land area change in coastal louisiana from 1932 …...3 u.s. department of the interior u.s....

3

U.S. Department of the InteriorU.S. Geological Survey

Pamphlet to accompanyScientific Investigations Map 3164

Land Area Change in Coastal Louisiana from 1932 to 2010

By Brady R. Couvillion, John A. Barras, Gregory D. Steyer, William Sleavin, Michelle Fischer, Holly Beck, Nadine Trahan, Brad Griffin, and David Heckman

i

U.S. Department of the InteriorU.S. Geological Survey

Pamphlet to accompanyScientific Investigations Map 3164


U.S. Department of the InteriorKEN SALAZAR, Secretary

U.S. Geological SurveyMarcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

This and other USGS information products are available at http://store.usgs.gov/U.S. Geological SurveyBox 25286, Denver Federal CenterDenver, CO 80225

To learn about the USGS and its information products visit http://www.usgs.gov/1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report.

Suggested citation:Couvillion, B.R.; Barras, J.A.; Steyer, G.D.; Sleavin, William; Fischer, Michelle; Beck, Holly; Trahan, Nadine; Griffin, Brad; and Heckman, David, 2011, Land area change in coastal Louisiana from 1932 to 2010: U.S. Geological Survey Scientific Investigations Map 3164, scale 1:265,000, 12 p. pamphlet.

iii

Contents

Abstract ..........................................................................................................................................................1Introduction.....................................................................................................................................................1Methodology ..................................................................................................................................................1Land Area Changes ......................................................................................................................................4Land Change Trends .....................................................................................................................................5Discussion and Conclusions .......................................................................................................................5References ...................................................................................................................................................12

Figures1. Map of the study area in coastal Louisiana ............................................................................32. Land area in coastal Louisiana, 1932 to 2010 ...........................................................................43. Persistent land loss and land gain in coastal Louisiana by period

and by basin for 1932–2010 ..........................................................................................................84. Persistent land loss and land gain coastwide across Louisiana by

period for 1932–2010 ....................................................................................................................95. Linear regressions of land area change trends coastwide across

Louisiana, 1985–2010 .................................................................................................................106. Linear regressions of land area change trends in coastal Louisiana

by hydrologic basin, 1985–2010 ...................................................................................................11

Tables1. Land area in coastal Louisiana by basin, 1932–2010 ..............................................................22. Water levels at selected gages on the date of acquisition for imagery

used in the land area estimates ................................................................................................5 3. Persistent land loss and land gain in coastal Louisiana by basin, 1932–2010 ...................6

New

Orle

ans

Mis

siss

ippi

Loui

sian

a

Texas Lou

isiana

Cam

eron

Lake

Pon

tcha

rtrai

n

Big

Mar

Lake

Mau

repa

s

Lake

Sal

vado

r

Bara

taria

Bay

Tim

balie

r Ba

y

Terre

bonn

e Ba

y

Caill

ou L

ake

Lake

Mec

hant

Lake

Bou

drea

ux

Littl

e La

ke

Atch

afal

aya

Bay

Gulf

of M

exic

o

Lake

Cat

aoua

tche

Atcha

falaya River

Lake Borgne

East

Cot

e Bl

anch

e Ba

y

Wes

t Cot

e Bl

anch

e Ba

y

Verm

ilion

Bay

Whi

te L

ake

Gran

d La

ke

Calc

asie

uLa

ke

Blac

k L

ake

Freshwater Bayou

Wax Lake Outlet

Mar

shIs

land

Lake PontchartrainCauseway

Gulf

Intra

coas

tal W

ater

way

Gulf

Intra

coas

tal W

ater

way

Gulf I

ntrac

oasta

l Wate

rway

Mississ

ippi R

iver-G

ulf Outl

et Ca

nal

Mississ

ippi

Riv

er

Mississippi River

Mississ

ippi R

iver

Southwest Pass

South P

ass

Pass

a Lo

utre

East

Bay

Wes

t Bay

Gard

enIs

land

Ba

y

Bayou Lafourche

Labr

anch

e w

etla

nds

Calcasieu Ship Channel

Swee

t L

ake

Bret

on S

ound

Lake

Felic

ity

Gulf

of M

exic

o

Gulf of

Mexi

co

Calc

asie

u-Sa

bine

Bas

in

Chan

dele

ur S

ound

Chandeleur Islands

Tech

e-Ve

rmili

on

Bas

in

Atc

hafa

laya

D

elta

Bas

in

Terr

ebon

ne B

asin

Bar

atar

ia B

asin

Mis

siss

ippi

Riv

er

Del

ta B

asin

Bre

ton

Soun

dB

asin

Pont

char

trai

nB

asin

Lac

des

Alle

man

ds

Upl

ands

(>10

m)

Upl

ands

(>10

m)

Upl

ands

(>10

m)

Upl

ands

(>10

m)

Gulf

of M

exic

o

Hack

berry

John

sons

Bay

ouGr

and

Chen

ier

Wax

Lak

e De

lta

Atch

afal

aya

Delta

Mor

gan

City

Intra

coas

tal

City

Peca

nIs

land

Houm

a

Thib

odau

x

Gold

enM

eado

w

Port

Four

chon

Laro

se

Mon

tegu

t

Dula

c

Ther

iot

Amel

ia

Cut O

ff

Lake

Cha

rles

Sulp

hur

Vint

on

Iow

aW

elsh

Jenn

ings

Crow

ley

Rayn

e

Lafa

yette

New

Iber

ia

Jean

eret

te

Abbe

ville

Fran

klin

Dona

ldso

nvill

e

Whi

te

Cast

le

Plaq

uem

ine

Port

Alle

nBa

ton

Roug

e

Slid

ell

Man

devi

lle

Covi

ngto

n

Ponc

hato

ula

Gonz

ales

Lake

Ve

rret La

ke

Palo

urde

Flat

Lake

Lake

Fa

usse

Poi

nte

The

Pen

Brea

ux B

ridge

Redf

ish

Bay

Blin

dBa

y

Quar

antin

eBa

y

Adam

sBa

y

Bast

ian

Bay

Lost

Lak

eFo

ur L

eagu

eBa

y

Bayou Perot

Bayou Rigolettes

Gran

dLa

ke

Lake

De

Cade

Lake

Sain

t Cat

herin

e

Sabi

neLa

ke

Mer

men

tau

Basi

n

Lake

Ler

y

Scal

e 1:

265,

000

100

1020

3040

5K

ilom

eter

s

100

1020

3040

5M

iles

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)Up

land

s5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)Up

land

s5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Basi

n bo

unda

ry

1 Gain

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

wat

er to

land

and

rem

aine

d la

nd th

roug

hout

the

perio

d of

obs

erva

tion.

