Meta-analysis of influential factors on crop yield estimation by remote sensing

References

• Antman, E. M., J. Lau, B. Kupelnick, F. Mosteller, and T. C. Chalmers. 1992. “A Comparison of Results of Meta-Analyses of Randomized Control Trials and Recommendations of Clinical Experts. Treatments for Myocardial Infarction.” Journal of American Medical Association 268 (2): 240–248. doi:10.1001/jama.1992.03490020088036.
   PubMed Web of Science ®Google Scholar
• Arora, V. K., and P. R. Gajri. 2000. “Assessment of a Crop Growth-Water Balance Model for Predicting Maize Growth and Yield in a Subtropical Environment.” Agricultural Water Management 46 (2): 157–166. doi:10.1016/S0378-3774(00)00079-2.
   Web of Science ®Google Scholar
• Báez-González, A. D., P. Y. Chen, M. Tiscareño-López, and R. Srinivasan. 2002. “Using Satellite and Field Data with Crop Growth Modeling to Monitor and Estimate Corn Yield in Mexico.” Crop Science 42 (6): 1943–1949. doi:10.2135/cropsci2002.1943.
   Web of Science ®Google Scholar
• Bai, J. H., J. Li, and S. K. Li. 2011. “Monitoring the Cotton Growth Conditions Based on LAI from Remote Sensing and Expert Knowledge.” Equipment Manufacturing Technology and Automation, Pts 1–3, 317–319: 1050–1057. doi:10.4028/www.scientific.net/AMR.317-319.1050.
   Google Scholar
• Bai, W. L., and F. P. Zhang. 2012. “Estimation of Winter Wheat Yield in Guanzhong Area of Shanxi Province Using SPOT VGT/NDVI.” Resource Development & Market 28 (6): 483–485.
   Google Scholar
• Balaghi, R., B. Tychon, H. Eerens, and M. Jlibene. 2008. “Empirical Regression Models Using NDVI, Rainfall and Temperature Data for the Early Prediction of Wheat Grain Yields in Morocco.” International Journal of Applied Earth Observation and Geoinformation 10 (4): 438–452. doi:10.1016/j.jag.2006.12.001.
   Web of Science ®Google Scholar
• Beelmann, A., M. Petticrew, and H. Roberts. 2006. “Systematic Reviews in the Social Sciences: A Practical Guide.” European Psychologist 11 (3): 244–245. doi:10.1027/1016-9040.11.3.244.
   Web of Science ®Google Scholar
• Bégué, A., V. Lebourgeois, E. Bappel, P. Todoroff, A. Pellegrino, F. Baillarin, and B. Siegmund. 2010. “Spatio-Temporal Variability of Sugarcane Fields and Recommendations for Yield Forecast Using NDVI.” International Journal of Remote Sensing 31 (20): 5391–5407. doi:10.1080/01431160903349057.
   Web of Science ®Google Scholar
• Benedetti, R., and P. Rossini. 1993. “On the Use of NDVI Profiles as a Tool for Agricultural Statistics: The Case Study of Wheat Yield Estimate and Forecast in Emilia Romagna.” Remote Sensing of Environment 45 (3): 311–326. doi:10.1016/0034-4257(93)90113-C.
   Web of Science ®Google Scholar
• Boken, V. K., and C. F. Shaykewich. 2002. “Improving an Operational Wheat Yield Model Using Phenological Phase-Based Normalized Difference Vegetation Index.” International Journal of Remote Sensing 23 (20): 4155–4168. doi:10.1080/014311602320567955.
   Web of Science ®Google Scholar
• Bouman, B. A. M. 1995. “Crop Modeling and Remote-Sensing for Yield Prediction.” Netherlands Journal of Agricultural Science 43 (2): 143–161.
   Google Scholar
• Bowler, D. E., L. Buyung-Ali, T. M. Knight, and A. S. Pullin. 2010. “Urban Greening to Cool Towns and Cities: A Systematic Review of the Empirical Evidence.” Landscape and Urban Planning 97 (3): 147–155. doi:10.1016/j.landurbplan.2010.05.006.
