137. Xia, T., W. Ji, W. Li, C. Zhang and W. Wu. 2021. Phenology-based decision tree classification of rice-crayfish fields from Sentinel-2 imagery in Qianjiang, China. International Journal of Remote Sensing, 42(21): 8124-8144.
136. Kilany, M., C. Zhang, and W. Li. 2021. Optimization of urban land cover classification using an improved Elephant Herding Optimization algorithm and random forest classifier. International Journal of Remote Sensing, 42(15): 5731-5753. https://doi.org/10.1080/01431161.2021.1931533.
135. Zhang, P.; Hu, S.; Li, W.; Zhang, C.; Cheng, P. 2021. Improving Parcel-Level Mapping of Smallholder Crops from VHSR Imagery: An Ensemble Machine-Learning-Based Framework. Remote Sensing, 13(11): 2146. https://doi.org/10.3390/rs13112146.
134. Zhang, P., S. Hu, W. Li, C. Zhang, S. Yang, and S. Qu. 2021. Modeling fine-scale residential land price distribution: An experimental study using open data and machine learning. Applied Geography, 129: 102442.
133. Zhang, B., W. Li, N. Lownes, and C. Zhang. 2021. Estimating the impacts of proximity to public transportation on residential property values: An empirical analysis for Hartford and Stamford areas, Connecticut. ISPRS International Journal of Geo-Information. 10(2): 44. https://doi.org/10.3390/ijgi10020044.
132. Li, F., J. Yan, Y. Wei, J. Zeng, X. Wang, X. Chen, C. Zhang, W. Li, M. Chen, and G. Lü. 2021. PM2.5-bound heavy metals from the major cities in China: Spatiotemporal distribution, fuzzy exposure assessment and health risk management. Journal of Cleaner Production. 286: 124967. doi: 10.1016/j.jclepro.2020.124967.
131. Zhang, Z., A. Arshad, C. Zhang, S. Hussain, and W. Li. 2020. Unprecedented temporary reduction in global air pollution associated with COVID-19 forced confinement: A continental and city scale analysis. Remote Sensing, 12(15): 2420. https://doi.org/10.3390/rs12152420.
130. Yang, B., X. Chen, Z. Wang, W. Li, C. Zhang, and X. Yao. 2020. Analyzing land use structure efficiency with carbon emissions: A case study in the Middle Reaches of the Yangtze River, China. Journal of Cleaner Production, 274: 123076. https://doi.org/10.1016/j.jclepro.2020.123076.
129. Zhang, P., S. Hu, W. Li, and C. Zhang. 2020. Parcel-level mapping of crops in a smallholder agricultural area: A case of central China using single-temporal VHSR imagery. Computers and Electronics in Agriculture, 175: 105581. https://doi.org/10.1016/j.compag.2020.105581.
128. Qu, S., S. Hu, W. Li, H. Wang, C. Zhang, Q. Li. 2020. Interaction between urban land expansion and land use policy: An analysis using the DPSIR framework. Land Use Policy, 99: 104856. https://doi.org/10.1016/j.landusepol.2020.104856.
127. Zhai, R., C. Zhang, W. Li, X. Zhang, and X. Li. 2020. Evaluation of driving forces of land use and land cover change in New England area by a mixed method. ISPRS International Journal of Geo-information, 9(6): 350. doi: 10.3390/ijgi9060350.
126. Adams, A., X. Chen, W. Li, and C. Zhang. 2020. The disguised pandemic: The importance of data normalization in COVID-19 web mapping. Public Health, 183: 36-37. https://doi.org/10.1016/j.puhe.2020.04.034.
125. Zhou, X., L. Cheng, W. Li, C. Zhang, F. Zhang, F. Zeng, Z. Yan, X. Ruan, and M. Li. 2020. A comprehensive framework for patrol path planning in the marine environment. Applied Ocean Research, 100: 102155. https://doi.org/10.1016/j.apor.2020.102155.
124. Yang, S., S. Hu, W. Li, C. Zhang, and D. Song. 2020. Spatio-temporal nonstationary effects of impact factors on industrial land price in industrializing cities of China. Sustainability, 12(7): 2792. https://doi.org/10.3390/su12072792.
123. Zhang, C., T. Zhao, L. Usery, D. Varanka, and W. Li. 2020. Improving geospatial query performance of an interoperable geographic situation-awareness system for disaster response. Transactions in GIS, 24(2): 508-525. doi: 10.1111/tgis.12614.
122. Tian, J., B. Wang, C. Zhang, W. Li, and S. Wang. 2020. Mechanism of regional land use transition in underdeveloped areas of China: A case study of Northeast China. Land Use Policy, 94: 104538. https://doi.org/10.1016/j.landusepol.2020.104538.
121. Wan, M., W. Hu, M. Qu, W. Li, C. Zhang, J. Kang, Y. Hong, Y. Chen, and B. Huang. 2020. Rapid estimation of soil cation exchange capacity through sensor data fusion of portable XRF spectrometry and Vis-NIR spectroscopy. Geoderma, 363: 114163. https://doi.org/10.1016/j.geoderma.2019.114163.
120. Qu, S., S. Hu, W. Li, C. Zhang, Q. Li, and H. Wang. 2020. Temporal variation in the effects of impact factors on residential land prices. Applied Geography, 114: 102124. https://doi.org/10.1016/j.apgeog.2019.102124.
