Publications

 PUBLICATIONS:YEAR
1.Wei, Y., Yang, R., & Sun, D. (2023). Investigating Tropical Cyclone Rapid Intensification with an Advanced Artificial Intelligence System and Gridded Reanalysis Data. Atmosphere, 14 (2), 195.2023
2.Sha, D. (2023). Geophysical Feature Extraction and Spatiotemporal Analysis of Polar Sea Ice Using High Spatial Resolution Imagery. Mars.gmu.edu. http://hdl.handle.net/1920/130242023
1.Lou, A., Smith, S., Yang, C., Lan, H., & Li, Y. (2021). Al Based PM 2.5 Retrieval and Spatiotemporal Downscaling Using Earth Observation Data. Journal of Student-Scientists’ Research, 3.2022
2.Natarajan, A. V., Wang, K., Howell, K., Sha, D., & Yang, C. (2021). Developing Cloud-based Image Classification Management and Processing Service for High Spatial Resolution Sea Ice Imagery. 
Journal of Student-Scientists’ Research, 3.		2022
3.Kang, G., Lan, H., & Yang, C. (2021). Innovating a Computer Infrastructure for Spatiotemporal Studies. 
Journal of Student-Scientists’ Research, 3.		2022
4.Kim, J., S. Rapuri, E. Chuluunbaatar, E. Sumiyasuren, B. Lkhagvasuren, N. Budhathoki, M. Laituri. Developing and evaluating transit-based healthcare accessibility in a low- and middle-income country: A case study in Ulaanbaatar, Mongolia. Habitat International (in review). https://doi.org/10.1016/j.habitatint.2022.102729 2022
5.Liu, Q., Xu, H., Houser, P.R., Sun, D., Rice, M., Wang, L., Duffy, D.Q. and Yang, C., 2023. Cross-track infrared sounder cloud fraction retrieval using a deep neural network. Computers & Geosciences, 170, p.105268. https://doi.org/10.1016/j.cageo.2022.105268 2022
6.Springer book: The Geographies of COVID-19, M. Laituri, R. Richardson, J. Kim, publication – Oct/Nov 2022 https://link.springer.com/book/9783031117749  2022
7.Li, S., Goldberg, M., Kalluri, S., Lindsey, D. T., Sjoberg, B., Zhou, L., … & Sun, D. (2022). High Resolution 3D Mapping of Hurricane Flooding from Moderate-Resolution Operational Satellites. Remote Sensing , 14 (21), 5445.2022
8.Li, S., Sun, D., Goldberg, M. D., Kalluri, S., Sjoberg, B., Lindsey, D., … & Lander, K. (2022). A downscaling model for derivation of 3-D flood products from VIIRS imagery and SRTM/DEM. ISPRS Journal of Photogrammetry and Remote Sensing, 192, 279-298.2022
9.Lynnes, C., Little, M. M., Huang, T., Jacob, J. C., Yang, C. P., Hegde, M., & Zhang, H. (2022). Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations. Big Data Analytics in Earth, Atmospheric, and Ocean Sciences
, 137-151.		2022
10.Zifu Wang, Yudi Chen, Yun Li, Devika Kakkar, Wendy Guan, and et al (11). 9/7/2022. “Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method.” Vaccines, 10, 9. Publisher’s Version https://doi.org/10.3390/vaccines10091486 2022
11.Devika Kakkar, Jeffrey Blossom, and Wendy Guan. 8/5/2022. “RINX: A Solution for Information Extraction from Big Raster Datasets.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Publisher’s Version https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-245-2022 2022
12.Huang, T., Chung, N., Dunn, A., Hovland, E., Kang, J., Loubrieu, T., … & Liu, Q. (2022, July). An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
 (pp. 6574-6577). IEEE.		2022
13.Liu, Q., Srirenganathanmalarvizhi, A., Howell, K. and Yang, C., 2022. Tropospheric Nitrogen Dioxide Increases Past Pre-Pandemic Levels Due to Economic Reopening in India. Frontiers in Environmental Science. https://doi.org/10.3389/fenvs.2022.962891 2022
14.Alabduljabbar, A., Ma, R., Choi, S., Jang, R., Chen, S., & Mohaisen, D. (2022, May). Understanding the security of free content websites by analyzing their ssl certificates: A comparative study. In 
Proceedings of the 1st Workshop on Cybersecurity and Social Sciences
 (pp. 19-25).		2022
15.Li, Y., Yang, R., Su, H., & Yang, C. (2022). Discovering Precursors to Tropical Cyclone Rapid Intensification in the Atlantic Basin Using Spatiotemporal Data Mining. Atmosphere, 13(6), 882. https://doi.org/10.3390/atmos130608822022
16.Devika Kakkar, Ben Lewis, and Wendy Guan. 5/18/2022. “Interactive analysis of big geospatial data with high-performance computing: A case study of partisan segregation in the United States.” Transactions in GIS. Publisher’s Version https://doi.org/10.1111/tgis.12955 2022
17.Li, S., Sun, D., Goldberg, M., Kalluri, S., Lindsey, D., & Sjoberg, W. (2022, July). The Global GEO-LEO Flood Mapping System. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium
 (pp. 4773-4775). IEEE.		2022
18.Mengxi Zhang, Siqin Wang, Tao Hu, Xiaokang Fu, Xiaoyue Wang, Yaxin Hu, Briana Halloran, Zhenlong Li, Yunhe Cui, Haokun Liu, Zhimin Liu, and Shuming Bao. 3/3/2022. “Human mobility and COVID-19 transmission: a systematic review and future directions.” Annals of GIS. Publisher’s Version https://doi.org/10.1080/19475683.2022.2041725 2022
