TOPS from XML format
Acuña-Soto, R., Stahle, D. W., Therrell, M. D., & Diaz, J. V. (n.d.). 3 Historical, Scientific, and Technological Approaches to Studying the Climate-Disease Connection. Retrieved from
Augustine, D. J., Armstrong, W. E., Cully, J. F., & Antolin, M. F. (n.d.). Black-tailed Prairie Dog Habitat Suitability Modeling for the Southern Great Plains: Cross-scale Analysis of Soils, Topography and Climate. Retrieved from
Baccini, A., Carvalho, L., Dubayah, R., Goetz, S. J., & Friedl, M. A. (2011). Uncertainty Analysis in Large Area Aboveground Biomass Mapping.In AGU Fall Meeting Abstracts (Vol. 1, p. 4). Retrieved from
Badawy, B. (2014). Max-Planck-Institut für Biogeochemie. Retrieved from
Barker, C. M. (2008).Spatial and temporal patterns in mosquito abundance and virus transmission in California. ProQuest. Retrieved from
Barker, C. M., Johnson, W. O., Eldridge, B. F., Park, B. K., Melton, F., & Reisen, W. K. (2010). Temporal connections between Culex tarsalis abundance and transmission of western equine encephalomyelitis virus in California.The American Journal of Tropical Medicine and Hygiene, 82(6), 1185–1193. Retrieved from
Barker, C. M., Kramer, V. L., & Reisen, W. K. (2010).Decision support system for mosquito and arbovirus control in California. Retrieved from
Barker, C. M., Niu, T., Reisen, W. K., & Hartley, D. M. (2013).Data-Driven Modeling to Assess Receptivity for Rift Valley Fever Virus.PLoS Neglected Tropical Diseases, 7(11), e2515. Retrieved from
Basson, G., Schmidt, C., & Skiles, J. W. (2008). Monitoring Resources in the Fremont-Winema National Forest and Yosemite National Park Using Satellite Imagery. Retrieved from
Batyreu, V., & Zenchanka, S. (2012). Modelling of Water Cycle Processes. In Climate Change and the Sustainable Use of Water Resources (pp. 473–483). Springer. Retrieved from
Berbel, J., & Mateos, L. (2014). Does investment in irrigation technology necessarily generate rebound effects? A simulation analysis based on an agro-economic model. Agricultural Systems, 128, 25–34. Retrieved from
Brillinger, D. R. (n.d.). Keynote Address: Risk Analysis in Geoscience and Remote Sensing.
Britten, M., Network, N. P. S. I. R. M., Comiskey, J., Network, N. P. S. I. M.-A., Marshall, M., Rivers, N. P. S. I. E., & Network, M. (2012). Using NASA resources to inform climate and land use adaptation: Ecological forecasting, vulnerability assessment, and evaluation of management options across two US DOI Landscape Conservation Cooperatives. Retrieved from
Cabello, J., Fernández, N., Alcaraz-Segura, D., Oyonarte, C., Pineiro, G., Altesor, A., … Paruelo, J. M. (2012). The ecosystem functioning dimension in conservation: insights from remote sensing. Biodiversity and Conservation, 21(13), 3287–3305. Retrieved from
Carvalho, A. C. V. R. (2010). A detecção remota e os SIG na produção animal-análise da contribuição e situação actual. Retrieved from
Charland, K. M., Buckeridge, D. L., Hoen, A. G., Berry, J. G., Elixhauser, A., Melton, F., & Brownstein, J. S. (2013). Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza-related hospitalizations in the United States.Influenza and Other Respiratory Viruses, 7(5), 718–728. Retrieved from
Charland, K. M. L., Buckeridge, D. L., Sturtevant, J. L., Melton, F., Reis, B. Y., Mandl, K. D., & Brownstein, J. S. (2009). Effect of environmental factors on the spatio-temporal patterns of influenza spread.Epidemiology and Infection, 137(10), 1377–1387. Retrieved from
Clark, J. (2013). Effects of climate change on the habitats of the invasive species Ailanthus altissima along the Appalachian Trail. Retrieved from
Clark, J., Wang, Y., & August, P. V. (2014). Assessing current and projected suitable habitats for tree-of-heaven along the Appalachian Trail. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1643), 20130192. Retrieved from
