Future Directions of Map Analysis and GIS Modeling Presented by Joseph K. Berry Adjunct Faculty in Geosciences, Department of Geography, University of Denver Adjunct Faculty in Natural Resources, Warner College of Natural Resources, Colorado State University Principal, Berry & Associates // Spatial Information Systems Email: [email protected]— Website: www.innovativegis.com/basis Premise : There are three major forces driving map analysis/modeling— establishing a map-ematical framework (SpatialSTEM), utilizing a Universal Spatial Database Key and radical changes in Raster Data Structure 2014 Manitoba GIS User Group Fall Conference | October 1, 2014 | Winnipeg, Manitoba, Canada This PowerPoint with notes and online links to further reading is posted at www.innovativegis.com/basis/Present/Manitoba2014/ Premise : There are three major forces driving map analysis/modeling— establishing a map-ematical framework (SpatialSTEM), utilizing a Universal Spatial Database Key and radical changes in Raster Data Structure
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Future Directions of Map Analysis and GIS Modeling Presented by Joseph K. Berry Adjunct Faculty in Geosciences, Department of Geography, University of.
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Future Directions of Map Analysis and GIS Modeling
Presented by
Joseph K. Berry
Adjunct Faculty in Geosciences, Department of Geography, University of DenverAdjunct Faculty in Natural Resources, Warner College of Natural Resources, Colorado State University
Principal, Berry & Associates // Spatial Information Systems
Premise: There are three major forces driving map analysis/modeling— establishing a map-ematical framework (SpatialSTEM), utilizing a Universal Spatial Database Key
and radical changes in Raster Data Structure
2014 Manitoba GIS User GroupFall Conference | October 1, 2014 | Winnipeg, Manitoba, Canada
This PowerPoint with notes and online links to further reading is posted at
www.innovativegis.com/basis/Present/Manitoba2014/
Premise: There are three major forces driving map analysis/modeling— establishing a map-ematical framework (SpatialSTEM), utilizing a Universal Spatial Database Key
−Mapping that creates a spatial representation of an area
−Display that generates visual renderings of a mapped area
−Geo-query that searches for map locations having a specified classification, condition or characteristic
“Map”
(Descriptive Mapping)
“Analyze”
… and an Analytical Tool involving —
−Spatial Mathematics that applies scalar mathematical formulae to account for geometric positioning, scaling, measurement and transformations of mapped data
−Spatial Analysis that investigates the contextual relationships within and among mapped data layers
−Spatial Statistics that investigates the numerical relationships within and among mapped data layers
Spatial Analysis extends the basic set of discrete map features (points, lines and polygons) to
map surfaces that represent continuous geographic space as a set of contiguous grid cells (matrix),thereby providing a Mathematical Framework for map analysis and modeling of the
Contextual Spatial Relationships within and among grid map layers
(Berry)
GIS as “Technical Tool” (Where is What) vs. “Analytical Tool” (Why, So What and What if)
270/621= 43% of the entire road network is connected
Visual Exposure
Distance
Shortest straight line between two points (S,SL,2P)…
Travel-TimeSurface
Effective Proximity
…not necessarily straight lines (S movement)
HQ (start)On Road
26.5 minutes
…farthest away by truck
Off RoadAbsolute Barrier
On + Off Road
96.0 minutes
…farthest away by truck, ATV and hiking
Off RoadRelative Barriers
Plane Geometry
Connectivity
…like a raindrop, the “steepest downhillpath” identifies the optimal route(Quickest)
Farthest(end)
HQ (start) Truck = 18.8 min
ATV = 14.8 min Hiking = 62.4 min
Pythagoras500 BC
Splash Algorithm2000 AD
Spatial Statistics Operations (Numeric Context)
(Berry)
Spatial Statistics seeks to map the variation in a data set instead of focusing on a single typical response (central tendency), thereby providing a Statistical Framework for map analysis and modeling of the
Numerical Spatial Relationships within and among grid map layers
GIS as “Technical Tool” (Where is What) vs. “Analytical Tool” (Why, So What and What if)
Localized CorrelationMap Variable – continuous quantitative surface represents the localized spatial relationship between the two map surfaces
…625 small data tables within 5 cell reach =
81map values for localized summary
r = .432 Aggregated
+
Geographic Space
Predictive Statistics (Correlation)
The Latitude/Longitude grid forms a continuous surface for geographic referencing
where each grid cell represents a given portion of the earth’ surface.
300
90
Grid-based Map Data (geo-registered matrix of map values)2.50 Latitude/Longitude Grid (140mi grid cell size)
Coordinate of first grid cell is 900 N 00 E
AnalysisFrame(Matrix)
(Berry)
Conceptual Spreadsheet (73 x 144)
#Rows= 73 #Columns= 144
…each 2.50 grid cell is about 140mi x 140mi
18,735mi2…from Lat/Lon
“crosshairs to grid cells”
that contain map
values indicating characteristics or conditions at each
location
Lat/Lon
--------------------------------------------------------The easiest way to conceptualize a grid map is as an Excel spreadsheet with each cell in the table corresponding to a Lat/Lon grid space (location)
and each value in a cell representing the characteristic or condition (information) of a mapped variable occurring at that location.
…maximum Lat/Lon decimal degree resolution is
a four-inch squareanywhere in the world
…Spatially Keyed data in the cloud are downloaded and configured to the
Analysis Frame defining the Map Stack
Database Table
Geographic Space
GridSpace
“Where”
RDBMS Organization
Data SpaceEach column (field) represents a single map layer
with the values in the rows indicating the characteristic or condition at each grid cell location (record)
“What”
Universal Spatial Db Key (developing spatially-aware databases)
Lat/Lon as a
Universal Spatial Key
Once a set of mapped data is stamped with its Lat/Lon
“Spatial Db Key”
…it can belinked to any other database table
with spatially tagged records without the explicit storage of a fully
expanded grid layer—
All of the spatial relationships are implicit in the relative Lat/Lon positioning
in the raster grid.
(Berry)
Conceptual Organization
Elevation Surfa
ce
Spreadsheet 30m Elevation
(99 columns x 99 rows)
Keystone Concept
2D Matrix 1D Field
Spatially Keyed data in the cloud
Lat/Lon serves as a Universal dB Key for joining data tables based on location