19.Junghwan Kim, Erica Hagen, Zacharia Muindi, Gaston Mbonglou, and Melinda Laituri. 6/1/2022. “An examination of water, sanitation, and hygiene (WASH) accessibility and opportunity in urban informal settlements during the COVID-19 pandemic: Evidence from Nairobi, Kenya.” Science of the Total Environment, 823. Publisher’s Version https://doi.org/10.1016/j.scitotenv.2022.153398 2022
20.Chaowei Phil Yang, Shuming Bao, Wendy Guan, Kate Howell, Tao Hu, Hai Lan, Yun Li, Qian Liu, Jennifer Smith, Anusha Srirenganathan, Theo Trefonides, Kevin Wang & Zifu Wang (2022) Challenges and opportunities of the spatiotemporal responses to the global pandemic of COVID-19, Annals of GIS, 28:4, 425-4342022
21.Qian Liu, Hui Xu, Paul R. Houser, Donglian Sun, Matthew Rice, Likun Wang, Daniel Q. Duffy, Chaowei Yang, Cross-track infrared sounder cloud fraction retrieval using a deep neural network, Computers & Geosciences, Volume 170, 2023, 105268.2022
22.Liu, X.; Kim, R.; Zhang, W.; Guan, W.W.; Subramanian, S.V. Spatial Variations of Village-Level Environmental Variables from Satellite Big Data and Implications for Public Health–Related Sustainable Development Goals. Sustainability 2022, 14, 10450.2022
1.Qian Liu, Juan Gu, Jingchao Yang, Yun Li, Dexuan Sha, Mengchao Xu, Ishan Shams, Manzhu Yu and Chaowei Yang, 2021. Urban Informatics, Cloud, Edge and Mobile Computing for Smart Cities, Springer.2021
2.Li, Y., Li, M., Rice, M., Zhang, H., Sha, D., Li, M., Su, Y. and Yang, C., 2021. The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective. International Journal of Environmental Research and Public Health, 18(3), p.996.2021
1.Yang, C., Sha, D., Liu, Q., Li, Y., Lan, H., Guan, W. W., … & Ding, A. (2020). Taking the pulse of COVID-19: A spatiotemporal perspective. International journal of digital earth, 13(10), 1186-1211.2020
2.Yang, C., Clarke, K., Shekhar, S., & Tao, C. V. (2020). Big Spatiotemporal Data Analytics: A research and innovation frontier.2020
3.Liu, Q., Malarvizhi, A.S., Liu, W., Xu, H., Harris, J.T., Yang, J., Duffy, D.Q., Little, M.M., Sha, D., Lan, H. and Yang, C., 2021. Spatiotemporal Changes in Global Nitrogen Dioxide Emission Due to COVID-19 Mitigation Policies. Science of The Total Environment, p.146027.2020
4.Liu, Q., Harris, J.T., Chiu, L.S., Sun, D., Houser, P.R., Yu, M., Duffy, D.Q., Little, M.M. and Yang, C., 2021. Spatiotemporal impacts of COVID-19 on air pollution in California, USA. Science of The Total Environment, 750, p.141592.2020
5.Liu, Q., Xu, H., Sha, D., Lee, T., Duffy, D.Q., Walter, J. and Yang, C., 2020. Hyperspectral Infrared Sounder Cloud Detection Using Deep Neural Network Model. IEEE Geoscience and Remote Sensing Letters. DOI: 10.1109/LGRS.2020.3023683.2020
6.Liu, Q., Sha, D., Liu, W., Houser, P., Zhang, L., Hou, R., Lan, H., Flynn, C., Lu, M., Hu, T. and Yang, C., 2020. Spatiotemporal Patterns of COVID-19 Impact on Human Activities and Environment in Mainland China Using Nighttime Light and Air Quality Data. Remote Sensing, 12(10), p.1576. (Interviewed and reported by the Atlantic Magazine)2020
7.Liu, Q., Liu, W., Sha, D., Kumar, S., Chang, E., Arora, V., Lan, H., Li, Y., Wang, Z., Zhang, Y., Zhang, Z., Harris, J. T., 2020. An Environmental Data Collection for COVID-19 Pandemic Research. Data, 5(3), p.68. (Featured as front cover of the Data Journal 3rd quarter issue of 2020)2020
8.Sha, D., Liu, Y., Liu, Q., Li, Y., Tian, Y., Beaini, F., … and Yang, C. (2020). A spatiotemporal data collection of viral cases for COVID-19 rapid response. Big Earth Data, 1-22.2020
9.Sha, D., Malarvizhi, A. S., Liu, Q., Tian, Y., Zhou, Y., Ruan, S., … and Yang, C. (2020). A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research. Data, 5(4), 118.2020
10.Sha, D., Miao, X., Lan, H., Stewart, K., Ruan, S., Tian, Y., … and Yang, C. (2020). Spatiotemporal analysis of medical resource deficiencies in the US under COVID-19 pandemic. PloS one, 15(10), e0240348.2020
11.Sha, D., Miao, X., Xu, M., Yang, C., Xie, H., Mestas-Nuñez, A. M., … and Yang, J. (2020). An on-demand service for managing and analyzing arctic sea ice high spatial resolution imagery. Data, 5(2), 39.2020
12.Li, Y., Jiang, Y., Yang, C., Yu, M., Kamal, L., Armstrong, E.M., Huang, T., Moroni, D. and McGibbney, L.J., 2020. Improving search ranking of geospatial data based on deep learning using user behavior data. Computers & Geosciences, 142, p.104520.2020
13.Li, Y., Horowitz, M.A., Liu, J., Chew, A., Lan, H., Liu, Q., Sha, D. and Yang, C., 2020. Individual-level fatality prediction of COVID-19 patients using AI methods. Frontiers in Public Health, 8, p.566.2020
14.Li, Y., Jiang, Y., Goldstein, J.C., Mcgibbney, L.J. and Yang, C., (2020). A Query Understanding Framework for Earth Data Discovery. Applied Sciences, 10(3), p.1127.2020
15.

Yu, M., Bambacus, M., Cervone, G., Clarke, Keith., Duffy D., Huang, Q., Li, J., Li, W., Li, Z., Liu, Q., Resch, B., Yang, J and Yang, C. (2020): Spatiotemporal event detection: a review, International Journal of Digital Earth, DOI: 10.1080/17538947.2020.1738569.