2 Loss

is d

eter

min

ed b

y the

last

dat

e a

parti

cula

r pixe

l tra

nsiti

oned

from

land

to w

ater

and

rem

aine

d w

ater

thro

ugho

ut th

e pe

riod

of o

bser

vatio

n.

EXPL

ANAT

ION

1977

–85

land

gai

n1,4

1932

–56

land

gai

n1

1956

–73

land

gai

n1,4

1973

–75

land

gai

n1,4

1975

–77

land

gai

n1,4

1990

–95

land

gai

n1

1985

–88

land

gai

n1

1988

–90

land

gai

n1

2004

–6 la

nd g

ain1

1995

–98

land

gai

n1

1998

–99

land

gai

n1

1999

–200

2 la

nd g

ain1

1977

–85

land

loss

2,4

1932

–56

land

loss

2

1956

–73

land

loss

2,4

1973

–75

land

loss

2,4

1975

–77

land

loss

2,4

1990

–95

land

loss

2

1985

–88

land

loss

2

1988

–90

land

loss

2

2004

–6 la

nd lo

ss2

1995

–98

land

loss

2

1998

–99

land

loss

2

1999

–200

2 la

nd lo

ss2

2006

–8 la

nd g

ain1

2008

–9 la

nd g

ain1,

3

2006

–8 la

nd lo

ss2

2008

–9 la

nd lo

ss2,

3

Deve

lope

d5

3 Beca

use

this

date

rang

e ha

s onl

y one

end

ing

data

set,

som

e of

thes

e ef

fect

s may

be

tem

pora

ry p

heno

men

a.4 Th

is da

te ra

nge

cont

ains

at l

east

one

dat

e in

whi

ch th

e la

nd/w

ater

dat

a w

ere

crea

ted

from

Land

sat M

ultis

pect

ral S

cann

er S

yste

m (M

SS).

2002

–4 la

nd g

ain1

2002

–4 la

nd lo

ss2

5 Land

cov

er c

ateg

orie

s bas

ed o

n 20

08 d

ata.

“Per

siste

nt” i

s def

ined

as n

ot h

avin

g un

derg

one

a co

nsist

ent c

hang

e in

land

/wat

er c

ateg

ory d

urin

g t

he o

bser

vatio

n pe

riod.

2009

–10

new

land

1,3

2009

–10

new

wat

er2,

3

Upla

nds5

Pers

iste

nt f

ores

ted

wet

land

5

Pers

iste

nt w

ater

Pers

iste

nt w

etla

nd5

Deve

lope

d5

Back

grou

nd im

ager

y(o

utsi

de m

odifi

ed C

oast

al Z

one

Boun

dary

)

Back

grou

nd im

ager

y (in

side

mod

ified

Coa

stal

Zon

e Bo

unda

ry)

By Brady R. Couvillion, John A. Barras, Gregory D. Steyer, William Sleavin, Michelle Fischer, Holly Beck, Nadine Trahan, Brad Griffin, and David Heckman

AbstractCoastal Louisiana wetlands make up the seventh largest

delta on Earth, contain about 37 percent of the estuarine herbaceous marshes in the conterminous United States, and support the largest commercial fishery in the lower 48 States. These wetlands are in peril because Louisiana currently undergoes about 90 percent of the total coastal wetland loss in the continental United States. Documenting and understanding the occurrence and rates of wetland loss are necessary for effective planning, protection, and restoration activities.

The analyses of landscape change presented in this report use historical surveys, aerial data, and satellite data to track landscape changes. Summary data are presented for 1932–2010; trend data are presented for 1985–2010. These later data were calculated separately because of concerns over the comparability of the 1932 and 1956 datasets (which are based on survey and aerial data, respectively) with the later datasets (which are all based on satellite imagery).

These analyses show that coastal Louisiana has undergone a net change in land area of about -1,883 square miles (mi2) from 1932 to 2010. This net change in land area amounts to a decrease of about 25 percent of the 1932 land area. Persistent losses account for 95 percent of this land area decrease; the remainder are areas that have converted to water but have not yet exhibited the persistence necessary to be classified as “loss.” Trend analyses from 1985 to 2010 show a wetland loss rate of 16.57 mi2 per year. If this loss were to occur at a constant rate, it would equate to Louisiana losing an area the size of one football field per hour.

The use of 17 datasets plus the application of consistent change criteria in this study provide opportunities to better understand the timing and causal mechanisms of wetland loss that are critical for forecasting landscape changes in the future.

IntroductionThe U.S. Geological Survey (USGS) analyzed landscape

changes in coastal Louisiana by determining land and water classifications for 17 datasets. These datasets include survey data from 1932, aerial data from 1956, and Landsat

Multispectral Scanner System (MSS) and Thematic Mapper (TM) data from the 1970s to 2010. Previous studies have analyzed land change in coastal Louisiana, but many are out of date, provide data for limited time periods, or lack the temporal frequency necessary to provide information about when the loss occurred. The purpose of this study is to provide updated estimates of persistent land change and historical land change trends for coastal Louisiana and for each hydrologic basin, as defined by the Coastal Wetlands Planning, Protection and Restoration Act Program (n.d.), for the 1932–2010 period of record. The use of 17 datasets plus the application of consistent change criteria in this study provide opportunities to better understand the timing and causal mechanisms of wetland loss that are critical for forecasting landscape changes in the future.

