Determination of Crop Productivity Based on Climate Change using Geographic Information Systems
Mohamed Osman Abd Elhadi Eltaib
Mohamed Osman Abdelhadi, Department of Computer Science, College of Science and Arts, Jouf University, Tabarjal, Kingdom of Saudi Arabia.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 10204-10208 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8719118419/2019©BEIESP | DOI: 10.35940/ijrte.D8719.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Cultivated Area(CA), Harvested Area(HA), Damage Area(DA), Area affected by Evapotranspiration Negatively(AEVN).
Scope of the Article: Neural Information Processing.