Carte Crop Yield Forecast Modeling Ibrar ul Hassan Akhtar

Crop Yield Forecast Modeling

A Case Study of Sugarcane in Pakistan from Combined Remote Sensing and Agrometeorological Techniques

Limbă: engleză
Legare: Carte broșată
Disponibilitate: La editor doar la comandă
Expediem în 17-27 zile
254.13 lei
This text is mainly focused to highlight the improvement needs of the current system of statistical...

Informații despre carte

Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2011
Pagini
112
EAN
9783639372144
Enbook ID
06843915
Greutate
183
Dimensiuni
150 x 220 x 7

Descriere completă

This text is mainly focused to highlight the improvement needs of the current system of statistical sample based crop yield forecasting in developing country like Pakistan with latest state of the art, Remote Sensing & GIS technologies along with agro-meteorological science. Prime emphasis is to incorporate the synoptic variability in vegetation surface on earth through satellite technology instead of localized crop yield sampling method. Secondly, there is also a comparative study for linear (Regression), non-linear (Neural Network) and Crop Simulation model to conclude basis for sugarcane crop yield forecasting system. Remote sensing is mainly based on MODIS sensor data and GIS include mainly the geo-located crop cuttings at harvesting of Sugarcane. Crop Evapo-transpiration, crop water productivity, Nutrient availability, irrigation water, crop water stress index and Vegetation Index (NDVI) are prime parameters of all crop yield models. Benefits of such forecasting system are rational policy for food security and timely availability of agricultural statistics with reliability.

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