2020
16.van Genderen, J., Goodchild, M.F., Guo, H., Yang, C., Nativi, S., Wang, L. and Wang, C., (2020). Digital Earth Challenges and Future Trends. In Manual of Digital Earth (pp. 811-827). Springer, Singapore.2020
17.Li, Y., Yu, M., Xu, M., Yang, J., Sha, D., Liu, Q. and Yang, C., (2020). Big Data and Cloud Computing. In Manual of Digital Earth (pp. 325-355). Springer, Singapore.2020
1.Liu, Q., Li, Y., Yu, M., Chiu, L., Hao, X., Duffy, D. and Yang, C.P., (2019), December. Rainy Cloud Detection and Convective Precipitation Delineation Based on Deep Neural Network Method Using GOES-16 ABI Images. In AGU Fall Meeting 2019. AGU.2019
2.Yang, J., Yu, M. and Yang, C.P., (2019), December. Micro-scale Urban Heat Island Analytics with Anthropogenic Heat Releases and A Deep Learning Based Spatiotemporal Prediction Framework. In AGU Fall Meeting 2019. AGU.2019
3.Yang, C., Clarke, K., Shekhar, S. and Tao, C.V., (2019). Big Spatiotemporal Data Analytics: a research and innovation frontier.2019
4.Yu, M., Huang, Q., Qin, H., Scheele, C. and Yang, C., (2019). Deep learning for real-time social media text classification for situation awareness–using Hurricanes Sandy, Harvey, and Irma as case studies. International Journal of Digital Earth, 12(11), pp.1230-1247.2019
5.Chen, M., Yue, S., Lü, G., Lin, H., Yang, C., Wen, Y., Hou, T., Xiao, D. and Jiang, H., (2019). Teamwork-oriented integrated modeling method for geo-problem solving. Environmental modelling & software, 119, pp.111-123.2019
6.Gao, Y., Zhao, L., Wu, L., Ye, Y., Xiong, H. and Yang, C., (2019), July. Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 3638-3646).2019
7.Yue, S., Chen, M., Yang, C., Shen, C., Zhang, B., Wen, Y. and Lü, G., (2019). A loosely integrated data configuration strategy for web-based participatory modeling. GIScience & Remote Sensing, 56(5), pp.670-698.2019
8.Hu, F., Li, Z., Yang, C. and Jiang, Y., (2019). A graph-based approach to detecting tourist movement patterns using social media data. Cartography and Geographic Information Science, 46(4), pp.368-382.2019
9.Shams, I., Li, Y., Yang, J., Yu, M., Yang, C., Bambacus, M., Lewis, R., Nuth, J.A., Oman, L., Leung, R. and Seery, B.D., (2019). Planetary Defense Mitigation Gateway: A One-Stop Gateway for Pertinent PD-Related Contents. Data, 4(2), p.47.2019
10.Yang, C., Yu, M., Li, Y., Hu, F., Jiang, Y., Liu, Q., Sha, D., Xu, M. and Gu, J., (2019). Big Earth data analytics: A survey. Big Earth Data, 3(2), pp.83-107.2019
11.Yang, J., Yu, M., Qin, H., Lu, M. and Yang, C., (2019). A Twitter Data Credibility Framework—Hurricane Harvey as a Use Case. ISPRS International Journal of Geo-Information, 8(3), p.111.2019
12.Liu, Q., Li, Y., Yu, M., Chiu, L.S., Hao, X., Duffy, D.Q. and Yang, C., (2019). Daytime Rainy Cloud Detection and Convective Precipitation Delineation Based on a Deep Neural Network Method Using GOES-16 ABI Images. Remote Sensing, 11(21), p.2555.2019
13.Sun, D., Li, Y., Zhan, X., Houser, P., Yang, C., Chiu, L. and Yang, R., (2019). Land Surface Temperature Derivation under All Sky Conditions through Integrating AMSR-E/AMSR-2 and MODIS/GOES Observations. Remote Sensing, 11(14), p.17042019
14.Li, Y., Jiang, Y., Gu, J., Lu, M., Yu, M., Armstrong, E.M., Huang, T., Moroni, D., McGibbney, L.J., Frank, G. and Yang, C., (2019). A Cloud-Based Framework for Large-Scale Log Mining through Apache Spark and Elasticsearch. Applied Sciences, 9(6), p.1114.2019
15.Yang, C., Fu, P., Goodchild, M.F. and Xu, C., (2019). Integrating GIScience Application Through Mashup. In CyberGIS for Geospatial Discovery and Innovation (pp. 87-112). Springer, Dordrecht.2019
1.Shams, I., Barbee, B., Bambacus, M., Yang, C.P., Yu, M. and Jiang, Y., (2018), December. Planetary Defense Mitigation Gateway. In AGU Fall Meeting Abstracts.2018
2.Lu, M., Chen, M., Wang, X., Yu, M., Jiang, Y. and Yang, C., (2018). 3D modelling strategy for weather radar data analysis. Environmental earth sciences, 77(24), p.804.2018
3.Yu, M., Yang, C. and Jin, B., (2018). A framework for natural phenomena movement tracking–Using 4D dust simulation as an example. Computers & geosciences, 121, pp.53-66.2018
4.Xia, J., Yang, C. and Li, Q., (2018). Building a spatiotemporal index for earth observation big data. International journal of applied earth observation and geoinformation, 73, pp.245-252.2018
5.Xia, J., Yang, C. and Li, Q., (2018). Using spatiotemporal patterns to optimize Earth Observation Big Data access: Novel approaches of indexing, service modeling and cloud computing. Computers, Environment and Urban Systems, 72, pp.191-203.2018
6.Lynnes, C., Little, M.M., Huang, T., Jacob, J.C., Yang, C.P., Hegde, M. and Zhang, H., 2018. Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations.2018
7.Hu, F., Yang, C., Jiang, Y., Li, Y., Song, W., Duffy, D.Q., Schnase, J.L. and Lee, T., (2018). A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data. International Journal of Digital Earth, pp.1-19.2018
8.Jiang, Y., Li, Y., Yang, C., Hu, F., Armstrong, E.M., Huang, T., Moroni, D., McGibbney, L.J. and Finch, C.J., (2018). Towards intelligent geospatial data discovery: a machine learning framework for search ranking. International journal of digital earth, 11(9), pp.956-971.2018
9.Zheng, L., Sun, M., Luo, Y., Song, X., Yang, C., Hu, F. and Yu, M., (2018). Utilizing MapReduce to Improve Probe-Car Track Data Mining. ISPRS International Journal of Geo-Information, 7(7), p.287.2018
10.Hu, F., Yang, C., Schnase, J.L., Duffy, D.Q., Xu, M., Bowen, M.K., Lee, T. and Song, W., (2018). ClimateSpark: An in-memory distributed computing framework for big climate data analytics. Computers & geosciences, 115, pp.154-166.2018
