Publication

  1. Carolyn Ariori. C., M.E. Aiello-Lammens, and J. A. Silander Jr. 2017. Plant invasion along an urban-to-rural gradient in northeast Connecticut. Journal of Urban Ecology (in revision).

  2. Merow, C., S. Bois, J.M. Allen, Y. Xie, and J.A. Silander.  2016.  Climate change both facilitates and inhibits invasive plant ranges in New England.  Proceedings of the National Academy of Science 114(16): E3276-E3284.

  3. Zhao T., C. Zhang and W. Li. 2017. Adaptive and Optimized RDF Query Interface for Distributed WFS Data. ISPRS International Journal of Geo-Information 6, 108; doi:10.3390/ijgi6040108. http://www.mdpi.com/2220-9964/6/4/108.

  4. Zhang W., W. Li, C. Zhang and W. B. Ouimet. 2017. Detecting horizontal and vertical urban growth from medium resolution imagery and its relationships with major socioeconomic factors. International Journal of Remote Sensing, 38(12):3704-3734.

  5. Zhang W., W. Li, C. Zhang. D. Hanink, X. Li, and W. Wang. 2017. Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View. Computers, Environment and Urban Systems, 64: 215-228.        http://dx.doi.org/10.1016/j.compenvurbsys.2017.03.001.

  6. Zhang W., W. Li, C. Zhang. D. Hanink, X. Li, and W. Wang. 2017. Parcel feature data derived from Google Street View images for urban land use classification in Brooklyn, New York City. Data in Brief, 12: 175-179. http://doi.org/10.1016/j.dib.2017.04.002.

  7. Zhang W., W. Li, C. Zhang, and X. Li. 2017. Incorporating Spectral Similarity into Markov Chain Geostatistical Cosimulation for Reducing Smoothing Effect in Land Cover PostClassification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(3): 1082- 1095. DOI: 10.1109/JSTARS.2016.2596040.

  8. Zhai, R., C. Zhang, W. Li, M. Boyer, and D. Hanink. 2016. Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data. Land, 5(4), 44; doi:10.3390/land5040044. http://www.mdpi.com/2073-445X/5/4/44.

  9. Wang W., C. Zhang, J. M. Allen, W. Li, Mark A. Boyer, K. Segerson, and J. A. Silander, Jr. 2016. Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut. Land. 5, 25. doi:10.3390/land5030025.

  10. Li X., C. Zhang, W. Li, Y. A. Kuzovkina. 2016. Environmental inequities in terms of different types of urban greenery in Hartford, Connecticut. Urban Forestry and Urban Greening. 18, 163-172. doi:10.1016/j.ufug.2016.06.002.

  11. Li, X. and C. Zhang. 2016. Urban land use information retrieval based on scene classification of Google Street View images. Proceeding of GIScience 2016 (The Ninth International Conference on Geographic Information Science). Montreal, Canada, Sep. 27- 30th, 2016.

  12. Li, X. and C. Zhang. 2016. Urban land use information retrieval based on scene classification of Google Street View images. Proceeding of GIScience 2016 (The Ninth International Conference on Geographic Information Science). Montreal, Canada, Sep. 27- 30th, 2016. http://stko.geog.ucsb.edu/sdw16/paper_1.pdf

  13. Li, W, and C. Zhang. 2015. Spatiotemporal Markov Chain Modeling of Land Use/Cover Changes: A Preliminary Study. Proceedings of the 23th International Conference on Geoinformatics (Geoinformatics 2015), Wuhan, China. June 19-21, 2015.

  14. Zhang, C., Li, W., and D. Civco. 2014. Application of Geographically Weighted Regression to gaps-fill of SLC-off Landsat ETM+ satellite imagery. International Journal of Remote Sensing 35(22): 7650-7672.

  15. Li, W., C, Zhang, M. Willig, D. Dey, G. Wang, and L. You. 2015. Bayesian Markov Chain Random Field Cosimulation for Improving Land Cover Classification Accuracy. Mathematical Geosciences 47(2): 123-148.

  16. Zhang, W., W. Li, and C. Zhang. 2016. Land cover postclassifications by Markov chain geostatistical cosimulation based on pre-classifications by different conventional classifiers. International Journal of Remote Sensing, 37(4): 926-949.

  17. Li, X., W. Li, Q. Meng, C. Zhang, T. Jansco and K. Wu. 2016. Modelling building proximity to greenery in a three-dimensional perspective using multi-source remotely sensed data. Journal of Spatial Science, 61 (2): 389-403. http://dx.doi.org/10.1080/14498596.2015.1132642

  18. Li, X., Zhang, C., Li, W., Kuzovkina, Y. A., and Weiner, D. 2015. Who lives in greener neighborhoods? The distribution of street greenery and its association with residents’ socioeconomic conditions in Hartford, Connecticut, USA. Urban Forestry & Urban Greening, 14(4), 751-759.

  19. Li, X., Zhang, C., Li, W., Ricard, R., Meng, Q., and Zhang, W. 2015. Assessing street-level urban greenery using Google Street View and a modified green view index. Urban Forestry & Urban Greening, 14(3), 675-685.

  20. Li, X., Zhang, C., and Li, W. 2015. Does the Visibility of Greenery Increase Perceived Safety in Urban Areas? Evidence from the Place Pulse 1.0 Dataset. ISPRS International Journal of Geo-Information, 4(3), 1166-1183.

  21. Li, W., Zhang, C., Willig, M. R., Dey, D. K., Wang, G., and You, L. 2014. Bayesian Markov Chain Random Field Cosimulation for Improving Land Cover Classification Accuracy. Mathematical Geosciences, 47(2), 123-148.

 

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