Transcript Forest Growth Model and Data Linkages

NLCD and MODIS Landuse
Processing Tools and Projection
Issues in Modeling
Limei Ran and Alison Eyth
Center for Environmental Modeling for Policy Development
Institute for the Environment
University of North Carolina at Chapel Hill
Outline of the Presentation
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Landuse Data
New Release of Spatial Allocator (SA) 3.5
Projection Issues in Modeling
Future Enhancements for SA
Acknowledgements
Landuse Data in WRF and MM5
• USGS Global Land Cover Characteristics
(GLCC) 30-second (around 1km) landuse
data are used in:
• WRF GEOGRID
• MM5 TERRAIN
• GLCC database was developed from:
• NOAA 1km AVHRR satellite images spanning
04/1992 through 03/1993
2001 NLCD and MODIS Landuse Data
• Two new land cover data sets are available:
• 2001 30m NLCD for US (Landsat 7 and 5 TM images)
• 2001 1km MODIS for the Globe (TERRA MODIS satellite images)
• 30m NLCD data can be obtained from two places:
USGS for US
• 21-classes USGS Land cover data
• Imperviousness
• Tree Canopy
NOAA Coastal Change Analysis Program (C-CAP) for coast regions
• 30-classes USGS Land cover data
• MODIS land cover database can be obtained from:
– Department of Geography, Boston University
• 20-classes IGBP land cover data
2001 NLCD Data
USGS
NOAA
2001 NLCD Classification
11 - Open Water
12 - Perennial Ice/Snow
21 - Developed - Open Space
22 - Developed - Low Intensity
23 - Developed - Medium Intensity
24 - Developed - High Intensity
31 - Barren Land (Rock/Sand/Clay)
32 - Unconsolidated Shore
41 - Deciduous Forest
42 - Evergreen Forest
43 - Mixed Forest
51 - Dwarf Scrub
52 - Shrub/Scrub
71 - Grassland/Herbaceous
72 - Sedge/Herbaceous
73 - Lichens
74 – Moss
75 - Tundra
81 - Pasture/Hay
82 - Cultivated Crops
90 - Woody Wetlands
91 - Palustrine Forested Wetland
92 - Palustrine Scrub/Shrub Wetland
93 - Estuarine Forested Wetland
94 - Estuarine Scrub/Shrub Wetland
95 - Emergent Herbaceous Wetlands
96 - Palustrine Emergent Wetland
97 - Estuarine Emergent Wetland
98 - Palustrine Aquatic Bed
99 - Estuarine Aquatic Bed
MODIS 2001 Land Cover Data
MODIS Land Cover IGBP
Classification
0 - water
1 - evergreen needleleaf forest
2 - evergreen broadleaf forest
3 - deciduous needleleaf forest
4 - deciduous broadleaf forest
5 - mixed forests
6 - closed shrublands
7 - open shrublands
8 - woody savannas
9 - savannas
10 - grasslands
11 - permanent wetlands
12 - croplands
13 - urban and built-up
14 - cropland/natural vegetation
mosaic
15 - permanent snow and ice
16 - barren or sparsely vegetated
17 - IGBP Water Bodies (recoded to
0 for MODIS Land Product
consistency).
254 - unclassified
255 - fill value
New Release of Spatial
Allocator 3.5
• New release is organized into three parts:
• Vector Tools to process shapefiles
• Raster Tools to process NLCD/MODIS landuse data
• Surrogate Tools to compute surrogates
• Uses PROJ4.6 to project between spherical
earth R and ellipsoid:
• PROJ4.6: no datum transformation. Matches WRF,MM5
projections.
• PROJ4.5 or older versions: performs datum transformation
automatically and results in mismatches.
NLCD and MODIS 2001 Data
Processing
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Two steps to generate modeling grid land cover
data from NLCD and MODIS data:
1. Pre-process original NLCD data sets to get rid of overlaps.
2. Compute modeling grid land cover information from:
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USGS NLCD land cover
USGS NLCD imperviousness
USGS canopy
NOAA coastal NLCD land cover
NASA MODIS land cover data
Two output files produced:
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WRF landuse NetCDF file
CSV text file
NC 1km Grids, NLCD and MODIS
NLCD and WRF Land Cover
NC 1km Grids
NLCD and WRF Land Cover
NC 1km Grids
NLCD and WRF Land and Water
Projection Issues in Modeling
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Map projection can be:
Forward:
Reverse:
P(x,y) = F { Projection, Parms(Earth_Model), P(long,lat) }
P(long,lat) = F { Projection, Parms(Earth_Model), P(x,y) }
Projection: LCC, AEAC, UTM
Earth model (datum): sphere R, ellipsoid WGS84 or NAD83, NAD27
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Datum transformation is needed when projecting a GIS data set to a
projection that uses a different earth model.
NLCD AEAC with NAD83 to LCC with R=6370000m
No
Reverse projection to
lat/long file in NAD83
transform datum?
Yes
Transform to
lat/long file in
sphere R
Forward projection to
x/y file in LCC with R
Conclusion:
1. Make sure that spatial data are in WGS84 datum (USGS GLCC data).
2. No Datum transformation from WGS84 to WRF or MM5 sphere (PROJ4.6).
Future Enhancements for
Spatial Allocator
• Develop programs to extract preprocessed
GOES satellite data for a modeling grid.
• User defined domain to extract GOES data
• Output in WRF NetCDF format
• Add variable grid option to:
• Surrogate computation
• BELD3 data processing
• Land cover computation
Acknowledgements
• This project is fully funded by US EPA
under the Contract No. EP-W-05-045,
“Operation of the Center for Community
Air Quality Modeling and Analysis”.
• We gratefully acknowledge the support of
William Benjey, Jonathan Pleim, and
Robert Gilliam from US EPA.