Air Pollution Prediction Presentation & Thesis -- 2
Budget: ₹600 – ₹1,500 INR
Project Title
Spatial Analysis and Machine Learning-Based Air Pollution Prediction in Bihar Using Land Use Regression (LUR), GIS, Remote Sensing, Kriging, and Machine Learning
Project Overview
I have completed a B.Tech major project on air pollution prediction in Bihar. Most of the technical work has already been completed. I have all the required outputs, maps, figures, tables, graphs, machine learning results, and ArcGIS outputs. I need a professional PowerPoint presentation and a thesis report prepared using my existing work.
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Work Already Completed
1. Data Collection
Landsat 8/9 satellite imagery downloaded from USGS Earth Explorer (2023–2025)
CPCB air quality monitoring data
Bihar administrative boundary
Meteorological variables (Temperature and Relative Humidity)
2. GIS & Remote Sensing (ArcGIS)
Area of Interest (AOI) creation
Image mosaicking
Image projection
Raster clipping
False Colour Composite (Band 5-4-3)
Training sample collection
Maximum Likelihood Classification (MLC)
LULC map generation for 2023, 2024, and 2025
Fishnet generation (5 km × 5 km)
Tabulate Area analysis
Spatial Join
Final LUR dataset preparation
3. Python Analysis
Data preprocessing
Exploratory Data Analysis (EDA)
Descriptive statistics
Histograms
Boxplots
Scatter plots
Correlation matrix
Correlation heatmap
4. Land Use Regression (LUR)
Predictor variable preparation
Response variable preparation
Linear regression modelling
Model evaluation
5. Machine Learning Models
The following models have already been implemented:
Linear Regression
Decision Tree
Random Forest
Gradient Boosting
Support Vector Regression (SVR)
Available results include:
R²
RMSE
MAE
Model comparison tables
Feature importance
Individual pollutant results
6. Kriging
Ordinary Kriging
Semivariogram
Nugget
Range
Sill
Spatial interpolation maps
7. Future Prediction
Future pollutant prediction maps
Future prediction tables
Model outputs
---
Files Available
I will provide:
Existing PowerPoint presentation (~70 slides)
ArcGIS screenshots
USGS screenshots
LULC maps
Fishnet maps
Tabulate Area outputs
Spatial Join outputs
LUR outputs
Machine learning results
Feature importance figures
Kriging outputs
Prediction maps
Thesis draft documents
Supporting ZIP files
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Task 1 – PowerPoint Presentation
Update my existing PowerPoint only.
Do NOT:
Create a new presentation.
Change the slide order.
Change the theme.
Change fonts.
Change colours.
Change layouts.
Remove existing images.
Required Work
For every image, map, graph, screenshot, or table:
Add concise technical content.
Add Objective.
Add Description.
Add Key Observations.
Add Significance.
Add Figure Caption.
If supporting documents contain explanations, use them after rewriting into presentation language.
If no explanation exists, generate technically correct content matching the figure.
Maintain a professional IIT/NIT seminar presentation style.
---
Task 2 – Thesis Report
Prepare a complete thesis using my project work.
Include:
Chapter 1
Introduction
Problem Statement
Research Gap
Objectives
Chapter 2
Literature Review
Chapter 3
Study Area
Dataset
Methodology
Chapter 4
LULC Analysis
Fishnet
Tabulate Area
Spatial Join
LUR Dataset
Chapter 5
Exploratory Data Analysis
Correlation Analysis
Regression Analysis
Chapter 6
Machine Learning Models
Individual Model Results
Feature Importance
Model Comparison
Chapter 7
Kriging
Semivariogram
Spatial Prediction
Chapter 8
Future Prediction
Discussion
Conclusion
Future Scope
---
Writing Requirements
Original content (no plagiarism)
Technical and academic language
Suitable for a B.Tech thesis
Consistent formatting
Proper figure captions
Proper table captions
Cross-references to figures and tables
Logical flow between sections
---
Expected Deliverables
1. Updated editable PowerPoint (.pptx) with all existing figures retained and completed technical content.
2. Complete thesis report (.docx) based entirely on my project.
3. Figure captions and table captions throughout.
4. Presentation and thesis aligned so that the same technical interpretations are used consistently.
Note: The research work, maps, models, and outputs are already completed. The task is to transform the existing material into a polished presentation and thesis without altering the technical workflow or results.