   Web of Science ®Google Scholar
• Breunig, F. M., L. S. Galvão, A. R. Formaggio, and J. C. N. Epiphanio. 2011. “Directional Effects on NDVI and LAI Retrievals from MODIS: A Case Study in Brazil With Soybean.” International Journal of Applied Earth Observation and Geoinformation 13 (1): 34–42. doi:10.1016/j.jag.2010.06.004.
   Web of Science ®Google Scholar
• Cai, D. H., R. Y. Wang, N. Guo, and X. W. Zhang. 2010. “Relation Between NDVI and Spring Wheat Yields and Their Response to Climate Warming in Minqin, Gansu.” Journal of Desert Research 30 (2): 376–382.
   Google Scholar
• Chaudhari, K. N., R. Tripathy, and N. K. Patel. 2010. “Spatial Wheat Yield Prediction Using Crop Simulation Model, GIS, Remote Sensing and Ground Observed Data.” Journal of Agrometeorology 12 (2): 174–180.
   Web of Science ®Google Scholar
• China.org.cn. 2012. “Yunnan Drought Set to Continue.” Accessed November 23. http://www.china.org.cn/environment/2012-02/20/content_24683525.htm
   Google Scholar
• Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. 2011. The Cochrane Collaboration. Accessed December 2012. http://handbook.cochrane.org/.
   Google Scholar
• Dabrowska-Zielinska, K., F. Kogan, A. Ciolkosz, M. Gruszczynska, and W. Kowalik. 2002. “Modelling of Crop Growth Conditions and Crop Yield in Poland Using AVHRR-Based Indices.” International Journal of Remote Sensing 23 (6): 1109–1123. doi:10.1080/01431160110070744.
   Web of Science ®Google Scholar
• Dadhwal, V. K., and V. N. Sridhar. 1997. “A Non-linear Regression Form for Vegetation Index-Crop Yield Relation Incorporating Acquisition Date Normalization.” International Journal of Remote Sensing 18 (6): 1403–1408. doi:10.1080/014311697218520.
   Web of Science ®Google Scholar
• Wit, A. J. W. de, and H. L. Boogaard. 2001. Monitoring of Crop Development and Crop Model Optimisation Using NOAA-AVHRR: Towards an Integrated Satellite and Model-based Crop Monitoring System in the European Context. Delft: Netherlands Remote Sensing Board (BCRS), Programme Bureau, Rijkswaterstaat Survey Department.
   Google Scholar
• Domenikiotis, C., M. Spiliotopoulos, E. Tsiros, and N. R. Dalezios. 2004. “Early Cotton Yield Assessment by the Use of the NOAA/AVHRR Derived Vegetation Condition Index (VCI) in Greece.” International Journal of Remote Sensing 25 (14): 2807–2819. doi:10.1080/01431160310001632729.
   Web of Science ®Google Scholar
• Doraiswamy, P. C., S. Moulin, P. W. Cook, and A. Stern. 2003. “Crop Yield Assessment from Remote Sensing.” Photogrammetric Engineering and Remote Sensing 69 (6): 665–674. doi:10.14358/PERS.69.6.665.
   Web of Science ®Google Scholar
• Egger, M., G. D. Smith, M. Schneider, and C. Minder. 1997. “Bias in Meta-Analysis Detected by a Simple, Graphical Test.” British Medical Journal 315 (7109): 629–634. doi:. doi:10.1136/bmj.315.7109.629.
   PubMed Web of Science ®Google Scholar
• Erickson, J. D. 1984. “The LACIE Experiment in Satellite Aided Monitoring of Global Crop Production.” In The Role of Terrestrial Vegetation in the Global Carbon Cycle: Measurement by Remote Sensing, edited by G. M. Woodwell. New York: Wiley.
   Google Scholar
• Fang, H., S. Liang, and G. Hoogenboom. 2011. “Integration of MODIS LAI and Vegetation Index Products with the CSM–CERES–Maize Model for Corn Yield Estimation.” International Journal of Remote Sensing 32 (4): 1039–1065. doi:10.1080/01431160903505310.
