Pratyush Tripathy's repositories
global_flood_mapper
This repository contains links to the Global Flood Mapper (GFM). Usage instructions are given here. For more details, please check the journal article titled "Global Flood Mapper: A novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR."
Landsat-Classification-Using-Neural-Network
All the files mentioned in the article on Towards Data Science Neural Network for Landsat Classification Using Tensorflow in Python | A step-by-step guide.
Landsat-Classification-Using-Convolution-Neural-Network
Source code and files mentioned in the medium post titled "Is CNN equally shiny on mid-resolution satellite data?" available at https://towardsdatascience.com/is-cnn-equally-shiny-on-mid-resolution-satellite-data-9e24e68f0c08
python_gdal_automated_windows
This repository contains the script for automated download, installation and set-up of Python and GDAL.
Land-Cover-Using-Machine-Learning
This repository contains links to resources for land cover classification.
pixel_level_land_classification
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
cnn_on_free_gee
This repository provides a way to extract water bodies using deep learning methods in GEE.
Dasymetric_mapping_using_GRASSGIS
Python script (Jupyter notebook) for modeling of population densities
dem_flattening
This repository contains the script and sample data to flatten a DEM raster horizontally.
Mask_RCNN_working
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
PratyushTripathy
Config files for my GitHub profile.
urban_growth_vs_public_policies
This repository contains the data used in the research "Evaluating sensitivity of urban policy on spatial transformation and urban growth"