Spatial Analysis and Machine Learning-Based Air Pollution Prediction in Bihar Using Land Use Regression (LUR), GIS, Remote Sensing, Kriging, and Machine Learning
Project Overview
I have completed a B.Tech major project on air pollution prediction in Bihar. Most of the technical work has already been completed. I have all the required outputs, maps, figures, tables, graphs, machine learning results, and ArcGIS outputs. I need a professional PowerPoint presentation and a thesis report prepared using my existing work.
---
Work Already Completed
1. Data Collection
Landsat 8/9 satellite imagery downloaded from USGS Earth Explorer (2023–2025)
CPCB air quality monitoring data
Bihar administrative boundary
Meteorological variables (Temperature and Relative Humidity)
2. GIS & Remote Sensing (ArcGIS)
Area of Interest (AOI) creation
Image mosaicking
Image projection
Raster clipping
False Colour Composite (Band 5-4-3)
Training sample collection
Maximum Likelihood Classification (MLC)
LULC map generation for 2023, 2024, and 2025
Fishnet generation (5 km × 5 km)
Tabulate Area analysis
Spatial Join
Final LUR dataset preparation
3. Python Analysis
Data preprocessing
Exploratory Data Analysis (EDA)
Descriptive statistics
Histograms
Boxplots
Scatter plots
Correlation matrix
Correlation heatmap
4. Land Use Regression (LUR)
Predictor variable preparation
Response variable preparation
Linear regression modelling
Model evaluation
5. Machine Learning Models
The following models have already been implemented:
Linear Regression
Decision Tree
Random Forest
Gradient Boosting
Support Vector Regression (SVR)
Available results include:
R²
RMSE
MAE
Model comparison tables
Feature importance
Individual pollutant results
6. Kriging
Ordinary Kriging
Semivariogram
Nugget
Range
Sill
Spatial interpolation maps
7. Future Prediction
Future pollutant prediction maps
Future prediction tables
Model outputs
---
Files Available
I will provide:
Existing PowerPoint presentation (~70 slides)
ArcGIS screenshots
USGS screenshots
LULC maps
Fishnet maps
Tabulate Area outputs
Spatial Join outputs
LUR outputs
Machine learning results
Feature importance figures
Kriging outputs
Prediction maps
Thesis draft documents
Supporting ZIP files
---
Task 1 – PowerPoint Presentation
Update my existing PowerPoint only.
Do NOT:
Create a new presentation.
Change the slide order.
Change the theme.
Change fonts.
Change colours.
Change layouts.
Remove existing images.
Required Work
For every image, map, graph, screenshot, or table:
Add concise technical content.
Add Objective.
Add Description.
Add Key Observations.
Add Significance.
Add Figure Caption.
If supporting documents contain explanations, use them after rewriting into presentation language.
If no explanation exists, generate technically correct content matching the figure.
Maintain a professional IIT/NIT seminar presentation style.
---
Task 2 – Thesis Report
Prepare a complete thesis using my project work.
Include:
Chapter 1
Introduction
Problem Statement
Research Gap
Objectives
Chapter 2
Literature Review
Chapter 3
Study Area
Dataset
Methodology
Chapter 4
LULC Analysis
Fishnet
Tabulate Area
Spatial Join
LUR Dataset
Chapter 5
Exploratory Data Analysis
Correlation Analysis
Regression Analysis
Chapter 6
Machine Learning Models
Individual Model Results
Feature Importance
Model Comparison
Chapter 7
Kriging
Semivariogram
Spatial Prediction
Chapter 8
Future Prediction
Discussion
Conclusion
Future Scope
---
Writing Requirements
Original content (no plagiarism)
Technical and academic language
Suitable for a B.Tech thesis
Consistent formatting
Proper figure captions
Proper table captions
Cross-references to figures and tables
Logical flow between sections
---
Expected Deliverables
1. Updated editable PowerPoint (.pptx) with all existing figures retained and completed technical content.
2. Complete thesis report (.docx) based entirely on my project.
3. Figure captions and table captions throughout.
4. Presentation and thesis aligned so that the same technical interpretations are used consistently.
Note: The research work, maps, models, and outputs are already completed. The task is to transform the existing material into a polished presentation and thesis without altering the technical workflow or results.
Related categories:
Python
Powerpoint
Health & Medicine
Machine Learning (ML)
Remote Sensing
Environmental Engineering
ArcGIS