Tools tagged with "Spectral Indices"

BD ORTHO®

The official geographical image of the French national territory, offering a sky-high view of France.

Data

BD ORTHO® provides high-resolution orthorectified imagery, serving as a key digital reference tool for local authorities and ministries across France. Updated regularly, this data enriches the visualization of professional data and projects.

HyperCoast

A Python package for comprehensive visualization and analysis of hyperspectral data in coastal environments.

Open Source Software

HyperCoast is a Python package designed for working with hyperspectral data, specifically focusing on coastal environments. It provides tools for both visualizing and analyzing this complex type of geospatial imagery. The package aims to facilitate research and applications related to coastal zone monitoring and environmental assessment.

EOReader

Remote-sensing opensource python library for sensor-agnostic reading of optical and SAR data, bands, clouds, DEM, and spectral indices.

Open Source SoftwareTooling

EOReader is a powerful open-source Python library designed for remote sensing applications. It provides a sensor-agnostic framework for reading and processing data from a wide range of optical and Synthetic Aperture Radar (SAR) satellite constellations. Users can efficiently load and stack various components such as spectral bands, cloud masks, Digital Elevation Models (DEMs), and spectral indices, simplifying complex satellite imagery workflows.

Forest Canopy Height in Mexican Ecosystems

A dataset offering lidar and Landsat-derived forest canopy height and vegetation indices for Mexican ecosystems.

Data

This dataset combines airborne lidar and Landsat satellite data to map vegetation structure in Mexican ecosystems. It includes lidar-derived canopy height values and Landsat-derived vegetation indices for 499,925 sample points across 1,105 aerial images, enabling fine-resolution ecological restoration monitoring.

Earthenv Habitat Heterogeneity

Global, remote-sensing supported environmental layers for assessing status and trends in biodiversity, ecosystems, and climate.

Data

This resource offers global datasets quantifying spatial heterogeneity of terrestrial habitats. Utilizing textural features from MODIS Enhanced Vegetation Index (EVI) imagery, it provides 14 distinct metrics at multiple resolutions. These layers are crucial for researchers and modelers focused on biodiversity and ecosystem assessments.

Awesome Spectral Indices

A curated list of spectral indices for remote sensing applications, integrated with Google Earth Engine.

Open Source SoftwareTooling

This resource provides a ready-to-use and curated list of spectral indices for various remote sensing applications. It keeps track of both classical and novel indices, ensuring they are standardized and usable across different environments and programming languages. The indices are available in convenient formats like CSV and JSON.