119. Li, X.-K., A. Seth, C. Zhang, R. Feng, X. Long, W. Li, and K. Liu. 2020. Evaluation of WRF-CMAQ simulated climatological mean and extremes of fine particulate matter of the United States and its correlation with climate extremes. Atmospheric Environment, 222: 117181. https://doi.org/10.1016/j.atmosenv.2019.117181.
118. Li, W., and C. Zhang. 2019. Markov chain random fields in the perspective of spatial Bayesian networks and optimal neighborhoods for simulation of categorical fields. Computational Geosciences, 23(5): 1087-1106. https://doi.org/10.1007/s10596-019-09874-z.
117. Zhai, R., W. Li, C. Zhang, W. Zhang, and W. Wang. 2019. The transiogram as a graphic metric for characterizing the spatial patterns of landscapes. Landscape Ecology, 34(9): 2103–2121. https://doi.org/10.1007/s10980-018-0760-7.
116. Zhang, W., W. Li, C. Zhang, and T. Zhao. 2019. Parallel computing solutions for Markov chain sequential simulation of categorical fields. International Journal of Digital Earth, 12(5): 566-582. doi: 10.1080/17538947.2018.1464073.
115. Yu, J., W. Li and C. Zhang. 2019. A framework of experimental transiogram modelling for Markov chain geostatistical simulation of landscape categories. Computers, Environment and Urban Systems, 73: 16–26. https://doi.org/10.1016/j.compenvurbsys.2018.07.007.
114. Qu, M., J. Chen, W. Li, C. Zhang, M. Wan, B. Huang, and Y. Zhao. 2019. Correction of in-situ portable X-ray fluorescence (PXRF) data of soil heavy metal for enhancing spatial prediction. Environmental Pollution, 254(A): 112993. https://doi.org/10.1016/j.envpol.2019.112993.
113. Yi, Y., Z. Zhang, W. Zhang, C. Zhang, W. Li, and T. Zhao. 2019. Semantic segmentation of urban buildings from VHR remote sensing imagery using deep convolutional neural network. Remote Sensing, 11(15), 1774. https://doi.org/10.3390/rs11151774.
112. Yang, S., H. Zhang, C. Zhang, W. Li, L. Guo, and J. Chen. 2019. Predicting soil organic matter content in a plain-to-hill transition belt using geographically weighted regression with stratification. Archives of Agronomy and Soil Science, 65(12): 1745–1757. doi: 10.1080/03650340.2019.1576171.
111. Li, X.-K., C. Zhang, W. Li, R.O. Anyah, and J. Tian. 2019. Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation. Journal of Cleaner Production, 223: 238-251. https://doi.org/10.1016/j.jclepro.2019.03.121.
110. Wan, M., M. Qu, W. Hu, W. Li, C. Zhang, H. Cheng, and B. Huang. 2019. Estimation of soil pH using PXRF spectrometry and Vis-NIR spectroscopy for rapid environmental risk assessment of soil heavy metals. Process Safety and Environmental Protection, 132: 73-81. https://doi.org/10.1016/j.psep.2019.09.025.
109. Zhang, W., W. Li, C. Zhang, D. Hanink, Y. Liu, and R. Zhai. 2018. Analyzing horizontal and vertical urban expansions in three East Asian megacities with the SS-coMCRF model. Landscape and Urban Planning, 177: 114-127. doi: 10.1016/j.landurbplan.2018.04.010.
108. Zhang, W., C. Witharana, W. Li, C. Zhang, X. Li, and J. Parent. 2018. Using deep learning to identify utility poles with crossarms and estimate their locations from Google Street View images. Sensors, 18(8), 2484, https://doi.org/10.3390/s18082484.
107. Wang, W., W. Li, C. Zhang and W. Zhang. 2018. Improving object-based land use/cover classification from medium resolution imagery by Markov chain geostatistical post-classification. Land, 7(1), 31. doi: 10.3390/land7010031.
106. Zhai, R., C. Zhang, J.M. Allen, W. Li, M.A. Boyer, K. Segerson, and K.E. Foote. 2018. Predicting land cover change in Long Island Sound Watersheds (LISW) and its effect on invasive species: A case study for glossy buckthorn. Annals of GIS, 24(2): 83-97. doi: 10.1080/19475683.2018.1450786.
105. Yu, J., C. Zhang, J. Wen, W. Li, D. Liu, and H. Xu. 2018. Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters. International Journal of Geographical Information Science, 32(9): 1884-1910. doi: 10.1080/13658816.2018.1463442.
104. Xu, H., C. Zhang, W. Li, W. Zhang, and H. Yin. 2018. Economic growth and carbon emission in China: a spatial econometric Kuznets curve? Zbornik Radova Ekonomskog Fakulteta u Rijeci - Proceedings of Rijeka Faculty of Economics, 36(1): 9-26. https://doi.org/10.18045/zbefri.2018.1.11.
103. Li, X., C. Zhang, and W. Li. 2017. Building block level urban land use information retrieval based on Google Street View images. GIScience & Remote Sensing, 54(6): 819-835, doi: 10.1080/15481603.2017.1338389.