12.Yu, M., Yang, C. and Li, Y., (2018). Big data in natural disaster management: a review. Geosciences, 8(5), p.165.2018
13.Hu, F., Xu, M., Yang, J., Liang, Y., Cui, K., Little, M. M., … & Yang, C. (2018). Evaluating the Open Source Data Containers for Handling Big Geospatial Raster Data. ISPRS International  Journal of Geo-Information, 7(4), 144.2018
14.Jiang, Y., Li, Y., Yang, C., Hu, F., Armstrong, E. M., Huang, T., … & Finch, C. J. (2018). A Smart Web-Based Geospatial Data Discovery System with Oceanographic Data as an Example. ISPRS International Journal of Geo-Information, 7(2), 62.2018
15.Rezgui, A., Malik, Z., Xia, J., Liu, K., & Yang, C. (2013). Data-intensive spatial indexing on the clouds. Procedia Computer Science, 18, 2615-2618.2018
16.Rice, M. T., Jacobson, D., Pfoser, D., Curtin, K. M., Qin, H., Coll, K., … & Aburizaiza, A. O. (2018). Quality Assessment and Accessibility Mapping in an Image-Based Geocrowdsourcing Testbed. Cartographica: The International Journal for Geographic Information and Geovisualization, 53(1), 1-14.2018
17.Fuhrmann, S. (2018). User-Centered Design for Geoinformation Technologies.2018
18.Li, S., Sun, D., Goldberg, M. D., Sjoberg, B., Santek, D., Hoffman, J. P., … & Holloway, E. (2018). Automatic near real-time flood detection using Suomi-NPP/VIIRS data. Remote Sensing of Environment, 204, 672-689.2018
19.Paolo Corti; Benjamin Lewis; Athanasios Tom Kralidis, Hypermap Registry: an open source, standards-based geospatial registry and search platform, Springer Open Publications, Open Geospatial Data, Software and Standards. April 2018.2018
20.Corti, P., Kralidis, A.T., Lewis, B., 2018. Enhancing discovery in spatial data infrastructures using a search engine. PeerJ Computer Science.2018
21.Paolo Corti and Ben Lewis. Implementing an Open Source Spatiotemporal Search Platform for Spatial Data Infrastructures. PeerJ Computer Science. April 2018.2018
22.Blodgett, D., Dornblut, I., Atkinson, R., Lieberman, J., Smith, D., Simons, B. Arctur, D., Beaufils, M., Grellet, S. Corchero, A., OGC® WaterML 2: Part 3 – Surface Hydrology Features (HY_Features) – Conceptual Model, Open Geospatial Consortium, 2018. http://docs.opengeospatial.org/is/14-111r6/14-111r6.html.2018
23.Josh Lieberman, Devika Kakkar, Benjamin Lewis, Weihe Wendy Guan and Todd Mostak, GPU-accelerated query and analysis of large spatiotemporal datasets applied to the National Water Model, AAG Annual Meeting. New Orleans. April 2018.2018
24.Irmischer, I. J and Clarke, K. C. (2018) Measuring and modeling the speed of human navigation. Cartography and Geographic Information Science 45 , 2, 177-186.2018
25.Seda Şalap-Ayça, Piotr Jankowski, Keith C Clarke, Phaedon C Kyriakidis & Atsushi Nara (2018) A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model, International Journal of Geographical Information Science, 32:4, 637-662, DOI: 10.1080/13658816.2017.14069442018
26.Martellozzo,F., Amato, F. Murgante, B. and Clarke, K. C. (2018) Modelling the impact of urban growth on agriculture and natural land in Italy to 2030. Applied Geography. 91, 156–16.2018
27.Aerts, J. C. J. H., Botzen, W. J., Clarke, K. C., Cutter, S. L., Hall, J.. W., Merz, B., Michel-Kerjan, E. Mysiak, J. , Surminski, S. and Kunreuther, H. (2018) Integrating human behaviour dynamics into flood disaster risk assessment. Nature—Climate Change, Perspective. doi.org/10.1038/s41558-018-0085-1.2018
45.Jiang, Y., Yang, C. P., Armstrong, E. M., Huang, T., Moroni, D. F., McGibbney, L. J., & Greguska III, F. R. (2017, December). Optimizing Earth Data Search Ranking using Deep Learning and Real-time User Behaviour. In AGU Fall Meeting Abstracts.2017
46.Xu, M., Hu, F., Yang, J., Yu, M., & Yang, C. P. (2017, December). Data Container Study for Handling array-based data using Hive, Spark, MongoDB, SciDB and Rasdaman. In AGU Fall Meeting Abstracts.2017
47.Li, Y., Jiang, Y., Yang, C. P., Armstrong, E. M., Huang, T., Moroni, D. F., … & McGibbney, L. J. (2017, December). A Geospatial Data Recommender System based on Metadata and User Behaviour. In AGU Fall Meeting Abstracts.2017
48.Armstrong, E. M., Yang, C. P., Moroni, D. F., McGibbney, L. J., Jiang, Y., Huang, T., … & Finch, C. J. (2017, December). Building a better search engine for earth science data. In AGU Fall Meeting Abstracts.2017
49.Yang, C. P., Bambacus, M., Duffy, D., & Little, M. M. (2017, December). A Big Data Platform for Storing, Accessing, Mining and Learning Geospatial Data. In AGU Fall Meeting Abstracts.2017
50.Jiang, Y., Li, Y., Yang, C., Liu, K., Armstrong, E. M., Huang, T., … & Finch, C. J. (2017). A comprehensive methodology for discovering semantic relationships among geospatial vocabularies using oceanographic data discovery as an example. International Journal of Geographical Information Science, 31(11), 2310-2328.2017
51.Li, Y., Yang, R., Yang, C., Yu, M., Hu, F., & Jiang, Y. (2017). Leveraging LSTM for rapid intensifications prediction of tropical cyclones. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 4.2017
52.Jiang, Y., Li, Y., Yang, C., Hu, F., Armstrong, E. M., Huang, T., … & Finch, C. J. (2017). Towards intelligent geospatial data discovery: a machine learning framework for search ranking. International Journal of Digital Earth, 1-16.2017
53.Bambacus, M., Yang, C. P., Leung, R. Y., Barbee, B., Nuth, J. A., Seery, B., … & Xu, M. (2017). A Planetary Defense Gateway for Smart Discovery of relevant Information for Decision Support.2017
54.Yu, M., & Yang, C. (2017). A 3D multi-threshold, region-growing algorithm for identifying dust storm features from model simulations. International Journal of Geographical Information Science, 31(5), 939-961.2017
