Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.
<ul><li>Improvement of  </li></ul><ul><li>spatial data quality  through data conflation  </li></ul><ul><li>Silvija Stankut...
<ul><li>Increasing availability of remote sensing (RS) data is complica-ting orientation in data bases of remote sensing d...
Search in databases  Data acquisition <ul><li>DESCW </li></ul><ul><li>Retrieval system: Display Earth Remote Sensing Swath...
Processing chain National ground segment Landsat 7 Monitor & Control, MWD WS (SGI O2 with 128MB) 18 GB disk 2 x DLT 7000 E...
Derivation of test data Receiving circle of Neustrelitz ground station Spatial distribution of Landsat 7/ETM+ database
Definitions of data quality <ul><li>Assessment of cloud cover degreee </li></ul><ul><li>Detection and identification of cl...
Quick-look data for quality assessment <ul><li>Quality assessment by interpreters </li></ul><ul><li>4 quadrants </li></ul>...
Equations Assessment of evaluation subjectivity  Acceptable error   0.05 (significance level of 5 %) z-value Standard nor...
Equations Mean error vs single interpreter | metadata <ul><li>Modulus of absolute error of mean data usability with regard...
Mean data usability vs standard deviation <ul><li>Interpreter assessment plotted vs. data usability class standard deviati...
Mean data usability vs data usability within metadata <ul><li>Comparison of mean data usability and data usability (metada...
Single interpretation assessment vs Standard deviation <ul><li>Evaluation by interpreters plotted against standard deviati...
Operational aspects  Extended quick-look product with cloud mask, operator vote and automaton vote
Extended quick-look product for monitoring the actual processing status Operational aspects
Thank you for your attention! Questions, comments, feedback? [email_address] [email_address] ICCSA 2011 | GEOG-AN-MOD 2011...
Nächste SlideShare
Wird geladen in …5
×

Data Usability Assessment for Remote Sensing Data: Accuracy of Interactive Data Quality Interpretation

731 Aufrufe

Veröffentlicht am

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 Potsdam

Veröffentlicht in: Technologie, Business
  • Als Erste(r) kommentieren

Data Usability Assessment for Remote Sensing Data: Accuracy of Interactive Data Quality Interpretation

  1. 1. <ul><li>Improvement of </li></ul><ul><li>spatial data quality through data conflation </li></ul><ul><li>Silvija Stankute, Hartmut Asche </li></ul><ul><li>Geoinformation Research Group </li></ul><ul><li>Dept of Geography | University of Potsdam | Germany </li></ul>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 Asche DFD | German Aerospace Centre | Neustrelitz Dept of Geography | University of Potsdam | Germany ICCSA 2011 | GEOG-AN-MOD 2011 | University of Santander | 20-23/06/2011
  2. 2. <ul><li>Increasing availability of remote sensing (RS) data is complica-ting orientation in data bases of remote sensing data </li></ul><ul><li>To facilitate orientation in RS data bases data providers make available additional data information, such as geographic loca-tion, acquisition time, data quality </li></ul><ul><li>To assess RS data quality cloud cover degree is a frequently used quality parameter which records data quality insufficiently </li></ul><ul><li>ESA has defined a new quality measure data usability which is interactively interpreted by operators based on: </li></ul><ul><li>Technical data errors : lost image lines/segments, scan mirror anomalies, </li></ul><ul><li>Unusable image segment : Clouds, haze, shadow, derivation within a scene </li></ul>Motivation
  3. 3. Search in databases Data acquisition <ul><li>DESCW </li></ul><ul><li>Retrieval system: Display Earth Remote Sensing Swath Coverage </li></ul><ul><li>Data selection criteria of LANDSAT 7 / ETM+ data include </li></ul>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
  4. 4. 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 18GBdisk Catalogue, OH Workstation (O2 with 128MB) SWITCH MATRIX (EMP) SGI Origin 200 server 4CPUs 512 MB plus GigaChannel PCI ingestion boards (Ciel) 5 x 18 GB disk array internal SCSI Controller 2 x DLT 7000 18 GB disk SGI O2 Station Data Server EXABYTE CD Master Labelling system Label Printer Reports Printer Fast Ethernet Label Printer Reports Printer R S 2 3 2 R S 2 3 2 Front-End Handler (PC - RS232/IEEE488) Demod 1 (Alcatel) Exabyte CD-ROM DLT 7000 c o n t r o l l e r 4 x S C S I SGI Origin 200 server 4CPUs 512 MB plus GigaChannel PCI ingestion boards (Ciel) 5 x 18 GB disk array internal SCSI Controller c o n t r o l l e r 4 x S C S I 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) I Q <ul><li>Objectives </li></ul><ul><li>Decoding and data syncronisation </li></ul><ul><li>De-communitation </li></ul><ul><li>Production of browse data </li></ul><ul><li>Status information </li></ul><ul><li>Storage of raw data </li></ul>Schematic representation of Landsat ground segment (modified from Beruti 2002) Red: interactive data usability assessment STOP Interactive Data Usability Estimation
  5. 5. Derivation of test data Receiving circle of Neustrelitz ground station Spatial distribution of Landsat 7/ETM+ database
  6. 6. Definitions of data quality <ul><li>Assessment of cloud cover degreee </li></ul><ul><li>Detection and identification of cloud covered pixel </li></ul><ul><li>Ration of number of cloud covered pixel to total number of pixels of assessment unit </li></ul><ul><li>Data usability assessment </li></ul><ul><li>Not usable image segment: detection of clouds and cloud shadows, distribution and configuration within scene </li></ul><ul><li>Technically induced image errors: lost lines and sectors, scan mirror anomalies </li></ul>Cloud No Cloud 25 % Cloudiness
  7. 7. Quick-look data for quality assessment <ul><li>Quality assessment by interpreters </li></ul><ul><li>4 quadrants </li></ul><ul><li>Real colour coded data </li></ul>
  8. 8. Equations Assessment of evaluation subjectivity  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 d i Absolute error SD DU Standard deviation
  9. 9. Equations Mean error vs single interpreter | metadata <ul><li>Modulus of absolute error of mean data usability with regard to single interpreter assessment </li></ul><ul><li>Modulus of absolute error of mean data usability with regard to metadata assessment </li></ul>
  10. 10. Mean data usability vs standard deviation <ul><li>Interpreter assessment plotted vs. data usability class standard deviation </li></ul><ul><li>Dashed line: trend </li></ul>
  11. 11. Mean data usability vs data usability within metadata <ul><li>Comparison of mean data usability and data usability (metadata) for 400 quadrants </li></ul><ul><li>Dotted line is 1:1 line, solid line is regression line </li></ul>
  12. 12. Single interpretation assessment vs Standard deviation <ul><li>Evaluation by interpreters plotted against standard deviation </li></ul><ul><li>Results of each individual interpreter marked by separate symbol and colour </li></ul>
  13. 13. Operational aspects Extended quick-look product with cloud mask, operator vote and automaton vote
  14. 14. Extended quick-look product for monitoring the actual processing status Operational aspects
  15. 15. Thank you for your attention! Questions, comments, feedback? [email_address] [email_address] ICCSA 2011 | GEOG-AN-MOD 2011 | University of Santander | 20-23/06/2011

×