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Visualizing SRTM-NASA DEMs in ArcGIS: Practical Examples
Temporal and Spatial Assessment of temperature and precipitation over Djibouti (1961–2017)
The study area covers the capital of the Republic of Djibouti (Lat: 11.33 and long: 43.50), located to the southwest. A province of Africa in which climate change is impacting rural populations. The work of (Ozer and Ayan, 2013) describes it. The temporal evaluation will be limited only to the capital. The station at Djibouti International Airport provides historical data on precipitation and min and max temperature. The spatial framework covers the five regions of the Republic of Djibouti, including Tadjourah, Dikhil (Lat: 11.10 and Long: 42.37), Ali-Sabieh (Lat: 11.15 and Long: 42.70), Arta (Lat: 11.50 and Long: 42.83) and Obock (Lat: 11.97 and Long: 43.28). We analyze a daily historical base of the station of the international airport of Djibouti (Lat: 11.33 and long: 43.50). For precipitation, the daily series is between 1980 and 2017. We also had another series of data from 1950 to 1970. For lack of more than 10 years of information, the latter is neglected. The monthly precipitation ranges from 1961 to 2017. With regard to temperature, the daily data series is studied between 1966 to 2009. We also have the same monthly series from 1961 to 2017.
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Comparative study of satellite data and surface air temperature observations
Comparative study of satellite data and precipitation observations
Temporal-spatial Meteorological Variability of Drought and Flood Characteristics using in situ observations and Multi- satellites Reanalysis Products over the Republic of Djibouti From 1901 to 2021
The Spatial-temporal studies of drought and flood events was conducted for the first time, using data from 35 rainfall stations, distributed over the 6 districts of the Republic of Djibouti. The drought assessment is based on the SPEI and SPI indices at three time scales (3, 6 and 12 months) during the period 1961 to 2016. Accuracy of the very high resolution satellite product reanalysis was conducted using (CHIRPS), (ERA-5), (PERSIANNCDR), Terra Climate, (CHELSA) for precipitation and (CHIRTS), (CFR), (ERA-5) and Terra Climate for Minimum and Maximum temperature.
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Evolution of the Intelligence of the Human Species
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https://www.impactio.com/laboratory/ABIA?tab=posts
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Statistical Analysis of Environmental and Climate Data Using Pixel-Wise Multiple Regression, OLS, and Geographically Weighted Regression in the R Programming Language: Application to Vegetation Index (VI) and Land Surface Temperature (LST), Potential Evap
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https://www.impactio.com/laboratory/ABIA-1?tab=publications
The Abdi-Basid Courses Institute
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