The document discusses space data analytics and various applications of analyzing data collected from satellites and space-based sensors. It provides examples of how satellite data can be used for applications like flood monitoring, wildfire risk forecasting, human activity analysis, and more. It also discusses challenges like spectrum sharing between sensors and the use of machine learning for tasks like space navigation, rocket landing, and analyzing data from planets.

1. SPACE DATA ANALYSIS
M S PRASAD
AMITY UNIVERSITY NOIDA U.P

2. • SPACE Data : Is it a Big Data or large data ?
• Unique Properties
• Data Analytics.
• AI Based data analysis
Space data – or big data from space – is a term used to describe the camera
and sensor information gathered by space-borne monitoring equipment
(satellites), and the process of extrapolating patterns from it using analytical
software

3. • HUMAN ACTIVITY ANALYTICS
• GREENHOUSE GAS EMISSIONS
• WILDFIRE RISK FORECASTING
• EARTH OBSERVATION [ GIS etc.]
• FLOOD MONITORING
• DIGITAL FARMING
Primary Satellite data analytics SPACE DATA ANALYTICS
• PLANET CONSTITUENTS /
COMPOSITION
• PROBABILITY OF LIFE SAVING
MICROBES / ELEMENTS
• KNOWING ABOUT UNIVERSE

4. Tangible
data
collected
DATA
ANALYTICS
Intangible
data
collected
Data
Analytics
Meaningful /Labelled Information
Satellite Data Analytics
Tangible information derived
SPACE DATA ANALYTICS

5. The future of farming will rely on big data to give farmers
new insights into how they can grow crops more efficiently
and sustainably.
There has long been a wealth of coastal information but
no easy way to analyse and make sense of it. Big data
analytics is changing that.
Space information network (SIN) is an integrated network
system of various space information platforms (e.g.,
satellites, stratospheric airships, manned or unmanned
aerial vehicles) to enable real-time sensing, collection,
transmission, and processing of various space
information, as well as to realize both global and localized
tailor-made systematized information services.

7. Spectrum Sharing between Sensors

8. FLOOD MONITORING
Flood extent monitoring and mapping with both optical
and radar-based payloads, making this solution robust to
all-weather and day-and-night conditions. Down to 5 days
monitoring frequency and on-demand high-resolution
mapping capabilities.
WILDFIRE RISK FORECASTING
More than ten thousand homes and hundreds of lives
have been lost to wildfires in recent years. This trend is
likelly to continue due to climate change. Wildfire risk
models can predict the likelihood and magnitude of
wildfires to occur. Such models can be used to simulate
wildfires, providing insights and risk metrics for wildfire-
prone zones.

9. HUMAN ACTIVITY ANALYTICS
Monitoring human activity provides valuable information
across several retail categories. Maps can be generated
for benchmarking human activity across several
commercial locations that can be used for real-estate
development, retail, tourism and recreation. The data is
available worlwide and is fully-anonymous.

10. Big Data driven analytical engines for their
Curiosity Rover project. The underlying
technology was an open source program,
called Elasticsearch,

11. CASE STUDY : MARS EXPRESS EUROPEAN SPACE AGENCY 2004
The spacecraft generates huge volumes of
scientific data, which must be downloaded to Earth
at the right time and in the correct sequence,
otherwise data packets can be permanently lost
when the limited on-board memory is overwritten
by newly collected data.
Traditionally, data downloading was managed using human-operated scheduling software to
generate command sequences sent to Mars Express "This is tedious, time-consuming and never
really eliminated the occasional loss - forever - of valuable science data
MEXAR2 (MARS Express AI tool ) works by intelligently projecting which on-board data
packets might be later lost due to memory conflicts, optimising the data download schedule
and generating the commands needed to implement the download.

12. DEEP SPACE NAVIGATION
Spacecraft navigation :
•Orbit determination, or estimation and prediction of spacecraft position and velocity
•Flight path control, or firing a rocket engine or thruster to alter a spacecraft’s velocity

13. Future capabilities explored:
•Missions consisting of multiple spacecraft could require coordinated navigation.
•Missions in the New Frontiers and Discovery classes could require development of low-thrust and low-
energy mission design and navigation capabilities, as well as multiple-flyby trajectories.
•Future small-body sample-return and interior-characterization missions could require further reductions of
uncertainties in navigation delivery to small bodies by an order of magnitude.
•Missions that could need very high accuracy relative to their targets will require the continued development
and extension of the multi mission, autonomous, onboard navigation system (AutoNav) to be a complete
autonomous guidance, navigation, and control system, or AutoGNC.

14. Earth Observation Data Analytics
Space 4.0 and Industry 4.0
Machine Learning in Outer Space Data
Transmission
Machine Learning in Planet Data Analytics
Machine Learning in Space Navigation
Machine Learning in Rocket Landing
Future Endeavours

15. Defenders:
•Jammers
•Spoofers (for GPS signals)
•Hackers
•Sonic – Fox News has a article on how this technology could
counter drones.
•Destroyers
• Lasers
• Electromagnetic Pulse
• High Energy Microwave
• Irritated Property Owners with Shotguns
•Snaggers (a net carried under a drone, shot from an air cannon,
or bolo/net shotgun shell projectile.)
•Attack Birds such as Eagles. – I’m sure PETA will love this one.
•Random Stuff: Spears, T-Shirts, Baseballs, Soccer Balls
• Russian Spear Thrower (My personal favorite because he
can protect you from ground and air attacks. 2 for 1 deal!)
• Baseballs
• Soccer Ball

16. Technolog
y
Example Threat Industry Solution
Wi-Fi
Communi
cations
Spoofing,
hijacking, jamming
RF wireless drone detection
tool
Design commercial drones
with authentication
GPS Links
Spoofing,
intrusion, jamming
Cryptographic authentication
signal on civilian radio
frequencies
Software
Hacking, denial of
service
Design software with transit
encryption in mind
Wireless
Sensors
Jamming, denial of
service
Secure encryption