MethodologyThis study analyzed changes in the extent of land in

coastal Louisiana by using 17 datasets summarizing land and water areas from 1932 to 2010 (table 1). The datasets were derived from multiple sources including (1) historical survey data (1932); (2) National Wetlands Inventory (NWI) data based on aerial photography (1956); (3) Landsat Multi-Spectral Scanner (MSS) data (1973–79); and (4) Landsat Thematic Mapper (TM) satellite imagery classified into land and water categories (1985–2010). Variable data coverage among the 1932 and 1956 datasets and all subsequent data required an assumption of no change in the area of no data coverage (areas with no overlap) in those datasets. No change is assumed in land area from 1932 to 1956 and from 1956 to 1973 in portions of the dataset that occur outside the boundaries of the 1932 and 1956 data coverage. (Refer to figure 1 for more information regarding the areas within the coastal basins to which this assumption was applied.)

The areas missing from the 1932 and 1956 datasets mostly consist of forested wetlands. These areas are historically stable, so the assumption of “no change” is correct in most instances; however, the area and change summaries should only be used with an in-depth understanding of the impacts of this assumption in areas where there are no data in 1932 and 1956.


2 Land Area Change in Coastal Louisiana from 1932 to 2010

Tabl

e 1.

La

nd a

rea

in c

oast

al L

ouis

iana

by

basi

n, a

s de

fined

by

the

Coas

tal W

etla

nds

Plan

ning

, Pro

tect

ion

and

Rest

orat

ion

Act P

rogr

am (n

.d.)

, 193

2–20

10.

[Lan

d ar

ea in

squ

are

mile

s. D

ates

are

app

roxi

mat

e av

erag

es o

f im

ager

y us

ed f

or v

ario

us p

ortio

ns o

f th

e co

ast.

Are

a es

timat

es a

re k

now

n to

be

high

ly in

flue

nced

by

wat

er le

vels

on

the

date

of

acqu

isiti

on

of th

e im

ager

y. R

efer

to ta

ble

2 fo

r w

ater

leve

l inf

orm

atio

n]

Dec

imal

dat

e1B

asin

Atc

hafa

laya

D

elta

Bar

atar

iaB

reto

n So

und

Calc

asie

u-Sa

bine

Mer

men

tau

Mis

siss

ippi

Ri

ver D

elta

Pont

char

trai

nTe

che-

Ve

rmili

onTe

rreb

onne

Coas

twid

e

1932

221

2.58

1,47

9.78

427.

6382

4.99

958.

2726

2.07

1,10

5.19

548.

941,

726.

487,

545.

92

1956

219

7.57

1,38

2.60

376.

0781

0.52

918.

7824

1.82

1,03

8.25

520.

241,

618.

437,

104.

28

1973

.919

7.04

1,33

9.06

395.

0869

1.40

888.

9480

.34

1,02

9.61

529.

781,

598.

436,

749.

68

1975

.721

0.52

1,22

4.77

347.

7669

7.76

902.

9594

.27

999.

0852

8.12

1,52

9.68

6,53

4.90

1977

.419

0.51

1,29

7.88

356.

4959

1.98

799.

8913

8.71

993.

7250

0.33

1,39

6.13

6,26

5.65

1985

.118

6.80

1,14

9.74

333.

8761

5.44

780.

5412

1.63

979.

2249

2.36

1,32

5.53

5,98

5.12

1988

.120

5.89

1,17

0.51

339.

8663

6.36

785.

7612

9.06

991.

1948

7.43

1,39

3.58

6,13

9.65

1990

.819

8.92

1,10

4.10

313.

0065

9.23

835.

7113

7.99

970.

8747

7.91

1,32

2.58

6,02

0.31

1995

.722

5.18

1,02

6.72

292.

1763

7.31

849.

7713

6.91

934.

5147

6.86

1,26

3.14

5,84

2.57

1998

.218

0.94

1,09

2.40

313.

3359

6.14

738.

0411

4.04

961.

9948

4.70

1,26

6.84

5,74

8.43

1999

.923

1.23

1,05

5.72

300.

2664

4.40

834.

0315

2.01

946.

9148

9.33

1,27

0.68

5,92

4.58

2002

.221

1.68

1,08

2.12

304.

5862

9.88

781.

1913

3.59

944.

5848

5.88

1,29

4.11

5,86

7.61

2004

.921

8.90

1,04

8.56

295.

8765

4.05

816.

4811

9.02

936.

7147

4.31

1,25

3.01

5,81

6.89

2006

.821

3.99

1,03

5.94

264.

1062

5.14

731.

2910

5.98

912.

3347

7.43

1,24

1.69

5,60

7.89

2008

.820

3.15

1,01

6.36

240.

4058

0.23

727.

7011

3.74

900.

9846

4.57

1,20

4.62

5,45

1.75

2009

.821

9.35

1,01

0.85

242.

5056

8.86

731.

0310

8.69

903.

2347

0.82

1,20

4.45

5,45

9.78

2010

.822

9.31

1,02

4.19

253.

4061

1.42

803.

0913

8.03

910.

9647

1.57

1,22

0.73

5,66

2.71

1 Dec

imal

dat

ing

is a

mor

e sp

ecif

ic d

atin

g sy

stem

than

the

cale

ndar

yea

r an

d is

use

d to

fac

ilita

te s

tatis

tical

ana

lyse

s. I

t is

deri

ved

by d

ivid

ing

the

day

of th

e ye

ar (

in th

e Ju

lian

syst

em)

by th

e nu

mbe

r of

d

ays

in th

e ye

ar.

2 Cal

enda

r da

tes

wer

e no

t ava

ilabl

e.