Colditz, R. R., Acosta-Velázquez, J., Díaz Gallegos, J. R., Vázquez Lule, A. D., Rodríguez-Zúñiga, M. T., Maeda, P., … Ressl, R. (2012). Potential effects in multi-resolution post-classification change detection.International Journal of Remote Sensing, 33(20), 6426–6445. Retrieved from
Cóndor, P.-E. (n.d.). 4. Gestión de ecosistemas de montaña para la regulación del agua, el clima y la conservación de policultivos tradicionales en la Reserva de Biosfera Podocarpus-El Cóndor. Retrieved from
Coombs, A. (2008). Climate change concerns prompt improved disease forecasting. Nature Medicine, 14(1), 3–3. Retrieved from
Crabtree, R. L., Sheldon, J. W., & Wang, Y. (2012). Monitoring and modeling environmental change in protected areas: integration of focal species populations and remote sensing. Remote Sensing of Protected Lands. CRC Press, Boca Raton, Florida, 495–524. Retrieved from
Crabtree, R., Potter, C., Mullen, R., Sheldon, J., Huang, S., Harmsen, J., … Jean, C. (2009). A modeling and spatio-temporal analysis framework for monitoring environmental change using NPP as an ecosystem indicator. Remote Sensing of Environment, 113(7), 1486–1496. Retrieved from
Craciunescu, V., Brown, H. E., Comrie, A. C., Zelicoff, A., Ward, T. G., Ragain, R. M., … others. (2012). Information and decision support systems.Environmental Tracking for Public Health Surveillance, 11, 369. Retrieved from
Cuenca, R. H., Ciotti, S. P., & Hagimoto, Y. (2013). Application of Landsat to evaluate effects of irrigation forbearance.Remote Sensing, 5(8), 3776–3802. Retrieved from
Danner, E. M., Melton, F. S., Pike, A., Hashimoto, H., Michaelis, A., Rajagopalan, B., … Nemani, R. R. (2012). River temperature forecasting: A coupled-modeling framework for management of river habitat. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 5(6), 1752–1760. Retrieved from
Danner, E., Pike, A., Lindley, S., Mendelssohn, R., Dewitt, L., Melton, F. S., … Hashimoto, H. (2010). River water temperature and fish growth forecasting models. In AGU Fall Meeting Abstracts (Vol. 1, p. 974). Retrieved from
Data, A. T. G. (2014).TOPS_Derivatives> Climate and Vegetation Variations> Time series of temperature, precipitation and NDVI (1982-2006). Retrieved from
Di Blasi, S. (2012). La ricerca applicata ai vini di qualità (Vol. 124). Firenze University Press. Retrieved from
Diuk-Wasser, M. A., Vourc’h, G., Cislo, P., Hoen, A. G., Melton, F., Hamer, S. A., … others. (2010). Field and climate-based model for predicting the density of host-seeking nymphal Ixodes scapularis, an important vector of tick-borne disease agents in the eastern United States. Global Ecology and Biogeography, 19(4), 504–514. Retrieved from
Dominici, R., Worthley, J. S., Barba, T., O’Brien, W., Ornellas, L., Walsh, H., & Watson, R. A. (2011). STU DY AGENCY. Retrieved from Agency/agendas/2011/December/SA_Agenda_12_Dec_15_2011.pdf
Dungan, J. L., Wang, W., Hashimoto, H., Michaelis, A., Milesi, C., Ichii, K., & Nemani, R. R. (2009).Convergence and Divergence in a Multi-Model Ensemble of Terrestrial Ecosystem Models in North America.In AGU Fall Meeting Abstracts (Vol. 1, p. 334). Retrieved from
Dungan, J. L., Wang, W., Michaelis, A., Votava, P., & Nemani, R. (n.d.).Sources of uncertainty in predicting land surface fluxes using diverse data and models. Retrieved from
Dungan, J. L., Wang, W., Michaelis, A., Votava, P., & Nemani, R. (2010).Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models. Retrieved from
Enterprise, M. R., & Areas, S. R. I. I. (n.d.). 4.1. CURRENT STATUS OF R&D IN MONTANA. Retrieved from INSTEP III Project Description.pdf
Eschtruth, A. K., Cleavitt, N. L., Battles, J. J., Evans, R. A., & Fahey, T. J. (2006). Vegetation dynamics in declining eastern hemlock stands: 9 years of forest response to hemlock woolly adelgid infestation. Canadian Journal of Forest Research, 36(6), 1435–1450. Retrieved from
