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New Orleans

MISSISSIPPI

LOUISIANA

Lake Pontchartrain

Big

 Mar

ke Maurepas

Lake Salvador

Barataria Bay

Timbalier Bay

Terrebonne Bay

Little Lake

Lake Cataouatche

Lake Borgne

 Lake Pontchartrain Causeway

Gulf Intracoastal Waterway

Mississippi River-Gulf Outlet Canal

Mississ pi pi River

Mississippi River

Southwest Pass

South Pass

Pass a Loutre

East Bay

West Bay

Garden

Island 

Bay

Bayou Lafourche

Labranche wetlands

Breton Sound

Lake

Felicity

GULF OF MEXICO

GULF OF MEX

Chandeleur Sound

Golden

Meadow

Port

Fourchon

The 

Pen

Redfish 

Bay

Blind

Bay

Quarantine

Bay

Adams

Bay

Bastian

Bay 

Bayou Perot

Bayou Rigolettes

Grand

Lake

Lake

Saint 

Catherine

Lake Lery

asin

Barataria Basin

Breton Sound

Basin

Pontchartrain

Basin

U.S. Department of the Interior

U.S. Geological Survey

Pamphlet to accompany

Scientific Investigations Map 3381

Land Area Change in Coastal Louisiana (1932 to 2016)

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New Orleans

MISSISSIPPI

LOUISIANA

TEXAS

LOUISIANA

Cameron

Lake Pontchartrain

Big

 Mar

Lake Maurepas

Lake Salvador

Barataria Bay

Timbalier Bay

Terrebonne Bay

Caillou Lake

Lake

 Mechant

Lake

 Boudreaux

Little Lake

Atchafalaya Bay

GULF OF MEXICO

Lake Cataouatche

Atchafalaya River

Lake Borgne

East Cote 

Blanche Bay

West Cote 

Blanche Bay

Vermilion Bay

White Lake

Grand Lake

Calcasieu

Lake

Black

 Lake

Freshwater Bayou

Wax Lake Outlet

Marsh

Island

 Lake Pontchartrain Causeway

Gulf Intracoastal Waterway

Gulf Intracoastal Waterway

Gulf Intracoastal Waterway

Mississippi River-Gulf Outlet Canal

Mississ pi pi River

Mississippi River

Southwest Pass

South Pass

Pass a Loutre

East Bay

West Bay

Garden

Island 

Bay

Bayou Lafourche

Labranche wetlands

Calcasieu Ship Channel

Sweet

 Lake

Breton Sound

Lake

Felicity

GULF OF MEXICO

GULF OF MEXICO

Chandeleur Sound

Chandeleur Is al nds

Lac des 

Allemands

GULF OF MEXICO

Hackberry

Johnsons Bayou Grand Chenier

Wax Lake Delta

Atchafalaya Delta

Intracoastal

City

Pecan

Island

Houma

Golden

Meadow

Port

Fourchon

Montegut

Dulac

Theriot

Amelia

Lake 

Verret

Lake 

Palourde

The 

Pen

Redfish 

Bay

Blind

Bay

Quarantine

Bay

Adams

Bay

Bastian

Bay Lost Lake Four League

Bay

Bayou Perot

Bayou Rigolettes

Grand

Lake

Lake De Cade

Lake

Saint 

Catherine

Sabine

Lake

Mermentau Basin

Lake Lery

Calcasieu-Sabine Basin

Teche-Vermilion 

Basin

Atchafalaya 

Delta Basin

Terrebonne Basin

Barataria Basin

Breton Sound

Basin

Pontchartrain

Basin

Land Area Change in Coastal Louisiana 

(1932 to 2016)

By Brady R. Couvillion, Holly Beck, Donald Schoolmaster, and Michelle Fischer

Pamphlet to accompany

Scientific Investigations Map 3381

U.S. Department of the Interior

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

RYAN K. ZINKE, Secretary

U.S. Geological Survey

William H. Werkheiser, Acting Director

U.S. Geological Survey, Reston, Virginia: 2017

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment—visit

http://www.usgs.gov/ or call 1–888–ASK–USGS (1–888–275–8747).

For an overview of USGS information products, including maps, imagery, and publications,

visit http://www.usgs.gov/pubprod/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply

endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it also may

contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items

must be secured from the copyright owner.

Suggested citation:

Couvillion, B.R., Beck, Holly, Schoolmaster, Donald, and Fischer, Michelle, 2017, Land area change in coastal Louisiana 

1932 to 2016: U.S. Geological Survey Scientific Investigations Map 3381, 16 p. pamphlet, https://doi.org/10.3133/

sim3381.

