454
Challenges and Opportunities
Abadi, L. S. K., Shamsai, A., & Goharnejad, H. (2014). An analysis of the sustainability of basin
water resources using vensim model. KSCE Journal of Civil Engineering, 19(6), 1941–1949.
https://doi.org/10.1007/s12205-014-0570-7.
Allen, M., Rodrigo, M. F., Vargas, O., Graham, E. A., Swenson, W., Hamilton, M., Taggart, M.,
& Harmon, T. C. (2007). Soil sensor technology: Life within a pixel. BioScience, 57(10), 859.
https://doi.org/10.1641/B571008.
Brander, M., Tipper, R., Hutchison, C., & Davis, G. (2008). Consequential and attributional
approaches to LCA: A guide to policy makers with specific reference to greenhouse gas
LCA of biofuels. Econometrica Press, 44, 1–14. http://onlinelibrary.wiley.com/doi/10.1002/
cbdv.200490137/abstract%5Cnhttp://www.globalbioenergy.org/uploads/media/0804_
Ecometrica_-_Consequential_and_attributional_approaches_to_LCA.pdf%5Cnhttp://
d3u3pjcknor73l.cloudfront.net/assets/media/pdf/approachest.
Chang, K.-T. (2006). Introduction to geographic information systems. Boston: McGraw-Hill
Higher Education.
Chen, D., Cane, M. A., Kaplan, A., Zebiak, S. E., & Huang, D. (2004). Predictability of El Niño
over the past 148 years. Nature, 428(6984), 733–736. https://doi.org/10.1038/nature02439.
Cheng, R., Emrich, T., Kriegel, H. P., Mamoulis, N., Renz, M., Trajcevski, G., & Züfle, A. (2014).
Managing uncertainty in spatial and spatio-temporal data. In Proceedings – International conference on data engineering (pp. 1302–1305). https://doi.org/10.1109/ICDE.2014.6816766.
Costanza, R., & Voinov, A. (2001). Modeling ecological and economic systems with STELLA: Part
III. Ecological Modelling, 143(1–2), 1–7. https://doi.org/10.1016/S0304-3800(01)00358-1.
Eftelioglu, E., Li, Y., Tang, X., Shekhar, S., Kang, J. M., & Farah, C. (2016b). Mining network
hotspots with holes: A summary of results. Lecture Notes in Computer Science (Including
Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9927,
51–67. https://doi.org/10.1007/978-3-319-45738-3_4.
Elshorbagy, A., Corzo, G., Srinivasulu, S., & Solomatine, D. P. (2010). Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology –
Part 2: Application. Hydrology and Earth System Sciences, 14(10), 1943–1961. https://doi.
org/10.5194/hess-14-1943-2010.
ESRI, Redlands. (2011). ArcGIS desktop: Release 10. CA: Environmental Systems Research
Institute.
European Commission. (2015). Eurostat database, Luxemburg. European Commission 2008.
Food and Agriculture Organization. (n.d.). Farmers brace for extreme weather conditions as El
Nino effect hits Latin America and Australia. Retrieved October 1, 2017, from http://www.fao.
org/NEWS/1997/970904-e.htm.
Frischknecht, R., & Rebitzer, G. (2005). The ecoinvent database system: A comprehensive webbased LCA database. Journal of Cleaner Production, 13(13–14), 1337–1343.
Gazzola, V., van der Worp, H., Mulder, T., Wicker, B., Rizzolatti, G., & Keysers, C. (2007).
Aplasics born without hands mirror the goal of hand actions with their feet. Current Biology,
17(14), 1235–1240. https://doi.org/10.1016/j.cub.2007.06.045.
Gonzalez-Dugo, M. P., Neale, C. M. U., Mateos, L., Kustas, W. P., & Li, F. (2006). Comparison of
remote sensing-based energy balance methods for estimating crop evapotranspiration. Remote
Sensing, 63590Z. https://doi.org/10.1117/12.690056.
Goovaerts, P., Vellidis, P., & Ortiz, B. V. (2010). Geostatistical modeling of the spatial variability
and risk areas of southern root-knot nematodes in relation to soil properties. Geoderma, 156,
243–252. https://doi.org/10.1016/j.geoderma.2010.02.024.Geostatistical.
Graedel, T. E., Allenby, B. R., & Comrie, P. R. (1995). Matrix approaches to abridged life cycle
assessment. Environmental Science & Technology, 29(3), 134A–139A.
Greilich, S., Glasmacher, U. A., & Wagner, G. A. (2002). Spatially resolved detection of luminescence: A unique tool for archaeochronometry. Naturwissenschaften, 89(8), 371–375. https://
doi.org/10.1007/s00114-002-0341-z.
