The MIMS Spatial Allocator: A Tool for Generating Emission Surrogates without a Geographic Information System* Alison M. Eyth, Kimberly Hanisak Carolina.

Slides:



Advertisements
Similar presentations
Atlas Server – A Tool for Atlas Mapping Altai State Technical University Public Fund Altai 21-st Century Barnaul, Russia Irina Mikhailidi.
Advertisements

Geographic Information Systems GIS Data Models. 1. Components of Geographic Data Spatial locations Attributes Topology Time.
Geographic Information Systems
NLCD and MODIS Landuse Processing Tools and Projection Issues in Modeling Limei Ran and Alison Eyth Center for Environmental Modeling for Policy Development.
Fire Modeling Protocol MeetingBoise, IDAugust 31 – September 1, 2010 Applying Fire Emission Inventories in Chemical Transport Models Zac Adelman
UC Riverside Attribution of Haze Meeting, June 22, 2005, Seattle, WA UNC/CEPENVIRON Corp. Spatial Processing and Display of WRAP Emissions Data, and Source.
A Discussion of the Visualization Needs of the Community Carolina Environmental Program University of North Carolina at Chapel Hill A Discussion of the.
Spatial Allocation  Philosophy  Tools  Design  Standard reports  Questions.
Raster Based GIS Analysis
Geographic Information Systems GIS Analysis and Modeling.
Application of HEC- HMS for Hydrologic Studies Texas A&M University Department of Civil Engineering CVEN689 – Applications of GIS in CE Instructor: Dr.
Geographic Information Systems
Coordinate systems.
Geographic Information Systems
@ 2007 Austin Troy. Geoprocessing Introduction to GIS Geoprocessing is the processing of geographic information. Perform spatial analysis and modeling.
Introduction to ArcGIS for Environmental Scientists Module 3 – GIS Analysis ArcGIS Toolbox.
Rebecca Boger Earth and Environmental Sciences Brooklyn College.
Introduction to ArcGIS for Environmental Scientists Module 2 – GIS Fundamentals Lecture 5 – Coordinate Systems and Map Projections.
Introduction to the course January 9, Points to Cover  What is GIS?  GIS and Geographic Information Science  Components of GIS Spatial data.
Add a File with X, Y coordinates to MapWindow
B.H. Baek and Catherine Seppanen Institute for the Environment-UNC at Chapel Hill Allison DenBleyker, Chris Lindhjem and Michele Jimenez ENVIRON International.
Laura Boothe Attainment Planning Branch Supervisor January 11, 2012.
Geographic Information Systems Coordinate Systems.
Basic Coordinate Systems Grid Systems RG 620 May 09, 2013 Institute of Space Technology, Karachi RG 620 May 09, 2013 Institute of Space Technology, Karachi.
Advances in SIGRID-based formats: Toward a new archive standard With input from the GDSIDB Ad-hoc Format Subgroup: H. Andersen (DMI) C. Bertoia (NIC) R.
Preparing Data for Analysis and Analyzing Spatial Data/ Geoprocessing Class 11 GISG 110.
ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation,
©2005,2006 Carolina Environmental Program Sparse Matrix Operator Kernel Emissions SMOKE Modeling System Zac Adelman and Andy Holland Carolina Environmental.
Open Emissions Model(OPEM) Emissions Model for Models3/CMAQ and CAMX Mark Janssen – LADCO/MWRPO Zion Wang – UC Riverside
Carolina Environmental Program UNC Chapel Hill The Analysis Engine – A New Tool for Model Evaluation, Sensitivity and Uncertainty Analysis, and more… Alison.
GIS 1 GIS Lecture 4 Geodatabases. GIS 2 Outline Administrative Data Example Data Tables Data Joins Common Datasets Spatial Joins ArcCatalog Geodatabases.
Coordinate Systems Global Coordinate System – Latitude, Longitude and elevation UTM – eastings and northings, reference points are the equator and the.
Carolina Environmental Program Status of SMOKE Catherine Seppanen Carolina Environmental Program University of North Carolina - Chapel Hill.
School of Geography FACULTY OF ENVIRONMENT Introduction to ArcToolbox and Geoprocessing.
SmartMap Intelligent Crash Location Tool AASHTO GIS-T San Diego March 1999 Reg Souleyrette Dan Gieseman Center for Transportation Research and Education.