55.Yang, C. (2017). Introduction to GIS Programming and Fundamentals with Python and ArcGIS®. CRC Press.2017
56.Yang, C. P., Yu, M., Xu, M., Jiang, Y., Qin, H., Li, Y., … & Seery, B. (2017, March). An architecture for mitigating near earth object’s impact to the earth. In Aerospace Conference, 2017 IEEE (pp. 1-13). IEEE.2017
57.Yang, C., Huang, Q., Li, Z., Liu, K., & Hu, F. (2017). Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth, 10(1), 13-53.2017
58.Li, Z., Hu, F., Schnase, J. L., Duffy, D. Q., Lee, T., Bowen, M. K., & Yang, C. (2017). A spatiotemporal indexing approach for efficient processing of big array-based climate data with MapReduce. International Journal of Geographical Information Science, 31(1), 17-35.2017
59.Yang, C., Yu, M., Hu, F., Jiang, Y., & Li, Y. (2017). Utilizing cloud computing to address big geospatial data challenges. Computers, Environment and Urban Systems, 61, 120-128.2017
60.Li, Z., Yang, C., Huang, Q., Liu, K., Sun, M., & Xia, J. (2017). Building Model as a Service to support geosciences. Computers, Environment and Urban Systems, 61, 141-152.2017
61.Züfle, A., Trajcevski, G., Pfoser, D., Renz, M., Rice, M. T., Leslie, T., … & Emrich, T. (2017, April). Handling uncertainty in geo-spatial data. In Data Engineering (ICDE), 2017 IEEE 33rd International Conference on (pp. 1467-1470). IEEE.2017
62.Fayne, J. V., Bolten, J. D., Doyle, C. S., Fuhrmann, S., Rice, M. T., Houser, P. R., & Lakshmi, V. (2017). Flood mapping in the lower Mekong River Basin using daily MODIS observations. International journal of remote sensing, 38(6), 1737-1757.2017
63.Shortridge, A. M., Fayne, J. V., & Rice, M. T. (2017). Modeling Uncertainty in Digital Elevation Models. The International Encyclopedia of Geography.2017
64.Pettitt, A., & Fuhrmann, S. (2017). The Robinson House in the AR-Based Manassas Battlefield National Park Experience. i-com, 16(3), 215-222.2017
65.Dailey, L. A., & Fuhrmann, S. (2017). GIS-Based Logistic Regression for Landslide Susceptibility Analysis in Western Washington State. International Journal of Applied Geospatial Research (IJAGR), 8(2), 1-19.2017
66.Fayne, J. V., Bolten, J. D., Doyle, C. S., Fuhrmann, S., Rice, M. T., Houser, P. R., & Lakshmi, V. (2017). Flood mapping in the lower Mekong River Basin using daily MODIS observations. International journal of remote sensing, 38(6), 1737-1757.2017
67.Zheng, W., Sun, D., & Li, S. (2017). Mapping coastal floods induced by hurricane storm surge using ATMS data. International Journal of Remote Sensing, 38(23), 6846-6864.2017
68.Li, S., Sun, D., Goldberg, M., Sjoberg, W., Santek, D., & Hoffman, J. (2017, December). Introduction to SNPP/VIIRS Flood Mapping Software Version 1.0. In AGU Fall Meeting Abstracts.2017
69.Hu, T., Cao, B., Du, Y., Li, H., Wang, C., Bian, Z., … & Liu, Q. (2017). Estimation of Surface Upward Longwave Radiation Using a Direct Physical Algorithm. IEEE Transactions on Geoscience and Remote Sensing, 55(8), 4412-4426.2017
70.DeWeese, M., Li, S., Sun, D., Goldberg, M., & Sjoberg, B. (2017, July). Application of suomi-npp/viirs data in near real time flood detection. In Geoscience and Remote Sensing Symposium (IGARSS), 2017 IEEE International (pp. 2790-2793). IEEE.2017
71.Benjamin Lewis, Weihe Wendy Guan and Alenka Poplin. Evaluating the Current State of Geospatial Software as a Service Platforms: A Comparison Study. In Citizen Empowered Mapping. Michael Leitner and Jamal Jokar Arsanjani eds. Springer. June 2017.2017
72.Blodgett, D., Rea, A., and Lieberman, J., “The future of hydrography from the perspective of David Blodgett, USGS; Alan Rea, USGS; and Joshua Lieberman, Harvard CGA”, in “GIS for Surface Water”, Simley, J. ed., 2017, ESRI Press, Redlands.2017
73.Cortia, P. and Lewis, B., “Making temporal search more central in spatial data infrastructures.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-4/W2, 2017. 2nd International Symposium on Spatiotemporal Computing 2017, 7–9 August, Cambridge, USA.2017
74.Kakkar, D. and Lewis, B., “Building a billion spatio-temporal object search and visualization platform.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-4/W2, 2017. 2nd International Symposium on Spatiotemporal Computing 2017, 7–9 August, Cambridge, USA.2017
75.Devika Kakkar, Ben Lewis, David Smiley and Ariel Nunez. The Billion Object Platform (BOP): a system to lower barriers to support big, streaming, spatio-temporal data sources. FOSS4G, Boston, Massachusetts, August 18, 2017. http://gis.harvard.edu/publications/billion-object-platform-bop-streaming-spatio-temporal-data-sources.2017
76.Lieberman, J., Bermudez, L., Leinenweber, L., Botts,M., and Liang, S., “Rapid-response sensor networks leveraging open standards and the Internet of Things”, January 2017, Earth Science Information Partners Winter Meeting, Bethesda2017
77.Benjamin Lewis, Paolo Corti and Wendy Guan. Harvard Hypermap: An Open Source Framework for Making the World’s Geospatial Information more Accessible. AAG Annual Meeting. Boston, Massachusetts. April 2017. http://gis.harvard.edu/publications/harvard-hypermap-open-source-framework-making-world%E2%80%99s-geospatial-information-more2017
78.Lieberman, J., “Applications for a Surface Hydro Ontology and Linked Data Model”, April 2017, AAG Annual Meeting Boston2017
79.Gonzalez, B., “A Statistical Analysis for Linked Data”, April 2017, AAG Annual Meeting Boston2017
