• Share
  • Email
  • Embed
  • Like
  • Private Content
Leprince imagin labs_2012_09_28_4
 

Leprince imagin labs_2012_09_28_4

on

  • 1,559 views

 

Statistics

Views

Total Views
1,559
Views on SlideShare
1,528
Embed Views
31

Actions

Likes
0
Downloads
13
Comments
0

2 Embeds 31

http://www.linkedin.com 24
https://www.linkedin.com 7

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Leprince imagin labs_2012_09_28_4 Leprince imagin labs_2012_09_28_4 Presentation Transcript

    • Space Borne Environmental Intelligence via SUPER high-precision co-registration of satellite imagerywww.imaginlabs.com# of CustomersDay 1 11Day 2 12Day 3 5Day 4 10Day 5 3Total 41 Sebastien Francois Jiao James Tamara Leprince (PhD) Ayoub (MS) Lin (PhD) Hollingsworth (PhD) Knutsen (grad)
    • Day 1Partners Activities Value Prop. Cust. Relations Cust. Segments • R&D on multi-angle imagery, image • Precision• Imagery providers Service for 2D or • “consulting” style fusion/registration(DigitalGlobe) 3D sub-pixel agriculture • Computing engine dev/testing/releasing? companies/Forestry registration of• USGS/NASA • (web) UIscientists • Dev/admin computing satellite images • NASA: processing of infrastructure Mars imagery • Customizing to • USGS: damage• University customer needsresearchers using our assessment/earthqufree software Resources Channels akes • Scientists / developers • Oil and Gas: sand • Hardware (cloud?) • Direct sales or via dune risk and • High bandwidth pipeline routing distribution partner network • Patents and company • Data exchange via “know how” network (ftp) • User • Data exchange via feedbacks/newsletters/ FedEX for large blogs volumeCosts Revenue• Wages, office space • Revenue from processing services (subscription, pay per• Workstations and servers image with volume discount)• High-bandwidth internet connection• Cloud services• Caltech royalties
    • Day 1• Technology description: Caltech technology to co-register time-series of satellite and aerial imagery with accuracy better than 1/10 of the image pixel size.• Initial hypothesis: Basically, everyone in remote sensing SHOULD be interested!• Customer Segments: – Oil & Gas, Pipeline monitoring – Disaster assessment – Agriculture – Mars imagery processing• Experiments: – Discussions with NASA, USGS, USDA personnel – Discussions with pipeline consultant
    • Day 2Partners Activities Value Prop. Cust. Relations Cust. Segments • R&D on multi-angle imagery, image Automated and fast • Crop-consulting• Imagery providers • “consulting” style fusion/registration companies for crop(DigitalGlobe) service for multi- • Computing engine monitoring dev/testing/releasing? spectral image • vegetable crops = most• USGS/NASA • (web) UI registration lucrativescientists • Dev/admin computing • high-end in-season infrastructure problems faced by crop crop monitoring • Customizing to consultants: manual companies are• University customer needs registration, data interested, but still needresearchers using our timeliness, higher to find good leads atfree software Resources resolution harder to Channels Cargill+ADM • Scientists / developers register, in-season •Possible interest from • Hardware (cloud?) analysis • Direct sales or via DEA, difficult to find • High bandwidth contacts distribution partner network • Defense • Patents and company Service for 2D or 3D • Data exchange via • NASA: processing of “know how” sub-pixel registration network (ftp) Mars imagery • User of satellite images • Data exchange via • USGS: damage feedbacks/newsletters/ FedEX for large assessment/earthquakes blogs volume • Oil and Gas: sand dune risk and pipeline routingCosts Revenue• Wages, office space • Revenue from processing services (subscription, pay per• Workstations and servers image with volume discount)• High-bandwidth internet connection• Cloud services• Caltech royalties
    • Day 2• Not everyone cares!• Too many market segments. Refocus on agriculture only, drop other customer segments. Agriculture seems to be the most responsive customer segment with strongest feedback.• New hypothesis: Crop monitoring needs better image registration to extract maps of crop/soil variability over time• Need to better understand the global remote sensing ecosystem.• Experiments: – Contacted crop consultant companies – Contacted several branches of USDA and academic agriculture institutions
