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Challenges and Opportunities for Image Use: UK England 2016 Control with Remote Sensing

CYIENT © 2016 CONFIDENTIAL11/24/2016

Eamonn ProwseManuel Sanabria

11/24/2016 CYIENT © 2016 CONFIDENTIAL

About Rural Payments Agency for England and Cyient

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21Nationalities

14,000+Global Workforce

AerospaceEnergy and Natural Resources

Rail Transportation Off-highwayUtilities

Semiconductor

Communications

Medical and Consumer

Geospatial

Others

38Global LocationsRural Payments Agency (RPA) is the CAP

paying agency for EnglandCyient work alongside RPA as Digitising and Remote Sensing Service ProviderComputer Aided Photo Interpretation (CAPI) control BPS claims and checks:

Land eligibility parcel boundaries, splits and merges, land covers, eligible and ineligible featuresCrop diversification & EFA land uses (crop types)

$472mGlobal Revenue (2016)

11/24/2016 CYIENT © 2016 CONFIDENTIAL

Cyient Marquee geospatial clients - Global

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LA CountyOrthophoto generation

Triumph Aero Structures

Supply Chain Management Scheinder Electric

Live trip information for passengers

Town of Glastonbury, CTLarge Scale Base Map creation

TomTomData Update,

Application Development

Rural Payment Agency

Update and maintain rural map cadaster

Ordnance Survey (OS)

Map updateDefence EstateManagement of estate portfolio

Digital GlobeElevation modeling and

Airport mapping

Occidental PetroleumData management and

ESRI integration

Loudoun CountyPlanimetric and

topographic mapping

SURVY OF INDIAICZM

Government of Karnataka

Urban property ownership records

Survey Commissioner and Director of Land Records

GandhinagarResurvey Gandhinagar

HARSAC Land records modernization

Bihar Government Land records modernization

DLPE LiDAR data processing

ALGGICapturing of

topographical data GHD

Orthophoto generation

CoreLogicGIS mapping and

LiDAR data processing

Aerial Surveys LimitedTopography and LiDAR

data processing

11/24/2016 CYIENT © 2016 CONFIDENTIAL

Covering:

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Control with Remote Sensing (CwRS) in England

Analysis of use of Pleiades 1B as Very High Resolution (VHR) imagery compared to other VHR sources

A hybrid spectral model for large scale crop classification using high resolution multi-sensor data.

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

Processing Scope:15 Zones throughout England- 250K+ Agricultural parcels processed- 45+ Crop types discrimination required- 12,969 sq. Km covered

1. TASKS / REQUIREMENTS

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Requirements:Classification cover the majority of the crop types.Accuracy

Splitting Accuracy: 70%

Land Use 85% Overall accuracy.60% Class-specific accuracy.

11/24/2016 CYIENT © 2016 CONFIDENTIAL

GeoEye_1_SPEN_10_04_2016Characteristics

2. INPUT DATA (Raster)

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SPOT6_SPEN_09_05_2016Characteristics

Pleiades_MICK_09_05_2016Characteristics

Sentinel_2_MICK_20_04_2016Characteristics

MICK ZONE

MICK Vs SPEN

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/20168

IMAGERY ACQUISITIONRPA found that the Pleiades 1B zone (MICK) took the longest to acquire imagery, however, this was due to:

a) Only one sensor flying over the zone which decreased the number of sensor passes for imagery acquisition (instead of WorldView 2 (WV2), WV3, and GeoEye)b) Zone MICK was one of the largest areas (1600km²) whereas the majority of the other RS zones were 1000km² in area or less.c) The zone is located in the north of England which long term weather statistics show is mostly covered with cloud.

The table below shows the imagery acquisition of zones MICK and SPEN which have similar weather conditions

3. PLEIADES 1B ANALYSIS FINDINGS (Pre-CAPI)

Zone VHR1 AcquisitionWindow

VHR1 AcquisitionDate

Days taken to capture full VHR1

VHR2 AcquisitionWindow

VHR2 AcquisitionDate

Days taken to capture full VHR2

MICK 15/04/16 30/05/16

09/05/16 24 days 13/06/16 15/08/16

19/07/16 & 15/09/16 94 days

SPEN 01/04/1614/06/16

12/04/16 (GeoEye1) 11 days 27/06/16

07/09/1616/07/2016

(WorldView3) 19 days

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/20169

IMAGERY PROCESSINGLike all other VHR zones (sourced from WV2, WV3, and GeoEye), the raw 4 band multispectral and panchromatic data was orthorectified, pansharpened(to 50cm) and colour balanced in line with the OTSC requirements.

4. PLEIADES 1B ANALYSIS FINDINGS (Pre-CAPI)

Orthorectification RMSE value <2m

RadiometryContrastHistogram Peak Overall clipping

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

Processing:

5. INPUT DATA (vector)

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Splitting

GROUND TRUTHING SAMPLING PLANReferenceParcelLayer

NDVI multi-temporal stack for multi-crop delineation

Proportion matchEfficiency

KEY:

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6. CHALLENGES

11Sentinel 2 catalogue

MULTISENSORMULTITEMPORALITYIMAGE AVAILABILITY

Zones covered with a combination of sensors /at different times inside the acquisition windows.LESS 5% CCBETWEEN 6-20% CC 11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

7. CHALLENGES

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CROP CALENDARCROP VARIABILITY

PlantingGrowth SeasonHarvest

DIVISION INTO MAJOR AND MINOR CROPSREJECTION OF NON REPRESENTATIVE CROP TYPES

Considered in the ground truthing sampling planCrop phenology

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

8. ANALYSIS

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Pre-processing Classification Post-processingDATA

CATALOGUINGORTHORECTIFICATION

VEGETATION INDEX

GENERATIONMASKING

RAST

ER

REFERENCE PARCEL

PROCESSINGGROUND TRUTH

PROCESSING

VECT

OR

RANDOM FOREST PIXEL BASED

CLASSIFICATION

DECISION TREE PIXEL BASED

CLASSIFICATION

VEGETATION INDEX INTEGRATION

SAVI

GNDVINDVIZONAL

STATISTICS

ACCURACY ASSESSMENT

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

9. RESULTS

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020406080

100120

Accur

acy (%

)

Crop Types

SPEN MICK

Class-specific AccuracyMICK vs SPEN

Overall Zone Accuracy

11/24/2016 CYIENT © 2016 CONFIDENTIAL11/24/2016

10. ACHIEVEMENTS

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AREA COVERED IN THE ANALYSIS CROP TYPES REQUIRED CLASSIFIED

AGRICULTURAL PARCELS PROCESSED DELIVERY TURNAROUND

AVERAGE ACCURACY ACHIEVED IN THE AUTOMATED CLASSIFICATION PRE-CAPI.

CYIENT © 2016 CONFIDENTIAL11/24/2016

Thank you for your attention

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