Fan, H., Di, L., Yang, W., Bonnlander, B., & Li, X. (2007). Use of binary logistic regression technique with MODIS data to estimate wild fire risk. In International Symposium on Multispectral Image Processing and Pattern Recognition (p. 67863L–67863L).International Society for Optics and Photonics. Retrieved from
Fortner, R. W., & Manzo, L. (2011). Great lakes literacy principles.Eos, Transactions American Geophysical Union, 92(13), 109–110. Retrieved from
FRENCH, N. H. F., BOURGEAU—CHAVEZ, L. L., FALKOWSKI, M. J., Goetz, S., JENKINS, L. K., Camill, P., … Brown, D. G. (2013). Remote sensing for mapping and modeling of land-based carbon flux and storage.Land Use and the Carbon Cycle: Advances in Integrated Science, Management, and Policy, 95. Retrieved from
Friggens, M. M., Pinto, J. R., Dumroese, R. K., & Shaw, N. L. (2012). Decision support: vulnerability, conservation, and restoration. Climate Change in Grasslands, Shrublands, and Deserts of the Interior American West: A Review and Needs Assessment, 116. Retrieved from
Fukuda, K. (2013). 22 Promoting Risk Insurance in the Asia-Pacific Region: Lessons from the Ground for the Future Climate Regime under UNFCCC. Climate Change Adaptation in Practice: From Strategy Development to Implementation, 303. Retrieved from
Gallego, F., Alcaraz-Segura, D., Baeza, S., Altesor, A., Bagnato, C., Paruelo, J. M., & Aires, T. B. (2011).Tendencias temporales y anomalías espaciales del funcionamiento ecosistémico en dos áreas protegidas de Uruguay.Simpósio Brasileiro de Sensoriamento Remoto, 15 (SBSR), 3127–3134. Retrieved from
Geller, G. N., & Melton, F. (2008). Looking forward: Applying an ecological model web to assess impacts of climate change. Biodiversity, 9(3-4), 79–83. Retrieved from
Geller, G. N., & Nemani, R. (2009). COS 75-9: The ecological model web: Facilitating a modeling infrastructure. In The 94th ESA Annual Meeting. Retrieved from
Geller, G. N., & Turner, W. (2007). The model web: a concept for ecological forecasting. In Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International (pp. 2469–2472). IEEE. Retrieved from
Gharib, S. H., von Schübelbach, S. Z., Itten, K. I., Zimmermann, N. E., & Kneubühler, M. (n.d.). ESTIMATION OF ECOLOGICALLY RELEVANT LAND COVER VARIABLES FROM IMAGING SPECTROSCOPY. Retrieved from
Glenn, E. P., Neale, C. M. U., Hunsaker, D. J., & Nagler, P. L. (2011). Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems. Hydrological Processes, 25(26), 4050–4062. Retrieved from
Glick, P., & Stein, B. (2010). Scanning the conservation horizon: a guide to climate change vulnerability assessment. National Wildlife Federation, 168pp. Retrieved from
Goetz, S. J., Bond-Lamberty, B., Law, B. E., Hicke, J. A., Huang, C., Houghton, R. A., … others. (2012). Observations and assessment of forest carbon dynamics following disturbance in North America.Journal of Geophysical Research: Biogeosciences (2005–2012), 117(G2). Retrieved from
Goetz, S., Melton, F., Wang, W., Milesi, C., & Theobald, D. (2009).Modeling Strategies for Adaptation to Coupled Climate and Land Use Change in the United States.In Proc/of the World Bank 2009 Marseille Cities and Climate Change Urban Research Symposium, World Bank, net/papers. html. Retrieved from
Golden, K. (2002). DPADL: An action language for data processing domains. In Proceedings of the 3rd NASA Intl. Planning and Scheduling workshop (pp. 28–33). Citeseer.
Golden, K., Brafman, R., & Pang, W. (2005).Preferences in Data Production Planning.In Multidisciplinary IJCAI-05 Workshop on Advances in Preference Handling. Retrieved from (Golden).pdf
Golden, K., Nemani, R., Pang, W., & Votava, P. (2005).Intelligent Agents for Science Data Processing.In AGU Fall Meeting Abstracts (Vol. 1, p. 314). Retrieved from
Golden, K., & Pang, W. (2004). A Hybrid Constraint Representation and Reasoning Framework.
