USDA Forest ServiceForest Inventory and Analysis

(FIA)

MRLC Land Characterization Partners Meeting

Nov. 7-8, 2000

OUTLINE

• Federal mandates that FIA more effectively use remote sensing

• FIA Business needs from satellite data• Classification detail• Classification accuracy• Geographic priorities• Information needed by FIA

Management Team

Federal mandates that FIA more effectively use remote

sensing• 1998 Farm Bill• White House Office of Science and

Technology, Committee on the Environment and Natural Resources

• RAND Corporation review of forest monitoring conducted by federal agencies

• FIA Staff Director Rich Guldin http://fia.fs.fed.us/library.htm - Papers

Improve consistency of data and process using a top down

approach• Consistent data is like a common

language

• Centralized data collection, documentation and dissemination

• Decentralized analyses and decision making

• Economies of scale

FIA Business needs from satellite data

• Stable, dependable and economical production of accurate and consistent forest cover and land use maps

• Cover entire USA every 3 to 10 years

• Adherence to Federal Geographic Data Committee (FGDC) standards

FIA Business needs from satellite data

• Automated image processing algorithms that require little human intervention– Product consistency and accuracy– Cost reduction– Timeliness– Diversity of geospatial products– Henry Ford analogy

FIA Business needs from satellite data

• Improve accuracy of FIA statistics– Improve statistical efficiency through

stratification on forest v. nonforest cover– Improve statistical estimates for small

geographic areas (e.g., counties) using remotely sensed ancillary data

FIA Business needs from satellite data

• Improve timeliness of statistics in annualized FIA– 10% - 15% of field plots re-measured each year– Remotely sensed data “refreshed” every 3 to 5

years– This is a goal, not an absolute design requirement– Could use change detection to update

forest/nonforest in a 10-year MRLC product

FIA Business needs from satellite data

• Change detection– Keep forest/nonforest map current to

maintain FIA statistical efficiency through stratification

• 2005 update to 2000 landcover map

– Better identify spatial patterns of change in broad landscapes

FIA Business needs from satellite data

• Change detection– Improve accuracy of FIA statistical

estimates for• Timber removals• Reforestation• Afforestation

FIA Business needs from satellite data

• Help provide 30-m/1:24,000 products to FIA customers– User-friendly data base for GIS analyses– Attractive maps for distribution– Spatial analysis tool box (internal and

external users)

FIA Business needs from satellite data

• Characterize context surrounding each FIA field plot that are not easily measured in field– Landscape fragmentation– Size and shape of forest stand – Distance to roads, surface waters, other

land uses (important components of wildlife habitat)

FIA Business needs from satellite data

• Substitute satellite data for 1:40,000 NAPP– Reduce cost of FIA stratification with Phase 1

plots (1-km grid)– Continue to provide imagery for navigation by field

crews– 15-m pan-sharpened Landsat 7– 10-m pan-sharpened SPOT– Superimpose ancillary geospatial data (DLG,

DEM, topos., etc.)– Downloadable to field crews (federal, state,

contractors)

FIA Business needs from satellite data

• Implementation schedule– Prototype products available for 10% -20%

of USA by September 2002– Production system functional by

September, 2003

FIA Business needs from satellite data

• New remotely sensed products in the future– Net primary productivity or photosynthesis rates– Tree mortality– Indicators of drought, acidic deposition, or pest

attack– Boundaries between different forest stands– Indicators of human infrastructure (e.g., individual

buildings)

FIA Business needs from satellite data

• Developers’ tools to implement a variety of spatial models with centralized database– Linkages to other geospatial databases (e.g.,

Census Bureau)– Sharing geomatic models– Facilitate local improvements to national map

products• Accuracy• Classification detail

Minimum spatial resolution

• 1-km pixel for global/national assessments• 250-m to 30-m pixel for regional assessments• FIA definition of forest requires 30-m scale• Special assessment needs require 30-m

scale (e.g., riparian management zones)• Functionality request:

– change spatial scale of data to balance assessment needs with technology

Classification detail

• Might need separate MRLC products for forest cover and timberland use

• Forest v. nonforest (most valuable for statistical efficiency through stratification)