Methodology 3

Path

24

Path

23

Path

22

Path

21

Mis

sing

from

193

2 da

ta: 1

,115

mi2 w

ithin

mod

ified

Coa

stal

Zon

e Bo

unda

ryM

issi

ng fr

om 1

956

data

: 920

mi2

with

in m

odifi

ed C

oast

al Z

one

Boun

dary

Mis

sing

from

193

2 an

d 19

56 d

ata:

577

mi2

with

in m

odifi

ed C

oast

al Z

one

Boun

dary

EXPL

ANAT

ION

Mod

ified

Coa

stal

Zon

e Bo

unda

ry: 1

4,58

7 m

i2Do

mai

n sh

own:

22,

895

mi2

Land

sat W

orld

wid

e Re

fere

nce

Syst

em-2

(WRS

-2)

Excl

uded

from

dom

ain

(sho

wn

for r

efer

ence

pur

pose

s on

ly)

Upla

nds

(>10

m)

Upla

nds

(>10

m)

Figu

re 1

. M

ap o

f the

stu

dy a

rea

in c

oast

al L

ouis

iana

. The

coa

stal

zone

bou

ndar

y w

as m

odifi

ed to

impr

ove

the

cons

erva

tion

plan

bou

ndar

y. T

he c

onse

rvat

ion

plan

bo

unda

ry d

elin

eate

s th

e zo

ne fo

r whi

ch s

tatis

tics

wer

e ca

lcul

ated

and

isol

ates

coa

stal

regi

ons

whi

le e

xclu

ding

fast

land

s (d

efin

ed a

s de

velo

ped,

agr

icul

tura

l, an

d ot

her p

rote

cted

are

as) f

rom

sta

tistic

al a

naly

sis

of c

oast

al la

nd c

hang

e. O

f par

ticul

ar n

ote

are

the

area

s of

non

-ove

rlapp

ing

data

cov

erag

e in

the

1932

and

195

6 da

tase

ts (b

ased

on

surv

ey a

nd a

eria

l dat

a) a

nd in

the

1973

–201

0 da

tase

ts (b

ased

on

sate

llite

imag

ery

data

). Be

caus

e no

dat

a ex

ist f

or th

ese

non-

over

lapp

ing

area

s, a

n as

sum

ptio

n of

no

chan

ge in

thos

e ar

eas

has

been

use

d fo

r tho

se ti

me

perio

ds in

the

anal

yses

(a re

ason

able

ass

umpt

ion

sinc

e a

maj

ority

of t

hese

dat

a vo

ids

occu

rs

in a

reas

dom

inat

ed b

y fo

rest

ed w

etla

nds,

a h

abita

t typ

e kn

own

to h

ave

been

par

ticul

arly

sta

ble

in p

ast o

bser

vatio

ns).

The

back

grou

nd im

age

is s

how

n fo

r ref

eren

ce

purp

oses

to a

nor

ther

n bo

unda

ry d

elin

eate

d by

the

10-m

ele

vatio

n co

ntou

r (re

fere

nced

to th

e N

orth

Am

eric

an V

ertic

al D

atum

of 1

988

[NAV

D 88

]).


Preprocessing of all datasets included use of ERDAS IMAGINE AutoSync (ERDAS Inc., Norcross, Ga.), a software that uses an automated process to align common landform features between images. To assess change, the geometric registration between datasets must be highly accurate. Misalignment of features at the same location could produce invalid land change results. This processing step was critical in ensuring that the 1932 and 1956 data aligned with the later satellite-based data. The Landsat MSS data (1973, 1977, and 1979), which have a native 60-meter (m) resolution, were first resampled to a 30-m resolution by using a cubic convolution resampling method to facilitate comparability with later Landsat TM-based data (native 30-m resolution). Conducting this resampling prior to land-water classification is more appropriate than resampling the results of the land-water classification. All satellite imagery data were then classified into land/water categories by using a standard methodology similar to that used in previous studies (Barras, 2006, 2007; Barras and others, 2008).

The methodology used in this study relied heavily on the use of the near infrared band of Landsat data (MSS: Band 7; TM: Band 5) in the early stages of classification. Near infrared (NIR) was selected because the wavelengths in this range, 1.55–1.75 micrometers, are particularly informative and discriminatory with regard to land and water categories. Supervised and unsupervised classification was then used to account for areas that may be incorrectly classified by the NIR band alone. Areas that need further attention for accurate classification commonly include highly turbid water areas and floating aquatic vegetation. These areas were manually recoded to their appropriate land/water categories by expert analyses.

Land Area Changes The resulting land area

data were summarized by time period and by basin (table 1 and fig. 2). These analyses show that coastal Louisiana has experienced a net change in land area of approximately -1,883 mi2 from 1932 to 2010. Land area estimates can vary substantially because of environmental variations such

as seasonality and, most notably, water-level variations on the date of acquisition (DOA) of the data (Morton and others, 2005; Bernier and others, 2006). (Refer to table 2 for more information regarding the water levels on the DOA for the data used in these analyses.) To reduce some of the errors associated with apparent land change caused by misclassification or transient environmental phenomena, two approaches were utilized. Changes must persist for at least two time periods (of variable length, depending upon availability of cloud-free imagery) following the initial change, and anomalous changes among land and water categories can only occur in less than 20 percent of the remaining datasets. The mapped dataset identifies only these areas of persistent and consistent change (table 3; figs. 3 and 4). For this reason, recent land changes (2008–9 and 2009–10) cannot yet be defined as persistent because data are not available to confirm that these changes have persisted into the two following analysis periods. These unconfirmed changes are instead referred to as “new land investigation areas” and “new water investigation areas” (figs. 3 and 4).

It is important to note that there is a difference between net land area change (table 1 and fig. 1) and persistent losses and gains (table 3, figs. 3, 4). As classification of an area as

2 1956 assumes no change from 1956 to 1973 in 920 mi2 of coastal Louisiana.

1 1932 assumes no change from 1932 to 1956 in 1,115 mi2 and no change from 1932 to 1973 in 577 mi2

of coastal Louisiana.

3 Datasets are based on Landsat Multispectral Scanner System (MSS) data, which are originally at 60-m resolution.

7,722

7,529

7,143

7,336

6,950

6,757

6,564

6,371

6,178

5,985

5,792

5,598

5,405

Coas

tal L

ouis

iana

land

are

a, in

squ

are

mile

s

1930 1940 1950 1960 1970 1980 1990 2000 2010Year

1

2

3

3

3

Figure 2. Land area in coastal Louisiana, 1932–2010. Coastwide, net land area decrease from 1932 to 2010 was 1,883 mi2. (See table 1 for specific area measurements.)

