Projects
2020
𝗣𝗵𝗻𝗼𝗺 𝗣𝗲𝗻𝗵: 𝗨𝗿𝗯𝗮𝗻 𝗚𝗿𝗼𝘄𝘁𝗵 𝗳𝗿𝗼𝗺 𝟭𝟵𝟴𝟴 𝘁𝗼 𝟮𝟬𝟮𝟬 𝗯𝘆 𝗟𝗮𝗻𝗱𝘀𝗮𝘁 𝗦𝗮𝘁𝗲𝗹𝗹𝗶𝘁𝗲 𝗜𝗺𝗮𝗴𝗲𝗿𝗶𝗲𝘀
𝗦𝗲𝗻𝘁𝗶𝗻𝗲𝗹-𝟭 𝗦𝗔𝗥: 𝗖𝗮𝗺𝗯𝗼𝗱𝗶𝗮 𝗙𝗹𝗼𝗼𝗱 𝗶𝗻 𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟮𝟬𝟮𝟬
𝗖𝗮𝗺𝗯𝗼𝗱𝗶𝗮 𝗙𝗼𝗿𝗲𝘀𝘁 𝗖𝗼𝘃𝗲𝗿 𝗖𝗵𝗮𝗻𝗴𝗲 𝟮𝟬𝟬𝟬-𝟮𝟬𝟭𝟵
2021
𝗗𝗲𝘃𝗲𝗹𝗼𝗽 𝗽𝗮𝗱𝗱𝘆 𝗮𝗿𝗲𝗮 𝗺𝗮𝗽 𝗳𝗿𝗼𝗺 𝗠𝗢𝗗𝗜𝗦 𝘀𝗮𝘁𝗲𝗹𝗹𝗶𝘁𝗲 𝗶𝗺𝗮𝗴𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴
1. Export MODIS satellite images from Google Earth Engine
2. Create Mosaic of 2011 NDVI Images
3. Create DataFrame of NDVI Timeseries
4. Noise Reduction in NDVI Timeseries
5. Validation Data
6. KMeans Clustering and Results
𝗜𝗻𝗱𝗼𝗻𝗲𝘀𝗶𝗮 𝗽𝗿𝗼𝗷𝗲𝗰𝘁: 𝗵𝗶𝗴𝗵-𝗿𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝘀𝗮𝘁𝗲𝗹𝗹𝗶𝘁𝗲 𝗶𝗺𝗮𝗴𝗲 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀
1. Extracting vegetation area
2. Extracting water area
3. Extracting building area
2022
𝗞𝗮𝗻𝗼 & 𝗬𝗼𝘀𝗵𝗶𝗶 𝗿𝗶𝘃𝗲𝗿: 𝗟𝗮𝗻𝗱 𝗰𝗼𝘃𝗲𝗿 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴
1. Prepare input data of Kano River
2. Prepare input data of Yoshii River
3. Supervised learning model development
4. Predicting the whole Kano and Yoshii River
𝗠𝗮𝗽𝗽𝗶𝗻𝗴 𝗳𝗹𝗼𝗼𝗱 𝗳𝗿𝗲𝗾𝘂𝗲𝗻𝗰𝘆 𝗶𝗻 𝗖𝗮𝗺𝗯𝗼𝗱𝗶𝗮 𝗳𝗿𝗼𝗺 𝟭𝟵𝟴𝟴 𝘁𝗼 𝟮𝟬𝟮𝟬 𝘂𝘀𝗶𝗻𝗴 𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝗮𝗿𝘁𝗵 𝗘𝗻𝗴𝗶𝗻𝗲
𝗟𝗮𝗻𝗱 𝗰𝗼𝘃𝗲𝗿 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝘀𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱 𝗶𝗻 𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝗮𝗿𝘁𝗵 𝗘𝗻𝗴𝗶𝗻𝗲
𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗳𝗼𝗼𝘁𝗽𝗿𝗶𝗻𝘁 𝗼𝗳 𝗖𝗮𝗺𝗯𝗼𝗱𝗶𝗮 𝗶𝗻 𝗚𝗼𝗼𝗴𝗹𝗲 𝗘𝗮𝗿𝘁𝗵 𝗘𝗻𝗴𝗶𝗻𝗲
𝗗𝘆𝗻𝗮𝗺𝗶𝗰 & 𝗡𝗲𝗮𝗿 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗟𝗮𝗻𝗱 𝗨𝘀𝗲 𝗟𝗮𝗻𝗱 𝗖𝗼𝘃𝗲𝗿 𝗠𝗮𝗽𝗽𝗶𝗻𝗴 - 𝗖𝗮𝗺𝗯𝗼𝗱𝗶𝗮
Documentations
LiDAR
Create DEM and Hillshade from point cloud data in Python
Create RGB image from las file in Python
Geo-Python
Read & visualize raster image using xarray
Classify iris dataset with random forest classifier
Create a subplot figure
Interactive geoplots in dashboard layout with Bokeh
Convert GPS-tracked bus movement data from JSON to GeoJSON format
Create water occurrence image from yearly satellite images
Download forecast precipitation dataset from CHIRPS-GEFS website using Python
Calculate daily average potential evaporation from 3-year dataset for Source Model
Convert from Vector to Raster
Google Earth Engine
Download DEM from SRTM90 dataset
Calculate monthly mean temperature from ECMWF Climate dataset
Calculate monthly mean precipitation from CHIRPS Daily dataset
Calculate water turbidity index (WTI) from Sentinel-2
Machine Learning
Land Use Classification with Random Forests Classifier
Deep Learning
UNET Building footprint extraction using PyTorch
Convert WorldView-3 satellite images from Uint16 to 8byte
Convert building polygons to building masks for semantic segmentation model
UNet-Building Segmentation Model for WorldView-3 Satellite Images (PyTorch)
Split large satellite image into small images for model prediction
Building Footprint Prediction on WorldView-3 Satellite Images
Lessons
Geospatial data analysis with Python
Session 1: Geometric Objects
Session 2: Vector Data Analysis and Map Projection
Session 3: Geocoding and Nearest Neighbour Analysis
Session 4: Geometric operation and Data classification
Session 5: Plotting Static and Interactive Map on Leaftlet
Session 6: Raster Data Analysis
Index