102. Li, X.-K., C. Zhang, W. Li, and K. Liu. 2017. Evaluating the use of DMSP/OLS nighttime light imagery in predicting PM2.5 concentrations in the Northeastern United States. Remote Sensing, 9(6): 620. doi: 10.3390/rs9060620.
101. Yang, S., S. Hu, W. Li, C. Zhang, and J. A. Torres. 2017. Spatiotemporal effects of main impact factors on residential land price in major cities of China. Sustainability, 9(11), 2050; doi: 10.3390/su9112050.
100. Zhang, W., W. Li, C. Zhang, D. M. 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://dx.doi.org/10.1016/j.dib.2017.04.002.
99. Zhao, T., C. Zhang, and W. Li. 2017. Adaptive and optimized query interface for distributed WFS data. ISPRS International Journal of Geo-information, 6(4): 108. doi: 10.3390/ijgi6040108.
98. Zhang, W., W. Li, C. Zhang, D. M. 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. doi: 10.1016/j.compenvurbsys.2017.03.001.
97. 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. http://dx.doi.org/10.1080/01431161.2017.1302113.
96. Li, W. and C. Zhang, 2017. Comments on "Spatial hidden Markov chain models for estimation of petroleum reservoir categorical variables". Journal of Petroleum Exploration and Production Technology, 7(3): 905-909. doi: 10.1007/s13202-016-0312-0.
95. 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.
94. Du Z., Y. Gu, C. Zhang, F. Zhang, R. Liu, J. Sequeira, and W. Li. 2017. ParSymG: a parallel clustering approach for unsupervised classification of remotely sensed imagery. International journal of Digital Earth, 10(5): 471-489. http://dx.doi.org/10.1080/17538947.2016.1229818.
93. Zhai, R., C. Zhang, W. Li, M.A. 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.
92. Qu, M., W. Li, C. Zhang, B. Huang, and Y. Zhao. Spatial assessment of soil nitrogen availability and varying effects of related main soil factors on soil available nitrogen. Environmental Science: Processes & Impacts, 18(11): 1449-1457. doi: 10.1039/C6EM00407E.
91. Wang, W., C. Zhang, J.M. Allen, W. Li, M.A. Boyer, K. Segerson, 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(3): 25. doi:10.3390/land5030025.
90. Li, X., C. Zhang, W. Li, and Y. Kuzovkina. 2016. Environmental inequities in terms of different types of urban greenery in Hartford, Connecticut. Urban Forestry & Urban Greening, 18: 163-172.
89. Hu, S., S. Yang, W. Li, C. Zhang, and F. Xu. 2016. Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China. Applied Geography, 68: 48-56.
88. Zhang, W., W. Li and C. Zhang. 2016. Land cover post-classifications by Markov chain geostatistical cosimulation based on pre-classifications by different conventional classifiers. International Journal of Remote Sensing, 37(4): 926-949. http://dx.doi.org/10.1080/01431161.2016.1143136.
87. Li, X., W. Li, Q. Meng, C. Zhang, T. Jansco and K. Wu. 2016. Modeling 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.
86. Qu, M., W. Li, C. Zhang, B. Huang, and Y. Zhao. 2015. Assessing the pollution risk of soil Chromium based on loading capacity of paddy soil at a regional scale. Scientific Reports, 5: 18451; doi: 10.1038/srep18451.
85. Zhang, C., T. Zhao and W. Li. 2015. Towards an interoperable online volunteered geographic information system for disaster response. Journal of Spatial Science, 60(2): 257-275.
84. Li, X., C. Zhang, W. Li, Y. Kuzovkina, and D. Weiner. 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.
83. Zhang, C.T., Y. Yang, W. Li, C. Zhang, R.X. Zhang, Y. Mei, X.S. Liao, and Y.Y. Liu. 2015. Spatial distribution and ecological risk assessment of trace metals in urban soils in Wuhan, central China. Environmental Monitoring and Assessment, 187(9): 556, doi: 10.1007/s10661-015-4762-5.
82. Li, X., C. Zhang, and W. Li. 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.
81. Li, X., C. Zhang, W. Li, R. Ricard, Q. Meng, and W. Zhang. 2015. Assessing street-level urban greenery using Google street view and a modified green view index. Urban Forestry & Urban Greening, 14(3): 675-685.
80. Li, W., C. Zhang, M.R. Willig, D.K. 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.
79. Zhao, T., C. Zhang, L. Anselin, W. Li and K. Chen. 2015. A parallel approach for improving geo-SPARQL query performance. International Journal of Digital Earth, 8(5): 383-402.
78. Qu, M., B. Huang, W. Li, C. Zhang and Y. Zhao. 2015. Spatial uncertainty of joint health risk of multiple trace metals in rice grain in Jiaxing city, China. Environmental Science: Processes & Impacts, 17(1): 120-130.
77. Zhang, C., T. Zhao, L. Anselin, W. Li, and K. Chen. 2015. A Map-Reduce based parallel approach for improving query performance in a geospatial semantic web for disaster response. Earth Science Informatics, 8(3): 499-509.
76. Chen, C., K. Hu, W. Li, Z. Li and B. Li. 2015. Three-dimensional mapping of clay content in alluvial soils using hygroscopic water content. Environmental Earth Sciences, 73(8): 4339-4346.