Discussion and Conclusions 5

loss or gain depends upon persistence criteria, the amount of area of persistent loss or gain for a particular period can be less than or greater than the net land area change for that period. This occurs because persistent losses in a particular location can be offset by transitory gains in another.

Land Change TrendsLand change trends by hydrologic basin within the

modified coastal zone were calculated solely on the basis of Landsat TM data for 1985–2010 (figs. 5 and 6). Linear regressions were calculated for two time periods, 1985–2004 and 1985–2010, because strong hurricanes in 2005 (Katrina and Rita) and 2008 (Gustav and Ike) greatly impacted both eastern and western coastal Louisiana wetlands. Results show that the Atchafalaya Delta Basin is the only area in coastal Louisiana showing increasing land area (positive land change slope), but the rate of growth in this one basin is not sufficient to offset the losses coastwide, particularly in years of

increased hurricane activity. The 2005 and 2008 datasets were excluded to reduce the influence of transitory storm effects. The variability in land area data points around the slope illustrates the influence of various sources of environmental variance or classification error.

Discussion and ConclusionsThis assessment provides a comprehensive analysis

of historical trends and rates of land area change in coastal Louisiana. The primary improvement over past efforts is an increased temporal frequency of analysis. This gives scientists the ability to better quantify the amount of wetland loss and the time period in which it was lost. Having this information can allow gradual loss patterns to be distinguished from losses due to episodic events such as hurricanes. The spatial and temporal patterns observed reveal a dynamic landscape changing as a result of the complex and often interactive effects of natural and human-induced processes.

Table 2. Water levels at a selected gage (station ID: 8761724, located near Grand Isle, La.) on the date of acquisition for imagery used in the land area estimates.

Path 211 Path 221 Path 231 Path 241

Decimal date2

Calendar date

Gage height, in feet3

Calendardate


Calendardate


Calendardate


19324 Not available Not available Not available Not available

19564 Not available Not available Not available Not available

1973.9 12/5/1973 Not available 2/3/1973 Not available 12/7/1973 Not available 12/9/1973 Not available



1985.1 10/11/1985 6.79 1/19/1985 5.81 1/26/1985 5.94 12/3/1985 6.30

1988.1 12/4/1987 6.46 1/28/1988 5.02 12/2/1987 6.33 1/26/1988 5.97

1990.8 2/14/1991 5.97 11/1/1990 6.56 11/24/1990 6.40 10/30/1990 6.69

1995.7 10/7/1995 6.89 9/28/1995 6.86 10/5/1995 6.92 9/10/1995 6.82

1998.2 2/17/1998 6.04 2/24/1998 5.64 3/3/1998 6.14 3/10/1998 6.17

1999.9 11/27/1999 6.36 11/18/1999 6.46 11/16/1999 6.50 10/24/1999 6.73

2002.2 1/3/2002 6.00 2/27/2002 5.45 2/2/2002 5.97 1/8/2002 6.00

2004.9 10/15/2004 6.76 11/7/2004 6.46 10/13/2004 6.79 11/5/2004 6.59

2005.8 10/18/2005 6.73 10/25/2005 6.10 10/16/2005 6.66 10/23/2005 6.69

2006.8 1/25/2007 5.97 10/28/2006 6.53 11/4/2006 6.66 12/13/2006 6.23

2008.8 10/26/2008 6.82 10/1/2008 6.89 10/8/2008 6.89 9/29/2008 6.89

2009.8 11/14/2009 6.66 11/5/2009 6.69 11/12/2009 6.66 11/3/2009 6.73

2010.8 10/16/2010 6.53 10/7/2010 6.30 10/14/2010 6.36 10/5/2010 6.861Refer to figure 1. These “path” designations correspond to the Landsat Worldwide Reference System-2 (WRS-2) tiling system.

2Decimal dating is a more specific dating system than the calendar year and is used to facilitate statistical analyses. It is derived by dividing the day of the year (in the Julian system) by the number of days in the year.

3Elevations provided in station datum.

4Calendar dates were not available.


Table 3. Persistent land loss and land gain in coastal Louisiana by basin, as defined by the Coastal Wetlands Planning, Protection and Restoration Act Program (n.d.) ,1932–2010.

[Land area in square miles]

Basin 1932–56 1956–73 1973–75 1975–77 1977–85 1985–88 1988–90 1990–95 1995–98 1998–99 1999–2002 2002–4 2004–6 2006–8 2008–9 2009–10Total

persistent

Loss Loss Negative change

Atchafalaya Delta -4.48 -1.92 -1.75 -0.90 -0.64 -0.99 -1.37 -1.15 -0.83 -0.49 -0.39 -0.51 -0.37 -0.66 -0.01 -0.02 -16.49

Barataria -56.46 -70.98 -64.21 -27.94 -42.81 -16.80 -26.30 -26.76 -16.76 -17.83 -9.12 -8.95 -13.76 -15.86 -3.94 -3.23 -421.71

Breton Sound -30.94 -11.34 -9.95 -9.58 -7.97 -5.67 -8.28 -9.64 -6.93 -6.47 -4.26 -5.48 -29.32 -12.25 -0.98 -1.79 -160.87

Calcasieu-Sabine -8.41 -66.70 -17.30 -15.08 -9.59 -6.19 -4.22 -6.90 -7.15 -5.19 -2.85 -1.59 -22.00 -23.74 -1.30 -0.72 -198.94

Mermentau -18.68 -24.35 -7.00 -9.31 -10.01 -6.59 -5.49 -6.58 -5.74 -3.96 -4.03 -2.76 -22.26 -6.13 -0.43 -0.60 -134.37

Mississippi River Delta -34.06 -61.93 -10.51 -9.61 -4.86 -2.44 -5.64 -4.41 -1.89 -1.02 -1.02 -3.46 -10.11 -0.90 -0.14 -0.03 -152.02

