Open AccessDetermination of Crop Productivity Based on Climate Change using Geographic Information Systems
Author(s) -
Mohamed Osman Abdelhadi*
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d8719.118419
Subject(s) - productivity , crop productivity , environmental science , climate change , crop , sorghum , crop yield , agricultural engineering , agriculture , evapotranspiration , agricultural productivity , vegetation (pathology) , production (economics) , agroforestry , mathematics , geography , agronomy , forestry , ecology , engineering , medicine , archaeology , pathology , biology , economics , macroeconomics
This study is aimed at designing an algorithm to analyze the effects of climate on crops. Two different crops named sorghum and sesame were selected as a case study in Doka area in Sudan because this area receives good amount of rain suitable for the production of the selected crops, so GIS technology was used to determine the vegetation map of the study area. The idea applied was to select a sample of data for a period of ten years and determine the productivity of the crop in this period and then the production values of these years were arranged from the highest value of productivity to the lowest value and then determined the highest value of productivity in these years and note to the values of the climate effects (the best climatic conditions led to high productivity) which led to predicate and determine the crop productivity based on climate affected values, cultivated area (CA) ,Harvested Area (HA) , Damage Area (DA) and the area affected by Evapotranspiration Negatively (AEVN), so the results which have been accessed are that the algorithm can calculate crop yield with high accuracy because it depends on all climatic elements that affect crop growth, so all meteorological organizations in the world can use this algorithm principle to assess crop yields and Accurate assessment of production.