Instruction for preparing gisdaa or VLM
Guide pratique : Instruction for preparing gisdaa or VLM. Recherche parmi 300 000+ dissertationsPar hakimos • 16 Décembre 2016 • Guide pratique • 5 627 Mots (23 Pages) • 767 Vues
INSTRUCTIONS FOR PREPARING GISDATA FOR VLM
These instructions provide a step-by-step guide to preparing input GIS layers for version 5 of the VLM model (SELES). All input layers go in the gisdata folder.
Instructions are to create Arc ASCII files, which take a long time to load in SELES. Once created, it is recommended that each layer be opened in SELES and saved in the GRASS compressed format; this can be done simply through the File -> Save As menu in SELES.
Note: these instructions are based on the data from the 4e décennal SIFORT, but would be similar for 3e décennal.
General:
To Convert Polygon to ASCII in ArcGIS
- In Toolbox, select Convert Polygon to Raster
Value field = ageDominant //or whatever the value of interest
Cell assignment test = CELL_CENTER
Priority field = none
Cellsize = 50 //for 50m x 50m raster
- In Toolbox, select Convert Raster to ASCII. Resulting ASCII file will be .txt. Put it in the directory …gisdata/cell
- Open ASCII in Notepad and change commas (,) to periods (.) on lines 3 and 4 (beginning xllcorner and yllcorner)
- Open in SELES and save as grass compressed.
To create clipped ecoforestry map of the study area (UAF)
- Merge all appropriate c08PEEFO files and clip by study area
GISdata files needed:
Ecoregion
ageDominant
serievolGrouping
ManagementZone
UTR8 or UTR32
Drainage
Soils
Slopepercent
TreeSpp
AU
RoadState
Dist2ActiveRoad
NearestRoadSegmentLoc_all
NearestRoadSegment_all
RoadSegmentID
RoadBackbone
DistFromExit
Landunit
ageDominant:
Base file: clipped ecoforestry map (see above)
Field of interest: CAG_CO
This file consists of ages from 0 to 120. These are really 20-year age-classes (10, 30, 50, 70, 90, 120)
This field has ages of dominants and subdominants in one field. For example, CAG_CO = 3050 corresponds to AgeDominant = 30 and AgeSubdominant = 50.
Create a new column (AgeDominant) and extract the appropriate ages from CAG_CO. Note that JIRs and JINs were assigned an AgeDominant value of 30, while VIRs and JIRs were assigned an AgeDominant value of 45.
Convert polygon to ascii (see above) : ageDominant.txt.
Ecoregion:
Base file: clipped shapefile of ecoregions
Field of interest: field containing ecoregion names or codes
This file is a series of strings indicating bioclimatic regions (“domaines bioclimatiques”).
BoulotJaune = Sapinière à Bouleau jaune
BoulotBlanc = Sapinière à Bouleau blanc
Erabliere = Érablière à bouleau jaune
Pessiere = Pessière noire à mousse
Clip the study area out of a shapefile with ecoregions.
Create the appropriate field in a shapefile with ecoregions (i.e., an Ecoregion field where Sapinière à bouleau jaune is designated BoulotJaune, for example).
Convert polygon to ascii (see above) : ecoregion.txt.
slopePercent:
Base file: clipped ecoforestry map (see above)
Field of interest: CLP_CO
This file is a series of codes from 2 to 41, but there are really only 6 classes:
CLP_CO | Actual value | Value to be extracted to slopePercent |
A | 0-3% | 1 |
B | 3-8% | 6 |
C | 8-15% | 12 |
D | 15-30% | 23 |
E | 30-40% | 35 |
F & S | >= 41% | 41 |
Create a slopePercent field and assign values according to the above table (i.e., if CLP_CO = A, slopePercent = 1). Note that a table join can be used to do this quickly (join a table like the one above to the ecforestry data table by clp_co).
Convert polygon to ascii (see above) : slopePercent.txt.
Drainage:
Base file: clipped ecoforestry map (see above)
Field of interest: CDR_CO
This file is a series of codes from 2 to 16.
CDR_CO | Actual value (defined for 3e décennal) | VLM legend value for drainage | Value to be extracted to drainage |
00 | Excessif | dVeryRapidExcessiveDrainage | 10 |
10 | Rapide | dRapidDrainage | 4 |
11 | Rapide drainage lateral | dRapidLateralDrainage | 16 |
12 | Rapide horizon gelé | dRapidSolidHorizon | 4 |
16 | Drainage complexe | dModerate | 7 |
20 | Bon | dGood | 8 |
21 | Bon drainage lateral | dGoodLateralDrainage | 14 |
22 | Bon horizon gelé | dGoodSOlidHorizon | 8 |
30 | Modéré | dModerate | 7 |
31 | Modéré drainage latéral | dModerateLateralDrainage | 13 |
32 | Modéré horizon gelé | dModerateSolidHorizon | 15 |
33 | Modéré amelioration d’origine anthropique | dModerate | 7 |
40 | Imparfait | dImperfect | 5 |
41 | Imparfait drainage latéral | dImperfectLateralDrainage | 11 |
42 | Imparfait horizon gelé | dImperfectSolidHorizon | 20 |
43 | Imparfait amelioration d’origine anthropique | dImperfect | 5 |
44 | Imparfait ralentissement d’origine anthropique | dImperfect | 5 |
50 | Mauvais | dPoor | 3 |
51 | Mauvais drainage latéral | dPoorLateralDrainage | 6 |
53 | Mauvais amelioration d’origine anthropique | dPoor | 3 |
54 | Mauvais avec ralentissement d'origine anthropique | dPoor | 3 |
60 | Très mauvais | dVeryPoor | 2 |
61 | Très mauvais drainage lateral | dVeryPoorLateralDrainage | 12 |
62 | Très mauvais horizon gelé | dVeryPoorSolidHorizon | 9 |
Create a slopePercent field and assign values according to the above table (i.e., if CDR_CO = 00, drainage = 10).
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