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81.Merrick Lex Berman, Devika Kakkar, Wendy Guan, and Fei Carnes. Enabling Spatiotemporal Analysis and Visualization of Air Pollution in China and India. The 25th International Conference on Geoinformatics. Buffalo, NY. August 3, 2017. http://gis.harvard.edu/publications/enabling-spatiotemporal-analysis-and-visualization-air-pollution-china-and-india2017
82.Paolo Corti and Ben Lewis. Making Temporal Search Central in a Spatial Data Infrastructure. Second International Symposium on Spatiotemporal Computing. Cambridge, Massachusetts. August 7, 2017. http://gis.harvard.edu/publications/making-temporal-search-central-spatial-data-infrastructure2017
83.Devika Kakkar and Ben Lewis. Building a Billion Spatio-Temporal Object Search and Visualization Platform. Oral presentation in the Second International Symposium on Spatiotemporal Computing, Cambridge, Massachusetts, August 8, 2017. http://gis.harvard.edu/publications/building-open-source-real-time-billion-object-spatio-temporal-search-plaform.2017
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85.Zhang, M., Lieberman, J., and Yue, P., “An ontology for processing service orchestration”, August 2017, Sixth International Conference on Agro-Geoinformatics, Fairfax2017
86.Paolo Corti, Ben Lewis and Devika Kakkar. Building SDIs and geoportals with GeoNode and a search engine. FOSS4G, Cambridge, Massachusetts. August 15, 2017. http://gis.harvard.edu/publications/building-sdis-and-geoportals-geonode-and-search-engine2017
87.Paolo Corti, Ben Lewis and Ariel Nunez. Maintaining Spatial Data Infrastructures (SDIs) using distributed task queues. FOSS4G, Boston, Massachusetts. August 16, 2017 http://gis.harvard.edu/publications/maintaining-spatial-data-infrastructures-sdis-using-distributed-task-queues2017
88.Simone Dalmasso, Francesco Bartoli, Paolo Corti, Jeffrey Johnson and Ariel Núñez. The State of GeoNode. FOSS4G. Boston, Massachusetts. August 16, 20172017
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90.Su Yeon Han, Ming-Hsiang Tsou & Keith C. Clarke (2017): Revisiting the death of geography in the era of Big Data: the friction of distance in cyberspace and real space, International Journal of Digital Earth, DOI: 10.1080/17538947.2017.1330366.2017
91.Park, S., Clarke, K.C.. Choi, C. and Kim, J. (2017) Simulating Land Use Change in the Seoul Metropolitan Area after Greenbelt Elimination Using the SLEUTH Model, Journal of Sensors, vol. 2017, Article ID 4012929. doi:10.1155/2017/40129292017
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95.Jiangxia Ye, Mingshan Wu, Zhongjian Deng, Shengji Xu , Ruliang Zhou and Keith C. Clarke (2017) Modeling the spatial patterns of human wildfire ignition in Yunnan province, China. Applied Geography. 89, 150–162. https://doi.org/10.1016/j.apgeog.2017.09.0122017
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107.Lynnes, C., Little, M. M., Huang, T., Jacob, J. C., Yang, C. P., & Kuo, K. S. (2016, February). Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations. In AGU Fall Meeting Abstracts.2016
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122.Sun, D., Li, S., Zheng, W., Croitoru, A., Stefanidis, A., & Goldberg, M. (2016). Mapping floods due to Hurricane Sandy using NPP VIIRS and ATMS data and geotagged Flickr imagery. International Journal of Digital Earth, 9(5), 427-441.2016
123.Merrick Lex Berman, Ruth Mostern, Humphrey Southall, edited. Placing Names: Enriching and Extending Gazetteers. Indiana University Press. The Spatial Humanities Series. August 4, 2016.2016
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125.Josh Lieberman, “Ontological Representation of Physical Feature Networks”, 2016, AAG Meeting.2016
126.Josh Lieberman, “Development and Application of a Linked Data Model for NHD and Related Datasets” poster presentation at CUAHSI 2016 Symposium.2016
127.Benjamin Lewis, David Strohschein, Paolo Corti, David Smiley. Building an Open Source, Real-Time, Billion Object Spatio-Temporal Search Plaform. International Workshop on Cloud Computing and Big Data. Fairfax, VA. July 2016. http://gis.harvard.edu/publications/building-open-source-real-time-billion-object-spatio-temporal-search-plaform2016
128.Paolo Corti and Ben Lewis. Implementing an Open Source Spatiotemporal Search Platform for Spatial Data Infrastructures. Open Source Geospatial Research & Education Symposium. Perugia, Italy. October 2016. http://gis.harvard.edu/publications/implementing-open-source-spatiotemporal-search-platform-spatial-data-infrastructures2016
129.Paolo Corti and Ben Lewis. Status of WorldMap. GeoNode Summit. Rome, Italy. November 11, 2016. http://gis.harvard.edu/publications/status-worldmap-20162016
130.Lieberman, J., Bermudez, L., Leinenweber, L., Botts,M., and Liang, S., “Rapid-response sensor networks leveraging open standards and the Internet of Things”, December 2016, American Geophysical Union Fall Meeting, San Francisco2016
131.Berberoğlu, S, Akın, A. and Clarke, K. C. (2016) Cellular automata modeling approaches to forecast urban growth for Adana, Turkey: A comparative approach. Landscape and Urban Planning. 153, 11–27. doi:10.1016/j.landurbplan.2016.04.0172016
132.Nittel, Bodum, Clarke, Gould, Raposo, Sharma and Vasardani (2016) CHAPTER 3: Emerging Technological Trends Likely to Affect GIScience in the Next Twenty Years. In Advancing Geographic Information Science: The Past and Next Twenty Years, Editors: Harlan Onsrud, Werner Kuhn. GSDI Association Press / Needham, MA. Available online at: https://spatial.umaine.edu/files/2016/02/AdvancingGIScience.pdf2016
133.Hu, F., Bowen, M. K., Li, Z., Schnase, J. L., Duffy, D., Lee, T. J., & Yang, C. P. (2015, December). A Columnar Storage Strategy with Spatiotemporal Index for Big Climate Data. In AGU Fall Meeting Abstracts.2015
