Interfacing R in a GIS environment for National Forest Systems

Transcription

1 Interfacing R in a GIS environment for National Forest Systems Tracey S. Frescino USDA, Forest Service, Interior-West, Rocky Mountain Research Station, Forest Inventory and Analysis, Ogden, Utah Kevin A. Halverson USDA, Forest Service, Intermountain Region, Region 4 Vegetation Information Management, Ogden, Utah

2 Main Goal Collaboration and Technology Transfer within USDA Forest Service National Forest System (NFS) Research and Development (R&D) NFS lands R&D regions

3 Objectives Define needs of NFS (Region 4) Present resources and tools available in Research (Interior-West, Rocky Mountain Station, Forest Inventory and Analysis (FIA) Program) Adapt resources and tools to accommodate NFS needs Design user-friendly interface for transferring technology

4 Overview of National Forest System

5 Region 4: Intermountain Region

6 National Forest Vegetation Information Needs Forest Planning Wildlife Habitat Wildfire Planning Hydrologic Timber Recreation Climate Adaptation Typical Variables Vegetation Dominance Type Canopy Cover Tree and Shrub Size Class Vegetation Structure Disturbance Biomass Habitat Type..

7 How the USFS Estimates Areas Vegetation Mapping Remote Sensing derived Interdisciplinary Effort Areas calculated using GIS Vegetation Sampled Inventory Field or Photo-interpreted Systematic and unbiased design Requirement of algorithms to apply area expansion factors for estimates

8 Maps use Sampled Data for Validation

9 FIA: Forest Inventory & Analysis National program to sample forest cover every five kilometers Pre-field phase is photo-based Field-sampled when certain criteria are met Maintains an Oracle Database filled with millions of records regarding plots Complex algorithms are used to summarize Plot locations are confidential. Public may only access fuzzed plot locations

10 FIA PLOTS* *Fuzzed FIA Plots are shown due to confidentiality of true locations

11 Mechanics of Calculation

12 Calculating Areas MAP: GIS Exercise FIA: Statistical Exercise Security Authentication Oracle Software Reports Vegetation Type Area (ac) Percent area Alpine Alpine Vegetation % Conifer Forest Conifer Mix 253, % Douglas-fir 1,303, % Douglas-fir/Lodgepole Pine 61, % Douglas-fir/Ponderosa Pine 37, % Lodgepole Pine 364, % Ponderosa Pine 69, % Spruce/Fir 207, % Whitebark Pine Mix 413, %

13 The Need: GIS Based Tools for FIA Tool Oracle Reports Vegetation Type Area (ac) Percent area Alpine Alpine Vegetation % Conifer Forest Conifer Mix 253, % Douglas-fir 1,303, % Douglas-fir/Lodgepole Pine 61, % Douglas-fir/Ponderosa Pine 37, % Lodgepole Pine 364, % Ponderosa Pine 69, % Spruce/Fir 207, % Whitebark Pine Mix 413, %

14 THE VISION: FIA Integration

15 THE ENTERPRISE VISION WEB-ENABLED SERVICES

16 Objectives Define needs of NFS (Region 4) Present resources and tools available in Research (Interior-West, Rocky Mountain Station, Forest Inventory and Analysis (FIA) Program) Adapt resources and tools to accommodate NFS needs Design user-friendly interface for transferring technology

17 17 USDA FIA Program Managed by the Research and Development organization with the USDA Forest Service. Originated from the McSweeney-McNary Forest Research Act of with the 1 st inventory starting in Monitor status and trends of the nation's forests with a continuous inventory of forest sample plots across the U.S., measured annually. Compile and maintain an extensive database of publically available resource data, including tree data, crown conditions, understory vegetation, down woody debris,...

18 USDA Research Units - FIA 18

19 19 USDA FIA Program Sample design Unbiased, semi-systematic, based on hexagons, and measured annually. Sample plot 4 subplots, 24ft-radius within ~1 acre (0.40 ha), representing ~ 6,000 ac (2,428 ha) of land.

