First, business as usual isn’t working for global environmental governance. Second, we have not yet fully harnessed digital technologies to address our most pressing global environmental challenges. Third, the digital economy itself is not yet being leveraged for a sustainable future.
It’s with mixed sentiments that we share that Planet’s RapidEye constellation will be retired at the end of March 2020. After 11 years of faithfully gathering imagery, it has aged gracefully, to say the least.
In some cases the cost of Cloud Run is equivalent to Cloud Functions, but in other scenarios the cost of Cloud Run is less than Cloud Functions.
This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth.
it is now possible to understand population food secuirty issues at the neighborhood level, even in places where data has been traditionally hard to access.
The remote sensing satellite is to be used collect data for agricultural, climate, mining and environmental observations but could also be used for citizen surveillance.
Radiant MLHub will accelerate the adoption of machine learning to help solve global development challenges, including food insecurity.
This new issue contains the following articles:
- Rainfall variability in the Brazilian northeast biomes and their interactions with meteorological systems and ENSO via CHELSA product
- Insights into CODE-DE – Germany’s Copernicus data and exploitation platform
- On the isolatitude property of the rHEALPix Discrete Global Grid System
- A generalized supervised classification scheme to produce provincial wetland inventory maps: an application of Google Earth Engine for big geo data processing
- Identification and temporally-spatial quantification of geomorphic relevant changes by construction projects in loess landscapes: case study Lanzhou City, NW China
As Lead of the NASA Harvest Eastern Africa-Hub program and part of the NASA Harvest and SERVIR Global Applied Science Team, she conducts remote sensing training in the use of EO tools to assess and forecast crop conditions. Her EO capacity building portfolio includes the government ministries in Kenya, Rwanda, Tanzania, Uganda, and Mali, as well as regional agencies such as the Regional Centre For Mapping Resource For Development (RCMRD) and IGAD Climate Prediction and Applications Center.
The Society for Ecosystem Restoration in Northern BC (SERNbc), BC Government, and Hatfield completed a systematic analysis of landscape disturbance and vegetation recovery for four woodland caribous ranges in northeastern BC (more than 33,000 km2). The analysis used the 30-year history of free and open Landsat imagery and innovative disturbance detection and spectral recovery analytics.