   Web of Science ®Google Scholar
• FAO. 2013. “Crop Prospects and Food Situation – No. 1 March 2013.” FAO Corporate Document Repository. Accessed March 29. http://www.fao.org/docrep/017/al998e/al998e00.htm.
   Google Scholar
• Ferencz, C., P. Bognár, J. Lichtenberger, D. Hamar, G. Tarcsai, G. Timár, G. Molnár, Pásztor S. Z., Steinbach P., Székely B., Ferencz O. E., Ferencz-Árkos I. 2004. “Crop Yield Estimation by Satellite Remote Sensing.” International Journal of Remote Sensing 25 (20): 4113–4149. doi:10.1080/01431160410001698870.
   Web of Science ®Google Scholar
• Fermont, A., and T. Benson. 2011. Estimating Yield of Food Crops Grown by Smallholder Farmers: A Review in the Uganda Context. Washington, DC: International Food Policy Research Institute.
   Google Scholar
• Fernandes, J. L., J. V. Rocha, and R. A. C. Lamparelli. 2011. “Sugarcane Yield Estimates Using Time Series Analysis of Spot Vegetation Images.” Scientia Agricola 68 (2): 139–146.
   Web of Science ®Google Scholar
• Fontana, D. C., A. B. Potgieter, and A. Apan. 2007. “Assessing the Relationship Between Shire Winter Crop Yield and Seasonal Variability of the MODIS NDVI and EVI Images.” Applied Gis 3 (7): 1–16.
   Google Scholar
• Freund, J. T., C. Funk, M. E. Budde, J. Michaelsen, and G. Galu. 2007. “MODIS NDVI-Based Crop Production Estimates for Zimbabwe in 2006/07.” American Geophysical Union, Fall Meeting, San Francisco, CA, December 15.
   Google Scholar
• Funk, C., and M. E. Budde. 2009. “Phenologically-Tuned MODIS NDVI-Based Production Anomaly Estimates for Zimbabwe.” Remote Sensing of Environment 113 (1): 115–125. doi:10.1016/j.rse.2008.08.015.
   Web of Science ®Google Scholar
• Gao, Z. L., X. G. Xu, J. H. Wang, H. A. Jin, and H. Yang. 2012. “Cotton Yield Estimation Based on Similarity Analysis of Time-Series NDVI.” Transactions of The CSAE 28 (2): 148–153. doi:10.3969/j.issn.1002-6819.2012.2.028.
   Google Scholar
• Gitelson, A. A., B. D. Wardlow, G. P. Keydan, and B. Leavitt. 2007. “An Evaluation of MODIS 250-m Data for Green LAI Estimation in Crops.” Geophysical Research Letters 34 (20): L20403. doi:10.1029/2007GL031620.
   Web of Science ®Google Scholar
• Glass, G. V. 1976. “Primary, Secondary, and Meta-Analysis of Research.” Educational Researcher 5 (10): 3–8. doi:10.3102/0013189X005010003.
   Google Scholar
• Glass, G. V. 1977. “Integrating Findings: The Meta-Analysis of Research.” Review of Research in Education 5: 351–379. doi:10.3102/0091732X005001351.
   Google Scholar
• Groten, S. M. E. 1993. “NDVI—Crop Monitoring and Early Yield Assessment of Burkina Faso.” International Journal of Remote Sensing 14 (8): 1495–1515. doi:10.1080/01431169308953983.
   Web of Science ®Google Scholar
• Hamar, D., C. Ferencz, J. Lichtenberger, G. Tarcsai, and I. Ferencz-ÁRkos. 1996. “Yield Estimation for Corn and Wheat in the Hungarian Great Plain Using Landsat MSS Data.” International Journal of Remote Sensing 17 (9): 1689–1699. doi:10.1080/01431169608948732.