75. Zhang, C., W. Li 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.
74. Qu, M., W. Li, C. Zhang, B. Huang, and Y. Zhao. 2014. Spatially nonstationary relationships between copper accumulation in rice grain and some related soil properties in paddy fields at a regional scale. Soil Science Society of America Journal, 78(5): 1765-1774.
73. Li, X., Q. Meng, W. Li, C. Zhang, T. Jansco, S. Mavromatis. 2014. An explorative study on the proximity of buildings to green spaces in urban areas using remotely sensed imagery. Annals of GIS, 20(3): 193-203.
72. Qu, M., W. Li, and C. Zhang, 2014. County-Scale Spatial Variability of Macronutrient Availability Ratios in Paddy Soils. Applied and Environmental Soil Science, vol. 2014, Article ID 689482, 10 pages, 2014.
71. Chen, C., K. Hu, W. Li, G. Wang and G. Liu. 2014. Estimation of the wet-end section of soil water retention curve using data in the dry-end section. Soil Science Society of America Journal, 78(6): 1878-1883.
70. Wang, K., C. Zhang, W. Li, J. Lin, and D. Zhang. 2014. Mapping soil organic matter with limited sample data using geographically weighted regression. Journal of Spatial Science, 59(1): 91-106.
69. Qu, M., W. Li, and C. Zhang, 2014. Spatial distribution and uncertainty assessment of potential ecological risks of soil heavy metals using sequential Gaussian simulation. Human and Ecological Risk Assessment, 20(3): 764-778.
68. Qu, M., W. Li, C. Zhang, and B. Huang. 2014. Geographically Weighted Regression and Its Application Prospect in Environmental and Soil Sciences. Soils, 46(1): 15–22 (in Chinese).
67. Qu, M., W. Li, C. Zhang, B. Huang, Y. Zhao. 2014. Estimating the pollution risk of cadmium in soil using a composite soil environmental quality standard. The Scientific World Journal, vol. 2014, Article ID 750879, http://dx.doi.org/10.1155/2014/750879.
66. Zhang, D., C. Zhang, W. Li, R. Cromley, D. Hanink, D. Civco, D. Travis. 2014. Restoration of the missing pixel information caused by contrails in multispectral remotely sensed imagery. Journal of Applied Remote Sensing, vol. 8(1), Article No. 083698 (January 06, 2014); doi: 10.1117/1.JRS.8.083698.
65. Li, W., C. Zhang, D. K. Dey, and M. R. Willig. 2013. Updating categorical soil maps using limited survey data by Bayesian Markov chain cosimulation. The Scientific World Journal (Soil Science Section), vol. 2013, Article ID 587284, 13 pages, doi:10.1155/2013/587284.
64. Qu, M., W. Li, C. Zhang, Y. Zhao, B. Huang, W. Sun, and W. Hu. 2013. Comparison of three methods for soil fertility quality spatial simulation with uncertainty assessment. Soil Science Society of America Journal, 77: 2182–2191.
63. Qu, M., W. Li, C. Zhang, S. Wang, Y. Yang and L. He. 2013. Source apportionment of heavy metals in soils using multivariate statistics and geostatistics. Pedosphere, 23(4): 437-444.
62. Wang, K., C. Zhang and W. Li. 2013. Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and ordinary cokriging. Applied Geography, 42: 73-85.
61. Qu, M., W. Li, and C. Zhang, 2013. Assessing the spatial uncertainty in soil nitrogen mapping through stochastic simulations with categorical land use information. Ecological Informatics, 16: 1-9.
60. Qu, M., W. Li, C. Zhang, B. Huang, and W. Hu. 2013. Source apportionment of soil heavy metal Cd based on the combination of receptor model and geostatistics. China Environmental Science, 33(5): 655-662, (in Chinese).
59. Zhang, B., W. Li, and C. Zhang, 2013. Statistical analyses of soil heavy metal pollution in the Wuhan Donghu High-tech Development Park. Environmental Chemistry, 32(9): 1714-1722 (in Chinese).
58. Zhang, C., T. Zhao, and W. Li. 2013. Towards improving query performance of Web Feature Services (WFS) for disaster response and management. ISPRS International Journal of Geo-Information, 2(1): 67-81.
57. Li, W. and C. Zhang. 2013. Some further clarification on Markov chain random fields and transiograms. International Journal of Geographical Information Science, 27(3): 423-430.
56. Qu, M., W. Li, and C. Zhang, 2013. Assessing the risk costs in delineating soil nickel contamination using sequential Gaussian simulation and transfer functions. Ecological Informatics, 13: 99-105.
55. Wang, S., W. Li, J. Li, X. Liu. 2013. Prediction of soil texture using FT-NIR spectroscopy and PXRF spectrometry with data fusion. Soil Science, 178(11): 626-638.
54. Wang, K., C. Zhang and W. Li. 2012. Comparison of geographically weighted regression and regression kriging for estimating the spatial distribution of soil organic matter. GIScience & Remote Sensing, 49(6): 915-932.
53. Li, W. and C. Zhang, 2012. Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorical fields’ with communications on some issues related to Markov chain geostatistics. International Journal of Geographical Information Science, 26(10): 1725–1739.
