Spectral Reflectance Newsletter #24
Spectral Reflectance Newsletter #24
Weekly newsletter on Earth Observation
Level-2 News
Airbus wins contract from Angola for Earth observation satellite Angeo-1 [link]
“Airbus Defence and Space has announced an agreement for Angeo-1, the first very high performance Angolan Earth observation satellite, to be manufactured by Airbus Defence and Space in France.”
The study concept for PERTEO, an AI-based Earth Observation constellation for Disaster Management, has been successfully concluded by Deimos, together with its partners German Aerospace Center (DLR) and KP Labs [link]
“PERTEO, or Persistent Real-Time Earth Observation for Responsive Disaster Management, is a mission concept to mitigate the impact of Natural Disasters in our society.
The concept proposes the use of for a heterogenous constellation combining the features of SAR, Hyperspectral and High-Resolution Optical sensors, providing a highly responsive service, with real-time tasking and real-time global product delivery, exploiting innovative real-time persistent Earth Observation services.”
Destination Earth demonstration products to be ready by mid-2024 [link]
“ECMWF will make sure that the EU’s Destination Earth (DestinE) initiative has completed the first steps in developing highly accurate replicas of Earth to facilitate action on climate change and environmental extremes by mid-2024.
The first two digital twins of the Earth system will support climate change adaptation policies and decision-making to reduce the impacts of weather-induced extremes”
The Copernicus Atmosphere charts including CO2 emissions, Ozone, UV index and more have been given a new layout [link]
Check it out here!
JACIE Online Compendium Adds Improvements [link]
“The Joint Agency Commercial Imagery Evaluation (JACIE) Land Remote Sensing Satellites Online Compendium has released its Phase 3 updates, providing new filtering and querying capabilities that give new views into the database for private and government/civil satellites.”
The compendium provides detailed information on past, current and future land remote sensing satellites and their sensors.
Click here to explore it!
Developer’s Orbit
Geemap and Leafmap are now available on Docker Hub [link]
Data
Hourly reanalysis data from ERA5, the fifth-generation global climate and weather reanalysis, is now available from 1940 to the present day [link]
“The Copernicus Climate Change Service (C3S*) is now making available an additional 19 years of reanalysis data from ERA5, the fifth-generation reanalysis of the global climate and weather from the European Centre for Medium-Range Weather Forecasts. This extends the ERA5 data record to over 83 years, from 1940 to the present day.”
Snapshots
Planet Snapshots Issue 65: Civil Gov [link]
In this week’s issue:
Satellites augment small team’s abilities
SoCal snowfall
Windswept patterns near Chinese factories
Interesting reads
How AI can help predict weather in the era of climate change [link]
Read this article by Priya Donti, a data scientist, soon-to-be professor at MIT, and the co-founder and executive director of Climate Change AI (CCAI), where she explains how AI can help improve weather forecasts.
The article follows a partnership between Climate Change AI and Women in Data Science (WiDS) Worldwide on their annual datathon (WiSDatathon). This year, the datathon challenged participants to find better ways to predict the weather in the face of climatechange.
Using a data cube to monitor forest loss in the Amazon [link]
Follow this article about an ESA-led project — Sentinel-1 for Science: Amazonas — that has processed billions of radar images over the entire Amazon basin and converted it into a data cube — helping detect forest loss.
Call for papers
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; Special Issue on “Exploring the Potential of Urban Remote Sensing” [link]
Learning
ARSET — Crop Mapping using Synthetic Aperture Radar (SAR) and Optical Remote Sensing [link]
“This three-part, advanced training presents more advanced radar remote sensing techniques using polarimetry and a canopy structure dynamic model to monitor crop growth. The training will also cover how to apply machine learning methods to classify crop type using a time series of Sentinel-1 & Sentinel-2 imagery. This series will include practical exercises using the Sentinel Application Platform (SNAP) and Python code written in Python Jupyter Notebooks, a web-based interactive development environment for scientific computing and machine learning.”
April 4, 2023 — April 11, 2023