    • Satellite Remote Sensing Ecosystem WHERE WE WANT TO BE! Oil & Gas, Mining Exxon Mobile, Shell, BP, Fugro, etc Agriculture Crop consultants, farmers, cooperatives, Satellite Cargill, Monsanto, GeoSys image Science Research Universities, Research labs MOST PROMISINGproviders Mapping Google Maps, Apple FEEDBACK! Therefore, focusing Insurance RMS, Aon, ABS, on this for now… 40%Annual revenue Civil engineering Parsons, McCarthy 60%Annual revenue Federal Military: USAF, USACE, NGA,… Federal Agencies: applications USGS, NASA, NOAA, Caltrans,…
    • Day 3Partners Activities Value Prop. Cust. Relations Cust. Segments • R&D on multi-angle imagery, image• Imagery providers • “consulting” U.S. Crop fusion/registration(DigitalGlobe) • Computing engine Problem: manual style consultants dev/testing/releasing? registration of International• USGS/NASA • (web) UIscientists • Dev/admin computing satellite image Crop consultant infrastructure before comparison • Customizing to• Universityresearchers using customer needs USDAour free software Resources Value Prop.: Channels (No registration • Scientists / developers - automated issue (for now!)) • Hardware (cloud?) - fast • Web access • High bandwidth - very accurate • Data exchange Agri. network • Patents and company via network (ftp) “know how” service for satellite • Data exchange Universities • User image registration via FedEX for large (lack of money, feedbacks/newsletter volume only use Landsat, s/blogs which has no registration issue)Costs Revenue• Wages, office space, workstations and servers • Revenue from processing services (subscription, pay per• Cloud services image with volume discount)• Caltech royalties
    • Day 3-4• Narrowed focus of customer segment to Precision Agriculture• New hypothesis: In-season crop monitoring needs better image registration to extract maps of crop/soil variability over time• Customer segments: – International crop consultants – Insurance, investment banks, commodity funds• Experiments: – Contacted farmer cooperatives about in-season monitoring – Contacted crop consultants
    • What we learned: Need is much smaller than expected USGS delivers free Landsat imagery  Contacted a major player for in-seasonwith decent registration, sufficient for crop monitoring (interested in precisebasic crop monitoring and fast registration of images from non- Landsat) Other satellite imagers are lesswidespread, due to costs  Provided trial runs on series of images they could not register. Confirmed that High-end crop monitoring requires our results exceeded all commercialnon-Landsat satellites (bad registration) solutions In-season crop monitoring interest is  Strongly interested in subcontractingHUGE registration processing to us  Potential revenue $75k-$250k/year Airborne or ground-based systems  need more crop consultant companiescompete with satellite imagery for high-end crop monitoring USDA delivers crop yield statistics butdoes not provides services to farmers
    • Precision Agriculture Ecosystem Ground-based RecommendersSensors Providers Agribusiness Owners Aerial Image Recommenders Providers: Farmers & Farm GeoVantage USERS Collectives Precision Ag Satellite Image Consultants: Recommenders Geosys Ag Insurance Providers: SatShot RapidEye Saboteur InTime Companies DMC Partnered Image Farmers Edge Digital Globe Processing: FarmWorks Recommenders Astrium Space Metric SST Software Commodities IB ZedX Monsanto Syngenta Recommenders Hedge, Equity Funds
    • Day 4Partners Activities Value Prop. Cust. Relations Cust. Segments • R&D on multi-angle imagery, image• Imagery providers • “consulting” International fusion/registration(DigitalGlobe) • Computing engine Problem: manual style Crop consultant dev/testing/releasing? registration of for farmers• USGS/NASA • (web) UIscientists • Dev/admin computing satellite image infrastructure before comparison Channels ‘Crop forecast’ • Customizing to• Universityresearchers using customer needs • Web access offices fromour free software Resources Value Prop.: • Fast data Insurance/Invest • Scientists / developers - automated exchange via ment firms • Hardware (cloud?) - fast network (ftp) • High bandwidth • Web access network - very accurate • Fast data • Patents and company service for satellite “know how” exchange via • User image registration network (ftp) feedbacks/newsletter s/blogs • Data exchange via FedEX for large USDA volume Agri. UniversitiesCosts Revenue• Wages, office space, workstations and servers • Revenue from processing services (subscription, pay per• Cloud services image with volume discount)• Caltech royalties
