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Map represent the cumulative displaced persons in UNRWA Shelters for 12/10/2023
15/10/2023

Map represent the cumulative displaced persons in UNRWA Shelters for 12/10/2023

Image represent the modification in Mangrove cover between 2016&2020 by using raster function in ArcGIS pro,this functio...
30/07/2023

Image represent the modification in Mangrove cover between 2016&2020 by using raster function in ArcGIS pro,
this function allows you to compare two raster datasets to identify and visualize the changes that have occurred over time.
Here are the steps to perform change detection using raster functions in ArcGIS Pro:
Step 1: Prepare the Data
Ensure you have two raster datasets that you want to compare for change detection. These datasets should represent the same area and cover the same spatial extent.
Step 2: Create a New Map Project
Open ArcGIS Pro and create a new map project. Import or add the raster datasets you want to compare into the map.
Step 3: Enable the Raster Function Editor
To access and create custom raster functions, you need to enable the Raster Function Editor in ArcGIS Pro. Go to the "Analysis" tab, and in the "Geoprocessing" group, click on "Raster Functions."
Step 4: Add Raster Function
In the Raster Function Editor window, click on the "Add Raster Function" button (it looks like a green plus sign).
Step 5: Choose Change Detection Function
In the "Search for functions" box, type "Change Detection." Several change detection functions will appear. Choose the one that suits your requirements. Some common options are "Change Detection - Image Analysis" or "Change Detection - Change Mapper."
Step 6: Configure the Change Detection Function
Once you've selected the change detection function, the function parameters will be displayed. These parameters vary depending on the specific function you chose. Typically, you'll need to specify the input raster datasets, date information, and any additional parameters related to change detection.
Step 7: Apply the Change Detection Function
Click on the "Run" button to apply the change detection function to your raster datasets. The output will be a new raster layer that represents the changes between the two input datasets. This output raster will display areas of change, such as areas that have been added, removed, or modified over time.
Step 8: Symbolize and Analyze the Output
Symbolize the output raster layer to visualize the changes effectively. You can use a color ramp to represent different types of changes or use transparency to overlay the change layer on top of the original datasets.
Step 9: Save and Share the Results
Save the change detection results as a new raster dataset if you wish to use it for further analysis or share it with others.

 # Between slope and CliffThe terms "slope" and "cliff" are both related to the steepness or inclination of landforms, b...
29/07/2023

# Between slope and Cliff
The terms "slope" and "cliff" are both related to the steepness or inclination of landforms, but they differ in their characteristics and scale. Here's an explanation of each term:
Slope: A slope refers to a gradual or gentle incline or decline of land. It is a more general term used to describe the gradual change in elevation over a distance. Slopes can be found in various natural and man-made landscapes, such as hillsides, mountainsides, and even roads or ramps. The degree of steepness can vary, ranging from a mild slope to a moderately steep one. Slopes are typically characterized by a gradual transition between different elevations.
Cliff: A cliff, on the other hand, refers to a steep or vertical rock face or escarpment. It represents a more abrupt change in elevation compared to a slope. Cliffs are typically formed by erosion processes, such as the action of water or weathering over a long period of time. They can be found in various geological settings, including coastlines, canyons, or mountain ranges. Cliffs are usually characterized by a distinct vertical or near-vertical drop, creating a prominent and often dramatic feature.
GEOGIS

The interpolation methods are commonly used GIS and spatial analysis. This term refers to the general concept of estimat...
29/07/2023

The interpolation methods are commonly used GIS and spatial analysis. This term refers to the general concept of estimating values at unknown locations based on known values at nearby locations within a GIS framework. It encompasses various interpolation techniques used in GIS software.
What is the different between each method?
1- Kriging:
Kriging is a geostatistical interpolation technique that estimates values at unmeasured locations by considering the spatial correlation between known data points. It incorporates statistical models to predict values based on the spatial relationship and spatial autocorrelation of the data. Kriging provides not only an interpolated surface but also an estimation of the uncertainty associated with the predictions.
2- Kernel Interpolation:
Kernel interpolation, also known as kernel density interpolation, is a method used to estimate values at unmeasured locations based on a weighted average of nearby known values. It assigns weights to neighboring data points based on their proximity, with closer points receiving higher weights.
3- Inverse Distance Weighting (IDW):
IDW is a simple and widely used interpolation method. It estimates values at unmeasured locations by assigning weights to known values based on their inverse distance to the target location. Closer points have higher influence on the estimation, while more distant points have less influence.
4- Radial Basis Function (RBF) Interpolation:
RBF interpolation is a technique that estimates values at unknown locations based on a combination of radial basis functions. These functions determine the influence of known values based on their distance from the unknown location. RBF interpolation is often used for irregularly spaced data points and can provide a smooth continuous surface.
GEOGIS

GNDVI (Green Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index) are both vegetation indic...
29/07/2023

