20160404
12205100
1.0
FALSE
FINALCNF_blackAshSt_ExportFeature
002
373452.500000
466211.312500
5202751.500000
5300008.000000
1
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_15N
<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/3.0.0'><WKT>PROJCS["NAD_1983_UTM_Zone_15N",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["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</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><WKID>26915</WKID><LatestWKID>26915</LatestWKID></ProjectedCoordinateSystem>
20221114
12175700
20221114
12175700
Esri ArcGIS 13.0.2.36056
FINALCNF_blackAshSt_ExportFeature
1
-94.691282
-93.444252
47.852525
46.966204
publication date
2022-09-07
change in mean NDVI values for black ash stands in CNF - polygons
File Geodatabase Feature Class
dataset
EPSG
6.11(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
FINALCNF_blackAshSt_ExportFeature
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
SHAPE
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
Join_Count
Join_Count
Integer
4
0
0
TARGET_FID
TARGET_FID
Integer
4
0
0
SPATIAL_ID
SPATIAL_ID
String
255
0
0
SETTING_ID
SETTING_ID
String
255
0
0
REGION_PROC
REGION_PROC
String
255
0
0
FOREST_PROC
FOREST_PROC
String
255
0
0
DISTRICT_NO
DISTRICT_NO
String
255
0
0
LOCATION
LOCATION
String
255
0
0
POLY_ID
POLY_ID
Integer
4
0
0
STAND_ACRES
STAND_ACRES
Double
8
0
0
NUM_EXAMS
NUM_EXAMS
Integer
4
0
0
NBR_PLOTS
NBR_PLOTS
Double
8
0
0
PROJECT_NAME
PROJECT_NAME
String
255
0
0
EXAM_DATE
EXAM_DATE
Double
8
0
0
EXAM_AGE
EXAM_AGE
Double
8
0
0
EXAM_PURPOSE_CODE
EXAM_PURPOSE_CODE
String
255
0
0
EV_CODE
EV_CODE
String
255
0
0
EV_NAME
EV_NAME
String
255
0
0
VEGETATION_TYPE
VEGETATION_TYPE
Integer
4
0
0
YEAR_OF_ORIGIN
YEAR_OF_ORIGIN
Integer
4
0
0
STAND_AGE
STAND_AGE
Double
8
0
0
SITE_INDEX
SITE_INDEX
Double
8
0
0
SITE_INDEX_SPP
SITE_INDEX_SPP
String
255
0
0
BA_GT1
BA_GT1
Double
8
0
0
DBH_QMD_GT1
DBH_QMD_GT1
Double
8
0
0
POLE_BA
POLE_BA
Double
8
0
0
POLE_DBH
POLE_DBH
Double
8
0
0
POLE_DOM_SPP
POLE_DOM_SPP
String
255
0
0
SAW_BA
SAW_BA
Double
8
0
0
SAW_DBH
SAW_DBH
Double
8
0
0
SAW_DOM_SPP
SAW_DOM_SPP
String
255
0
0
MERCH_BA
MERCH_BA
Double
8
0
0
MERCH_DBH
MERCH_DBH
Double
8
0
0
MERCH_DOM_SPP
MERCH_DOM_SPP
String
255
0
0
CAT1
CAT1
String
255
0
0
AGT1
AGT1
String
255
0
0
SEV1
SEV1
String
255
0
0
CAT2
CAT2
String
255
0
0
AGT2
AGT2
String
255
0
0
SEV2
SEV2
String
255
0
0
CAT3
CAT3
String
255
0
0
AGT3
AGT3
String
255
0
0
SEV3
SEV3
String
255
0
0
MNGMNT_OBJECTIVE
MNGMNT_OBJECTIVE
String
255
0
0
REMARKS
REMARKS
String
255
0
0
STAND_ID
STAND_ID
String
255
0
0
pointid
pointid
Integer
4
0
0
NDVIchange
NDVI change 2022 to 2013
Single
4
0
0
SHAPE_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
SHAPE_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20221114
Geospatial Interface Visualization:
HelpId: 690
DistributedIndicator: N
ProcessId: 4ada8f3d-a7d3-48f4-843d-f1a917f373e6
ProcessName: CNF FSVeg Puller (RSW)
OwnerName: R9_CHIPPEWA
Registry: REGION 09
ProcessType: Visualization
Purpose: Purpose: Pull FSVeg data for project base data and effects analysis. Includes columns for alternatives.
