Trend analysis of snow depth with avalanches using GIS and Machine learning approaches

Project Title

Trend analysis of snow depth with avalanches using GIS and Machine learning approaches

Project Area of Specialization Artificial IntelligenceProject Summary

Nalter valley Gilgit Baltistan is one of the highly exposed area in Pakistan to avalanches . The large variability of domestic geological factors combining with the difficulties in forecasting precipitation and in qualifying the level of earth quake related events, demand for coordinated procedure techniques to calculate and forecast the hazard and the harmful impact of slop failures. By using new techniques in Geographic Information System (GIS) technology , projecting the use of open-source tools, and machine learning approacrh  I plan to predict avalanches.

In this research work I intend to prepare a detail avalanche prediction  trends and graphs for Nalter Valley and make it representable to interested persons. 

Project Objectives

1. The proposed Avalanche assessment trends and graphs must be able to assist decision makers in land management activities and Hydropower Project activities.

2. Avalanche profile will be built from remote sensing imagery data and from ground survey.

3. Different Avalanche assessment models will be applied to develop Avalanche index. Based on this Avalance index predictions will be made about future Avlanche's using machine learning approaches. 

4.This whole work will be summarized into research paper by the end of Project.

5. In future I'll expend the study area .

Project Implementation Method

Project will be implemented in following steps:

1. Selection of Study area in Gilgit Nalter Valley.

2. Collection of GPS points of main avalanches.

3. Collection of satellite imagery of the study area to digitalize avalanche's.

4. Development of Landslide and hazard index using different models (Snow depth,)

5. Development of Area Under Curve to compare different models.

6. Accuracy assessment of the results with ground survey data.

7. Based on collected data different machine learning algorithms will be applied for future prediction of the test area.

Benefits of the Project

1. It will play as a major role for  planners and architects of Hydropower Project Naltar.

2. It will be helpful for general Public to get information about Avalanche's in Nalter Valley Gilgit.

3. It will be helpful to travelers and tourist of the area to know about dangerous/Avalanches and take immediate steps to avoid such areas. 

Technical Details of Final Deliverable

1. Highly accurate assessment model will be recommended for future assessments of Avalanche's.

2. In future development of Web portal and Android app for public to know about avalanche's with Avalanche index.

3. Prediction models based on different scenarios of Hydropower Project Naltar.

Final Deliverable of the Project Software SystemType of Industry IT Technologies Artificial Intelligence(AI)Sustainable Development Goals Decent Work and Economic Growth, Life on LandRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
Field Visit and Validation	Miscellaneous	2	5000	10000
High Resolution Images	Equipment	1	70000	70000
Field Visit and Validation	Miscellaneous	0	0	0
High Resolution Images	Equipment	0	0	0