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Instruction for preparing gisdaa or VLM

Guide pratique : Instruction for preparing gisdaa or VLM. Recherche parmi 231 000+ dissertations

Par   •  16 Décembre 2016  •  Guide pratique  •  5 627 Mots (23 Pages)  •  151 Vues

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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

  1. 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

  1. In Toolbox, select Convert Raster to ASCII. Resulting ASCII file will be .txt. Put it in the directory …gisdata/cell
  2. Open ASCII in Notepad and change commas (,) to periods (.)  on lines 3 and 4 (beginning xllcorner and yllcorner)
  3. Open in SELES and save as grass compressed.

To create clipped ecoforestry map of the study area (UAF)

  1. 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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