52. Li, W., C. Zhang and D.K. Dey, 2012. Modeling experimental cross transiograms of neighboring landscape categories with the gamma distribution. International Journal of Geographical Information Science, 26(4): 599-620.
51. Qu, M., W. Li, C. Zhang, and S. Wang, 2012. Effect of land use types on the spatial prediction of soil nitrogen. GIScience & Remote Sensing, 49(3): 397-411.
50. Li, W. and C. Zhang, 2012. Comments on ‘An efficient maximum entropy approach for categorical variable prediction’ by D. Allard, D. D’Or & R. Froidevaux. European Journal of Soil Science, 63(1): 120-124.
49. Yang, Y., W. Li and L. He. 2012. Spatial prediction of soil properties based on Bayesian maximum entropy and historical data. Highlights of Sciencepaper Online, 5(19): 1864-1870, (in Chinese).
48. Li, W. and C. Zhang, 2011. A Markov chain geostatistical framework for land-cover classification with uncertainty assessment based on expert-interpreted pixels from remotely sensed imagery. IEEE Transactions on Geoscience and Remote Sensing, 49(8): 2983-2992.
47. Zhang, B., W. Li, Y. Yang, S. Wang, and C. Cai, 2011. The Bayesian maximum entropy geostatistical approach and its application in soil and environmental sciences. Acta Pedologica Sinica, 48(4): 831-839, (in Chinese).
46. Yang, Y., W. Li, and L. He, 2011. Uniform expression of variogram nested model and parameter estimation in spatial prediction of soil properties. Transactions of the Chinese Society of Agricultural Engineering, 27(6): 85-89, (in Chinese).
45. Li, W., C. Zhang, D.K. Dey, and S. Wang, 2010. Estimating threshold-exceeding probability maps of continuous environmental variables with Markov chain random fields. Stochastic Environmental Research and Risk Assessment, 24(8): 1113-1126.
44. Zhang, C., T. Zhao, and W. Li, 2010. Automatic search of geospatial features for disaster and emergency management. International Journal of Applied Earth Observation and Geoinformation, 12(6): 409–418.
43. Zhang, C., T. Zhao, and W. Li, 2010. The framework for a geospatial semantic web based spatial decision support system for digital earth. International Journal of Digital Earth, 3(2): 111-134.
42. Li, W. and C. Zhang, 2010. Linear interpolation and joint model fitting of experimental transiograms for Markov chain simulation of categorical spatial variables. International Journal of Geographical Information Science, 24(6): 821-839.
41. Zhang, C., T. Zhao, W. Li, and J. Osleeb, 2010. Towards logic-based geospatial feature discovery and integration using web feature service and geospatial semantic web. International Journal of Geographical Information Science, 24(6): 903-923.
40. Li, W. and C. Zhang, 2010. Simulating spatial distribution of clay layer occurrence depth in alluvial soils with a Markov chain geostatistical approach. Environmetrics, 21(1): 21–32.
39. Li, W. and C. Zhang, 2009. Markov chain analysis. International Encyclopedia of Human Geography, 6: 455-460.
38. Zhang, C., W. Li, and D. Travis, 2009. Restoration of clouded pixels in multispectral remotely sensed imagery with cokriging. International Journal of Remote Sensing, 30(9): 2173-2195.
37. Zhang, C., Z. Peng, T. Zhao and W. Li, 2008. Transforming transportation data models from UML to OWL. Journal of the Transportation Research Board: Transportation Research Record, 2064: 81-89.
36. Zhang, C, and W. Li, 2008. Regional-scale modeling of the spatial distribution of surface and subsurface textural classes in alluvial soils using Markov chain geostatistics. Soil Use and Management, 24(3): 263-272.
35. Li, W., and C. Zhang, 2008. A single-chain-based multidimensional Markov chain model for subsurface characterization. Environmental and Ecological Statistics, 15(2):157-174.
34. Zhang, C. and W. Li, 2008. A comparative study of nonlinear Markov chain models in conditional simulation of categorical variables from regular samples. Stochastic Environmental Research and Risk Assessment, 22(2): 217-230.
33. Li, W. 2007a. Markov chain random fields for estimation of categorical variables. Mathematical Geology, 39(3): 321-335.
32. Li, W. 2007b. Transiograms for characterizing spatial variability of soil classes. Soil Science Society of America Journal, 71(3): 881-893.
31. Li, W. 2007c. A fixed-path Markov chain algorithm for conditional simulation of discrete spatial variables. Mathematical Geology, 39(2): 159-176.
30. Li, W., and C. Zhang, 2007. A random-path Markov chain algorithm for simulating categorical soil variables from random point samples. Soil Science Society of America Journal, 71(3): 656-668.
29. Zhang, C., W. Li, and T. Zhao, 2007. Geospatial data sharing based on geospatial semantic web technologies. Journal of Spatial Science, 52(2): 11-25.
28. Zhang, C. and W. Li, 2007. Comparing a fixed-path Markov chain geostatistical algorithm with sequential indicator simulation in categorical variable simulation from regular samples. GIScience & Remote Sensing, 44(3): 251-266.
27. Zhang, C., W. Li and D. Travis, 2007. Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach. International Journal of Remote Sensing, 28(22): 5103-5122.
