Spectral Reflectance Newsletter #90
Spectral Reflectance Newsletter #90
Weekly newsletter on Earth Observation
Level-2 News
Google is funding an AI-powered satellite constellation that will spot wildfires faster [link]
"Early next year, Google and its partners plan to launch the first in a series of satellites that together would provide close-up, frequently refreshed images of wildfires around the world, offering data that could help firefighters battle blazes more rapidly, effectively, and safely.
The online search giant’s nonprofit and research arms have collaborated with the Moore Foundation, the Environmental Defense Fund, the satellite company Muon Space, and others to deploy 52 satellites equipped with custom-developed sensors over the coming years.
The FireSat satellites will be able to spot fires as small as 5 by 5 meters (16 by 16 feet) on any speck of the globe. Once the full constellation is in place, the system should be capable of updating those images about every 20 minutes, the group says."
Capella Space Awarded a $15M Contract with the U.S. Air Force [link]
"Capella Space announced its selection for an AFWERX Ventures Strategic Funding Increase (STRATFI) award by the U.S. Air Force.
Capella Space will receive $15 million in funding to mature, scale and extend its world-leading synthetic aperture radar (SAR) technology."
PlanetiQ Awarded $6.5 Million NOAA Contract to Supply Radio Occultation (RO) Data for the Commercial Weather Pilot Data Program [link]
"PlanetiQ has been awarded a Delivery Order (DO-4) contract valued at over $6.5M to supply the National Oceanic and Atmospheric Administration (NOAA) with their proprietary radio occultation (RO) data for a period of one year beginning September 18, 2024."
Developer's Orbit
Geospatial Technology Radar 2024 [link]
"Element 84 launched the Geospatial Technology Radar as a platform for facilitating knowledge sharing in the geospatial community."
Interpretable forecasting models with skforecast [link]
"Skforecast is a Python library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others."
awesome-weather-models - A catalogue and categorization of AI-based weather forecasting models [link]
"The awesome-weather-model page lists and categorizes all models according to key attributes taken from the papers and Github repos (like spatial/time resolution, number of parameters and open source license, etc)." [link]
Open-source toolbox EOWater v0 release [link]
"EOWater: efficient cloud computing of water surface area time-series from Sentinel-2 and Landsat in GEE"
GitHub repo [link]
STAC 1.1.0 Released [link]
Data
Sen4Map Benchmark Dataset [link]
"Sen4Map is a large-scale benchmark dataset comprised of non-overlapping 64 x 64 patches extracted from Sentinel-2 time series images, covering over 335,125 geo-tagged locations across the European Union. These geo-tagged locations are associated with detailed landcover and land-use information, gathered by experts as part of the LUCAS survey 2018.
The dataset is available as 28 individual HDF5 files per country. In addition to this, H5 files used for training, validation, and testing are also available. "
Snapshots
Earth from Space: Adriatic bloom [link]
"An algal bloom describes the rapid growth of phytoplankton – microscopic marine plants that drift on or near the sea surface. The chlorophyll that phytoplankton use for photosynthesis collectively tints the surrounding waters, providing a means of detecting these tiny organisms from space with certain satellite sensors.
With its 13 spectral channels, Copernicus Sentinel-2’s imager can be used to detect the extent and evolution of these blooms. In this image from 12 August 2024, the emerald-green streaks, eddies and whirls of the bloom, mixed by winds and currents, are clearly visible and cover an area of around 9000 sq km."
Climate
WMO Update predicts 60% chance of La Niña [link]
"Latest forecasts from WMO Global Producing Centres of Long-Range Forecasts indicate a 55% likelihood of a transition from the current neutral conditions (neither El Niño nor La Niña) to La Nina conditions during September-November 2024. This likelihood increases to 60% from October 2024 to February 2025, with the chance of El Niño redeveloping during this time being negligible."
NASA Finds Summer 2024 Hottest to Date [link]
"August 2024 set a new monthly temperature record, capping Earth’s hottest summer since global records began in 1880, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. The announcement comes as a new analysis upholds confidence in the agency’s nearly 145-year-old temperature record.
June, July, and August 2024 combined were about 0.2 degrees Fahrenheit (about 0.1 degrees Celsius) warmer globally than any other summer in NASA’s record — narrowly topping the record just set in 2023. Summer of 2024 was 2.25 F (1.25 C) warmer than the average summer between 1951 and 1980, and August alone was 2.34 F (1.3 C) warmer than average."
The 2024 Global Methane Budget reveals alarming trends [link]
"The Global Methane Budget 2024 paints a troubling picture of the current state of global methane emissions. The new report reveals that human activities are now responsible for at least two-thirds of global methane emissions.
This marks a significant increase in human-produced methane sources over the past two decades, with emissions rising by 20%, with the fastest rise occurring over the last five years."
Interesting reads
Economic Valuation of Landsat and Landsat Next [link]
"The purpose of this report is to provide an update on the economic benefits of Landsat imagery, following the previous update in 2019 and determine the relative increase in potential economic value offered by Landsat Next.
The report also includes an analysis of the potential long-term value of Landsat Next and its complementarity with the growing commercial satellite imagery market, emphasizing the value of the Landsat’s long lifespan and the high-quality data that is considered a benchmark for satellite imagery."
Head over to
Synspective CEO Motoyuki Arai on the Japanese SAR Provider’s Plans to Scale [link]
"In June, Synspective announced a $44 million Series C round, and it became Rocket Lab’s largest launch customer to date, purchasing a block of 10 launches. Last month, Synspective saw the launch of its fifth SAR satellite.
With a current constellation of four satellites (its first demonstration satellite completed its mission), Synspective plans to have a 30-satellite constellation by the late 2020s.
Via Satellite interviewed Synspective founder and CEO Dr. Motoyuki Arai about the company’s recent milestones, the market for SAR data, and its position in the Japanese startup space market."
How is the hole in the ozone layer? [link]
"In 1974, scientists first sounded the alarm about the destruction of the ozone layer caused by human activities. Yet it would take several more years for the global community to reach a consensus on banning ozone-depleting chemicals.
At the time, Paul Crutzen and his research team played a pivotal role in bringing this issue to the world's attention. Today, the ozone hole is slowly healing, but progress is being hampered by the growing challenges of climate change."
The Critical Role of Ground-Based Data in Regression Model Accuracy for Remote Sensing Applications [link]
"Remote sensing has revolutionized environmental studies, allowing scientists to gather comprehensive data about the Earth’s surface and atmosphere from afar. From monitoring deforestation and mapping urban sprawl to assessing agricultural health and predicting natural disasters, the applications of remote sensing are vast and varied.
However, despite these technological advances, the accuracy of the regression models used in remote sensing heavily relies on ground-based data. This article delves into the indispensable role of ground-based data in calibrating and validating these models, thereby ensuring the reliability of remote sensing analytics."
Podcasts
Eyes on Earth Episode 123 – Bathymetry Mapping [link]
"In this episode, Tom Adamson talks to physical geographer Jeff Danielson about bathymetry and how it is critical for coastal modeling. Bathymetry captures the shape of underwater topography, and satellite-derived bathymetry helps fill in areas where there are data gaps."
Learning
EUMETSAT MTG-I1 Lightning Imager; background, data and application in thunderstorm detection and forecasting - recording availalbe [link]
"This short course on Lightning Imager (LI) onboard the Meteosat Third Generation Imager (MTG-I1) satellite is the first in the series of short courses on MTG data and applications.
This 4-hour course offers insight into the theory of lightning discharges and lightning measurements, details on the LI instrument, acquisition of data, filtering, noise removal, processing, LI baseline products and applications."