GNDVI (Green Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index) are both vegetation indices commonly used in remote sensing and vegetation monitoring. They are used to assess the health and vigor of vegetation, but they differ in their calculation methods and applications.
1. GNDVI (Green Normalized Difference Vegetation Index):
GNDVI is a vegetation index that measures the density and vigor of green vegetation. It primarily utilizes the reflectance values in the green and near-infrared (NIR) spectral regions. The formula for calculating GNDVI is:
GNDVI = (NIR - Green) / (NIR + Green)
In this formula, "NIR" refers to the reflectance in the near-infrared band, and "Green" refers to the reflectance in the green band. GNDVI values range from -1 to 1, with higher values indicating healthier and more abundant vegetation. GNDVI is sensitive to chlorophyll content and leaf area index (LAI) and is commonly used in agriculture, forestry, and land cover studies.
2. SAVI (Soil-Adjusted Vegetation Index):
SAVI is a vegetation index that attempts to minimize the influence of soil brightness on vegetation indices. It was developed to account for variations in soil reflectance, particularly in areas with high soil brightness or sparse vegetation. The formula for calculating SAVI is:
SAVI = ((NIR - Red) / (NIR + Red + L)) x (1 + L)
Here, "NIR" represents the reflectance in the near-infrared band, "Red" represents the reflectance in the red band, and "L" is a soil adjustment factor typically set to 0.5. SAVI values also range from -1 to 1, with higher values indicating healthier vegetation. SAVI is particularly useful in areas with a high proportion of bare soil or where vegetation cover is sparse, such as arid and semi-arid regions.

The different between hillshade, Aspect, slope, flow direction 🤔Hillshade, aspect, slope, and flow direction are all ter...
29/07/2023

The different between hillshade, Aspect, slope, flow direction 🤔

Hillshade, aspect, slope, and flow direction are all terrain analysis tools commonly used in Geographic Information Systems (GIS) and remote sensing.

Hillshade: Hillshade is a visualization tool that creates a shaded relief map of a digital elevation model (DEM) to simulate the effect of light on the terrain. This technique is commonly used to enhance the visual appearance of the terrain and highlight its features.

Aspect: Aspect is a measurement of the direction that a slope faces. It is usually measured in degrees clockwise from north and can provide important information about the exposure of the terrain to the sun and wind. Aspect is commonly used in a range of applications, from forestry to wildfire management.

Slope: Slope is a measurement of the steepness of the terrain. It is usually measured in degrees or as a percentage and can provide important information about the suitability of the terrain for various activities such as agriculture, construction, or transportation.

Flow direction: Flow direction is a measure of the direction in which water or other liquids would flow across the terrain. It is calculated based on the slope of the terrain and can provide information about the drainage patterns and hydrological properties of the terrain.

Jord El Kaytaa Hydrogeological map,Jord El Kaytaa is a region in North Lebanon that is characterized by its limestone be...
29/07/2023

Jord El Kaytaa Hydrogeological map,

Jord El Kaytaa is a region in North Lebanon that is characterized by its limestone bedrock, which is known for its karstic features. Karst is a type of topography that is formed by the dissolution of soluble rocks such as limestone, dolomite. This process leads to the formation of various features such as sinkholes, caves, underground rivers, and springs.

Generally, In Akkar, the karstic features are mainly formed by the dissolution of the Jurassic limestone that makes up the bedrock. The area is characterized by a series of sinkholes, underground rivers, and springs, which are important sources of water for the region.
The aquifers in this area are primarily composed of Jurassic limestone, which has a high permeability and porosity, making it an excellent water-bearing rock. The water in these aquifers is generally of good quality and is used for various purposes such as drinking, irrigation.

Syria population Density
29/07/2023

Syria population Density

Lebanon population density 2022GEO-GIS
29/07/2023

Lebanon population density 2022
GEO-GIS

It is difficult to imagine Egypt without the Nile, as the river has played a critical role in shaping the country's geog...
29/07/2023

It is difficult to imagine Egypt without the Nile, as the river has played a critical role in shaping the country's geography, culture, and history for thousands of years. The Nile River is the longest river in the world and runs through Egypt from south to north, providing a vital source of water for agriculture and human settlement.

Without the Nile, much of Egypt's land would be desert and uninhabitable, as the river has created a fertile green belt along its banks that supports agriculture and sustains life. Ancient Egyptian civilization developed along the Nile, and the river played a central role in their religion and mythology.

Today, the Nile continues to be an essential resource for Egypt, providing water for drinking, irrigation, and electricity generation. Without the Nile, Egypt would face significant challenges in meeting its basic needs and sustaining its economy. Therefore, it is challenging to imagine Egypt without the Nile as the river is a fundamental part of the country's identity and survival.

It is like python , right ? Egypt is one of the most populous countries in Africa and the Middle East, with a current po...
27/02/2023

It is like python , right ?

Egypt is one of the most populous countries in Africa and the Middle East, with a current population of approximately 104 million people as of 2021.

Between 1960 and 2020, Egypt's population grew from around 27 million to over 100 million. The country's population growth rate has fluctuated over the past several decades, with a peak in the 1980s and 1990s, followed by a gradual decline since the early 2000s.

As of 2021, Egypt's population growth rate is estimated to be around 1.9% per year, which is above the global average. This means that the country's population is expected to continue to grow in the coming years, albeit at a slower rate than in the past.

Data ref: worldpop

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