Remotely sensed innovative approach for the cumulative meteorological effects on cotton production

Christos Domenikiotis; Marios G. Spiliotopoulos; Emanouil K Tsiros; Nicolaos R. Dalezios

doi:10.1117/12.512392

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24 February 2004 Remotely sensed innovative approach for the cumulative meteorological effects on cotton production

Christos Domenikiotis; Marios G. Spiliotopoulos; Emanouil K Tsiros; Nicolaos R. Dalezios

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Proceedings Volume 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V; (2004) https://doi.org/10.1117/12.512392
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

In this study an innovative approach for investigating the accumulated meteorological effects on cotton production during the growing season is presented. The quantification of the meteorological effects is based on the incorporation of the Bhalme and Mooley Drought Index (BMDI) methodology into the Vegetation Condition Index (VCI) extracted by NOAA/AVHRR data. The resulted Bhalme and Mooley Vegetation Condition Index (BMVCI) uses the same scale as the Z-Index of the Palmer Drought Severity Index (PDSI) for drought monitoring. The study area consists of the country of Greece. Eighteen years of NOAA/AVHRR data are examined and processed with the BMVCI to examine the unfavourable conditions for cotton production. For the validation of BMVCI an empirical relationship between the cotton production and the BMVCI values is derived. The method is developed based on the first sixteen years time series data and validated utilizing the following two years. The resultant high correlation coefficient and the approximation of the production for the validated years refer to very favourable results and confirms the usefulness of this integrated methodological approach as an effective tool to assess cotton production in Greece.

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Christos Domenikiotis, Marios G. Spiliotopoulos, Emanouil K Tsiros, and Nicolaos R. Dalezios "Remotely sensed innovative approach for the cumulative meteorological effects on cotton production", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); https://doi.org/10.1117/12.512392

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