Golden, K., Pang, W., Nemani, R., & Votava, P. (2003). Automating the processing of earth observation data. In Intl Symposium on Artificial Intelligence, Robotics, and Automation in Space (i-SAIRAS). Retrieved from (Golden).pdf
Golden, K., Pang, W., & Votava, R. N. P. (2003).Automated Data Processing as an AI Planning Problem.NASA, Avalaible at: Arc. Nasa. gov/publications/pdf/0629. Pdf.
Gonzalez-Dugo, M. P., Escuin, S., Cano, F., Cifuentes, V., Padilla, F. L. M., Tirado, J. L., … Mateos, L. (2013). Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale. Agricultural Water Management, 125, 92–104. Retrieved from
Graves, S., He, M. Y., Hardin, D., Sever, T., & Irwin, D. (n.d.). SERVIR at the Age of Four: The Development of an Environmental Monitoring and Visualization System for Mesoamerica. Retrieved from
Great Northern, L. C. C., Olliff, T., Network, N. P. S. I. A. H., Emmott, R., Rivers, N. P. S. I. E., Network, M., … others. (n.d.). Using NASA resources to inform climate and land use adaptation: Ecological forecasting, vulnerability assessment, and evaluation of management options across two US DOI Landscape Conservation Cooperatives. Retrieved from
Grimm, N. B., Chapin III, F. S., Bierwagen, B., Gonzalez, P., Groffman, P. M., Luo, Y., … others. (2013). The impacts of climate change on ecosystem structure and function.Frontiers in Ecology and the Environment, 11(9), 474–482. Retrieved from
Gu, L., Hanson, P. J., Mac Post, W., Kaiser, D. P., Yang, B., Nemani, R., … Meyers, T. (2008). The 2007 eastern US spring freeze: increased cold damage in a warming world? BioScience, 58(3), 253–262. Retrieved from
Gu, Y., Brown, J. F., Miura, T., Van Leeuwen, W. J. D., & Reed, B. C. (2010). Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data. Remote Sensing, 2(2), 526–544. Retrieved from
Gutman, G., Justice, C., & King, L. (2012). 25 The NASA Land-Cover and. Remote Sensing of Land Use and Land Cover: Principles and Applications, 379. Retrieved from
Hall, B. L., Brown, T. J., & Bradshaw, L. S. (2005). Development of US operational fire danger 15-day forecasts.CEFA Report, 05–02. Retrieved from
Hall, B. L., Brown, T. J., Bradshaw, L. S., Jolly, W. M., & Nemani, R. (n.d.). J11. 10 NATIONAL STANDARDIZED ENERGY RELEASE COMPONENT FORECASTS. Retrieved from
Han, Y., Wang, Y., & Zhao, Y. (2010). Estimating soil moisture conditions of the greater Changbai Mountains by land surface temperature and NDVI. Geoscience and Remote Sensing, IEEE Transactions on, 48(6), 2509–2515. Retrieved from
Hannah, L., Midgley, G., Andelman, S., Araújo, M., Hughes, G., Martinez-Meyer, E., … Williams, P. (2007). Protected area needs in a changing climate. Frontiers in Ecology and the Environment, 5(3), 131–138. Retrieved from
Hansen, A. J., Goetz, S. J., Gross, J. E., Theobald, D. T., Melton, F. S., & Nemani, R. R. (2006). Ecological condition of US National Parks: Enhancing decision support through monitoring, analysis, and forecasting.
Hartley, D. M., Barker, C. M., Le Menach, A., Niu, T., Gaff, H. D., & Reisen, W. K. (2012).Effects of temperature on emergence and seasonality of West Nile virus in California.The American Journal of Tropical Medicine and Hygiene, 86(5), 884–894. Retrieved from
Hashimoto, H., Milesi, C., Wang, W., Ganguly, S., Michaelis, A., & Nemani, R. (2011).Vegetation response to climate variability in India from 2001 to 2010.In AGU Fall Meeting Abstracts (Vol. 1, p. 593). Retrieved from
Hashimoto, H., & others. (2009). Monitoring and forecasting climate impacts on ecosystem dynamics in protected areas using the terrestrial observation and prediction system.Remote Sensing of Protected Lands, 523–540.
