Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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One of the main factors determining the daily variation of the active surface temperature is the state of the vegetation cover. It can well be characterized by the Normalized Difference Vegetation Index (NDVI). The NDVI has the potential ability to signal the vegetation features of different eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. The vegetation phenology is the expression of the seasonal cycles of plant processes and contributes vital current information on vegetation conditions and their connections to climate change. The NDVI is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. A gapless time series of MODIS NDVI (MOD13A1) composite raster data from 18th February, 2000 to 16th November, 2012 with a spatial resolution of 500 m was utilized. Time-series terrestrial parameters derived from NDVI have been extensively applied to global climate change, since it analyzes each pixel individually without the setting of thresholds to detect change within a time series.
Dr. Farooq Ahmad. 2013. \u201cPhenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) For Monitoring Of Vegetation and Climate Change in North-Eastern Punjab, Pakistan\u201d. Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 12 (GJHSS Volume 12 Issue B13): .
Crossref Journal DOI 10.17406/GJHSS
Print ISSN 0975-587X
e-ISSN 2249-460X
The methods for personal identification and authentication are no exception.
Total Score: 106
Country: Pakistan
Subject: Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management
Authors: Dr. Farooq Ahmad (PhD/Dr. count: 1)
View Count (all-time): 126
Total Views (Real + Logic): 5067
Total Downloads (simulated): 2614
Publish Date: 2013 01, Thu
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One of the main factors determining the daily variation of the active surface temperature is the state of the vegetation cover. It can well be characterized by the Normalized Difference Vegetation Index (NDVI). The NDVI has the potential ability to signal the vegetation features of different eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. The vegetation phenology is the expression of the seasonal cycles of plant processes and contributes vital current information on vegetation conditions and their connections to climate change. The NDVI is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. A gapless time series of MODIS NDVI (MOD13A1) composite raster data from 18th February, 2000 to 16th November, 2012 with a spatial resolution of 500 m was utilized. Time-series terrestrial parameters derived from NDVI have been extensively applied to global climate change, since it analyzes each pixel individually without the setting of thresholds to detect change within a time series.
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