Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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The landsat ETM+ has shown great potential in agricultural mapping and monitoring due to its advantages over traditional receive procedures in terms of cost effectiveness and timeliness in availability of information over larger areas and ingredient the temporal dependence of multitemporal image data to identify the changing pattern of vegetation cover and consequently enhance the interpretation capabilities. Integration of multi-sensor and multitemporal satellite data effectively improves the temporal attribute and accuracy of the results. Since 2000, NASA’s MODIS sensors (onboard Terra satellite) has provided composite data at 16- days interval to produce estimates of gross primary production (GPP) that compare well with direct measurements. The MODIS Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which are independent of climatic drivers, also appears as valuable surrogate for estimation of seasonal patterns in GPP.
Dr. Farooq Ahmad. 2013. \u201cLandsat ETM+ and MODIS EVI/NDVI Data Products for Climatic Variation and Agricultural Measurements in Cholistan Desert\u201d. Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 12 (GJHSS Volume 12 Issue B13): .
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Crossref Journal DOI 10.17406/GJHSS
Print ISSN 0975-587X
e-ISSN 2249-460X
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Neural Networks and Rules-based Systems used to Find Rational and
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The landsat ETM+ has shown great potential in agricultural mapping and monitoring due to its advantages over traditional receive procedures in terms of cost effectiveness and timeliness in availability of information over larger areas and ingredient the temporal dependence of multitemporal image data to identify the changing pattern of vegetation cover and consequently enhance the interpretation capabilities. Integration of multi-sensor and multitemporal satellite data effectively improves the temporal attribute and accuracy of the results. Since 2000, NASA’s MODIS sensors (onboard Terra satellite) has provided composite data at 16- days interval to produce estimates of gross primary production (GPP) that compare well with direct measurements. The MODIS Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which are independent of climatic drivers, also appears as valuable surrogate for estimation of seasonal patterns in GPP.
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