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c-squares - a new method for representing, querying, displaying and exchanging dataset spatial extents System concept and development by: Tony Rees – PowerPoint PPT presentation

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Title: System concept and development by:


1
c-squares - a new method for representing,
querying, displaying and exchanging dataset
spatial extents
System concept and development by Tony
Rees Divisional Data Centre CSIRO Marine
Research, Australia
2
some example Metadatabases (Data Directories)
many others -- 100 lt 1000? ...
  • Typical features include searchability by
  • text
  • keywords
  • spatial and time constraints
  • This presentation - focus on spatial searching

3
current base level representation of spatial
data coverage in metadata is by bounding box
(minimum bounding rectangle, MBR)
  • concept introduced in 1994 (FGDC)
  • used for spatial searching, 1995 onwards
  • still the primary tool for metadata spatial
    searches

4
How well do MBRs represent spatial
data? (examples from our own metadata system)
MBR actual data locations
Franklin 02/1999 hydrology data
5
alternatives to MBRs for representation of data
spatial extents ...
  • bounding polygons
  • multiple bounding rectangles
  • defined regions - countries, administrative
    areas, bio- or geo-regions
  • circles (centre point radius)
  • pre-defined path distance (e.g. along a
    contour, coastline, satellite path)
  • actual point locations held in the metadata
    record
  • grid-based system

6
global grid systems already available ...
  • International Map of the World (IMW) rectangles
    (6 x 4 degrees)
  • Marsden Squares (10 x 10 degrees)
  • Maidenhead Squares (2 x 1 degree)
  • WMO (World Meteorological Organisation) Squares
    (10 x 10 degrees)
  • others ?
  • -- WMO squares eventually chosen for ease of
    subdivision (base 10) and simple relationship
    between WMO numbers and lat/long values

7
WMO 10-degree squares notation (part)
(Available via the web in NODC, 1998 World
Ocean Database 1998 Documentation)
8
The c-squares concept c-squares Concise
Spatial Query and Representation System
9
c-squares principle
data footprint using bounding rectangle
actual ships track - Franklin voyage 10/87
10
c-squares numbering system
  • each square is numbered according to a globally
    applicable system based on recursive divisions of
    WMO (World Meteorological organisation) 10-degree
    squares, e.g.
  • 10 degree
    square 3414 ( WMO number)
  • 5 degree square 34142
  • 1 degree square 3414227
  • 0.5 degree square
    34142274
  • 0.1 degree square
    3414227466
  • (etc.)
  • strings of codes represent an individual dataset
    extent, e.g.
  • 301349731114683111478311147931114883111
    489311149931121223112123
  • 311213131121323112134311214131121423112
    143311221731122183112219
  • 311222631122353112350311235131123523112
    353311236031123613112362
  • 311236331123703112371311238031123813112
    390311310031131013113102
  • 311310331131043113205311320631132073113
    216311321731132283113238
  • 3113239
  • encodes the extent
  • shown in the example

11
Codes have straightforward relationship with
lats/longs, mapsheets, etc. ...
e.g. 1400458 (1-degree square with origin at
45 º N, 008 º E)
additional degrees E
008 8 additional
degrees N 405 45
5-degree quadrant, i.e. 3 4

1 2 tens of degrees E (i.e., 00)
tens of degrees N (i.e., 40) global sector
(1NE, 3SE, 5SW, 7NW)
46
45
44
110 km
10
8
9
12
quad tree -type approach used where numerous
adjacent squares are occupied
squares can be bulked - example 3212
instead of specifying every 1-degree square
within 10 degree square 3212. This leads to
corresponding data reduction, e.g. Australia (at
1-degree resolution) can be described in 343
squares rather than 800
13
Example database-level implementation of
c-squares for metadata records (e.g. at 1 degree
resolution)
(etc.)
14
Spatial queries using c-squares
  • c-squares spatial queries simply test whether a
    text string representing the search box (ideally
    one or several c-squares) is matched anywhere in
    the c-squares string
  • example - search square 31132 will match any
    c-squares string which includes 31132 within it,
    e.g.
  • ltcsquaresgt
  • 311236331123703112371311238031123813112
    390311310031131013113102
  • 311310331131043113205311320631132073113
    216311321731132283113238
  • 3113239
  • lt/csquaresgt
  • hierarchical naming system for c-squares means
    that finer resolution squares are automatically
    picked up in any coarser resolution search

