استخدام نظم المعلومات الجغرافية في التببؤ بمحصول الحنطة في جنوب العراق == The Use of Geographic Information Systems In The Prediction of The Wheat Crop In Southern Iraq
Author name:
هلاء سعدون شكر
Supervisor name:
محمود مهدي حسن البياتي
General topic:
Administration and Economics
Specific topic:
Applied Statistics
Degree:
Higher Diploma
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T4150 - p.pdf
Abstract:
The wheat crop is considered one of the most important strategic food crops and takes the first place in some countries in the world. So this crop requires growth control began from the time of planting and until harvesting. The study focused on predicting the productivity of wheat crop in township Shihamia / Essaouira district / in Wasit province as a model adopted for the rest of Iraq's provinces by using technologies (Remote Sensing and Geographic Information Systems) in devising data independent of the factorsthat have affected the productivity of the crop using (Geostatistic) analysis through (kriging) tool in an environment (Arcgis), and visual satellite captured from satellite (landsat 8) is also used. The extraction of natural vegetative differences guide (NDVI), as evidence showed reflectivity values ranging between ( - 0.02 - 0.5) as the minimum value of the evidence which indicated that the production of wheat crop in these places is low. The upper limit indicated that the production of wheat crop is high density in thoseareas. The surface temperature extracted from the space visible as well as the natural vegetative differences guide. Results indicate that the month of March is one of the appropriate months to get to know the productivity of wheat crop. The results showed when conducting analysis in the SPSS program that factor relative humidity though influential in the expected output when using directory natural vegetative differences values (NDVI). The climatic factors and the surface temperature and salinity influential in expected production in Geostatistic analysis, as Geostatistic analysis in an environment (Arcgis) is better than in the SPSS statistical analysis software because it depends on the spatial relationships between the studied samples