Pontchartrain -34.41 -32.50 -12.74 -12.84 -9.47 -6.88 -9.67 -11.07 -7.85 -6.68 -4.20 -5.70 -15.14 -7.24 -1.26 -1.60 -179.25

Teche- Vermilion

-14.68 -8.40 -4.43 -4.22 -3.06 -3.23 -3.23 -2.81 -3.57 -3.15 -1.71 -3.23 -3.78 -4.51 -0.29 -0.29-64.61

Terrebonne -75.28 -46.25 -45.65 -50.87 -35.11 -22.97 -27.54 -30.63 -23.12 -22.50 -11.99 -9.63 -18.27 -23.40 -12.31 -4.49 -459.99

Total -277.41 -324.39 -173.55 -140.35 -123.52 -71.78 -92.18 -99.94 -73.83 -67.29 -39.57 -41.30 -135.02 -94.69 -20.65 -12.77 -1,788.241

Basin 1932–56 1956–73 1973–75 1975–77 1977–85 1985–88 1988–90 1990–95 1995–98 1998–99 1999–2002 2002–4 2004–6 2006–8 2008–9 2009–10Total

persistent

Gain Gain Positive change

Atchafalaya Delta 0.89 1.12 0.63 0.32 1.77 1.17 0.60 2.47 0.76 4.74 0.98 1.12 2.28 2.08 3.77 5.25 29.95

Barataria 1.11 0.10 0.05 0.45 0.24 0.05 0.08 0.15 0.29 0.09 0.30 0.31 1.25 0.58 0.35 0.52 5.91

Breton Sound 1.34 0.32 0.01 0.12 0.20 0.06 0.16 0.14 0.38 0.20 0.31 0.27 1.15 0.59 0.29 0.49 6.03

Calcasieu-Sabine 1.87 1.68 0.18 0.26 0.74 0.19 0.19 0.57 0.20 0.28 0.40 0.86 0.81 0.51 0.08 0.19 9.02

Mermentau 1.71 0.57 0.12 0.10 0.28 0.13 0.53 1.16 0.70 0.18 0.33 0.28 0.44 0.19 0.04 0.11 6.87

Mississippi River Delta 2.43 0.50 0.95 2.34 2.52 1.10 1.06 0.67 0.83 1.62 1.43 0.63 2.62 2.52 0.37 2.16 23.74

Pontchartrain 1.59 1.69 0.61 0.17 0.30 0.16 0.28 0.20 0.16 0.07 0.32 0.30 1.11 0.64 0.27 0.46 8.31

Teche- Vermilion

1.64 0.34 0.01 0.04 0.13 0.05 0.05 0.16 0.09 0.10 0.12 0.14 0.51 0.24 0.13 0.113.85

Terrebonne 2.96 0.21 0.25 0.31 0.49 0.26 0.24 0.28 0.40 0.76 0.47 0.37 1.67 0.67 0.66 0.43 10.42

Total 15.53 6.52 2.82 4.10 6.68 3.17 3.21 5.79 3.80 8.03 4.66 4.27 11.82 8.03 5.95 9.71 104.111

1Data are rounded to two decimal places; values shown may not add to totals shown.


*As persistence of these changes cannot yet be determined, these areas are coined “new water investigation areas” and “new land investigation areas.” These are areas under investigation for persistence of the changes observed.

-325

-300

-275

-250

-225

-200

-175

-150

-125

-100

-75

-50

-25

0

25 *

*

Per

sist

ent a

rea

chan

ge, i

n sq

uare

mile

s

Figure 3. Persistent land loss and land gain across coastal Louisiana by period for 1932–2010.

EXPLANATION

1Gain is determined by the last date a particular pixel transitioned from water to land and remained land throughout the period of observation.2Loss is determined by the last date a particular pixel transitioned from land to water and remained water throughout the period of observation.3Because this date range has only one ending dataset, some of these effects may be temporary phenomena.4This date range contains at least one date in which the land/water data were created from Landsat Multispectral Scanner System (MSS).

1977–85 land gain1,4

1932–56 land gain1







2004–6 land gain1




1977–85 land loss2,4

1932–56 land loss2







2004–6 land loss2




2006–8 land gain1


2006–8 land loss2


2002–4 land gain1 2002–4 land loss2

2009–10 new land1,3 2009–10 new water2,3


* **

* **

* **

-5-4-3-2-10123456

-80-70-60-50-40-30-20-10010

-35-30-25-20-15-10-505

-70-60-50-40-30-20-10010

-25-20-15-10-505

-65-55-45-35-25-15-55

-35-30-25-20-15-10-505

-16-14-12-10-8-6-4-202

-80-70-60-50-40-30-20-10010

* As p

ersis

tenc

e of

thes

e ch

ange

s can

not y

et b

e de

term

ined

, the

se a

reas

are

coi

ned

“new

wat

er in

vest

igat

ion

area

s” a

nd “n

ew la

nd in

vest

igat

ion

area

s.”

T

hese

are

are

as u

nder

inve

stig

atio

n fo

r per

siste

nce

of th

e ch

ange

s obs

erve

d.

Atch

afal

aya

Delta

Bas

in

Bara

taria

Bas

in

Bret

on S

ound

Bas

in

Calc

asie

u-Sa

bine

Bas

in

Mer

men

tau

Basi

n M

issi

ssip

pi R

iver

Del

ta B

asin

Pont

char

train

Bas

in

Tech

e-Ve

rmili

on B

asin

Te

rreb

onne

Bas

in

Land area, in square miles









Figu

re 4

. Pe

rsis

tent

land

loss

and

land

gai

n ac

ross

Lou

isia

na b

y ba

sin

(as

defin

ed b

y th

e Co

asta

l Wet

land

s Pl

anni

ng, P

rote

ctio

n an

d Re

stor

atio

n Ac

t Pro

gram

, n.

d.) a

nd p

erio

d fo

r 193

2–20

10 (s

ee m

ap o

n pa

ge iv

for c

olor

cod

ing

of p

erio

ds).