   Web of Science ®Google Scholar
• Hasegawa, K., H. Matsuyama, H. Tsuzuki, and T. Sweda. 2010. “Improving the Estimation of Leafareaindex by Using Remotely Sensed NDVI with BRDF Signatures.” Remote Sensing of Environment 114 (3): 514–519. doi:10.1016/j.rse.2009.10.005.
   Web of Science ®Google Scholar
• Hatfield, J. L. 1983. “Remote-Sensing Estimators of Potential and Actual Crop Yield.” Remote Sensing of Environment 13 (4): 301–311. doi:10.1016/0034-4257(83)90032-9.
   Web of Science ®Google Scholar
• Hayes, M. J., and W. L. Decker. 1996. “Using NOAA AVHRR Data to Estimate Maize Production in the United States Corn Belt.” International Journal of Remote Sensing 17 (16): 3189–3200. doi:10.1080/01431169608949138.
   Web of Science ®Google Scholar
• Hu, S., and X. G. Mo. 2011. “Interpreting Spatial Heterogeneity of Crop Yield with a Process Model and Remote Sensing.” Ecological Modelling 222 (14): 2530–2541. doi:10.1016/j.ecolmodel.2010.11.011.
   Web of Science ®Google Scholar
• Jiang, D., N. B. Wang, X. H. Yang, and J. H. Wang. 2003. “Study on the Interaction Between NDVI Profile and the Growing Status of Crops.” Chinese Geographical Science 13 (1): 62–65. doi:10.1007/s11769-003-0086-4.
   Web of Science ®Google Scholar
• Kogan, F. N. 1994. “NOAA Plays Leadership Role in Developing Satellite Technology for Drought Watch.” Earth Observation Magazine 11: 1405–1409.
   Google Scholar
• Labus, M. P., G. A. Nielsen, R. L. Lawrence, R. Engel, and D. S. Long. 2002. “Wheat Yield Estimates Using Multi-Temporal NDVI Satellite Imagery.” International Journal of Remote Sensing 23 (20): 4169–4180. doi:10.1080/01431160110107653.
   Web of Science ®Google Scholar
• Lau, J., E. M. Antman, J. Jimenez-Silva, B. Kupelnick, F. Mosteller, and T. C. Chalmers. 1992. “Cumulative Meta-Analysis of Therapeutic Trials for Myocardial Infarction.” The New England Journal of Medicine 327 (4): 248–254. doi:10.1056/NEJM199207233270406.
   PubMed Web of Science ®Google Scholar
• Lewis, J. E., J. Rowland, and A. Nadeau. 1998. “Estimating Maize Production in Kenya Using NDVI: Some Statistical Considerations.” International Journal of Remote Sensing 19 (13): 2609–2617. doi:10.1080/014311698214677.
   Web of Science ®Google Scholar
• Lillesand, T. M., and R. W. Kiefer. 1994. Remote Sensing and Photo Interpretation. New York: Wiley.
   Google Scholar
• Lipsey, M. W., and D. B. Wilson. 1993. “The Efficacy of Psychological, Educational, and Behavioral Treatment: Confirmation from Meta-analysis.” American Psychologist 48 (12): 1181–1209. doi:10.1037/0003-066X.48.12.1181.
   PubMed Web of Science ®Google Scholar
• Lipsey, M. W., and D. B. Wilson. 2011. Practical Meta-Analysis, Applied Social Research Methods. Vol. 49. New York: SAGE.
   Google Scholar
• Maselli, F., and F. Rembold. 2001. “Analysis of GAC NDVI Data for Cropland Identification and Yield Forecasting in Mediterranean African Countries.” Photogrammetric Engineering and Remote Sensing 67: 593–602.
   Web of Science ®Google Scholar
• Ma, B. L., L. M. Dwyer, C. Costa, E. R. Cober, and M. J. Morrison. 2001. “Early Prediction of Soybean Yield from Canopy Reflectance Measurements.” Agronomy Journal 93 (6): 1227–1234. doi:10.2134/agronj2001.1227.
   Google Scholar
• Maselli, F., S. Romanelli, L. Bottai, and G. Maracchi. 2000. “Processing of GAC NDVI Data for Yield Forecasting in the Sahelian Region.” International Journal of Remote Sensing 21 (18): 3509–3523. doi:10.1080/014311600750037525.
