IMED 2018: An intro to Remote Sensing and Machine Learning
1. An Intro to
Remote Sensing and
Machine Learning
HAMED ALEMOHAMMAD
LEAD GEOSPATIAL DATA SCIENTIST, RADIANT EARTH FOUNDATION
IMED, 2018, Vienna, Austria
3. Satellite Remote Sensing
Satellites carry instruments or
sensors which measure
electromagnetic radiation
coming from the earth-
atmosphere system.
3
4. Measuring Earth Surface and
Atmospheric Properties
The intensity of reflected and emitted
radiation to space is influenced by the
surface and atmospheric conditions.
Thus, satellite measurements contain
information about the surface and
atmospheric conditions.
6. Interaction with Vegetation
Example: Healthy, green vegetation absorbs Blue and Red
wavelengths and reflects Green and Infrared.
Since we cannot see infrared radiation,
we see healthy vegetation as green.
7. Spectral Signatures in Imagery
Remotely sensed imagery acquires information in different wavelengths,
representing different parts of the Electromagnetic Spectrum.
9. Solar Induced Fluorescence (SIF)
Energy absorbed by plant through its chlorophyll
used for gross primary production (GPP)
lost as heat
re-emitted (SIF: byproduct)
SIF responds to stressors (water, light, T).
Babani, F., et al. 2005
10. Except for Indonesia all tropical regions exhibit some
seasonal cycle due to light/water limitations
27. Intelligence Augmentation (IA):
Computation and data used to create services that augment
human intelligence and creativity.
Search engine
Natural language translation
Intelligent Infrastructure (II):
A web of computation, data and physical entities that makes
human environments more supportive, interesting and safe.
Starting to appear in domains such as transportation, medicine,
commerce and finance.
Credit: Michael Jordan, Professor at UC Berkeley
39. Training Data Challenges
Capturing the wide range of possible outcomes both in
space and time;
Accuracy;
GeoDiversity
Accessibility;
Inter-Operability;
ML-Readiness;
40. Open source machine learning commons
for Earth Observations.
Promoting creation of open libraries of labeled images and
algorithms to advance ML for global development, and
democratize ML applications for EO data.
Developers can join the collaborative initiative and
contribute their tools and knowledge on Github.
Imagery training data will be created as STAC compliant
and in COG format.
41. • The Problem: Need for an open,
dynamic, global, and comprehensive
LC map
Open Training Library for Land Cover
Classification:
• Using Deep Learning for labeling
imagery
• Crowdsourcing and citizen
science to verify / correct the
labels
Sponsored by:
Open Source
10 m resolution
Global
ML Centric
• Solution: Training labeled image library
for land cover classification
42. Radiant Earth Foundation:
Vision & Mission
Open Geospatial Data for Positive Global Impact
Connecting people globally to Earth Imagery, geospatial data, tools and
knowledge to meet the world’s most critical challenges
43. What we do
Provide Open Access to
Earth Imagery & Tools
Provide Education on
Geospatial Data & Tools
Provide Neutral Leadership
to Enhance Industry-Wide
Collaboration
44. Attributes of the Platform
AGILE
Experiment with data,
visualization, and collaborate in
a cross-domain multidisciplinary
ecosystem.
OPEN
Work with open
imagery, data sets and
technology standards.
NEUTRAL
Discover both government &
commercial imagery, and
collaborate with tech-and non-
technical users at the intersection
of global development & remote
sensing.
COLLABORATIVE
Learn and share ideas to
improve collaboration across
domains.
FEDERATED
Find and work with diverse
imagery data sets covering the
globe with a federated
catalogue.
45. Available Open Imagery
Datasource Temporal Coverage Temporal Revisit Spatial Resolution
Sentinel 2-A/B 2015 - present 5 days 10 m
Landsat 4/5/7/8 1982 - present 16 days 30 m
MODIS 2000 - present 8 day composite from daily 250 m
ISERV 2012 - 2015 Specific operation times 3.5 m
46. Platform Features
Supporting any imagery type:
Satellite
Drone
Airborne
Uploading pipelines:
Local
Dropbox
Amazon Web Services (AWS) S3 Bucket
Planet API Connection
Radiant Earth Foundation API
51. Get in touch Follow Us
740 15th St NW, Suite 900
Washington DC 20005
+ 1. 202.596.3603
hello@radiant.earth
www.radiant.earth | app.radiant.earth | help.radiant.earth | demos.radiant.earth
@OurRadiantEarth
https://www.facebook.com/OurRadiantEarth
Q & A