1985 1990 1995 2000 2005 2010 2015

5,405

5,791

6,177

6,563

Gustav/IkeKatrina/Rita

Land

are

a, in

squ

are

mile

s

Year

95 percent confidence band, 1985–2010

Regression trend line, 1985–2010

Regression trend line, 1985–2004

Land areaExcluded data points, 2005–8

EXPLANATION

(r 2 =

0.7208)

1985–2004 = 0.4969)

(r 2 =1985–2010 =

-11.76 ± 4.47

-16.57 ± 3.26 mi2/year

mi2/year

Figure 5. Linear regressions of land area change trends coastwide across Louisiana, 1985–2010; negative measurements indicate land loss, while positive measurements indicate land gain. Rates including and excluding the effects of the hurricanes of 2005 and 2008 are shown for comparison.

Variability in land area estimates can often be attributed to temporary wind and water level fluctuations present at the date and time of acquisition of the aerial and satellite imagery. Morton and others (2005) found that water area varied by as much as 5 percent over short time periods, largely as the result of environmental variability. The 17 dates of imagery analyzed provide a more robust estimate of change by reducing the inclusion of land area fluctuations caused by environmental variability.

The desire to reduce errors associated with environmental variability was a driving force behind the development of the persistence criteria utilized in this analysis. An area must experience a change in land/water category, and that change must persist for at least two time periods following the initial conversion before that area is classified as “loss” or “gain”. The temporal resolution, as well as the persistence criteria used in this analysis, ensures that the data presented are more likely to represent permanent changes compared to previous studies; however, it is important to note when examining wetland loss/gain by time period that wetland

areas often fluctuate between land and water categories. These fluctuations can take place for multiple time periods prior to a persistent conversion of an area from land to open water or, conversely, from open water to land. Consequently, loss that is shown to have occurred in a specific time period may have begun that transition in an earlier period. Initial losses often recover temporarily, only to be lost again because of a secondary or compound stressor. With the exception of anomalies, this assessment documents the last time period in which the persistent conversion occurred as opposed to the first time a change was documented.

These analyses have shown that episodic events, such as hurricanes and other extreme storms, have contributed significantly to coastal land loss, particularly in recent years. Annual rates of coastal land loss for 1985 to 2010 (-16.57 ± 3.26 mi2/yr) increased by approximately 4.8 mi2/year relative to the 1985 to 2004 trends (-11.76 ± 4.47 mi2/yr), reflecting hurricane-induced acceleration of coastal land loss. This is consistent with previous analyses described in Barras and others (2008). In addition to the immediate loss caused by

Discussion and Conclusions 11At

chaf

alay

a De

lta B

asin

1985

1990

1995

2000

2005

2010

2015

116

154

192

230

268

306

Gust

av/Ik

eKa

trina

/Rita


Bara

taria

Bas

in

1985

1990

1995

2000

2005

2010

2015

849

926

1,003

1,080

1,157

1,234

1,311

1,388

Gust

avKa

trina


Bret

on S

ound

Bas

in

1985

1990

1995

2000

2005

2010

2015

232

309

386

Gust

avKa

trina


Mer

men

tau

Basi

n

1985

1990

1995

2000

2005

2010

2015

579

676

773

870

967

IkeRi

ta


Mis

siss

ippi

Rive

r Del

ta B

asin

1985

1990

1995

2000

2005

2010

2015

77115

153

191

Gust

avKa

trina


Pont

char

train

Basin

1985

1990

1995

2000

2005

2010

2015

849

887

925

963

1,001

1,039

Gust

avKa

trina


Terre

bonn

e Ba

sin

1985

1990

1995

2000

2005

2010

2015

1,081

1,158

1,235

1,312

1,389

1,466

Gust

avKa

trina


Tech

e-Ve

rmilio

n Bas

in

1985

1990

1995

2000

2005

2010

2015

444

463

482

501

520

IkeRit

a


Calc

asie

u-Sa

bine

Bas

in

1985

1990

1995

2000

2005

2010

2015

541

618

695

772

IkeRit

a


Year

Year

Year

Year

Year

Year

Year

Year

Year

(r2 =

0.39

09)

1985

–200

4 =

0.27

58)

(r2 =19

85–2

010

=1.32

± 0

.81

1.22

± 0

.48

mi2 /y

ear

mi2 /y

ear

(r2 =

0.70

70)

1985

–200

4 =

0.60

33)

(r2 =19

85–2

010

=-5.2

7 ±

1.62

-4.7

6 ±

0.97

mi2 /y

ear

mi2 /y

ear

(r2 =

0.81

26)

1985

–200

4 =

0.65

44)

(r2 =19

85–2

010

=

-1.9

7 ±

0.54

-2.9

8 ±

0.45

mi2 /y

ear

mi2 /y

ear

(r2 =

0.10

09)

1985

–200

4 =

0.05

010)

(r2 =

1985

–201

0 =

0.67

± 1

.10

-0.9

7 ±

0.91

mi2 /y

ear

mi2 /y

ear

(r2 =

0.06

836)

1985

–200

4 =

0.01

922)

(r2 =19

85–2

010

=

0.74

± 2

.01

-1.3

0 ±

1.52

mi2 /y

ear

mi2 /y

ear

(r2 =

0.03

195)

1985

–200

4 =

0.01

624)

(r2 =19

85–2

010

=

0.22

± 0

.65

-0.2

9 ±

0.51

mi2 /y

ear

mi2 /y

ear

(r2 =

0.84

37)

1985

–200

4 =

0.70

54)

(r2 =19

85–2

010

=-2.4

4 ±

0.60

-2.8

1 ±

0.38

mi2 /y

ear

mi2 /y

ear

(r2 =

0.69

10)

1985

–200

4 =

0.57

97)

(r2 =19

85–2

010

=

-4.7

3 ±

1.52

-4.3

7 ±

0.92

mi2 /y

ear

mi2 /y

ear

(r2 =

0.37

74)

1985

–200

4 =

0.14

51)