Prerequisites:
Results:
Created By:
Contact:
PreRequisites:
Results:
DetailsUrl:
StandardsUrl:
Contact: R9_CHIPPEWA
CreatedBy:
CreatedDate: 12/14/2010 1:32:51 PM
ModifiedBy: JRICKERS
ModifiedDate: 6/22/2018 2:49:41 PM
Assigned Keywords:
Vegetation
Conn Set at Report Generation: Citrix CNF Connection Set
CNF FSVeg Puller (RSW)
publication date
2022-09-07
Process Step for CNF FSVeg Puller (RSW):
Step Name: Pull FSVeg Data for Project
Step Type: RSW
Sequence: 1
Required: True
Minimum Inputs: 2
Is Distributed: N
Help ID: 290
Output Feature Template: CNF_FSVeg_Stand
Do not prompt user for selection: True
Each run has own output: False
Input Feature Template: FSVeg-Sp Vegetation Polygons
Feature Include Fields: (None)
Feature Join Field: SPATIAL_ID
Query Join Field: SPATIAL_ID
Dyn Seg Mode: None
Join Cardinality: OneToMany
Is Outer Join: False
Rt Bmp:
Rt Emp:
Query Name: qryRswPullFSVegDataforProject
Query will run on 'NRM Oracle FSVeg Sp Chippewa NF' connection in the current conn set.
SQL:
select vp.spatial_id,
vp.setting_id,
vp.region_proc,
vp.forest_proc,
vp.district_no,
vp.location,
vp.poly_id,
vp.acres stand_acres,
vp.num_exams,
q.nbr_plots,
vc.project_name,
extract(year from vp.SAMPLE_DATE) exam_date,
to_number(to_char(sysdate,'YYYY')) - to_number(to_char(vp.sample_date,'YYYY')) exam_age,
vp.purpose_code exam_purpose_code,
vc.ev_code,
ev.common_name ev_name,
vpl.VEGETATION_TYPE,
vc.year_of_origin Year_of_Origin,
to_number(to_char(sysdate,'YYYY')) - vc.year_of_origin Stand_Age,
vc.site_index,
vc.site_index_spp,
round(vc.basal_area,0) BA_GT1,
round(vc.dbh,0) DBH_QMD_GT1,
round(spp.Pole_BA,0) Pole_BA,
round(spp.Pole_DBH,0) Pole_DBH,
spp.Pole_DOM_SPP,
round(sps.Saw_BA,0) Saw_BA,
round(sps.Saw_DBH,0) Saw_DBH,
sps.Saw_DOM_SPP,
round(spm.Merch_BA,0) Merch_BA,
round(spm.Merch_DBH,0) Merch_DBH,
spm.Merch_DOM_SPP,
dams.cat1,
dams.agt1,
dams.sev1,
dams.cat2,
dams.agt2,
dams.sev2,
dams.cat3,
dams.agt3,
dams.sev3,
vpl.mngmnt_objective,
substr(vc.remarks, 1,255) Remarks,
vp.region_proc || vp.forest_proc || vp.district_no || vp.location || lpad(to_char(vp.poly_id),3,'0') stand_id
from s_r09_cnf.nris_vegpoly_aprv vp,
s_r09_cnf.nris_vegcharacterizations_aprv vc,
s_r09_cnf.nris_vegpolylinks_aprv vpk,
s_r09_cnf.nris_vegpolylocal_aprv vpl,
(select plt.setting_id, count(plt.plot_cn) nbr_plots
from nrv_plot_vm plt
where plt.archive_flag is null
and plt.region_admin = '09'
and plt.forest_admin = '03'
group by plt.setting_id ) q,
(select spatial_id,
BASAL_AREA As Pole_BA,
DIAMETER AS Pole_DBH,
DOMINANT_SPECIES AS Pole_DOM_SPP