26. Hu, K., R. White, D. Chen, B. Li and W. Li, 2007. Stochastic simulation of water drainage at the field scale and its application to irrigation management. Agricultural Water Management, 89 (1-2): 123-130.
25. Li, W. 2006. Transiogram: A spatial relationship measure for categorical data. International Journal of Geographical Information Science, 20(6): 693-699.
24. Li, W., and C. Zhang, 2006. A generalized Markov chain approach for conditional simulation of categorical variables from grid samples. Transactions in GIS, 10(4): 651-669.
23. Zhang, C., W. Li and M. Day, 2006. Effective protected-area boundary designation in China using a web-based spatial decision support system. Journal of Spatial Science, 51(2): 33-46.
22. Li, W. and C. Zhang, 2005. Application of transiograms to Markov chain modeling and spatial uncertainty assessment of land cover classes. GIScience & Remote Sensing, 42(4): 297-319.
21. Li, W., C. Zhang, J.E. Burt and A. Zhu, 2005. A Markov chain-based probability vector approach for modeling spatial uncertainties of soil classes. Soil Science Society of America Journal, 69(6): 1931-1942.
20. Zhang, C. and W. Li, 2005. The roles of Web Feature and Web Map Services in real-time geospatial data sharing for time-critical applications. Cartography and Geographical Information Science, 32(4): 269-283.
19. Zhang, C., W. Li and M. Day, 2005. Towards establishing effective protective boundaries for the Lunan Stone Forest using an online spatial decision support system. Acta Carsologica, 34(1): 151-167.
18. Zhang, C. and W. Li, 2005. Markov chain modeling of multinomial land-cover classes. GIScience & Remote Sensing, 42(1): 1-18.
17. Li, W., C. Zhang, J.E. Burt, A. Zhu and J. Feyen, 2004. Two-dimensional Markov chain simulation of soil type spatial distribution. Soil Science Society of America Journal, 68(5): 1479-1490.
16. Zhang, C., W. Li, M. Day and Z. Peng, 2003. GML-based interoperable geographical databases. Cartography, 32(2): 1-16.
15. Zhang, C., M. Day and W. Li, 2003. Land use and land cover change in the Lunan Stone Forest, China. Acta Carsologica, 32(2): 161-174.
14. Li, W., B. Li, Y. Shi, D. Jacques and J. Feyen, 2001. Effect of spatial variation of textural layers on regional field water balance. Water Resources Research, 37(5): 1209-1219.
13. Li, W., B. Li and Y. Shi, 1999. Markov-chain simulation of soil textural profiles. Geoderma, 92(1, 2): 37-53.
12. Li, W., B. Li and Y. Shi, 1999. Stochastic simulation models for regional field soil textural profiles. Acta Pedologica Sinica, 36(3): 289-300 (in Chinese).
11. Li, W., B. Li and Y. Shi, 1999. Application of Markov-chain theory to quantitatively describe the vertical change of textural layers in regional alluvial soils. Acta Pedologica Sinica, 36(1): 15-24 (in Chinese).
10. Li, B., W. Li and Y. Shi, 1998. Some distribution characteristics of regional soil textural layers in an alluvial plain. Acta Pedologica Sinica, 35(4): 433-440 (in Chinese).
9. Li, W., B. Li, Y. Shi and D. Tang, 1997. Application of the Markov chain theory to describe spatial distribution of textural layers. Soil Science, 162(9): 672-683.
8. Li, W., 1997. Progress of studies on equilibration of water, nitrogen and carbon cycling in terrestrial ecosystem. Progress in Geography, 16 supplement: 15-20 (in Chinese).
7. Li, W., D. Tang, Q. Wang and B. Yang, 1997. Moisture physical properties of Black Clay Soils and amelioration measures. Scientia Agricultura Sinica, 30(6): 30-35 (in Chinese).
6. Li, W., Q. Wang and B. Yang, 1996. Components and characteristics of humic substances in Black Clay Soils. Journal of Huazhong Agricultural University, 15(6): 527-533 (in Chinese).
5. Li, W., M. Zhang, H. Pang, Q. Wang and B. Yang, 1996. Characteristics of humic substances and their relationships with genesis of black clay soils in warm temperature zone of China. Acta Pedologica Sinica, 33(4): 433-438 (in Chinese).
4. Li, W., B. Li, and Y. Shi, 1996. Stochastic simulation of regional alluvial soil textural profiles and its application in soil water transformation (briefing). Journal of China Agricultural University, 1(5): 46, 62 (in Chinese).
3. Li, W. and Q. Wang, 1994. Components of clay minerals and discussion on the origin of smectite in black clay soils. Acta Agriculturae Universitatis Pekinensis, 20(2): 192-196 (in Chinese).
2. Li, W. and Q. Wang, 1993, Morphological features of black clay soils in China. Journal of Huazhong Agricultural University, 12(3): 245-249 (in Chinese).
1. Cheng, R., W. Li, and Y. Ai, 1993. Soil nutrition status and forest growth conditions in Shennongjia mountain region. Chinese Journal of Soil Science, 24(1): 11-13 (in Chinese).
