20161128
21325200
1.0
FALSE
LF_us_140evt
002
-2362425.000000
2263815.000000
258945.000000
3177435.000000
1
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_Albers
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.5'><WKT>PROJCS["NAD_1983_Albers",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-96.0],PARAMETER["Standard_Parallel_1",29.5],PARAMETER["Standard_Parallel_2",45.5],PARAMETER["Latitude_Of_Origin",23.0],UNIT["Meter",1.0]]</WKT><XOrigin>-16901100</XOrigin><YOrigin>-6972200</YOrigin><XYScale>266467840.99085236</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem>
16
FALSE
RLE
1
GRID
TRUE
continuous
signed integer
-32768
20171110
14490100
20171110
14490100
Version 6.2 (Build 9200) ; Esri ArcGIS 10.5.1.7333
LF_us_140evt
1
-127.987753
-65.254445
51.649681
22.765715
BAGIS Tag End Tag
30-meter Landfire Existing Vegetation Type with additional attributes of intcp_snow, intcp_srain, intcp_wrain, root_depth, and alpine_abv_treeline.
30-meter Landfire Existing Vegetation Type with additional attributes of intcp_snow, intcp_srain, intcp_wrain, root_depth, and alpine_abv_treeline.
Geography, Portland State University
Public for BAGIS Users
File Geodatabase Raster Dataset
dataset
ESRI
10.3.1
2
1
0
-2362425.000000 258945.000000
-2362425.000000 3177435.000000
2263815.000000 3177435.000000
2263815.000000 258945.000000
-49305.000000 1718190.000000
154208
30.000000
97283
30.000000
VAT_LF_us_140evt
Table
640
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Value
VALUE
Integer
4
0
0
Count
COUNT
Integer
4
0
0
CLASSNAME
CLASSNAME
String
254
0
0
EVT_FUEL
EVT_FUEL
Double
8
0
0
EVT_FUEL_N
EVT_FUEL_N
String
254
0
0
EVT_LF
EVT_LF
String
254
0
0
EVT_GP
EVT_GP
Double
8
0
0
EVT_PHYS
EVT_PHYS
String
254
0
0
EVT_GP_N
EVT_GP_N
String
254
0
0
SAF_SRM
SAF_SRM
String
254
0
0
EVT_ORDER
EVT_ORDER
String
254
0
0
EVT_CLASS
EVT_CLASS
String
254
0
0
EVT_SBCLS
EVT_SBCLS
String
254
0
0
R
R
Double
8
0
0
G
G
Double
8
0
0
B
B
Double
8
0
0
RED
RED
Double
8
0
0
GREEN
GREEN
Double
8
0
0
BLUE
BLUE
Double
8
0
0
COV_TYPE
COV_TYPE
SmallInteger
2
0
0
root_depth
root_depth
SmallInteger
2
0
0
intcp_snow
intcp_snow
Single
4
0
0
intcp_srain
intcp_srain
Single
4
0
0
intcp_wrain
intcp_wrain
Single
4
0
0
EVT_OLD_VALUE
EVT_OLD_VALUE
SmallInteger
2
0
0
CHECK
CHECK
SmallInteger
2
0
0
CHECK2
CHECK2
SmallInteger
2
0
0
EVT_KEY
EVT_KEY
SmallInteger
2
0
0
Band_1
16
3999.000000
-9999.000000
20171110
Pixel
97283
154208
30.000000
30.000000
16
1
Upper Left
FALSE
LZ77
1
pixel codes
FGDBR
TRUE
row and column
30.000000
30.000000
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