___________________________________________GIST: A New Tool for Visualizing Geographic Data Environmental Modeling Center__________________________________________________.
How do we represent the world in a GIS database?
Intro to GIS and ESRI Trainers: Randy Jones, GIS Technician, Douglas County Jon Fiskness, GISP GIS Coordinator, City of Superior.
Exploring ArcToolbox Presented by: Isaac Johnson.
Introduction to EPA’s Multimedia Integrated Modeling System Software Suite: A New Framework for Models-3 Steve Fine (EPA/NOAA), Steve Howard (EPA/NOAA),
An ENIF Image Is Worth A Thousand Lines of EMME/2 Output By Steve Hayto, PEng, S5 Services Carlos M Perez, PEng, Delcan Corporation 19 th Annual International.
Design and Development of MAQM, an Air Quality Model Architecture with Process-Level Modularity Weimin Jiang, Helmut Roth, Qiangliang Li, Steven C. Smyth,
Using the EMF for Emissions Sensitivities and for CMAQ Alison M. Eyth Alexis Zubrow Qun He UNC Institute for the Environment October, 2008.
University of North Carolina at Chapel Hill Carolina Environmental Programs Models-3 Adel Hanna Carolina Environmental Program University of North Carolina.
Carolina Environmental Program 1 UNC Chapel Hill A New Control Strategy Tool within the Emissions Modeling Framework Alison M. Eyth Carolina Environmental.
John Pickford IBM H11 Wednesday, October 4, :30. – 14:30. Platform: Informix Practical Applications of IDS Extensibility (Part 2 of 2)
Intro to GIS | Summer 2012 Attribute Tables – Part 1.
1 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features.
Modeling Wildfire Emissions Using Geographic Information Systems (GIS) Technology and Satellite Data STI-3009 Presented by Neil J. M. Wheeler Sonoma Technology,
Geographic Data in GIS. Components of geographic data Three general components to geographic information Three general components to geographic information.
Intro to GIS & Pictometry Trainers: Randy Jones, GIS Technician, Douglas County Jon Fiskness, GISP GIS Coordinator, City of Superior.
Effects of Emission Adjustments on Peak Ground-Level Ozone Concentration in Southeast Texas Jerry Lin, Thomas Ho, Hsing-wei Chu, Heng Yang, Santosh Chandru,
Introduction to Geographic Information Systems (GIS)
Map Projections Goal: translate places on the Earth (3D) to Cartesian coordinates (2D)
University of North Carolina at Chapel Hill Carolina Environmental Programs Community Modeling and Analysis System (CMAS) Year 3 Adel Hanna Director, CMAS.
Center for Community Modeling and Analysis System (CMAS) Adel Hanna Director, CMAS October 1, th Annual CMAS Conference, Chapel Hill, NC.
Recent Enhancements to Quality Assurance and Case Management within the Emissions Modeling Framework Alison Eyth, R. Partheepan, Q. He Carolina Environmental.
Introduction to Geographic Information Systems Fall 2013 (INF 385T-28620) Dr. David Arctur Research Fellow, Adjunct Faculty University of Texas at Austin.
Emission Inventory Input Format Eastern Canadian Premiers/New England Governors Conference Data Exchange Workgroup Gregory Stella U.S. Environmental Protection.
Uploading Data Matthew Hanson  GeoNode made up of several components  Web Framework – Django  OGC Server – GeoServer  Database – PostGIS.
Limei Ran 1, Ellen Cooter 2, Verel Benson 3, Dongmei Yang 1, Robert Gilliam 2, Adel Hanna 1, William Benjey 2 1 Center for Environmental Modeling for Policy.
Lecture 18: Spatial Analysis Using Rasters Jeffery S. Horsburgh CEE 5190/6190 Geographic Information Systems for Civil Engineers Spring 2016.
Spatial Allocator Version 4.3
EPA Tools and Data Update
ArcGIS Topology Shapefiles, Coverages, Geodatabases
GIS Lecture: Geoprocessing
Vector Geoprocessing.
Overview Activities from additional UP disciplines are needed to bring a system into being Implementation Testing Deployment Configuration and change management.
Software Re-engineering and Reverse Engineering
Presentation transcript:

The MIMS Spatial Allocator: A Tool for Generating Emission Surrogates without a Geographic Information System* Alison M. Eyth, Kimberly Hanisak Carolina Environmental Program University of North Carolina at Chapel Hill October 28, 2003 *This material was originally presented at the Emission Inventory conference in San Diego, CA on May 1, 2003 Carolina Environmental Program UNC Chapel Hill

Multimedia Integrated Modeling System (MIMS) Program sponsored by EPA Office of Research and Development Successor to Models-3 Computer Framework Components: Java-based computer framework for running multimedia (and other complex) models Spatial allocator, Analysis engine, etc. Framework contains tool for designing/visualizing air quality model grids (also developed by MCNC) Free to users mostly open source components, but uses some proprietary (but free) libraries http://www.epa.gov/asmdnerl/mims Multimedia Integrated Modeling System (MIMS) • Project funded by EPA Office of Research and Development • Successor to Models-3 • Includes a computer framework to support running multimedia (and other complex) models • Also includes Spatial Allocator • Many components are open source () • Uses some proprietary libraries with free end user licenses • Software provided to users for free Carolina Environmental Program UNC Chapel Hill

MIMS Spatial Allocator Initially developed at MCNC Most of MCNC EMC is now at UNC Chapel Hill New version provided in March with optimizations, new features, and bug fixes Additional changes provided in October Operating modes: Generates spatial surrogates that can be input to SMOKE Change map projection of Shapefiles Performs other types of spatial allocation Aggregate county data to state data Convert between county data and gridded data Carolina Environmental Program UNC Chapel Hill

Benefits of Spatial Allocator Zero cost makes surrogate generation accessible to more people Focused purpose of software makes it easier to use to create surrogates than a GIS Runs on UNIX and Windows Input data in commonly used ESRI Shapefile format Output Surrogates Computed for regular grid (but could support adaptive grids) Written in SMOKE format (but other formats could be added) Supported map projections include Universal Transverse Mercator (UTM), Lambert Conformal, and Latitude-Longitude Carolina Environmental Program UNC Chapel Hill

What are Spatial Surrogates? Used to map county level emission inventory data into the rectangular grid cells used by air quality models For example, dry cleaning emissions values may be available for a county, but CMAQ requires them by grid cell Surrogate value is the fraction of the emissions for a county that should be apportioned to a grid cell emis(GC) = srg(Cty,GC) * emis(Cty) Surrogates allow for more spatial accuracy in emissions distribution than assuming a uniform spread over the county E.g. Applying a population surrogate causes higher levels emissions to be placed in the grid cells that cover more densely populated parts of the county Carolina Environmental Program UNC Chapel Hill

Computing Spatial Surrogates Surrogates are computed using a fraction Numerator = the value of a weight attribute in the area of intersection between the grid cell and county Denominator = the value of a weight attribute in the entire county Sum of surrogates values for each county within the grid should be 1 Weight attributes can be based on objects that are points, lines, or polygons (e.g. port berths, railroads, population) Sometimes use number of points, length, or area for weight Carolina Environmental Program UNC Chapel Hill

Overall Surrogate equation Where Wt(x) = value of weight attribute for x, Cty = County, GC = grid cell, wp = weight polygon Carolina Environmental Program UNC Chapel Hill

Impact of Weight Attribute on Surrogate Values Grid Cell # Ports in gc i, cty C # Berths in gc i, cty C Surrogate wt=Count Surrogate wt=Berths 1 2 6 1 / 4 = 0.25 6 / 12 = 0.5 3 2 / 4 = 0.5 4 Total 12 Carolina Environmental Program UNC Chapel Hill

Using the GRIDDESC File to Specify the Output Grid ! coords ‑‑line: name; type, P‑alpha, P‑beta, P‑gamma, xcent, ycent 'LAT_LON' 1, 0.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0 'UTM_10' 5, 10.0D0, 0.0D0, 0.0D0, 0.0D0, 0.0D0 'LAM_40N105W' 2, 30.0D0, 60.D0,‑105.D0,‑105.D0, 40.D0 ' ' ! end coords. Grid name;xorig,yorig,xcell,ycell,ncols,nrows,nthik 'EPAW36_56X78' 'LAT_LON' , ‑127.0D0, 26.0D0, 0.5000D0, 0.33333D0, 56, 78, 1 'NEW_YORK' 'UTM_18', 480.0D3, 4440.0D3, 5.0D3, 5.0D3, 58, 46, 1' 'DENVER8_34X45' 'LAM_40N105W', ‑116.D3, ‑188.D3, 8.D3, 8.D3, 34, 45, 1 Carolina Environmental Program UNC Chapel Hill

Visualizing Grids with MIMS Grid Family GUI Carolina Environmental Program UNC Chapel Hill