Hashimoto, H., Wang, W., Melton, F., Milesi, C., Michaellis, A., & Nemani, R. (2008). Initializing Weather Research and Forecasting (WRF) model with land surface conditions from the Terrestrial Observation and PredictionSystem (TOPS). In AGU Fall Meeting Abstracts (Vol. 1, p. 807). Retrieved from
Hashimoto, H., Wang, W., Michaelis, A. R., Melton, F. S., Ichii, K., & Nemani, R. R. (2007). Estimating evapotranspiration over Yosemite National Park using a regional ecosystem model driven by satellite-based climate data. In AGU Fall Meeting Abstracts (Vol. 1, p. 1596). Retrieved from
Hashimoto, H., Wang, W., Milesi, C., Xiong, J., Ganguly, S., Zhu, Z., & Nemani, R. R. (2013).Structural uncertainty in model-simulated trends of global gross primary production.Remote Sensing, 5(3), 1258–1273. Retrieved from
HAYNES, J. A. (2010). NASA SA℡LITE OBSERVATIONS FOR CLIMATE RESEARCH AND APPLICATIONS non PUBLIC HEALTH.In International Seminar on Planetary Emergencies-42nd Session (p. 407). World Scientific. Retrieved from
He, Y., Liu, F., & Wu, D. (2013). Nutrition Management and Automation. Agricultural Automation: Fundamentals and Practices, 231. Retrieved from
Hiatt, S. H., Ganguly, S., Melton, F. S., Michaelis, A., Milesi, C., Nemani, R. R., … others. (2010). An Open Source Platform for Earth Science Research and Applications.In AGU Fall Meeting Abstracts (Vol. 1, p. 1168). Retrieved from
Hiatt, S. H., Guzman, A., Melton, F. S., Michaelis, A., Nemani, R., Johnson, L., … others. (2011). Web Services for Satellite Irrigation Monitoring and Management Support.In AGU Fall Meeting Abstracts (Vol. 1, p. 1297). Retrieved from
Hiatt, S. H., Hashimoto, H., Melton, F. S., Michaelis, A., Milesi, C., Nemani, R. R., … Wang, W. (2009). Enhanced Access to Earth Science Data through Standards-based Web Services and Applications. In AGU Fall Meeting Abstracts (Vol. 1, p. 1069). Retrieved from
Hiatt, S. H., Hashimoto, H., Melton, F. S., Michaelis, A. R., Milesi, C., Nemani, R. R., & Wang, W. (2008). Building Geospatial Web Services for Ecological Monitoring and Forecasting. In AGU Fall Meeting Abstracts (Vol. 1, p. 1151). Retrieved from
Homolová, L., Schaepman, M. E., Lamarque, P., Clevers, J., de Bello, F., & Thuiller, W. (2013).Comparison of remote sensing and plant trait-based modelling to predict ecosystem services in subalpine grasslands.Imaging Spectroscopy for Ecological Analysis in Forest and Grassland Ecosystems, 87. Retrieved from
Ichii, K., Suzuki, T., Kato, T., Ito, A., Hajima, T., Ueyama, M., … others. (2009). Multi-model analysis of terrestrial carbon cycles in Japan: reducing uncertainties in model outputs among different terrestrial biosphere models using flux observations. Biogeosciences Discussions, 6(4), 8455–8502. Retrieved from
Ichii, K., Suzuki, T., Kato, T., Ito, A., Hajima, T., Ueyama, M., … others. (2010). Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations. Biogeosciences, 7(7), 2061–2080. Retrieved from
Ichii, K., Wang, W., Hashimoto, H., Yang, F., Votava, P., Michaelis, A. R., & Nemani, R. R. (2007). Objective refinements to a diagnostic terrestrial biosphere model using satellite data: North America carbon and water cycle simulations. In AGU Fall Meeting Abstracts (Vol. 1, p. 1173). Retrieved from
Ichii, K., Wang, W., Hashimoto, H., Yang, F., Votava, P., Michaelis, A. R., & Nemani, R. R. (2009).Refinement of rooting depths using satellite-based evapotranspiration seasonality for ecosystem modeling in California.Agricultural and Forest Meteorology, 149(11), 1907–1918. Retrieved from
Ichii, K., White, M. A., Votava, P., Michaelis, A., & Nemani, R. R. (2008). Evaluation of snow models in terrestrial biosphere models using ground observation and satellite data: impact on terrestrial ecosystem processes. Hydrological Processes, 22(3), 347–355. Retrieved from
Jetz, W., McPherson, J. M., & Guralnick, R. P. (2012). Integrating biodiversity distribution knowledge: toward a global map of life. Trends in Ecology & Evolution, 27(3), 151–159. Retrieved from
Johnson, L. F., Nemani, R., Hornbuckle, J., Bastiaanssen, W., Thoreson, B., Tisseyre, B., & Pierce, L. (2012).Remote sensing for viticultural research and production.In The Geography of Wine (pp. 209–226). Springer. Retrieved from
Johnson, L., Nemani, R., Melton, F., Michaelis, A., Votava, P., Wang, D., & Trout, T. (2010).Information Technology Supports Integration of Satellite Imagery with Irrigation Management in California’s Central Valley (pp. 5–7).
