Imagery Libraries

16 Components & Libraries

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Imagery Libraries

Deep learning with satellite & aerial imagery

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

Google Earth Enterprise - Open Source

Earth Enterprise is the open source release of Google Earth Enterprise, a geospatial application which provides the ability to build and host custom 3D globes and 2D maps. Earth Enterprise does not p…

A collection of all earth related space Images in one script to set as your Desktop background.

Quickly view satellite imagery, hyperspectral imagery, and machine learning image outputs directly in your iTerm2 terminal.

Here are a number of examples that show how this tool can be used. Display a 3.5 billion pixel single-band image (3.3GB) using only 467KB over a SSH connection. If your bands are located in seperate …

Limited Error Raster Compression

LERC is an open-source image or raster format which supports rapid encoding and decoding for any pixel type (not just RGB or Byte). Users set the maximum compression error per pixel while encoding, s…

Sample scripts and notebooks on processing satellite imagery Python Geospatial raster

EEG-Motor-Imagery-Classification-CNNs-TensorFlow

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

Meanwhile, the codes in this repository are based on the raw EEG data without the ESI and JTFA process, and can also achieve a good result. The main CNNs Tensorflow framework codes in the "MI_Propose…

Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.

Additionally, it also provides multiple methods for computing land surface emissivity. It is targeted towards supporting research and science workflows in many fields including climate science, earth…

Google Maps keeps old satellite imagery around for a while – this tool collects what's available for a user-specified region in the form of a GIF.

Scroll down to learn how to set it up on your machine, or stay up here for some examples. Once you've set everything up, run the following command: For example, the following invocation will create t…

OptimizeRasters is a set of tools for converting raster data to optimized Tiled TIF or MRF files, moving data to cloud storage, and creating Raster Proxies.

OptimizeRasters is a set of tools for accomplishing three tasks: converting raster data to optimized file formats, moving data to cloud storage, and creating raster proxies. The result is more effici…

DSen2-CR: A network for removing clouds from Sentinel-2 images. This repo contains the model code, written in Python/Keras, as well as links to pre-trained checkpoints and the SEN12MS-CR dataset.

This repository contains the code and models for the paper Meraner, A., Ebel, P., Zhu, X. X., & Schmitt, M. (2020). Cloud removal in Sentinel-2 imagery using a deep residual neural network and SA…

📡 Receive images from weather satellite GEO-KOMPSAT-2A (GK-2A).

MDCS is an acronym for Mosaic Dataset Configuration Script and is the entry point to a collection of Python classes/libraries that could be consumed by a Python client application to complete a given workflow for creating a mosaic dataset, populating it with data, and setting all required/desired parameters.

An introduction to script-based satellite image processing using Python

Satellite imagery has become a primary data source in the natural sciences, economics, archaeology, sustainability, national security & defence, and many other domains which utilize geospatial in…

Python code to assist in familiarizing meteorologists with machine learning

Meteorological journal articles mentioning or using machine learning is growing rapidly (see figure above or Figure 1 in the paper; Data are derived from Clarivate Web of Science). Since there is suc…