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GeoSpatail Vision يقدم لكمدورة تدريبية لنظم المعلومات الجغرافية من الصفر اونلاين ✅التفاصيل في الصور أدناه👇بأسعار رمزية 👌...
13/03/2024

GeoSpatail Vision يقدم لكم
دورة تدريبية لنظم المعلومات الجغرافية من الصفر اونلاين ✅
التفاصيل في الصور أدناه👇
بأسعار رمزية 👌

رابط التقديم في أول تعليق 👈

إذا كنت طالب بكلاريوس أو ماجستير أو دكتوراه 👨‍🎓👩‍🎓 وتتضمن منهجية بحثك على مهام في مجال نظم المعلومات الجغرافية🌍 او الاست...
10/01/2024

إذا كنت طالب بكلاريوس أو ماجستير أو دكتوراه 👨‍🎓👩‍🎓 وتتضمن منهجية بحثك على مهام في مجال نظم المعلومات الجغرافية🌍 او الاستشعار عن بعد 🛰️ وتحتاج الى مساعدة! 💁‍♂️ فأنت في المكان الصحيح ✅
GeoSpatial Vision تقدم لك خدمات مميزة في نظم المعلومات الجغرافية والإستشعار عن بعد بأسعار مخفضة:

🗺️ خرائط لمنطقة الدراسة.
🗺️ خرائط إستخدام الأرض والغطاء الأرضي.
🗺️ خرائط الطقس.
🗺️ خرائط التربة والخرائط الجيولوجية.
🗺️ خرائط الارتفاع والكنتور.
🗺️ خرائط توزيع السكان والكثافة السكانية وغيرها.

وكذلك من التحليلات:
✳️ التحليلات الهيدرولوجية.
✳️ تحليلات طوبغرافية.
✳️ تصنيف صور الاقمار الصناعية.
✳️ كشف التغير بين الفترات الزمنية.
✳️ التحليلات الجيواحصائية.
✳️ تحليلات الملائمة المكانية.
✳️ تحليلات الشبكات المكانية وغيرها.

لطلب خدمتنا يمكنك ارسال رسالة في الصفحة✉️ وسيتم التواصل معك في اقرب وقت ممكن 📞

Risk Assessment: Determining the Risk of Malaria Transmission in Aljazeera State:Weighted Vulnerability Score: Distanc...
14/09/2022

Risk Assessment: Determining the
Risk of Malaria Transmission in Aljazeera State:
Weighted Vulnerability Score:
 Distance to Rivers is the most important factor (weighted 30%)
 Slope is the next most important factor (weighted 25%)
 Land cover is an equally important factor (weighted 25%)
 Elevation is somewhat less important (weighted 15%)
 Hospitals are least important (5%)
Determine the Risk per Aljazeera localities:
While the risk scores might be helpful for determining specific locations with high risk, public health officials might like to know which zones (similar to provinces) within Aljazeera are most at risk. Therefore, these administrative boundaries called zones can allocate funds towards assisting with malaria prevention.
By: Mohamed Alfateh Abdrahim

22/08/2022

يدعوكم نادي نظم المعلومات الجغرافية لحضور فعاليته المقامة في يوم الثلاثاء الموافق 23/08/2022 الساعة 3 مساءا
بعنوان : تحديد خطر انتقال الملاريا في ولاية الجزيرة determining the risk of malaria transmission in aljazira state
تقديم: الطالب في المستوى الخامس GIS محمد الفاتح عبد الرحيم

In this lesson, you'll explore acqua alta conditions on both a 2D map and a 3D scene of Venice. You'll map an exceptiona...
03/06/2022

In this lesson, you'll explore acqua alta conditions on both a 2D map and a 3D scene of Venice. You'll map an exceptionally high tide of 1.4 meters to visualize and quantify what areas of the city are at risk of flood damage, especially the historical landmarks, and create a realistic 3D scene.

The link to the lesson from ESRI LearnArcGIS:
https://lnkd.in/eepAKdPj

Use deep learning to assess palm tree health:In this lesson, you obtained open-source drone imagery and created training...
03/06/2022

Use deep learning to assess palm tree health:

In this lesson, you obtained open-source drone imagery and created training samples of palm trees in the image. That image chips were provided to data scientists image chips and used by a trained deep learning model to extract more than 11,000 palm trees in the image.

You learned about deep learning and image analysis, as well as configurable apps across the ArcGIS system. You can use this workflow for any number of tasks if you have the imagery and knowledge of deep learning models. For example, you can use these tools to assess structural damage resulting from natural disasters, count vehicles in an urban area, or find structures near geological danger zones.

*Tutorial link:
https://lnkd.in/etmf6KeD

Automate fire damage assessment with deep learning:In this lesson, you prepared data to train a deep learning model, tra...
03/06/2022

Automate fire damage assessment with deep learning:

In this lesson, you prepared data to train a deep learning model, trained the model, classified a set of features using your model, and examined the results.
Being able to train a model to automatically classify features can save an organization valuable time and money while reducing the possibility of human error. This is especially critical when time is limited and people's lives and property are at risk.

A tutorial link:
https://lnkd.in/eJ9PtjD8

Classify mangroves using deep learning:In this lesson, you used imagery to create a deep learning model and then applied...
03/06/2022

Classify mangroves using deep learning:

In this lesson, you used imagery to create a deep learning model and then applied it. First, you created a training dataset, and this was converted to a pixel classification format. You trained a model to recognize mangroves in Landsat 8 imagery. Then, you applied the model to more recent imagery.
-1 = Decreased
1 = Increased
0 = NoChange

Finally, the change in mangrove forests was displayed on the map to make it clear where this tree species is expanding and where it is being lost. These results can be used to help plan mangrove restoration and conservation efforts. Additionally, your deep learning model can be used to classify mangrove habitats all around the world.

*A tutorial link:
https://lnkd.in/etfmHiY5

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