20 FIA Population Estimates FIA Base Grid Tree biomass Canopy cover Trees per acre... Remotely-sensed Data Classified map - Strata Estimators Green-book Bechtold and Patterson 2005 Reports Species Number of Trees % Sample Error Total 36,709,907, white fir 695,859, corkbark fir 177,147, subalpine fir 3,273,455, Utah juniper 2,373,483, blue spruce 316,863, ,834,431,

21 21 FIA Standard Tools

22 FIA Current Requests Unique population boundaries. Different evalidation time periods (i.e. Annual). Customized stratification schemes. Non-standard estimation categories and filters (ex. NFS dominance types). Non-standard variance equations (ex. NonResponse). Supplementary inventory data (ex. photo-based inventory). Integration of remotely-sensed and other ancillary data. 22

23 FIESTA (Forest Inventory ESTimation for Analysts) We needed a flexible estimation engine.. That we can use to answer any question.. Using ancillary data we think is best.. Whenever we want. Frescino, T.S.; Patterson, P.L.; Freeman, E.A.; Moisen, G.G Using FIESTA, an R-based tool for analysts, to look at temporal trends in forest estimates. In: Morin, R.S.; Liknes, G.C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department 23 of Agriculture, Forest Service, Northern Research Station. [CD-ROM]:

24 24 What is FIESTA? An estimation tool developed at the Interior-West Forest Inventory and Analysis (FIA) program. Designed for analysts that work in the open-source, R statistical programming environment. A collection or package of R functions that can access FIA databases, summarize and compile plot and spatial data, and generate estimates of forest resource data. It is flexible, customizable, and interfaces with other R tools.

25 FIESTA - Structure Inventory Data (DB) (Oracle/Access) Spatial Tools (sp) Data Tools (dat) Modules (GB, SAE, PB..) Analysis Tools (an) Database tools (DB) query and extract data tables from FIA database (Oracle/Access). Data tools (dat) summarize and explore FIA data. Spatial tools (sp) manipulate and summarize spatial data. Modules (GB, PB, SAE, KF, MODA,..) different estimation strategies (ex. Green Book, Photo-based, etc.) Analysis tools (an) wrapper functions for analysts to stream-line estimation strategies. 25

26 FIESTA Green Book (GB) Module FIA data DBgetplots() Strata layer (Raster or Polygon) (plt, cond, tree, veg) spstrata() PLOTID STRATA Extract strata values to plots Calculate area by strata STRATA ACRES Tree/Per-acre (Ratio) Estimates? Area Estimates? Summarize FIA tree data to Plot- Condition-level (ex. Basal Area (BA), Volume,..) Calculate adjustment factors for nonsampled plots (ie. Hazardous,..) PLOTID TREE BA datsumtree() PLOTID STRATA BA_SUM Calculate estimates GBestArea() GBestTree() GBestRatio() 26

27 FIESTA Command Line R Designed for analysts that work in R programming environment. R command line Get FIA plot data dat <- anfiadata(states="utah", cur10yrs=true) plt <- dat$plt cond <- dat$cond tree <- dat$tree shp <- dat$shp_actual Some GUI dat <- () 27

28 28 FIESTA Command Line R command line Estimates estdat <- GBestTree(tree=tree, cond=cond, pltstrat=plt, stratalut=strlut, puniqueid="plt_cn", estvar="drybio_ag", estvar.tpa=true, estvar.filter="statuscd == 1", rowvar="fortypcd", colvar="stdszcd") est <- estdat$treeest estcv <- estdat$treecv

29 Objectives Define needs of NFS (Region 4) Present resources and tools available in Research (Interior-West, Rocky Mountain Station, Forest Inventory and Analysis (FIA) Program) Adapt resources and tools to accommodate NFS needs Design user-friendly interface for transferring technology

30 FIESTA NFS Prototype Salmon-Challis National Forest, ID Objective: Generate estimates of classified FIA plots using a customized stratification layer Vegetation Dominance Type Canopy Cover Tree and Shrub Size Class

31 FIESTA ArcMap Salmon-Challis NF 31

32 FIESTA ArcMap getfiadata Gets data from FIA DataMart (Includes FIA data tables and summarized tree data). - This data will then need to be classified by R4 folks to different types specific to them (i.e. Dominance types, Stand-size ) Note: - The coordinates from FIA DataMart have been fuzzed to protect the scientific integrity of the plot locations and privacy of landowners (on private land). - For obtaining actual plot coordinates, contact FIA Spatial Data Services (

33 FIESTA ArcMap getstratdata Gets stratification information from a specified stratification layer. Extracts values from spatial layer and calculates area (in acres) by strata. Output: csv file plots and attached strata value and csv file of area by strata.