2. Zhang, C., T. Zhao and W. Li. 2015. Geospatial Semantic Web. Springer, pp. 194. ISBN: 978-3-319-17800-4 (Print) 978-3-319-17801-1 (Online) (Monograph)
1. Tang, D., W. Li, and W. Cheng (eds.). 1997. Sustainable Agricultural Development in Huang-Huai-Hai Plain. Meteorology Press, Beijing, China. pp. 251. ISBN: 9787502924850 (in Chinese)
Other Articles and Extended Abstracts (in collections and conference proceedings, mostly peer-reviewed)
32. Li, W. and C. Zhang. 2015. Spatiotemporal Markov chain modeling of land use/cover changes: A preliminary study. The 23rd International Conference on Geoinformatics, June 19-21, 2015, Wuhan, China.
31. Zhang, W., W. Li, and C. Zhang. 2015. Comparison of land cover post-classifications by Markov chain random field cosimulation with different conventional classifiers. The 23rd International Conference on Geoinformatics, June 19-21, 2015, Wuhan, China.
30. Li, W. 2014. A review on advances in geostatistics. In: Huanchun Chen et al. (eds.), Collected Works for Commemorating Huakui Chen’s Centennial Birthday. Science Press, pp. 304-317 (in Chinese).
29. Zhang, C. and W. Li. 2014. Geospatial semantic web for spatial data sharing. In: M. Khosrow-Pour (ed.). Encyclopedia of Information Science and Technology (3rd ed.), IGI Global, p. 551-559.
28. Li, W. and C. Zhang. 2013. Updating categorical soil map with limited survey data by Bayesian Markov chain co-simulation. GeoComputation 2013 Extended Abstracts, May 23-25, Wuhan University, China. http://www.geocomputation.org/2013/papers/55.pdf.
27. Zhang, R., J. Ba, Y. Ma, S. Wang, J. Zhang, and W. Li. 2012. A comparative study on wheat leaf area index by different measurement methods. Proceedings of 1st International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2012, Shanghai, 02-04 Aug., 2012; Article number 6311671, p. 365-369.
26. Li, W. and C. Zhang. 2012. A Bayesian Markov chain approach for land use classification based on expert interpretation and auxiliary data. GIScience 2012, Sept. 19-21, Columbus, Ohio. http://www.giscience.org/proceedings/abstracts/giscience2012_paper_137.pdf.
25. Qu, M., W. Li, S. Wang, and L. He. 2012. Using direct sequential simulation to assess the regional scale spatial uncertainty of soil total nitrogen content (article). 2012 International Conference on Remote Sensing, Environment and Transportation Engineering. June 1-3, 2012, Nanjing, China, p. 537-540, (in Chinese).
24. Zhang, B., W. Li, Q. Huang and S. Wang, 2011. Risk assessment of soil Cd exceedance in the Wuhan Donghu Hgh-tech Developing Zone by disjunctive kriging (article). In: The International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2011), June 24-26, 2011, Nanjing, China, p. 1548-1551 (in Chinese).
23. Qu, M., W. Li, L. He, S. Wang, S. Li and J. Ba, 2011. Integration of categorical information of land use maps in spatial prediction of soil available Cu in Hanchuan County, China (article). In: The International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2011), June 24-26, 2011, Nanjing, China, p. 1301-1304, (in Chinese).
22. Li, W and C. Zhang, 2010. Quantification of spatial uncertainty in categorical fields (article). In: The International Workshop on Advances in Spatial Statistics and Intelligence. June 22-23, 2010, Wuhan, Hubei, China.
21. Zhang, B., Y. Yang, W. Li, M. Qu and S. Wang, 2010. Multivariate and geostatistical analysis of soil heavy metals in the urban-rural transition zone of Wuhan (online article). In: Proceedings of the Conference on Environmental Pollution and Public Health (CEPPH 2010), September 10-12, 2010, Wuhan, China (in Chinese).
20. Zhang, C. and W. Li, 2010. Challenges for developing a Geospatial Semantic Web for automatic search of geospatial features (short article). In: Geoinformatics 2010, June 18-20, Beijing, CD-Room.
19. Li, W. and C. Zhang, 2010. Geostatistical mapping of threshold-exceeding probabilities of environmental pollutants (article). In: The Workshop on Pollution Remediation and Process Control in International Petroleum Industry, Sept. 27-29, Beijing (in Chinese).
18. Zhang, C. and W. Li, 2009. Towards spatial data discovery and integration using Geospatial Semantic Web techniques (short article). In: The 6th International Symposium on Digital Earth (ISDE6). Sept. 9-12, 2009. Beijing, China, CD-Room.
17. Zhang, C. and W. Li, 2009. Markov chain simulation of land cover classes with spatial uncertainty assessment (short article). In: Proceedings of MultiTemp 2009 - The Fifth International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, July 28-30, 2009, Groton, Connecticut, CD-Room.
16. Zhang, C., T. Zhao, and W. Li, 2008. An interoperable spatial decision support system based on geospatial semantic web technologies. In: Proceedings of SPIE, vol. 7144, 71442B (2008); DOI: 10.1117/12.812831; Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, June 28-29, Guangzhou, 2008.
15. Li, W. and C. Zhang, 2008. Mapping the probabilities of soil clay layer thickness exceeding some threshold values with Markov chain geostatistics. In: T.J. Cova, H.J. Miller, K. Beard, A.U. Frank, M.F. Goodchild, (eds.) GIScience 2008, Park City, UT, Sept 23-26, 2008, pp. 270-274.
