Normalized Difference Fraction Index (NDFI): a new spectral index for enhanced detection of forest canopy damage caused by selective logging and forest fires

Carlos Souza Jr., ImazonDar Roberts, UCSB

Mark Cochrane, USDSamia Nunes, Imazon

Deforestation vs Forest Degradation

Creates a complex environment: Undisturbed forests Canopy gaps Exposed soils Dead vegetation

Caused by: Selective logging Forest fires Forest fragmentation

Souza Jr. and Roberts (2005) - IJRS

Ikonos Image – Paragominas, PA

Very Challenge with Landsat!

Selective logging

1998

1999

Old Selective logging

Selective logging and burning

2000

2001 Old selective logging andburning

Souza Jr. et al. (2003), Rev. Ciência Hoje

Objective

Develop a technique that combines spectral and spatial information to enhance the detection and mapping of canopy damage caused by selective logging and forest fires

New spectral index: Normalized Difference Spectral Index (NDFI)

Contextual classification algorithm (CCA) Spectral: NDFI Spatial: log landings

Forest Transect Classes

Forest class Field Description

Intact(n=4)

Mature and undisturbed forest

Non-mechanized logging(n=5)

Logged forest without the use of vehicles such as skidders and trucks, also known as traditional logging. Log landings, roads and skid trails are not built.

Managed logging(n=5)

Planned selective logging where a tree inventory is conducted, followed by road and log landing planning to reduce harvesting impacts.

Conventional Logging(n=2)

Conventional unplanned selective logging using skidders and trucks. Log landings, roads and skid trails are built.

Logged and burned(n=3)

Either non-mechanized or conventionally logged forests that have subsequently been damaged by intense surface fires.

Deg

rad

atio

n In

ten

sity

Souza Jr. et al. (2005), Earth Interactions

Forest Transects

Forest inventories Transects (10 m x 500 m = 0.5 ha)

Trees with DBH ≥ 10 cm Sub-plots (10 m x 10 m)

All trees Forest canopy cover Vine density % soil exposed % of dead vegetation

Aboveground biomass estimation Allometric equations (Gerwing, 2000)

Objective I

0

10

20

30

40

50

60

Intact Non-mechanizedLogging

ManagedLogging

ConventionalLogging

Logged andBurned

Fra

cti

on

Va

lue

(%

)

GV NPV Shade Soil

SMA Fraction Images

Forest Degradation Separability

Souza Jr. et al. (2005), Earth Interactions

Normalized Difference Fraction Index

SoilNPVGV

Soil)(NPVGVNDFI

Shade

Shade

Shade100

GVGVShade

-1 ≤ NDFI ≤1

NDFI low to moderate

NDFI near 1

High GVLow NPV and Soil

Low to moderate GVModerate to high NPV and Soil

Souza Jr. et al. (2005), RSE

SMA ResultsGVshade

NPV

Soil

NDFI

Fraction Value (%)

Fraction Value (%) Fraction Value (%)

NDFI

Souza Jr. et al. (2005), RSE

-20

-15

-10

-5

0

5

10

Non-mechanized

Logging

ManagedLogging

Logged Logged andBurned

Ch

an

ge

fro

m I

nta

ct

Fo

res

t (%

)

GV

NPV

Soil

Shade

NDFI % Change

NDFI vs. Fraction Images

Percent Change from Intact Forest

Souza Jr. et al. (2005), RSE

Class Separability

ClassClassIntactIntact

Non-Non-mechanized mechanized

LoggingLogging

Managed Managed LoggingLogging

Conventional Conventional LoggingLogging

Logged and Logged and BurnedBurned

Mean Stdev. Mean Stdev. Mean Stdev. Mean Stdev. Mean Stdev.

GVGV 40a 4 41a 5 41a 5 38b 9 25c 7

NPVNPV 6a 2 5a 2 6a 2 10bc 4 11bd 3

SoilSoil 2a 1 1a 1 3ab 1 4bc 3 7d 3

ShadeShade 51a 3 53a 5 51ab 4 49bc 3 56d 3

NDFINDFI 0.84a 0.08 0.87a 0.07 0.79b 0.07 0.58c 0.24 0.49d 0.22

Tukey test at P<0.01

Souza Jr. et al. (2005), RSE

Contextual Classification Algorithm - CCA

Step 1: Find log landingsStep 1: Find log landingsSoil > 10%Soil > 10%Find regions and calculate areaFind regions and calculate area1 ≤ Area ≤ 4 pixels1 ≤ Area ≤ 4 pixels

Step 2: Grow a canopy damage region around log Step 2: Grow a canopy damage region around log landingslandings Search for NDFI neighboring cell valuesSearch for NDFI neighboring cell values

If NDFI > 0.75 then If NDFI > 0.75 then Intact ForestIntact Forestif 0 if 0 ≤≤ NDFI ≤ 0.75 then NDFI ≤ 0.75 then Canopy DamageCanopy Damage

SoilFraction

LogLandings

CanopyDamage

CCA ResultsC

on

ven

tio

nal

Lo

gg

ing

Lo

gg

ed a

nd

B

urn

ed

NDFI Canopy Damage

Accuracy Assessment

ClassifiedPixels

Reference Pixels

Users Accuracy

(%)Non-forestNon-forest ForestForestCanopy Canopy DamageDamage Total

Non-Forest 454 0 17 471 96.4

Forest 6 625 117 748 83.6

Canopy Damage 40 0 616 656 93.993.9

Total 500 625 750 1875

Producers Accuracy (%) 91.0 100.0 82.0

Overall Accuracy = (1695/1875) = 90.4%90.4% Kappa Coefficient = 0.85

Generic Image Endmembers

Objective IV

Standardized Fractions and NDFIa) Paragominas,Pará State - 223/62

Soil

GV NDFI

NPV

Objective IV

b) Santarém, Pará State - 227/62

Soil

GVShade NDFI

NPV

Standardized Fractions and NDFI

Objective IV

c) Ji-paraná, Rondônia State - 231/67

Soil

GVshade NDFI

NPV

Standardized Fractions and NDFI

Objective IV

StandardizedNDFI (2001)

Rondônia

N

StandardizedNDFI (2001)

Summary

NDFI enhances the detection and mapping of degraded forests and performs better than any individual fraction.

CCA can unambiguously map canopy damage due to selective logging and forest fires.

These techniques can be applied over the Amazon region.