34 FIESTA ArcMap getestarea Calculates area estimates (and variance of estimates) by specified category. Output: csv file with table of estimates (in acres) and % standard error. Estimated acres and standard error by fortypnm on all lands; Idaho; FORTYPNM Estimate Percent Standard Error Nonforest 1,179, Rocky Mountain juniper 6, Douglas-fir 1,320, Ponderosa pine 84, Engelmann spruce 27, Engelmann spruce / subalpine fir 190, Subalpine fir 328, Lodgepole pine 456, Limber pine 36, Whitebark pine 184, Cottonwood 5, Aspen 55, Cercocarpus (mountain brush) woodland 72, Nonstocked 403, Total 4,353,

35 FIESTA ArcMap getesttree Calculates total and per-acre estimates with known variance for specified tree attribute by specified category. Output: csv file with table of estimates (in acres) and % standard error. Estimates (Sample Error) of basal area (sqft) of live trees by fortypnm and stdsznm on forest land; Idaho; STDSZNM FORTYPNM Large diameter Medium diameter Small diameter Nonstocked Total Rocky Mountain juniper 660,792 (105.45) ,792 (105.45) Douglas-fir 104,962,609 ( 7.04) 9,592,253 ( 26.90) 2,563,987 ( 28.50) 0 117,118,849 ( 6.40) Ponderosa pine 5,078,598 ( 34.10) 0 221,969 (105.45) 0 5,300,568 ( 32.93) Engelmann spruce 2,879,731 ( 50.70) ,879,731 ( 50.70) Engelmann spruce / subalpine fir 19,192,389 ( 24.44) 1,245,683 ( 64.13) 1,417,876 ( 48.00) 0 21,855,949 ( 21.76) Subalpine fir 14,831,723 ( 23.16) 6,145,184 ( 33.00) 3,487,983 ( 34.27) 0 24,464,890 ( 16.30) Lodgepole pine 13,727,745 ( 26.92) 20,472,692 ( 19.25) 5,294,401 ( 33.28) 0 39,494,838 ( 13.49) Limber pine 4,826,881 ( 40.99) ,826,881 ( 40.99) Whitebark pine 10,693,609 ( 24.82) 1,000,607 ( 59.38) 1,513,961 ( 48.44) 0 13,208,178 ( 20.91) Cottonwood 0 605,049 (103.02) ,049 (103.02) Aspen 0 103,583 ( 98.52) 686,205 ( 50.71) 0 789,788 ( 49.72) Cercocarpus woodland 2,823,791 ( 44.47) 1,761,044 ( 58.77) 323,564 ( 65.74) 0 4,908,399 ( 29.22) Nonstocked ,286,327 ( 27.26) 1,286,327 ( 27.26) Total 179,677,869 ( 4.92) 40,926,095 ( 12.50) 15,509,947 ( 15.74) 1,286,327 ( 27.26) 237,400,238 ( 3.39)

36 FIESTA ArcMap link Necessary for configuration: ArcGIS Desktop v. >= 10.0 with Python support Install R ( Add file location (full path) of R executable path to Systems Environment variable Path (..or add a parameter to scripts)

37 FIESTA ArcMap link In Python: 1. Import subprocess module 2. Build process command cmd = "Rscript " + rscript + " " + args 3. Specify location of R executable and location of R script. 4. Execute command using subprocess.popen p = subprocess.popen(cmd, shell=true, stdout=subprocess.pipe, stderr=subprocess.stdout) 5. Write errors to screen errors = '' for line in p.stdout.readlines(): errors += line retval = p.wait()

38 FIESTA ArcMap link In R Script: 1. Load FIESTA package 2. Load R libraries necessary for FIESTA (RODBC, raster, sp, rgeos, maptools, rgdal, sqldf) 3. Get arguments from Python 4. Run FIESTA functions

39 Summary NFS, R&D Collaboration NFS needs include data and estimates (with known variance) for Forest Planning, wildlife habitat assessment, wildfire planning,... FIA has an extensive database of forest inventory data and an unbiased, design-based sample for estimation and variance. FIESTA is an R package developed by R&D with specific use with FIA data to generate area and total tree and per-acre estimates with known variances. ArcMap is a familiar, user-friendly interface to integrate FIESTA estimation tools with ArcMap's spatial manipulation tools.

40 FIESTA ArcMap Next Steps More sophisticated Python scripts Improve R-ArcMap interaction Design prettier user-interface Build ArcMap Add-in tool Get FIESTA package up to CRAN website Tech Transfer Web interface

41 CHEERS? 41