from s_r09_cnf.nris_vegsubpopulations_aprv
where subgroup_1 = 'POLE TIMBER'
order by spatial_id) spp,
(select spatial_id,
BASAL_AREA As Saw_BA,
DIAMETER AS Saw_DBH,
DOMINANT_SPECIES AS Saw_DOM_SPP
from s_r09_cnf.nris_vegsubpopulations_aprv
where subgroup_1 = 'SAW TIMBER'
order by spatial_id) sps,
(select spatial_id,
BASAL_AREA As Merch_BA,
DIAMETER AS Merch_DBH,
DOMINANT_SPECIES AS Merch_DOM_SPP
from s_r09_cnf.nris_vegsubpopulations_aprv
where subgroup_1 = 'MERCH TIMBER'
order by spatial_id) spm,
(SELECT spatial_id,
MAX(DECODE(seq, 1, category_code, NULL)) cat1,
MAX(DECODE(seq, 1, agent_code, NULL)) agt1,
MAX(DECODE(seq, 1, severity_rating_code, NULL)) sev1,
MAX(DECODE(seq, 2, category_code, NULL)) cat2,
MAX(DECODE(seq, 2, agent_code, NULL)) agt2,
MAX(DECODE(seq, 2, severity_rating_code, NULL)) sev2,
MAX(DECODE(seq, 3, category_code, NULL)) cat3,
MAX(DECODE(seq, 3, agent_code, NULL)) agt3,
MAX(DECODE(seq, 3, severity_rating_code, NULL)) sev3
FROM (SELECT spatial_id,
category_code,
agent_code,
severity_rating_code,
row_number() OVER
(PARTITION BY spatial_id
ORDER BY spatial_id NULLS LAST) seq
FROM s_r09_cnf.nris_vegdisturbances_aprv)
WHERE seq <= 3
GROUP BY spatial_id) dams,
nrv_ev_cover_types ev
where
vp.spatial_id = vpk.spatial_id (+)
and vp.spatial_id = vc.spatial_id (+)
and vp.spatial_id = vpl.SPATIAL_ID (+)
and (vc.ev_ref_code = ev.ref_code (+) and vc.ev_code = ev.ev_code (+))
and vp.SETTING_ID = q.setting_id (+)
and vp.spatial_id = spp.spatial_id (+)
and vp.spatial_id = sps.spatial_id (+)
and vp.spatial_id = spm.spatial_id (+)
and vp.spatial_id = dams.spatial_id (+)
order by vp.spatial_id
Parameters (0):
2022-09-07
USDA Forest Service
CNF FSVeg Puller (RSW)
FSVeg-Sp Vegetation Polygons
withheld
publication date
2022-09-07
Resolved Query SQL:
select vp.spatial_id, vp.setting_id, vp.region_proc, vp.forest_proc, vp.district_no, vp.location, vp.poly_id, vp.acres stand_acres, vp.num_exams, q.nbr_plots, vc.project_name, extract(year from vp.SAMPLE_DATE) exam_date, to_number(to_char(sysdate,'YYYY')) - to_number(to_char(vp.sample_date,'YYYY')) exam_age, vp.purpose_code exam_purpose_code, vc.ev_code, ev.common_name ev_name, vpl.VEGETATION_TYPE, vc.year_of_origin Year_of_Origin, to_number(to_char(sysdate,'YYYY')) - vc.year_of_origin Stand_Age, vc.site_index, vc.site_index_spp, round(vc.basal_area,0) BA_GT1, round(vc.dbh,0) DBH_QMD_GT1, round(spp.Pole_BA,0) Pole_BA, round(spp.Pole_DBH,0) Pole_DBH, spp.Pole_DOM_SPP, round(sps.Saw_BA,0) Saw_BA, round(sps.Saw_DBH,0) Saw_DBH, sps.Saw_DOM_SPP, round(spm.Merch_BA,0) Merch_BA, round(spm.Merch_DBH,0) Merch_DBH, spm.Merch_DOM_SPP, dams.cat1, dams.agt1, dams.sev1, dams.cat2, dams.agt2, dams.sev2, dams.cat3, dams.agt3, dams.sev3, vpl.mngmnt_objective, substr(vc.remarks, 