14. Li, W. and C. Zhang, 2008. Simulating the vertical two-dimensional structures of alluvial soil textural layers from borehole observations (article). In: Proceedings of 3rd Global Workshop on Digital Soil Mapping, Logan, UT, Sept 30 - Oct 3, 2008.
13. Li, W., and C. Zhang, 2007. The nonlinear Markov chain geostatistics. In: Proceedings of IAMG 2007, Geomathematics and GIS Analysis of Resources, Environment, and Hazards, IAMG 2007 Annul Conference. Aug. 26-31, Beijing, China. pp. 573-578.
12. Li, W., and C. Zhang, 2007. A middle-insertion algorithm for Markov chain simulation of soil layering. In: Proceedings of ACMGIS 2007, 15th ACM International Symposium on Advances in Geographic Information Systems, Nov. 7-9, 2007, Seattle, USA. pp. 328-331.
11. Li, W. and C. Zhang. 2006. Visualizing spatial uncertainty of multinomial classes in area-class mapping (online article). AutoCarto 2006, June 26-28, Vancouver, Washington, 13 pages. http://www.cartogis.org/publications/autocarto-2006/lizhang.pdf/view.
10. Zhang, C., and W. Li. 2004. Predictive area class mapping of multinomial land-cover categories using Markov chains. pp. 239-242. In: GIScience 2004 - The Third International Conference on Geographic Information Science, Maryland.
9. Zhang, C., Z. Peng, W. Li and M. Day, 2003. GML-based interoperable geographical databases (online article). UCGIS Summer Assembly 2003. University Consortium of Geographic Information Science.
8. Li, W., D. Jacques and J. Feyen, 1999. Application of Markov-chain simulation of soil textural profiles to regional field-water balance. In: J. Feyen and K. Wiyo (ed.) Modeling of Transport Processes in Soils at Various Scales in Time and Space. pp. 693-700. Wageningen Press, Wageningen, the Netherland.
7. Li, W. and D. Tang, 1997. Relationship between regional agricultural integrated exploitation and agricultural sustainable development in North China Plain. Chinese Youth Agricultural Science Academic Annual, Collection A. pp. 824-829 (in Chinese).
6. Li, W. and F. Yuan, 1997. Observation and study of some moisture physical properties in black clay soils. In: Soil Science Association of Chinese Youth, (ed.), Soil and Plant Nutrition Sciences Toward 21 Century. pp. 40-45. China Agri. Press, Beijing (in Chinese).
5. Li, W. and D. Tang, 1997. Relationship between regional agricultural integrated exploitation and agricultural sustainable development in North China Plain. In: D. Tang et al., (eds.), Sustainable Agricultural Development in Huang-Huai-Hai Plain (collected articles from the Symposium on Agricultural Development in Huang-Huai-Hai Plain, Yucheng, Shandong, 1996). Meteorology Press, Beijing, China (in Chinese).
4. Li, W., B. Li and Y. Shi, 1995. Progress of studies on field spatial variability and soil water transfer models. In: Y. Shi et al., (ed.), Progress of Studies on Applied and Fundamental Theories of Water-Saving Agriculture. pp. 64-71, China Agri. Press, Beijing (in Chinese).
3. Li, W., B. Li and Y. Shi, 1995. Spatial probability distribution characteristics of soil textural layer thickness, first clay layer emerging depths and soil textural types in North China Plain. In: Y. Shi et al., (ed.), Studies on Water-Saving Agriculture in North China Plain (in Chinese).
2. Li, W. and Q. Wang, 1993. Genetic characteristics and systematical classification of Chinese Shajiang black soils (presentation and article). In: Editor Committee of Chinese Soil Taxonomy (ed.), Progress of Studies on Chinese Soil Taxonomy, pp. 263-266. Science Press, Beijing, China (in Chinese).
1. Li, W. and Q. Wang, 1992. A discussion on the parent material origin of black soil horizon in Shajiang black soils. In: Z. Gong, (ed.), Environment Change of Soils. pp. 75-78. China Science and Technology Press, Beijing (in Chinese).
Theses and postdoctoral reports
5. Calculating and Analyzing the Averaged Solute Concentration Distribution along Soil Profile at Field Scale Based on Random Lognormally-Distributed Saturated Hydraulic Conductivity. Postdoctoral report, Israel Institute of Technology, Haifa, Israel, Nov., 2000 (with Prof. Peter Indelman).
4. Two-Dimensional Stochastic Simulation of Spatial Distributions of Soil Layers and Types Using the Coupled Markov Chain Method. Postdoctoral report, Catholic University of Leuven, Leuven, Belgium, June, 1999 (with Prof. Jan Feyen).
3. A Study on Regional Field Water Balance. Postdoctoral report, Institute of Geography, Chinese Academy of Science, Beijing, July, 1997.
2. Stochastic Simulation of Soil Textural Profiles at Regional Scale and Its Application in Estimating Field Water Balance. PhD dissertation, China Agricultural University, Beijing, June, 1995.
1. Genesis and Classification of Shajiang Black Soils. Master thesis, Huazhong Agricultural University, Wuhan, June, 1991.