Classification detail

• FIA definition for forest uses– 10% stocking, which can be applied with field data

but not directly with remotely sensed data– At least 1-acre and 120-foot wide– Includes non-stocked clearcuts and

seedling/sapling stands– Accuracy of remotely sensed classifications need

to be high, but not necessarily 100%

Classification detail

• FIA definition for nonforested land use includes– Urban and suburban areas with tree cover– tree stocking less than 10%

• Pasture with tree cover• Rangeland

Classification detail

• Broad forest types (global/national assessments)– Softwoods– Bottomland hardwoods– Upland hardwoods– Mixed hardwoods and softwoods

Classification detail More specific cover types

• Softwood forest – White-red-jack pine – Spruce-fir – Longleaf-slash pine – Loblolly-shortleaf pine – Douglas-fir– Hemlock-Sitka spruce – Ponderosa pine– Western white pine– Lodgepole pine– Larch– Fir-spruce– Redwood

• Upland hardwood forest– Oak-hickory – Maple-beech-birch – Aspen-birch– Western hardwoods

• Bottomland hardwoods– Oak-gum-cypress – Elm-ash-cottonwood

• Oak-pine • Woodland

– Chaparral– Pinyon-juniper

Classification detail

• Open v. closed stands

• Non-timber land use (e.g., urban with forest cover)

• Special categories– Forested wetlands– Mesquite– Krummholtz

Classification detail

• National Forest System needs for Map Product 2 (Forest Planning)– Cover Type

• 30-35 categories of forest• 6-10 categories of grass/forb/shrub types• 6 non-vegetated categories (rock, snow/ice,

etc.)

– Stand Size Class (5 categories)– Stand Crown Closure Class (4 categories)

Classification detail

• National Forest System needs for Map Product 2 (less detailed )– Cover Type

• 9 categories of forest• 4 categories of grass/forb/shrub types• 5 non-vegetated categories (rock, snow/ice,

etc.)

– Stand Size Class (2 categories)– Stand Crown Closure Class (3 categories)

Classification detail

• Need to agree on detailed description– Classification rules for each category– Devil is in the details

Classification Accuracy

• Forest v. nonforest 90% to 99% accuracy– Needed for stratification efficiency– Inaccuracies caused by FIA field-definition

of forest included with usual classification error

– No formal FIA accuracy standards for more detailed categorizations

– Known accuracy relative to FIA field data

Classification Accuracy

• National Forest System (Montana, Idaho) Map Product 2 (most detailed)– 60-65% overall for cover types

• at least 40% for any individual class

– 40% overall for stand size class– 60%-70% for stand density classes

Classification Accuracy

• National Forest System (Montana, Idaho) Map Product 3 (less detailed)– 75% overall for cover types

• at least 65% for any individual class

– 75% overall for stand size class– 75% for stand density classes

Timeliness

• Less than 5% net change in forest cover since date of imagery – stratification efficiency

• Less than 5 years old is desirable

Registration Accuracy

• Sufficient to link 1-acre FIA field plots to 30-m pixels

Geographic priorities Forest/non-forest mask September 2002

Geographic priorities Forest/non-forest mask September 2002• Maine• Iowa• Indiana• Minnesota• Missouri• Wisconsin• Utah• Arizona• Colorado• Oregon

• Alabama• Virginia• Georgia • Kentucky• South Carolina• Tennessee

Geographic priorities Forest/non-forest mask September 2003

• Arkansas• Louisiana• Tennessee• Texas

• Pennsylvania• Michigan• Puerto Rico• Hawaii

Information needed by FIA

• Cost to FIA for Part II of MRLC

Information needed by FIA

• Timing of coverage– Will MRLC land characterizations always

be 5 to 15 years out of date?– Can MRLC incorporate re-characterization

or change detection in between 10-year MRLC cycle?

Information needed by FIA

• Classification detail– Potential role of FIA in determining detail of

classification system– What decisions have already been made– What is on the table?– Need a thorough review of detailed classification

descriptions and rules– Can MRLC produce map of forest cover optimized

to FIA definitions of forest land use?– Consistency of MRLC and FGDC standards?