ankshah131

ARC_Curator_Guide

Please review and edit this guide in your own branch. Each branch except the master branch has the editor's name.

arcgis-python-api

Documentation and samples for ArcGIS API for Python

Boulder_Land_Use_Classification

Code for shapefile generation

Compressive-Sensing-and-Deep-Learning-Framework

We propose Compressive Sensing and Deep Learning framework (CS-DL) for multiple satellite sensor based data fusion. It’s aims to improve spatial and temporal resolution for long term analysis. Compressive Sensing is used as an initial guess to combine data from multiple sources. Deep Learning model, using Long Short Term Memory Neural Network (LSTM/RNN) refines and further improves the resulting data fusion output from CS. Our CS-DL framework has been tested to fuse CO2 from the NASA Orbiting Carbon Observatory-2 (OCO-2) and the JAXA Greenhouse gases from Orbiting Satellites (GOSAT). It achieves lower errors and high correlation compared with the original data. This work demonstrates the use of CS-DL for fusing CO2 from NASA Orbiting Carbon Observatory-3 and GOSAT2 at higher resolution.

Contrail_Detection

Lets detect lines in the air

copernicus-training

This repository hosts Jupyter notebook tutorials on the Copernicus Climate Change (C3S) and Atmosphere Monitoring (CAMS) Services.

cresi

Road network extraction from satellite imagery, with speed and travel time estimates

DeepSegmentor

A Pytorch implementation of DeepCrack and RoadNet projects.

deepwatermap

a deep model that segments water on multispectral images

road_detection

Algorithm trials for road extraction

ankshah131/road_detection

Algorithm trials for road extraction

ankshah131/ARC_Curator_Guide

Please review and edit this guide in your own branch. Each branch except the master branch has the editor's name.

ankshah131/arcgis-python-api

Documentation and samples for ArcGIS API for Python

ankshah131/Boulder_Land_Use_Classification

Code for shapefile generation

ankshah131/Compressive-Sensing-and-Deep-Learning-Framework

We propose Compressive Sensing and Deep Learning framework (CS-DL) for multiple satellite sensor based data fusion. It’s aims to improve spatial and temporal resolution for long term analysis. Compressive Sensing is used as an initial guess to combine data from multiple sources. Deep Learning model, using Long Short Term Memory Neural Network (LSTM/RNN) refines and further improves the resulting data fusion output from CS. Our CS-DL framework has been tested to fuse CO2 from the NASA Orbiting Carbon Observatory-2 (OCO-2) and the JAXA Greenhouse gases from Orbiting Satellites (GOSAT). It achieves lower errors and high correlation compared with the original data. This work demonstrates the use of CS-DL for fusing CO2 from NASA Orbiting Carbon Observatory-3 and GOSAT2 at higher resolution.

ankshah131/Contrail_Detection

Lets detect lines in the air

ankshah131/copernicus-training

This repository hosts Jupyter notebook tutorials on the Copernicus Climate Change (C3S) and Atmosphere Monitoring (CAMS) Services.

ankshah131/cresi

Road network extraction from satellite imagery, with speed and travel time estimates

ankshah131/DeepSegmentor

A Pytorch implementation of DeepCrack and RoadNet projects.

ankshah131/deepwatermap

a deep model that segments water on multispectral images

ankshah131/dlaicourse

Notebooks for learning deep learning

ankshah131/gdal

GDAL is an open source X/MIT licensed translator library for raster and vector geospatial data formats.

ankshah131/hello-world

My very first Github repo

ankshah131/Interactive-TSNE

ankshah131/inverse_distance_weighting

Interpolation in D-dimensional spaces using inverse distance weighted, k-nearest neighbours

ankshah131/marine_debris_ML

Marine debris detection with commercial satellite imagery and deep learning.

ankshah131/notebooks

interactive notebooks from Planet Engineering

ankshah131/oco-2-to-raster

Convert OCO-2 data to single variable raster

ankshah131/Reading-List-2020

This is a full reading list of books for 2020

ankshah131/Road-Segmentation

Road Detection in satellite imagery.

ankshah131/roaddetection

Detection and classification of roads in satellite images

ankshah131/RoadNet

RoadNet: A Multi-task Benchmark Dataset for Road Detection, TGRS.

ankshah131/scikit-image

Image processing in Python

ankshah131/U-Net-Satellite

Road Detection from satellite images using U-Net.