   Web of Science ®Google Scholar
• Mather, P., and M. Koch. 2011. Computer Processing of Remotely-Sensed Images: An Introduction. New York, NY: Wiley.
   Google Scholar
• Meyer-Roux, J., and P. Vossen. 1993. “The First Phase of the MARS Project, 1988–1993: Overview, Methods and Results.” In Conference on the MARS Project: Overview and Prospectives, 33–79. Lake Maggiore: European Commission.
   Google Scholar
• Miraglia, M., H. J. Marvin, G. A. Kleter, P. Battilani, C. Brera, E. Coni, F. Cubadda, L. Croci, B. De Santis, S. Dekkers, L. Filippi, R. W. A. Hutjes, M. Y. Noordam, M. Pisante, G. Piva, A. Prandini, L. Toti, G. J. van den Born, A. Vespermann. 2009. “Climate Change and Food Safety: An Emerging Issue with Special Focus on Europe.” Food and Chemical Toxicology 47 (5): 1009–1021. doi:10.1016/j.fct.2009.02.005.
   PubMed Web of Science ®Google Scholar
• Mkhabela, M. S., P. Bullock, S. Raj, S. Wang, and Y. Yang. 2011. “Crop Yield Forecasting on the Canadian Prairies Using MODIS NDVI Data.” Agricultural and Forest Meteorology 151 (3): 385–393. doi:10.1016/j.agrformet.2010.11.012.
   Web of Science ®Google Scholar
• Mkhabela, M. S., S. M. Milton, and N. N. Mashininic. 2005. “Early Maize Yield Forecasting in the Four Agro-ecological Regions of Swaziland Using NDVI Data Derived from NOAA’s-AVHRR.” Agricultural and Forest Meteorology 129 (1–2): 1–9. doi:10.1016/j.agrformet.2004.12.006.
   Google Scholar
• Moulin, S., A. Bondeau, and R. Delecolle. 1998. “Combining Agricultural Crop Models and Satellite Observations: From Field to Regional Scales.” International Journal of Remote Sensing 19 (6): 1021–1036. doi:10.1080/014311698215586.
   Web of Science ®Google Scholar
• Mukherjee, J., G. Gebru, A. Sood, R. K. Mahey, S. K. Bal, H. Singh, and P. K. Sidhu. 2010. “Wheat Yield and Acreage Prediction Using LISS-III and AWiFS Sensors Data of Indian Remote Sensing Satellite of Rupnager District of Punjab, India.” Rivista Italiana Di Telerilevamento 42 (3): 115–127. doi:10.5721/ItJRS20104239.
   Web of Science ®Google Scholar
• Muthy, C. S., S. Jonna, P. V. Raju, S. Thurivengadachari, and K. A. Hakeem. 1994. “Crop Yield Prediction in Command Area using Satellite Data.” In Proceedings of the 15th Asian Conference on Remote Sensing, 14.1-.6. Bangalore: ISRO.
   Google Scholar
• Parry, M. L., O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson. 2007. “Impacts, Adaptation and Vulnerability.” In IPCC Fourth Assessment Report: Climate Change 2007. New York, NY: Cambridge University Press.
   Google Scholar
• Paruelo, J. M., M. Oesterheld, C. M. Di Bella, M. Arzadum, J. Lafontaine, M. Cahuepé, and C. M. Rebella. 2000. “Estimation of Primary Production of Subhumid Rangelands from Remote Sensing Data.” Applied Vegetation Science 3 (2): 189–195. doi:10.2307/1478997.
   Web of Science ®Google Scholar
• Platonov, A., P. S. Thenkabail, C. M. Biradar, X. L. Cai, M. Gumma, V. Dheeravath, Y. Cohen, V. Alchanatis, N. Goldshlager, E. Ben-Dor, J. Vithanage, H. Manthrithilake, S. Kendjabaev, and S. Isaev. 2008. “Water Productivity Mapping (WPM) Using Landsat ETM plus Data for the Irrigated Croplands of the Syrdarya River Basin in Central Asia.” Sensors 8 (12): 8156–8180. doi:10.3390/S8128156.