Example Windows .bat for Ports Surrogate set MIMS_PROCESSING=SURROGATE set POLY_OUT_TYPE=RegularGrid set DATA=C:\surrogates\inputs set GRIDDESC=%DATA%\GRIDDESC.txt set GRID=M_08_99NASH set POLY_DATA_TYPE=ShapeFile set POLY_DATA=%DATA%\cnty_tn set ATTR_DATA_ID=FIPS_CODE set POLY_WEIGHT_TYPE=ShapeFile set POLY_WEIGHT=%DATA%\tn_ports set ATTR_WEIGHT=BERTHS set CATEGORY_WEIGHT=4 set SURROGATE_FILE=C:\surrogates\output\srg_ports.%GRID%.txt C:\surrogates\bin\mims_spatial.exe Carolina Environmental Program UNC Chapel Hill

Quality Assurance Options for Surrogates OUTPUT_SRG_NUMERATOR: writes surrogate numerator as a comment in output file OUTPUT_SRG_DENOMINATOR: writes surrogate denominator as a comment in output file MIMS_QASUM: writes a running sum of the surrogate values for each county in output file (should sum to 1) POLY_OUT_NAME: creates a shape file (and .csv file) that contain sums of the surrogate numerators for each grid cell (gridded version of weight attribute Carolina Environmental Program UNC Chapel Hill

Excerpt of Surrogate Output with Quality Assurance Options On Cat County Col Row Srg value Numerator Denominator QA Sum 4 47011 44 20 1 ! 8 8 1 4 47037 19 28 0.2 ! 2 10 0.2 4 47037 20 27 0.3 ! 3 10 0.5 4 47037 20 28 0.3 ! 3 10 0.8 4 47037 21 29 0.2 ! 2 10 1 4 47039 6 18 1 ! 3 3 1 5 47027 32 34 0.491036 ! 12917.80 26307.3 0.49104 5 47027 32 35 0.005787 ! 152.24 26307.3 0.49682 5 47027 33 35 0.338548 ! 8906.28 26307.3 0.83537 5 47027 33 36 0.164629 ! 4330.96 26307.3 1 Carolina Environmental Program UNC Chapel Hill

GIST Visualization of Airport Surrogate (Weight = Count) Carolina Environmental Program UNC Chapel Hill

GIST Visualization of Port Surrogate (Weight = Berths) Carolina Environmental Program UNC Chapel Hill

Specifying Map Projections and Ellipsoids PROJ.4 library is used (http://www.remotesensiong.org/proj) Supports most map projections Lambert conformal example: setenv DATA_POLY_MAP_PRJN "+proj=lcc,+lat_1=33,+lat_2=45,+lat_0=40,+lon_0=‑97“ UTM example: setenv WEIGHT_POLY_MAP_PRJN "+proj=utm,+zone=17“ Ellipsoid examples: setenv WEIGHT_POLY_ELLIPSOID=+GRS80 setenv WEIGHT_POLY_ELLIPSOID=+a=6378137.0,+rf=298.2572 Carolina Environmental Program UNC Chapel Hill

Converting the Map Projection of Shapefiles #!/bin/csh -f setenv MIMS_PROCESSING CONVERT_SHAPE setenv POLY_DATA_TYPE ShapeFile setenv POLY_DATA $argv[1] # no extension setenv POLY_OUT_TYPE ShapeFile setenv POLY_OUT_NAME $argv[2] # no extension setenv DATA_POLY_MAP_PRJN "+proj=lcc,+lat_1=33,+lat_2=45,+lat_0=40,+lon_0=‑97" setenv DATA_POLY_ELLIPSOID +WGS84 setenv OUTPUT_POLY_MAP_PRJN LATLON setenv OUTPUT_POLY_ELLIPSOID SPHERE /apps/mims_spatial/bin/mims_spatial.exe Carolina Environmental Program UNC Chapel Hill

Software Implementation Software is written in C Blocks of code to perform specific tasks that are reused for different operating modes First read data (then weight) polygons & convert map projection to output projection Next compute intersection of weight and data polygons (then of weight-data polygons with grid polygons) Then compute surrogates Numerator = sum of weight for each county and gc Denominator = sum of weight for each county Public domain libraries used PROJ.4 for map projection conversions Shapelib for reading / writing shapefiles Generic Polygon Clipper for polygon intersection Carolina Environmental Program UNC Chapel Hill

Carolina Environmental Program UNC Chapel Hill Limitations Currently only SMOKE-ready output Output assumed to be on sphere Line-based inputs must be “dissolved” at the county boundaries Carolina Environmental Program UNC Chapel Hill

Carolina Environmental Program UNC Chapel Hill Future Directions Produce biogenic inputs for SMOKE Easier conversion between county and gridded data Generalize spatial allocation to support more forms of regridding Create surrogates for adaptive and other non-regular grids Further reduce memory usage to support use of larger data sets (~ 1 GB) Carolina Environmental Program UNC Chapel Hill