1. Introduction to Spatial Information Technologies in the Earth Sciences Miles Logsdon mlog@u.washington.edu http://faculty.washington.edu/~mloghttp://faculty.washington.edu/~mlog Or http://sal.ocean.washington.edu/peoplehttp://sal.ocean.washington.edu/people OR What is GIS/RS and what can it do for me? OR Why is Miles on the faculty in this College?

2. “Our” agenda today zWhat are “spatial information technologies? zWhat is the difference between GIS, Spatial Analysis, and Spatial Data Analysis? zWhat is the difference between a Spatial model and a Spatial Explicit Model zWhat is a theoretical basis for the application of GIS and spatial data analysis in Ecological Studies? zWhat research “methods” or “tools” directly apply between the two fields?

3. My agenda Show you pretty pictures Talk about myself Justify our time together Stop talking - Sooner or later Spatial Information Technologies GIS - GPS – Remote Sensing

4. Spatial Information Technologies Geographic Information Systems – GIS Global Positioning System – GPS Remote Sensing and Image Processing - RS Technologies to help answer: What is “here”? … give a position What is “next” to “this”? … given some description Where are all of the “???” … detecting or finding What is the spatial pattern of “???” When “X” occurs here, does “Y” also occur?

5. GIS Geographic Information System GIS - A system of hardware, software, data, people, organizations and institutional arrangements for collecting, storing, analyzing, and disseminating information about areas of the earth. (Dueker and Kjerne 1989, pp. 7-8) GIS - The organized activity by which people Measure aspects of geographic phenomena and processes; Represent these measurements, usually in a computer database; Operate upon these representations; and Transform these representations. ( Adapted from Chrisman, 1997) A KEY POINT: Geo-referenced Data

6. Suggested Reading Chrisman, Nicholas, 1997, “Exploring Geographic Information Systems”, John Wiley & Sons, Burrough, P. A., 1986, “Principles of Geographical Information Systems for Land Resources Assessment”, Monographs on Soil and Resources Servey #12, Oxford Science Publications Miller, Roberta Balstad, 1996, "Information Technology for Public Policy", in GIS and Environmental Modeling: Progress and Research Issues, editors, Michael F. Goodchild, Louis T. Steyaert, Bradley O. Parks, Carol Johnston, David Maidment, Michael Crane, and Sandi Glendinning, GIS World Books. Goodchild, Michael F., "The Spatial Data Infrastructure of Environmental Modeling", in GIS and Environmental Modeling: (see above). Faber, G. Brenda, William W. Wallace, Raymond M. P. Miller, "Collaborative Modeling for Environmental Decision Making", proceedings of the GIS'96 Tenth Annual Symposium on Geographic Information Systems, Vancouver, B.C., March 1996.

7. The larger context (Chrisman, 1997)

8. Concept of Spatial Objects POINTS LINES AREA 000 0 000 01 POINT 1 0 1 1 1 00 0 0 0 553 331 12 LINE AREA Raster Data Encoding Vector Data Encoding

9. Vector - Topology Object Spatial Descriptive 1 23 4 5 15 12 11 10 123123 x1,y1 x2,y2 x3,y3 123123 1212 1212 1212 1212 VAR1 VAR2 Fnode Tnode x1y1, x2y2 1 2 xxyy, xxyy 2 3 xxyy,xxyy 10, 11, 12, 15 10, ……. 1 2 3 1 2 Vector - Topology Data Relationships are invariant to translation and rotation

10. Map Algebra Raster topology In a raster GIS, cartographic modeling is also named Map Algebra. Mathematical combinations of raster layers several types of functions: Local functions – do not consult the 8 neighbors Focal functions – function on the “kernel” of neighboring cells Zonal functions – function on cells that test true in a different layer Global functions – based upon the distribution of “all” cells Functions can be applied to one or multiple layers

11. Focal Function: Examples 2 0 1 1 2 3 0 4 2 1 1 2 2 3 3 2 2 0 1 1 2 3 0 4 4 2 2 3 1 1 3 2 Focal Sum (sum all values in a neighborhood) = = Focal Mean (moving average all values in a neighborhood) 1.8 1.3 1.5 1.5 2.2 2.0 1.8 1.8 2.2 2.0 2.2 2.3 2.0 2.2 2.3 2.5 (3x3) 16 13 17 19

12. Spatial Data Analysis The accurate description of data related to a process operating in space, the exploration of patterns and relationships in such data, and the search for explanation of such patterns and relationships Spatial Analysis vs. Spatial Data Analysis Spatial Analysis = what is here, and where are all the X’s ??? Spatial Data Analysis = observation data for a process operating in space and methods are used to describe or explain the behavior, and/or relationship with other phenomena.

13. GPS – Finding distance by measuring time X A B u 4:00 p.m. >> << 7/100 of a second after 4:00 G J K E T Y U O W V W T D H K … G J K E T Y U O W... Receiver: Satellite: The precise location is determined by the intersection of 4 spheres of “time” GPS SV

14. Satellite Remote Sensing June 27, 2001

15. A “zonal” function between 3 raster layers SeaWifs, April 24, 1999 Thanks to Seelye Martion

16. PATTERN: (Landscape Ecology) Structure = the spatial relationships among the distinctive ecosystems or “elements” Function = the interactions among the spatial elements Change = the alteration in the structure and function of the ecological mosaic over time

17. Landscape Structure Physiognomy / Pattern Composition = The presence and amount of each element type without spatially explicit measures. –Proportion, richness, evenness, diversity Configuration = The physical distribution in space and spatial character of elements. –Isolation, placement, adjacency ** some metrics do both **

18. Types of Metrics Area Metrics Patch Density, Size and Variability Edge Metrics Shape Metrics Core Area Metrics Nearest-Neighbor Metrics Diversity Metrics Contagion and Interspersion Metrics

19. Represent the Data Explore the Data Fit a Model Perform Diagnostics Compare the Models Structured Process in Geostatistics

20. Introduction to Geostatistics Z(s)Z(s) D D is the spatial domain or area of interest s contains the spatial coordinates Z is a value located at the spatial coordinates { Z ( s ): s  D } Geostatistics : Z random; D fixed, infinite, continuous Lattice Models : Z random; D fixed, finite, (ir)regular grid Point Patterns : Z  1; D random, finite

21. Merge Bathymetry & Topography Thanks to David Finlayson

22. Puget Sound DEM: Resolving Coast Geomorphology Thanks to David Finlayson

23. Dec. 1998 June, 1981 Classified “land surface” response

24. AprMayJun JulAugSep Ocean Remote Sensing: SeaWifs, 1999, 1km monthly mean chlorophyll-a estimates Our collection Pacific Northeast, Apr – Sep, 1999 - 2002

25. Flying