E. Eftelioglu and S. Shekhar
Challenges and Opportunities
Abadi, L. S. K., Shamsai, A., & Goharnejad, H. (2014). An analysis of the sustainability of basin
water resources using vensim model. KSCE Journal of Civil Engineering, 19(6), 1941–1949.
https://doi.org/10.1007/s12205-014-0570-7.
Allen, M., Rodrigo, M. F., Vargas, O., Graham, E. A., Swenson, W., Hamilton, M., Taggart, M.,
& Harmon, T. C. (2007). Soil sensor technology: Life within a pixel. BioScience, 57(10), 859.
https://doi.org/10.1641/B571008.
Brander, M., Tipper, R., Hutchison, C., & Davis, G. (2008). Consequential and attributional
approaches to LCA: A guide to policy makers with specific reference to greenhouse gas
LCA of biofuels. Econometrica Press, 44, 1–14. http://onlinelibrary.wiley.com/doi/10.1002/
cbdv.200490137/abstract%5Cnhttp://www.globalbioenergy.org/uploads/media/0804_
Ecometrica_-_Consequential_and_attributional_approaches_to_LCA.pdf%5Cnhttp://
d3u3pjcknor73l.cloudfront.net/assets/media/pdf/approachest.
Chang, K.-T. (2006). Introduction to geographic information systems. Boston: McGraw-Hill
Higher Education.
Chen, D., Cane, M. A., Kaplan, A., Zebiak, S. E., & Huang, D. (2004). Predictability of El Niño
over the past 148 years. Nature, 428(6984), 733–736. https://doi.org/10.1038/nature02439.
Cheng, R., Emrich, T., Kriegel, H. P., Mamoulis, N., Renz, M., Trajcevski, G., & Züfle, A. (2014).
Managing uncertainty in spatial and spatio-temporal data. In Proceedings – International conference on data engineering (pp. 1302–1305). https://doi.org/10.1109/ICDE.2014.6816766.
Costanza, R., & Voinov, A. (2001). Modeling ecological and economic systems with STELLA: Part
III. Ecological Modelling, 143(1–2), 1–7. https://doi.org/10.1016/S0304-3800(01)00358-1.
Eftelioglu, E., Li, Y., Tang, X., Shekhar, S., Kang, J. M., & Farah, C. (2016b). Mining network
hotspots with holes: A summary of results. Lecture Notes in Computer Science (Including
Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9927,
51–67. https://doi.org/10.1007/978-3-319-45738-3_4.
Elshorbagy, A., Corzo, G., Srinivasulu, S., & Solomatine, D. P. (2010). Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology –
Part 2: Application. Hydrology and Earth System Sciences, 14(10), 1943–1961. https://doi.
org/10.5194/hess-14-1943-2010.
ESRI, Redlands. (2011). ArcGIS desktop: Release 10. CA: Environmental Systems Research
Institute.
European Commission. (2015). Eurostat database, Luxemburg. European Commission 2008.
Food and Agriculture Organization. (n.d.). Farmers brace for extreme weather conditions as El
Nino effect hits Latin America and Australia. Retrieved October 1, 2017, from http://www.fao.
org/NEWS/1997/970904-e.htm.
Frischknecht, R., & Rebitzer, G. (2005). The ecoinvent database system: A comprehensive webbased LCA database. Journal of Cleaner Production, 13(13–14), 1337–1343.
Gazzola, V., van der Worp, H., Mulder, T., Wicker, B., Rizzolatti, G., & Keysers, C. (2007).
Aplasics born without hands mirror the goal of hand actions with their feet. Current Biology,
17(14), 1235–1240. https://doi.org/10.1016/j.cub.2007.06.045.
Gonzalez-Dugo, M. P., Neale, C. M. U., Mateos, L., Kustas, W. P., & Li, F. (2006). Comparison of
remote sensing-based energy balance methods for estimating crop evapotranspiration. Remote
Sensing, 63590Z. https://doi.org/10.1117/12.690056.
Goovaerts, P., Vellidis, P., & Ortiz, B. V. (2010). Geostatistical modeling of the spatial variability
and risk areas of southern root-knot nematodes in relation to soil properties. Geoderma, 156,
243–252. https://doi.org/10.1016/j.geoderma.2010.02.024.Geostatistical.
Graedel, T. E., Allenby, B. R., & Comrie, P. R. (1995). Matrix approaches to abridged life cycle
assessment. Environmental Science & Technology, 29(3), 134A–139A.
Greilich, S., Glasmacher, U. A., & Wagner, G. A. (2002). Spatially resolved detection of luminescence: A unique tool for archaeochronometry. Naturwissenschaften, 89(8), 371–375. https://
doi.org/10.1007/s00114-002-0341-z.
E. Eftelioglu and S. Shekhar