15
example search result ...
(etc.)
16
Viewing the full metadata record produces ...
with clickable link to show dataset extent using
c-squares
(etc.)
17
Base maps for displayed data can be changed at
will by the user, e.g.
(numerous other maps available, sample only shown)
18
Process invoked for web mapping
c-squares strings can be sent directly to the CMR
c-squares mapper (accessible via the web), e.g.
from OBIS (Ocean Biogeographic Information
System, USA)
ltform action "http//www.marine.csiro.au/cgi-bin
/cs_map.pl" method"post"gt ltINPUT TYPE"hidden"
NAME"csq" VALUE"321545943215459332154594
(etc.)"gt ltINPUT TYPE"hidden" NAME"title"
VALUE"Global Distribution of ltigtRajalt/igt"gt ltINPUT
TYPE"submit" NAME"submit" VALUE"make map
..."gt lt/formgt
19
c-squares strings are suitable for inclusion as a
new metadata element alongside bounding box,
for example ...
ltmetadatagt lttitlegtFranklin Voyage FR 10/87 CTD
Datalt/titlegt ltcustodianOrggtCSIRO Marine
Researchlt/custodianOrggt (etc. etc.)
ltboundingBoxgt ltnorthBoundingCoordgt-9.0lt/no
rthBoundingCoordgt ltsouthBoundingCoordgt-19.
0lt/southBoundingCoordgt ltwestBoundingCoordgt
117.0lt/westBoundingCoordgt
lteastBoundingCoordgt145.8lt/eastBoundingCoordgt
lt/boundingBoxgt ltcsquaresgt311149923112390131
1148933112380331123804311238113111488
231123812311237133111478431123704311
237013111478131114792311147913112361
4311146843112363331123613311146723112
360231123631311236223112360131123524
311235233112350431123521311235123112
35223112353231123531lt/csquaresgt (etc.)
would permit interoperability with both enabled
and non-enabled systems
20
Summary - strengths and weaknesses of c-squares
  • Strengths ...
  • c-squares is a concise and flexible method of
    encoding simple to moderately complex forms
  • automated or manual code entry (and maintenance)
    is straightforward
  • spatial searching is simple text string matching
    operation (no GIS involved)
  • c-squares mapper utility available via simple
    web call
  • can be used as adjunct to bounding coordinates
    searches
  • Weaknesses
  • some other numbering systems in use (Marsden
    Squares, Maidenhead Locators) - needs willingness
    to standardise on a single system for
    interoperability
  • c-squares are not a fixed multiple of
    kilometres, miles, etc.
  • strings can become quite long for large, complex
    regions (e.g. Pacific Ocean) - need to be able
    to incorporate data reduction using bulk method

21
other comments ...
  • c-squares notation is language-independent -
    can be equally useful in English, French,
    Italian, Japanese also discipline-independent
  • downwards-scalability of the c-squares notation
    means that it can be applied to any size region
    (e.g. local level)
  • equally applicable to both terrestrial and
    marine data
  • uses established standards for nomenclature,
    basis already available via the web (e.g. NODC
    site)

22
c-squares current and future status...
  • Implemented already in CMRs MarLIN metadata
    system and CAAB taxon dictionary
  • concept is available for implementation in any
    other agencies metadata systems without cost or
    technology overhead
  • potential to to be recognised as a formal
    metadata element by relevant user communities /
    national bodies
  • current CMR c-squares mapper is already
    accessible for general use
  • c-squares website constructed as a focal point
    for all c-squares related materials - including
  • initial c-squares specification
  • connection information to the c-squares mapper
  • sample PL/SQL code (to convert lat/long pairs to
    c-squares)
  • on-line lat/long - to - c-square converter
  • example c-squares-enabled metadata records, and
    more

23
  • Acknowledgements
  • Miroslaw Ryba and other CMR staff for assistance
    with constructing the c-squares mapper and
    general feedback
  • Blue Pages Marine and Coastal Data Directory
    (MCDD) for the notation for subdividing WMO
    squares
  • Martin Dix (CSIRO Atmospheric Research) and NOAA
    Globe Project for base maps as used in the
    mapper (used by permission)

Questions, comments?
website http//www.marine.csiro.au/csquares/ (NB
handout available at this meeting) My email
Tony.Rees_at_csiro.au
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