    • What we learned: USDA is not a potential client -  Insurance companies andconfirmed Investment/hedge funds may contribute to a significant portion of the revenue Limitation: too long revisit time of the (WAG)satellite for in-season. Hardwarelimitation.  Performed bandwidth experiment with in-season imagery Limitation: lag-time between imageanalysis results and field decisions. Need  Automatic web-based processing isbetter integration with the tools of suitable for crop consultants as long asend-user. ( potential opportunity) data volume does not exceed more than a few images per day. Otherwise, should use faster bandwidth to insure timely Farmers and cooperatives do not seem delivery of information to farmers.to contribute to the largest revenue fromsatellite that needs correction.
    • Day 5Partners Activities Value Prop. Cust. Relations Cust. Segments • R&D on multi-angle imagery, image• Imagery providers • “consulting” US and fusion/registration(DigitalGlobe) • Computing engine Problem: manual style International dev/testing/releasing? registration of Crop consultants• USGS/NASA • (web) UIscientists • Dev/admin computing satellite image and for farmers infrastructure spectral analyses of Channels • Customizing to• University sat im time-seriesresearchers using customer needs • Web access ‘Crop forecast’our free software Resources • Fast data for • Scientists / developers Value Prop.: exchange via Insurance/Invest• USDA • Hardware (cloud?) - Fast, automated, network (ftp) • High bandwidth • Web access ment firms network accurate satellite • Fast data • Patents and company image “know how” exchange via • User registration and network (ftp) feedbacks/newsletter analysis s/blogs • Data exchange - More Intuitive via FedEX for large Decision Tools volume USDA Agri. UniversitiesCosts Revenue• Wages, office space, workstations and servers • Revenue from processing services (subscription, pay per• Cloud services image with volume discount)• Caltech royalties
    • What we learned about Precision Agriculture:• No universal “black box” solutions • NEED individuals or algorithms who• NEED better algorithms for: can compile and prepare data from – Fertilizer rates disparate data sources for Variable Rate and Site-Specific Ag – Seeding rates • Direct benefits of Prec. Ag: – Herbicide rates – Increased efficiency in terms of:• No “cheap” way of getting soil fertility labor hours, – Intense manual grid sampling crop yields, – Direct automatic soil sampling amounts of chemicals and water needed and applied. (like AgroBotics AutoProbe) – Long-term spatial recording of – indirect sampling technologies operations good for: (like electrical conductivity) Future land/ag management, – Remote sensing approaches litigations, (Airborne, satellite, in-field insurance claims, solutions) increased farm enterprise value
    • What we learned about farmer needs:• Farmer interest correlated with kind of crop: – Lucrative Vegetable/Fruit Crops >> Grains – Annual Sensitive Crops (Cotton,Tomato) >> Perennials (Vineyards)• Most farmers WOULD ADOPT satellite crop monitoring if cheaper and higher temporal sampling (comparisons every 2- 3 days rather than 2 weeks).
    • Day 5• New hypothesis: In-season crop monitoring needs improvements in image registration, spectral analyses and algorithms to turn satellite data into useful decision tools.• Customer segments: – International crop consultants – Insurance, investment banks, commodity funds• Experiments: – Contacted crop consultants about in-season monitoring
    • Some numbers… that don’t add-up!• Imagery costs between $0 (free low res Landsat) and $0.8/km2• Farmers can afford up to $1-2/acre/year on imagery for pasture crops (cheapest scenario) with ~2 week sampling  equiv $9.5/im/km2!• Nevertheless: many dedicated agriculture satellites exist  Who really uses them? (Hunch: Insurance and Investors)• Need better knowledge (more customer investigations) of who spends the most on satellite imagery for agriculture• Essential information to estimate the market potential is missing
    • Next Steps…• Customer Development Process with insurance and financial institutions (need more contacts like van Beurden Insurance in CA)• Cust. Dev. to explore interest/need in Integrated Data/Decision Tools and Long-term Spatial Data Management for Farmers• Figure out how to get lower cost, more frequent sat images for ag use.
    • Market Size• TAM: Precision Agriculture in US: $450M (2010), $1.5B (2017) McKinsey, December, 2011• SAM: ~50 worldwide (WAG) satellite crop-consultant companies. ~10 in US  $250K/yr * 50: $12.5M/yr• Current Target Market: 10% of SAM, ~ $1.2M/yr Niche Market• Future trends: Precision agriculture (TAM) growth: 19% annually. McKinsey, December, 2011