, J., Y. He, and T. Oguchi. 2014. An endmember optimization approach for linear spectral unmixing of fine-scale urban imagery. International Journal of Applied Earth Observation and Geoinformation; 27: 137-146. (5-Year IF: 2.809)
2013
Proctor, C, and Y. He. 2013. Estimation of foliar pigment concentration in floating Macrophytes using hyperspectral vegetation indices. International Journal of Remote Sensing. 34(22): 8011-8027. (5-Year IF: 1.67)
He, Y. 2013. Estimating grassland chlorophyll content from leaf to landscape level: bridging the gap in spatial scales. In Q. Weng (ed.) Scale Issues in Remote Sensing. John Wiley and Sons. Pg 127-138.
Jiang, X., B. Lu, and Y. He. 2013. Response of the turbidity maximum zone to fluctuations of sediment discharge from river to estuary in the Changjiang Estuary (China). Journal of Estuarine, Coastal and Shelf Science. 131: 24-30. (5-Year IF: 2.804)
Wong, K. and Y. He. 2013. Estimating grassland chlorophyll content using remote sensing data at the species, canopy, and landscape scales. Canadian Journal of Remote Sensing, 39(2): 155-166. (5-Year IF: 1.27)
Proctor, C., Y. He, and V. Robinson. 2013. Texture augmented detection of Macrophyte species using Decision Trees. ISPRS Journal of Photogrammetry and Remote Sensing. 80, 10-20. (5-Year IF: 4.026)
Tong, A., and Y. He, 2013. Remote sensing of leaf area index in a mixed grassland ecosystem: comparing SPOT, Landsat, MODIS, and AVHRR data. Journal of Applied Remote Sensing. 7 (1), 073599; doi: 10.1117/1.JRS.7.073599. (5-Year IF: 1.33)
Shen, L., Y. He, and X. Guo. 2013. Suitability of the normalized difference vegetation index and the adjusted transformed soil-adjusted vegetation index for spatially characterizing Loggerhead Shrike habitats in North American mixed prairie. Journal of Applied Remote sensing. 7 (1), 073574; doi: 10.1117/1.JRS.7.073574. (5-Year IF: 1.33)
Shen, L., Y. He, and X. Guo, 2013. Exploration of loggerhead shrike habitats in Grassland National Park based on in situ measurements and satellite-derived adjusted transformed soil-adjusted vegetation index. Remote sensing. 5: 452-453. (5-Year IF: 2.171)
2012
He, Y., P. Dixon, J.F. Wilmshurst, and X. Guo. 2012. AVHRR NDVI baseline for natural vegetation ecosystems in Northern Canadian national parks. J Geophys Remote Sensing 1:103. doi:10.4172/jgrs.1000103.
He, Y., A. Khan, and A. Mui. 2012. Integrating remote sensing and wavelet analysis for studying fine-scaled vegetation spatial variation among three different ecosystems, Photogrammetric Engineering & Remote Sensing. 78(2): 161–168. (AAG REMOTE SENSING SPECIALTY GROUP 2010 Early Career Award Winner). (5-Year IF: 2.04)
Proctor, C., V. Robinson, and Y. He. 2012. Multispectral detection of European Frog-bit in the South Nation River using Quickbird imagery. Canadian Journal of Remote Sensing, 38(4): 1-11. (5-Year IF: 1.27)
He, Y., X. Guo, P., Dixon, and J. Wilmshurst. 2012. NDVI variation and its relations to climate in Canadian Ecozones. The Canadian Geographer. 56(4): 492-507.
2011
Banerjee, S., Y. He, X. Guo, and B.C. Si. 2011. Spatial relationships between leaf area index and topographic factors in a semiarid grassland. Australian Journal of Crop Science. 5(6):756-763.
Franklin, S.E., Y. He, A.D. Pape, X. Guo and G.J. McDermid. 2011. Landsat-comparable land cover maps using ASTER and SPOT images: a case study for large-area mapping programmes. International Journal of Remote Sensing. 32(8): 2185-2205.
Guo, X., S. Black and Y. He. 2011. Estimation of leaf CO2 exchange rates using a SPOT image. International Journal of Remote Sensing. 32(2), 353-366.
2010
He, Y., and A. Mui. 2010. Scaling up semi-arid grassland biochemical content from the leaf to the canopy level: challenges and opportunities. Sensors. 10: 11072-11087; doi:10.3390/s101211072. (5-Year IF: 2.395)
He, Y., S.E. Franklin, X. Guo, and G.B. Stenhouse. 2010. Object-oriented classification of multi-resolution images for the extraction of narrow linear forest disturbance. Remote Sensing Letters, 2(2): 147-155.
2009
He, Y., S.E. Franklin, X. Guo, and G.B. Stenhouse. 2009. Narrow-linear and small-area forest disturbance detection and mapping from high spatial resolution Imagery. Journal of Applied Remote Sensing, 3:033570.
He, Y., X. Guo, and J. Wilmshurst. 2009. Reflectance measures of grassland biophysical structure. International Journal of Remote Sensing. 30 (10): 2509-2521.
Wang, K., S.E. Franklin, X. Guo, Y. He and G. J. McDermid. 2009. Problems in remote sensing of landscapes and habitats. Progress in Physical Geography. 33 (6): 747-768.
BEFORE 2008
Dixon, P., Y. He, and X. Guo. 2008. Satellite monitoring of Northern ecosystems. Geomatica. 62 (2):151-158.
Li, Z., X. Guo, P. Dixon, and Y. He. 2008. Applicability of land surface temperature (LST) estimates from AVHRR satellite image composites in northern Canada. Prairie Perspectives. 11:119-130.
Guo, X., and Y. He. 2008. Mismatch of band sequence between image and header file: a potential error in SPOT L1A Products. Canadian Journal of Remote Sensing. 34(1): 1-4.
He, Y., X. Guo, and B.C. Si. 2007. Detecting grassland spatial variation by a wavelet approach. International Journal of Remote Sensing. 28 (7): 1527 – 1545.
He, Y., X. Guo, and J. Wilmshurst. 2007. Comparison of different methods for measuring LAI in a mixed grassland. Canadian Journal of Plant Science. 87: 803-813.
He, Y., X. Guo, and J. Wilmshurst. 2006. Studying mixed grassland ecosystems II: optimum pixel size. Canadian Journal of Remote Sensing. 32(2): 108-115.
He, Y., X. Guo, and J. Wilmshurst. 2006. Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices. Canadian Journal of Remote Sensing. 32(2): 98-107.
He, Y., and X., Guo. 2006. Leaf Area Index Estimation Using Remotely Sensed Data in a Mixed Grassland Ecosystem. Prairie Perspectives. 9(1):105-117.
He, Y., X., Guo, and Y. Zheng. 2005. Impact of Climate Change with Enhanced UV-B Radiation on Chinese Agricultural NPP. Prairie Perspectives. 8:50-60.