134.Yu, M., Piccione, M., Sun, M., Yang, C. P., Bambacus, M., & Seery, B. (2015, December). Develop an Architecture to Enable Effective Information Process in Mitigating Asteroid’s Threat. In AGU Fall Meeting Abstracts.2015
135.Hu, F., Huang, Q., Scheele, C. J., Yang, C. P., Yu, M., & Liu, K. (2015, December). Rasdaman for Big Spatial Raster Data. In AGU Fall Meeting Abstracts.2015
136.Yang, C. P., Yu, M., Sun, M., Qin, H., & Robinson, E. (2015, December). DAsHER CD: Developing a Data-Oriented Human-Centric Enterprise Architecture for EarthCube. In AGU Fall Meeting Abstracts.2015
137.Xia, J., Yang, C., Liu, K., Gui, Z., Li, Z., Huang, Q., & Li, R. (2015). Adopting cloud computing to optimize spatial web portals for better performance to support Digital Earth and other global geospatial initiatives. International Journal of Digital Earth, 8(6), 451-475.2015
138.Li, Z., Yang, C., Jin, B., Yu, M., Liu, K., Sun, M., & Zhan, M. (2015). Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework. PloS one, 10(3), e0116781.2015
139.Xia, J., Yang, C., Liu, K., Li, Z., Sun, M., & Yu, M. (2015). Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services. International Journal of Geographical Information Science, 29(3), 375-396.2015
140.Li, M., Liu, H., & Yang, C. (2015). a Real-Time GIS Platform for High Sour Gas Leakage Simulation, Evaluation and Visualization. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(4), 225.2015
141.Yang, C., Sun, M., Liu, K., Huang, Q., Li, Z., Gui, Z., … & Lostritto, P. (2015). Contemporary computing technologies for processing big spatiotemporal data. In Space-time integration in geography and GIScience (pp. 327-351). Springer, Dordrecht.2015
142.Rice, M. T., Curtin, K. M., Pfoser, D., Rice, R. M., Fuhrmann, S., Qin, H., … & Seitz, C. R. (2015). Social moderation and dynamic elements in crowdsourced geospatial data: A report on quality assessment, dynamic extensions and mobile device engagement in the George Mason University Geocrowdsourcing Testbed. George Mason University Fairfax United States.2015
143.Qin, H., Aburizaiza, A. O., Rice, R. M., Paez, F., & Rice, M. T. (2015). OBSTACLE CHARACTERIZATION IN A GEOCROWDSOURCED ACCESSIBILITY SYSTEM. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 2.2015
144.Bevington-Attardi, D., & Rice, M. (2015). On the map: American cartography in 2015.2015
145.Fayne, J. V., Fuhrmann, S., Rice, M. T., & Rice, R. M. (2015). Exploring alternative map products to enhance transportation option awareness. Cartography and Geographic Information Science, 42(4), 345-357.2015
146.Qin, H., Rice, R. M., Fuhrmann, S., Rice, M. T., Curtin, K. M., & Ong, E. (2016). Geocrowdsourcing and accessibility for dynamic environments. GeoJournal, 81(5), 699-716.2015
147.Aburizaiza, A. O., Rice, M. T., & Goodchild, M. F. (2015). Generating Geospatial Footprints For Geoparsed Text From Crowdsourced Platial Data. In Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings (Vol. 15, No. 1, p. 49).2015
148.Rice, M. T., Curtin, K. M., Pfoser, D., Rice, R. M., Fuhrmann, S., Qin, H., … & Seitz, C. R. (2015). Social moderation and dynamic elements in crowdsourced geospatial data: A report on quality assessment, dynamic extensions and mobile device engagement in the George Mason University Geocrowdsourcing Testbed. George Mason University Fairfax United States.2015
149.Fuhrmann, S., Holzbach, M. E., & Black, R. (2015). Developing interactive geospatial holograms for spatial decision-making. Cartography and Geographic Information Science, 42(sup1), 27-33.2015
150.Fayne, J. V., Fuhrmann, S., Rice, M. T., & Rice, R. M. (2015). Exploring alternative map products to enhance transportation option awareness. Cartography and Geographic Information Science, 42(4), 345-357.2015
151.Li, S., Sun, D., Goldberg, M., Sjoberg, B., Plumb, E. W., Holloway, E., … & Kreller, M. (2015, December). Application of Snpp/viirs Data in Near Real-Time Supra-Snow Flood Detection. In AGU Fall Meeting Abstracts.2015
152.Li, S., Sun, D., Goldberg, M. E., & Sjoberg, B. (2015). Object-based automatic terrain shadow removal from SNPP/VIIRS flood maps. International Journal of Remote Sensing, 36(21), 5504-5522.2015
153.Sun, D., Yu, Y., Yang, H., Fang, L., Liu, Q., & Shi, J. (2015). A case study for intercomparison of land surface temperature retrieved from GOES and MODIS. International Journal of Digital Earth, 8(6), 476-494.2015
154.Zambotti, G., W. Guan and J. Gest, “Visualizing Human Migration through Space and Time”, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-4/W2, 2015, International Workshop on Spatiotemporal Computing, 13–15 July 2015, Fairfax, Virginia, USA.2015
155.Lieberman, J. (contributor), Habona, G. (editor), “Use of Semantic Linked Data with RDF for National Map NHD and Gazetteer Data”, 2015, OGC Public Engineering Report 15-0662015
156.Lieberman, J. (contributor), Fellah, S. (editor), “Linked Data & Semantic Enablement of OGC Services”, 2015, OGC Public Engineering Report 15-0542015
157.Wendy Guan, Investigating Hadoop for Large Spatiotemporal Processing Tasks, oral presentation in the Paper Session: Spatiotemporal Symposium: Big Data Sciences at AAG 2015 Annual Meeting in April 2015 at Chicago2015
158.Josh Lieberman, Spatial reification or how can I know the refrigerator is open, position paper accepted to 2015 Vespucci Institute on Spatial Ontologies.2015
159.Josh Lieberman, “Semantic modeling of Physical Relationships”, Vespucci Institute on Spatial Ontologies, 2015, Bar Harbor.2015
160.Josh Lieberman, “NHD Ontologies”, 2015, Third CUAHSI Hydroinformatics Conference.2015