Johnson, L., Pierce, L., Michaelis, A., Scholasch, T., & Nemani, R. (2006). Remote sensing and water balance modeling in california drip-irrigated vineyards. In Proceedings, ASCE World Environmental & Water Resources Congress, Omaha NE (pp. 21–25). Retrieved from
Johnson Sr, L., & Forrest Melton, S. (n.d.). Satellite irrigation management support with the terrestrial observation and prediction system.In Proc. ASPRS 18th William T. Pecora Memorial Remote Sensing Symp (pp. 14–17). Retrieved from
Justice, E., & Newcomer, M. (2010). NASA Ames DEVELOP Interns: Helping the Western United States Manage Natural Resources One Project at a Time. Retrieved from
Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., & Adams, P. (2009). Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment, 113(7), 1382–1396. Retrieved from
Khalsa, S. J. S., Nativi, S., & Geller, G. N. (2009). The GEOSS interoperability process pilot project (IP3).Geoscience and Remote Sensing, IEEE Transactions on, 47(1), 80–91. Retrieved from
Knutson, M. G., & Heglund, P. J. (2011). 12 Resource Managers Rise to the Challenge of Climate Change.Ecological Consequences of Climate Change: Mechanisms, Conservation, and Management, 261. Retrieved from
Kovalskyy, V., & Roy, D. P. (2013).The global availability of Landsat 5 TM and Landsat 7 ETM+ land surface observations and implications for global 30m Landsat data product generation.Remote Sensing of Environment, 130, 280–293. Retrieved from
Kürklü, E., Morris, R. A., & Oza, N. (2007). Learning points of interest for observation flight planning optimization: A preliminary report. Retrieved from
Kwan, J. L., Kluh, S., Madon, M. B., Nguyen, D. V, Barker, C. M., & Reisen, W. K. (2010). Sentinel chicken seroconversions track tangential transmission of West Nile Virus to humans in the greater Los Angeles area of California. The American Journal of Tropical Medicine and Hygiene, 83(5), 1137–1145. Retrieved from
Kwan, J. L., Kluh, S., Madon, M. B., & Reisen, W. K. (2010).West Nile virus emergence and persistence in Los Angeles, California, 2003–2008.The American Journal of Tropical Medicine and Hygiene, 83(2), 400–412. Retrieved from
Kwan, J. L., Park, B. K., Carpenter, T. E., Ngo, V., Civen, R., & Reisen, W. K. (2012). Comparison of enzootic risk measures for predicting West Nile disease, Los Angeles, California, USA, 2004–2010. Emerging Infectious Diseases, 18(8), 1298. Retrieved from
Langhoff, S., Martin, G., Barone, L., Wagener, W., & Director, S. C. (2009). Workshop Report On Sustainable Urban Development. Retrieved from
Little, M., Pitts, K., Loewenstein, M., Iraci, L. T., Milesi, C., Schmidt, C., & Skiles, J. W. (2011a).Using the Terrestrial Observation and Prediction System (TOPS) to Analyze Impacts of Climate Change on California Ecosystems.In AGU Fall Meeting Abstracts (Vol. 1, p. 1743). Retrieved from
Little, M., Pitts, K., Loewenstein, M., Iraci, L. T., Milesi, C., Schmidt, C., & Skiles, J. W. (2011b).Using the Terrestrial Observation and Prediction System (TOPS) to Analyze Impacts of Climate Change on Ecosystems within Southern California Climate Regions.In AGU Fall Meeting Abstracts (Vol. 1, p. 1742). Retrieved from
Lozano-Fuentes, S., Barker, C. M., Coleman, M., Coleman, M., Park, B., Reisen, W. K., & Eisen, L. (2011). Emerging information technologies to provide improved decision support for surveillance, prevention, and control of vector-borne diseases. Efficient Decision Support Systems–Practice and Challenges in Biomedical Related Domain, 89–114. Retrieved from
Marshall, M. T. (2012).Improvements in agricultural water decision support using remote sensing.In AGU Fall Meeting Abstracts (Vol. 1, p. 1249). Retrieved from