data usability assessment for remote sensing data: accuracy of interactive data quality...
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Data Usability Assessment for Remote Sensing Data: Accuracy of Interactive Data Quality Interpretation Erik Borg, Bernd Fichtelmann - German Aerospace Center, German Remote Sensing Data Center Hartmut Asche - Department of Geography, University of PotsdamTRANSCRIPT
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Improvement of spatial data quality through data conflation
Silvija Stankute, Hartmut AscheGeoinformation Research GroupDept of Geography | University of Potsdam | Germany
ICCSA 2011 | GEOG-AN-MOD 2011 | University of Santander | 20-23/06/2011
Data usability assessment for remote sensing data: Accuracy of interactive data quality interpretation
Erik Borg, Bernd Fichtelmann, Hartmut AscheDFD | German Aerospace Centre | NeustrelitzDept of Geography | University of Potsdam | Germany
ICCSA 2011 | GEOG-AN-MOD 2011 | University of Santander | 20-23/06/2011
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Increasing availability of remote sensing (RS) data is complica-ting orientation in data bases of remote sensing data
To facilitate orientation in RS data bases data providers make available additional data information, such as geographic loca-tion, acquisition time, data quality
To assess RS data quality cloud cover degree is a frequently used quality parameter which records data quality insufficiently
ESA has defined a new quality measure data usability which is interactively interpreted by operators based on:
Technical data errors: lost image lines/segments, scan mirror anomalies,
Unusable image segment: Clouds, haze, shadow, derivation within a scene
Motivation
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Search in databases Data acquisitionDESCW Retrieval system: Display Earth Remote Sensing Swath
Coverage Data selection criteria of LANDSAT 7 / ETM+ data include
Mission
Orbit
Track
Frame
Data
Time
Data quality
Station
Coordinates
.. ..
SCENE_LL_CORNER_LON = 25.4800 SCENE_LR_CORNER_LAT = 43.6500 SCENE_LR_CORNER_LON = 27.8100
HORIZONTAL_DISPLAY_SHIFT = 0 SCENE_CCA = 50
UL_QUAD_CCA = 60 UR_QUAD_CCA = 60 LL_QUAD_CCA = 30 LR_QUAD_CCA = 50
SUN_AZIMUTH_ANGLE = 138.5 SUN_ELEVATION_ANGLE = 59.8
CCA = Cloud Cover Assessment QUAD = quadrant UL = upper
left UR = upper
right LL = lower
left LR = lower
right
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Processing chain
National ground segment Landsat 7
Monitor & Control, MWD WS
(SGI O2 with 128MB)
18 GB disk
2 x DLT 7000
EXABYTE
CD Master Labelling system
3 x 18GBdiskCatalogue, OH Workstation
(O2 with 128MB)
SWITCH MATRIX (EMP)
SGI Origin
200 server 4CPUs512 MB
plus GigaChan
nel
PCI ingestion boards (Ciel)
5 x 18 GB disk arrayinternal SCSI Controller
2 x DLT 7000
18 GB disk
SGI O2 Station Data Server
EXABYTE
CD MasterLabelling system
Label Printer
Reports Printer
Fast Ethernet
Label Printer
Reports Printer
RS232
RS232
Front-End Handler(PC - RS232/IEEE488)
Demod 1 (Alcatel)
Exabyte
CD-ROM
DLT 7000
controller
4xSCSI
SGI Origin
200 server 4CPUs512 MB
plus GigaChan
nel
PCI ingestion boards (Ciel)
5 x 18 GB disk arrayinternal SCSI Controller
controller
4xSCSI
Quality Control Workstation(O2 with 128MB)
I Q I Q
I Q
Monitor & Control, MWD WS(SGI O2 with 128MB)
External lines
Demod 2 (Alcatel)
STOP
Interactive DataUsability Estimation
I Q
Objectives Decoding and data
syncronisation De-communitation Production of
browse data Status information Storage of raw data
Schematic representation of Landsat ground segment (modified from Beruti 2002)Red: interactive data usability assessment
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Derivation of test data
Receiving circle of Neustrelitz ground station
Spatial distribution of Landsat 7/ETM+ database
Number ofData Sets
9
8
7
6
5
4
3
2
1
Number ofData Sets
9
8
7
6
5
4
3
2
1
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Definitions of data quality
Assessment of cloud cover degreee Detection and identification of cloud
covered pixel Ration of number of cloud covered pixel
to total number of pixels of assessment unit
Data usability assessment Not usable image segment: detection of
clouds and cloud shadows, distribution and configuration within scene
Technically induced image errors: lost lines and sectors, scan mirror anomalies
Cloud No Cloud
25 % Cloudiness
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Quick-look data for quality assessment
Quality assessment by interpreters4 quadrantsReal colour coded data
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Equations
Assessment of evaluation subjectivity
2
2
)(
)1(*
PP
zn
n
iiO m
nROUNDM
1
1
Oii Mm
n
iODU Mm
nSD
1
2)()1(
1
Acceptable error 0.05 (significance level of 5 %)z-value Standard normal distribution 1.96,P Population 11,828 quadrants,
P(1-P) Maximum value 0.25
n ≥ 384 400
OM
di Absolute error
SDDU Standard deviation
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Equations
Mean error vs single interpreter | metadata
Modulus of absolute error of mean data usability with regard to single interpreter assessment
Modulus of absolute error of mean data usability with regard to metadata assessment
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Mean data usability vs standard deviation
Interpreter assessment plotted vs. data usability class standard deviation
Dashed line: trend
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Mean data usability vs data usability within metadata
Comparison of mean data usability and data usability (metadata) for 400 quadrants
Dotted line is 1:1 line, solid line is regression line
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Single interpretation assessment vs Standard deviation
Evaluation by interpreters plotted against standard deviation
Results of each individual interpreter marked by separate symbol and colour
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Operational aspects
Extended quick-look product with cloud mask, operator vote and automaton vote
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© borg, fichtelmann, asche·dlr·uni·potsdam 2011
Extended quick-look product for monitoring the actual processing status
Operational aspects
Thank you for your attention!Questions, comments, feedback?
ICCSA 2011 | GEOG-AN-MOD 2011 | University of Santander | 20-23/06/2011