   Google Scholar
• Pullin, A. S., and G. B. Stewart. 2006. “Guidelines for Systematic Review in Conservation and Environmental Management.” Conservation Biology 20 (6): 1647–1656. doi:10.1111/j.1523-1739.2006.00485.x.
   PubMed Web of Science ®Google Scholar
• Quarmby, N. A., M. Milnes, T. L. Hindle, and N. Silleos. 1993. “The Use of Multi-Temporal NDVI Measurements from AVHRR Data for Crop Yield Estimation and Prediction.” International Journal of Remote Sensing 14 (2): 199–210. doi:10.1080/01431169308904332.
   Web of Science ®Google Scholar
• Rasmussen, M. S. 1992. “Assessment of Millet Yields and Production in Northern Burkina-Faso Using Integrated NDVI from the AVHRR.” International Journal of Remote Sensing 13 (18): 3431–3442. doi:10.1080/01431169208904132.
   Web of Science ®Google Scholar
• Rasmussen, M. S. 1997. “Operational Yield Forecast Using AVHRR NDVI Data: Reduction of Environmental and Inter-Annual Variability.” International Journal of Remote Sensing 18 (5): 1059–1077. doi:10.1080/014311697218575.
   Web of Science ®Google Scholar
• Ren, J. Q., Z. X. Chen, Q. B. Zhou, and H. J. Tang. 2008. ”Regional Yield Estimation for Winter Wheat with MODIS-NDVI Data in Shandong, China.“ International Journal of Applied Earth Observation and Geoinformation 10 (4): 403–413. doi:10.1016/j.jag.2007.11.003.
   Google Scholar
• Ren, X., W. Xu, and A. Smith. 2012. “Remote Sensing, Crop Yield Estimation and Agricultural Vulnerability Assessment : A Case of Southern Alberta.” The Open Hydrology Journal 6: 68–77. doi:10.2174/1874378101206010068.
   Google Scholar
• Reynolds, C. A., M. Yitayew, D. C. Slack, C. F. Hutchinson, A. Huete, and M. S. Petersen. 2000. “Estimating Crop Yields and Production by Integrating the FAO Crop Specific Water Balance Model with Real-Time Satellite Data and Groundbased Ancillary Data.” International Journal of Remote Sensing 21: 3487–3508. doi:10.1080/014311600750037516.
   Web of Science ®Google Scholar
• Rojas, O. 2007. “Operational Maize Yield Model Development and Validation Based on Remote Sensing and Agro-Meteorological Data in Kenya.” International Journal of Remote Sensing 28 (17): 3775–3793. doi:10.1080/01431160601075608.
   Web of Science ®Google Scholar
• Ross, J. 1981. The Radiation Regime and Architecture of Plant Stands, Tasks for Vegetation Sciences, 3. The Hague: W. Junk.
   Google Scholar
• Sakamoto, T., A. A. Gitelson, and T. J. Arkebauer. 2013. “MODIS-Based Corn Grain Yield Estimation Model Incorporating Crop Phenology Information.” Remote Sensing of Environment 131: 215–231. doi:10.1016/j.rse.2012.12.017.
   Web of Science ®Google Scholar
• Salazar, L., F. Kogan, and L. Roytman. 2007. “Use of Remote Sensing Data for Estimation of Winter Wheat Yield in the United States.” International Journal of Remote Sensing 28 (17): 3795–3811. doi:10.1080/01431160601050395.
   Web of Science ®Google Scholar
• Singh, R. 2012. “Crop Yield Estimation and Forecasting Using Remote Sensing.” In Forecasting Techniques in Agriculture, edited by K. N. Singh, A. Kumar, and H. Chandra, 201–215. New Delhi: Indian Agricultural Statistics Research Institute.