1,255) Remarks, vp.region_proc || vp.forest_proc || vp.district_no || vp.location || lpad(to_char(vp.poly_id),3,'0') stand_id from s_r09_cnf.nris_vegpoly_aprv vp, s_r09_cnf.nris_vegcharacterizations_aprv vc, s_r09_cnf.nris_vegpolylinks_aprv vpk, s_r09_cnf.nris_vegpolylocal_aprv vpl, (select plt.setting_id, count(plt.plot_cn) nbr_plots from nrv_plot_vm plt where plt.archive_flag is null and plt.region_admin = '09' and plt.forest_admin = '03' group by plt.setting_id ) q, (select spatial_id, BASAL_AREA As Pole_BA, DIAMETER AS Pole_DBH, DOMINANT_SPECIES AS Pole_DOM_SPP from s_r09_cnf.nris_vegsubpopulations_aprv where subgroup_1 = 'POLE TIMBER' order by spatial_id) spp, (select spatial_id, BASAL_AREA As Saw_BA, DIAMETER AS Saw_DBH, DOMINANT_SPECIES AS Saw_DOM_SPP from s_r09_cnf.nris_vegsubpopulations_aprv where subgroup_1 = 'SAW TIMBER' order by spatial_id) sps, (select spatial_id, BASAL_AREA As Merch_BA, DIAMETER AS Merch_DBH, DOMINANT_SPECIES AS Merch_DOM_SPP from s_r09_cnf.nris_vegsubpopulations_aprv where subgroup_1 = 'MERCH TIMBER' order by spatial_id) spm, (SELECT spatial_id, MAX(DECODE(seq, 1, category_code, NULL)) cat1, MAX(DECODE(seq, 1, agent_code, NULL)) agt1, MAX(DECODE(seq, 1, severity_rating_code, NULL)) sev1, MAX(DECODE(seq, 2, category_code, NULL)) cat2, MAX(DECODE(seq, 2, agent_code, NULL)) agt2, MAX(DECODE(seq, 2, severity_rating_code, NULL)) sev2, MAX(DECODE(seq, 3, category_code, NULL)) cat3, MAX(DECODE(seq, 3, agent_code, NULL)) agt3, MAX(DECODE(seq, 3, severity_rating_code, NULL)) sev3 FROM (SELECT spatial_id, category_code, agent_code, severity_rating_code, row_number() OVER (PARTITION BY spatial_id ORDER BY spatial_id NULLS LAST) seq FROM s_r09_cnf.nris_vegdisturbances_aprv) WHERE seq <= 3 GROUP BY spatial_id) dams, nrv_ev_cover_types ev where vp.spatial_id = vpk.spatial_id (+) and vp.spatial_id = vc.spatial_id (+) and vp.spatial_id = vpl.SPATIAL_ID (+) and (vc.ev_ref_code = ev.ref_code (+) and vc.ev_code = ev.ev_code (+)) and vp.SETTING_ID = q.setting_id (+) and vp.spatial_id = spp.spatial_id (+) and vp.spatial_id = sps.spatial_id (+) and vp.spatial_id = spm.spatial_id (+) and vp.spatial_id = dams.spatial_id (+) order by vp.spatial_id
qryRswPullFSVegDataforProject
publication date
2022-09-07
withheld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=