161.Josh Lieberman, Cheatham, M., Varanka, D., “Application of Alignment Methodologies to Spatial Ontologies in the Hydro Domain”, 2015, AGU Fall Meeting.2015
162.Han, S.Y., Tsou, M-H and Clarke K.C. (2015) Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U. S. Cities. PLoS ONE 10(7): e0132464. doi:10.1371/journal.pone.01324642015
163.Chaudhuri, G. and Clarke, K. C. (2015) On the spatiotemporal dynamics of the coupling between land use and road networks: does political history matter? Environment and Planning B—Planning and Design. 42, 1, 133-156.2015
164.Wu, H., Li, K., Shi, W., Clarke, K. C., Zhang, J . and Li. H. (2015) A wavelet-based hybrid approach to remove the flicker noise and the white noise from GPS coordinate time series. GPS Solutions 19, 4, 511-523. http://dx.doi.org/10.1007/s10291-014-0412-62015
165.Chen, Y-J, McFadden, J. P., Clarke, K. C. and Roberts, D. (2015) Measuring Spatio-temporal Trends in Residential Landscape Irrigation Extent and Rate in Los Angeles, California Using SPOT-5 Satellite Imagery. Water Resources Management. 29, 15, 5749-5763.2015
166.Li, F., Liang, J., Clarke, K. C., Li, M., Liu, Y. and Huang, Q. (2015) Urban land growth in eastern China: a general analytical framework based on the role of urban micro-agents’ adaptive behavior. Regional Environmental Change, 15, 4, 695-707.2015
167.Li, Z., Yang, C. P., Schnase, J. L., Duffy, D., & Lee, T. J. (2014, December). Developing a Hadoop-based Middleware for Handling Multi-dimensional NetCDF. In AGU Fall Meeting Abstracts.2014
168.Sun, M., Jiang, Y., & Yang, C. P. (2014, December). Developing a middleware to support HDF data access in ArcGIS. In AGU Fall Meeting Abstracts.2014
169.Yu, M., Gui, Z., Yang, C. P., Xia, J., & Chen, S. (2014, December). Investigation on Accelerating Dust Storm Simulation via Domain Decomposition Methods. In AGU Fall Meeting Abstracts.2014
170.Yang, C. P., Xu, C., Sun, M., & Li, Z. (2014, December). Developing a comprehensive conceptual arhictecture to support Earth sciences. In AGU Fall Meeting Abstracts.2014
171.Xu, C., & Yang, C. (2014). Introduction to big geospatial data research. Annals of GIS, 20(4), 227-232.2014
172.Gui, Z., Yang, C., Xia, J., Huang, Q., Liu, K., Li, Z., … & Jin, B. (2014). A service brokering and recommendation mechanism for better selecting cloud services. PloS one, 9(8), e105297.2014
173.Xia, J., Yang, C., Gui, Z., Liu, K., & Li, Z. (2014). Optimizing an index with spatiotemporal patterns to support GEOSS Clearinghouse. International Journal of Geographical Information Science, 28(7), 1459-1481.2014
174.Dias, S., Yang, C., Stefanidis, A., & Rice, M. (2014). Mashing up Geographic Information for Emergency Response—An Earthquake Prototype. Journal of Geographic Information System, 6(05), 533.2014
175.Curtin, K. M., Voicu, G., Rice, M. T., & Stefanidis, A. (2014). A comparative analysis of traveling salesman solutions from geographic information systems. Transactions in GIS, 18(2), 286-301.2014
176.Rice, M. T., Paez, F. I., Rice, R. M., Ong, E. W., Qin, H., Seitz, C. R., … & Medina, R. M. (2014). Quality assessment and accessibility applications of crowdsourced geospatial data: A report on the development and extension of the George Mason University Geocrowdsourcing Testbed. GEORGE MASON UNIV FAIRFAX VA.2014
177.Sun, D., & Pinker, R. (2014). Factors contributing to the spatial variability of Satellite estimates of diurnal temperature range in the United States. IEEE Geoscience and Remote Sensing Letters, 11(9), 1524-1528.2014
12.Huang, C., Chen, X., Li, Y., Yang, H., Sun, D., Le, C., & Xu, L. (2014). Deriving inherent optical property for highly turbid productive inland water from MERIS data by semi-analytical model: A case study in Taihu Lake, China. Aquatic ecosystem health & management, 17(3), 252-260.2014
13.Li, H., Sun, D., Yu, Y., Wang, H., Liu, Y., Liu, Q., … & Cao, B. (2014). Evaluation of the VIIRS and MODIS LST products in an arid area of Northwest China. Remote Sensing of Environment, 142, 111-121.2014
14.Fang, L., Yu, Y., Xu, H., & Sun, D. (2014). New retrieval algorithm for deriving land surface temperature from geostationary orbiting satellite observations. IEEE Transactions on Geoscience and Remote Sensing, 52(2), 819-828.2014
15.Josh Lieberman, Development of National Map ontologies for organization and orchestration of hydrologic observations, talk at AGU Fall Meeting 20142014
16.Li, S., Yu, Y., Sun, D., Tarpley, D., Zhan, X., & Chiu, L. (2014). Evaluation of 10 year AQUA/MODIS land surface temperature with SURFRAD observations. International journal of remote sensing, 35(3), 830-856.2014
17.Clarke, K. C. (2014) Cellular Automata and Agent-Based Models. Chapter 62 in Fischer, M. M. and Nijkamp, P. (eds) Handbook of Regional Science. Springer-Verlag, Berlin Heidelberg.2014
18.Peiman, R. and Clarke, K. C. (2014) The Impact of Data Time Span on Forecast Accuracy through Calibrating the SLEUTH Urban Growth Model International Journal of Applied Geospatial Research, 5(3), 21-35.2014
19.Akin, A., Clarke, K, C., and Berberoglu, S. (2014) The impact of historical exclusion on the calibration of the SLEUTH urban growth model . International Journal of Applied Earth Observation and Geoinformation. 27, B, 156-168.2014
20.Chaudhuri, G. and Clarke, K. C. (2014) Temporal Accuracy in Urban Growth Forecasting: A Study Using the SLEUTH Model Transactions in GIS, 18, 2, 302-320.2014
21.Lippitt, C. D.; Stow, D. A. and Clarke, K. C. (2014) On the nature of models for time-sensitive remote sensing. International Journal of Remote Sensing. 35, 18, 6815-6841.2014
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