   Google Scholar
• Sterne, J. A. C., and M. Egger. 2001. “Funnel Plots for Detecting Bias in Meta-Analysis: Guidelines on Choice of Axis.” Journal of Clinical Epidemiology 54 (10): 1046–1055. http://dx.doi.org/10.1016/S0895-4356(01)00377-8. doi:10.1016/S0895-4356(01)00377-8.
   PubMed Web of Science ®Google Scholar
• Teal, R. K., B. Tubana, K. Girma, K. W. Freeman, D. B. Arnall, O. Walsh, and W. R. Raun. 2006. “In-season Prediction of Corn Grain Yield Potential Using Normalized dIfference Vegetation Index.” Agronomy Journal 98 (6): 1488–1494. doi:10.2134/agronj2006.0103.
   Web of Science ®Google Scholar
• Thomasson, J. A., J. R. Wooten, S. Gogineni, R. X. Sui, and B. M. Kolla, Gao W., Shaw D. R. 2004. “Remote Sensing and Weather Information in Cotton Yield Prediction.” Ecosystems’ Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture 5153: 127–135. doi:10.1117/12.506984.
   Google Scholar
• Van Ittersum, M. K., P. A. Leffelaar, H. van Keulen, M. J. Kropff, L. Bastiaans, and J. Goudriaan. 2003. “On Approaches and Applications of the Wageningen Crop Models.” European Journal of Agronomy 18 (3–4): 201–234. doi:10.1016/S1161-0301(02)00106-5.
   Web of Science ®Google Scholar
• Wang, J., P. M. Rich, K. P. Price, and W. Dean Kettle. 2005. “Relations Between NDVI, Grassland Production, and Crop Yield in the Central Great Plains.” Geocarto International 20 (3): 5–11. doi:10.1080/10106040508542350.
   Google Scholar
• Wang, L., Y. Bai, Y. Lu, H.E. Wang, and L. Yang. 2013. “NDVI Analysis and Yield Estimation in Winter Wheat Based on Green-Seeker.” Acta Agronomica Sinica 38 (4): 747–753. doi:10.3724/SP.J.1006.2012.00747.
   Google Scholar
• Wang, P. J., R. Sun, J. H. Zhang, Y. Y. Zhou, D. H. Xie, and Q. J. Zhu. 2011. “Yield Estimation of Winter Wheat in the North China Plain Using the Remote-Sensing-Photosynthesis-Yield Estimation for Crops (RS-P-YEC) Model.” International Journal of Remote Sensing 32 (21): 6335–6348. doi:10.1080/01431161.2010.508800.
   Web of Science ®Google Scholar
• Wang, Q., S. Adiku, J. Tenhunen, and A. Granier. 2005. “On the Relationship of NDVI with Leaf Area Index in a Deciduous Forest Site.” Remote Sensing of Environment 94 (2): 244-255. doi:. doi:10.1016/j.rse.2004.10.006.
   Web of Science ®Google Scholar
• Wiegand, C. L., J. D. Rhoades, D. E. Escobar, and J. H. Everitt. 1994. “Photographic and Videographic Observations for Determining and Mapping the Response of Cotton to Soil-Salinity.” Remote Sensing of Environment 49 (3): 212–223. doi:10.1016/0034-4257(94)90017-5.
   Web of Science ®Google Scholar
• Wilson, D. B. 2012. Meta-Analysis Macros for SAS, SPSS, and Stata. Accessed December 20. http://mason.gmu.edu/~dwilsonb/ma.html
   Google Scholar
• Zhang, F., B. F. Wu, and C. L. Liu. 2003. “An Advanced Tool for Real-Time Crop Monitoring in China.” In IEEE International Geoscience and Remote Sensing Symposium, 2242–2244. Toulouse: Institute of Electrical & Electronics Engineers (IEEE).
   Google Scholar
• Zhang, H., H. Chen, and G. Zhou. 2012. “The Model of Wheat Yield Forecast Based on MODIS-NDVI-- A Case Study of Xinxiang.” In The XXII ISPRS Congress of the Remote Sensing and Spatial Information Sciences, 25–28, Melbourne: Copernicus GmbH.
   Google Scholar