(r2 =19

85–2

010

=-0.3

2 ±

0.29

-0.4

5 ±

0.18

mi2 /y

ear

mi2 /y

ear

95 p

erce

nt c

onfid

ence

b

and,

198

5–20

10Re

gres

sion

tren

d lin

e, 1

985–

2010

Regr

essi

on tr

end

line,

198

5–20

04La

nd a

rea

Excl

uded

dat

a po

ints

, 200

5–8

EXPL

ANAT

ION

Figu

re 6

. Li

near

re

gres

sion

s of

land

ar

ea c

hang

e tre

nds

in c

oast

al L

ouis

iana

by

hyd

rolo

gic

basi

n (a

s de

fined

by

the

Coas

tal W

etla

nds

Plan

ning

, Pro

tect

ion

and

Rest

orat

ion

Act P

rogr

am, n

.d.),

19

85–2

010;

neg

ativ

e m

easu

rem

ents

in

dica

te la

nd lo

ss,

whi

le p

ositi

ve

mea

sure

men

ts

indi

cate

land

gai

n.

Rate

s in

clud

ing

and

excl

udin

g th

e ef

fect

s of

the

hurr

ican

es o

f 200

5 an

d 20

08 a

re s

how

n fo

r com

paris

on.

Publishing support provided by theUSGS Lafayette Publishing Service Center

direct physical impacts, hurricanes have been observed to induce excessive plant stress, such as from storm-driven elevated salinity and sulfides (Steyer and others, 2010), which has been suggested to contribute to future wetland losses. This analysis has shown areas that were not immediately observed as loss following a particular storm’s landfall, but those areas began to consistently appear as water several months later. Storm-induced stress likely contributed to at least some of the observed losses.

Excluding the high rates of wetland loss due to recent hurricanes, rates of wetland loss had been decreasing from the high rates observed in the 1970s. Britsch and Dunbar (1993) observed a similar trend of decreasing loss after 1978. Though the wetland loss in coastal Louisiana is a dire situation, this observed decrease is at least a measured source of positive news, as past trends are often indicative of potential future losses.

An interesting finding of this analysis may be observed in the increase in net land area in the 2009 and 2010 datasets, as seen in figure 2. Though it may be intuitive to interpret this land area increase as recovery from the low, hurricane-influenced land area estimates of 2008, the potential influence of environmental variability dictates caution before interpreting this pattern as “recovery.” Discriminating the permanence of these increases from the transitory effects of environmental variability may require several additional years of observations.

The temporal frequency of land change provided by this study is allowing scientists to further investigate the causal mechanisms of the loss that has occurred. These investigations will provide improved information to develop tools to monitor ecosystems, forecast possible impacts, and plan protection and restoration activities. These data can help support the development of strategies to adapt to our changing environment.

References

Barras, J.A., 2006, Land area change in coastal Louisiana after the 2005 hurricanes—A series of three maps: U.S. Geological Survey Open-File Report 2006–1274. (Also available at http://pubs.usgs.gov/of/2006/1274/.)

Barras, J.A., 2007, Land area changes in coastal Louisiana after Hurricanes Katrina and Rita, in Farris, G.S., Smith, G.J., Crane, M.P., Demas, C.R., Robbins, L.L., and Lavoie, D.L., eds., Science and the storms—the USGS response to the hurricanes of 2005: U.S. Geological Survey Circular 1306, p. 97–112. (Also available at http://pubs.usgs.gov/circ/1306/.)


Barras, J.A., Bernier, J.C., and Morton, R.A., 2008, Land area change in coastal Louisiana—A multidecadal perspective (from 1956 to 2006): U.S. Geological Survey Scientific Investigations Map 3019, scale 1:250,000, 14 p. pamphlet. (Also available at http://pubs.usgs.gov/sim/3019/.)

Bernier, J.C., Morton, R.A., and Barras, J.A., 2006, Constraining rates and trends of historical wetland loss, Mississippi River delta plain, south-central Louisiana, in Xu, Y.J., and Singh, V.P., eds., Coastal environment and water quality—Proceedings of the AIH 25th Anniversary Meeting and International Conference Challenges in Coastal Hydrology and Water Quality: Highlands Ranch, Colo., Water Resources Publications, LLC, p. 371–373. (Also available at http://coastal.er.usgs.gov/gc-subsidence/historical-wetland-loss.html.)

Britsch, L.D., and Dunbar, J.B., 1993, Land-loss rates—Louisiana coastal plain: Journal of Coastal Research, v. 9, p. 324–338.

Britsch, L.D., and Dunbar, J.B., 2006, Land loss in coastal Louisiana 1932 to 2001—A series of maps: Vicksburg, Miss., Engineer Research and Development Center, U.S. Army Engineer District, New Orleans.

Louisiana Coastal Wetlands Planning, Protection and Restoration Act Program, n.d., Coastal Louisiana basins: Louisiana Coastal Wetlands Planning, Protection and Restoration Act Program Web site, accessed May 5, 2011, at http://lacoast.gov/new/About/Basins.aspx.

Morton, R.A., Bernier, J.C., Barras, J.A., and Fernia, N.F., 2005, Rapid subsidence and historical wetland loss in the Mississippi Delta Plain, likely causes and future implications: U.S. Geological Survey Open-File Report 2005-1216, 124 p. (Also available at http://pubs.usgs.gov/of/2005/1216/.)

Steyer, G.D., Cretini, K.F., Piazza, Sarai, Sharp, L.A., Snedden, G.A., Sapkota, Sijan, 2010, Hurricane influences on vegetation community change in coastal Louisiana: U.S. Geological Survey Open-File Report 2010–1105, 21 p. (Also available at http://pubs.usgs.gov/of/2010/1105/.)

http://pubs.usgs.gov/sim/3019/

http://coastal.er.usgs.gov/gc-subsidence/historical-wetland-loss.html

http://coastal.er.usgs.gov/gc-subsidence/historical-wetland-loss.html

http://lacoast.gov/new/About/Basins.aspx

http://pubs.usgs.gov/of/2005/1216/



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