ISSN 2329-1311 (print)

ISSN 2329-132X (online)

ISBN 978-1-4113-4151-7 
Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Study Area..............................................................................................................................................1

Methodology...................................................................................................................................................2

Results ...........................................................................................................................................................13

Land Area Changes ...........................................................................................................................13

Change in Land Change Rates through Time .................................................................................13

Discussion ....................................................................................................................................................13

Conclusions...................................................................................................................................................14

References Cited..........................................................................................................................................15

Figures

1. Map showing the study area in coastal Louisiana .................................................................2

2. Graph showing land area in coastal Louisiana, 1932–2016...................................................6

3. Graphs showing land area by hydrologic basin in coastal Louisiana, 1932–2016.............7

4. Graph showing finite-difference approximation of land area change rates

through time in coastal Louisiana, 1932–2016..........................................................................9

5. Graphs showing finite-difference approximation of land area change rates

through time in coastal Louisiana by hydrologic basin, 1932–2016....................................10

Tables

1. Observed and modeled land area, including Standard Error in hydrologic

basins and coastal Louisiana, 1932–2016 .................................................................................4

2. Water levels at a selected gage on the date of acquisition for imagery

used in the land area estimates .................................................................................................8

3. Finite-difference approximation estimates of long-term wetland change rates

including standard error estimates for each hydrologic basin and coastal

Louisiana from 1932 to 2016 ......................................................................................................11

iii
iv

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2)

Datum

Horizontal coordinate information is referenced to the [North American Datum of 1983 (NAD 83)].

Abbreviations

DOA date of acquisition

edf effective degrees of freedom

FAV floating aquatic vegetation

MIR mid-infrared

mNDWI modified Normalized Difference Water Index

MSS Landsat Multispectral Scanner

NWI National Wetlands Inventory

OLI Operational Land Imager

SLR sea-level rise

USGS U.S. Geological Survey

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New Orleans

TEXAS LOUISIANA

Cameron

Lake Pontchartrain

Big

 Mar

Lake Maurepas

Lake Salvador

Barataria Bay

Timbalier Bay

Terrebonne Bay

Caillou Lake

Lake

 Mechant

Lake

 Boudreaux

Little Lake

Atchafalaya Bay

GULF OF MEXICO

Lake Cataouatche

Atchafalaya

River

Lake Borgne

East Cote 

Blanche Bay

West Cote 

Blanche Bay

Vermilion Bay

White Lake

Grand Lake

Calcasieu

Lake

Black

 Lake

Freshwater Bayou

Wax Lake Outlet

Marsh

Island

 Lake Pontchartrain Causeway

Gulf Intracoastal Waterway

Gulf Intracoastal Waterway

Gulf Intracoastal Waterway

Mississippi River-Gulf Outlet Canal

Mississ pi pi Rive

r

Bayou Lafourche

Labranche wetlands

Calcasieu Ship Channel

Sweet

 Lake

Lake

Felicity

GULF OF MEXICO

Lac des 

Allemands

GULF OF MEXICO

Hackberry

Johnsons Bayou Grand Chenier

Wax Lake Delta

Atchafalaya Delta

IntracoastalCity

PecanIsland

Houma

Golden

Meadow

PortFourchon

Montegut

Dulac

Theriot

Amelia

Lake 

Verret

Lake 

Palourde

The 

Pen

Adams

Bay

Bastian

Bay

Lost Lake Four League Bay

Bayou Perot

Bayou Rigolettes

Grand

Lake

Lake De Cade

Lake

Saint 

Catherine

Sabine

Lake

Mermentau Basin

Lake Lery

Calcasieu-Sabine Basin

Teche-Vermilion 

Basin

Atchafalaya 

Delta Basin

Terrebonne Basin

Barataria Basin

0 10 20 40 KILOMETERS

0 10 20 

Scale 1:265,000

N

EXPLANATION

1932–56 Persistent land loss21956–73 Persistent land loss2,41973–75 Persistent land loss2,41975–77 Persistent land loss2,41977–85 Persistent land loss2,41985–88 Persistent land loss21988–90 Persistent land loss21990–95 Persistent land loss21995–98 Persistent land loss21998–99 Persistent land loss21999–2002 Persistent land loss22002–04 Persistent land loss2

2004–06 Persistent land loss22006–08 Persistent land loss22008–09 Persistent land loss22009–10 Persistent land loss22010–13 Persistent land loss22013–14 Persistent land loss22014–15 New water area31932–56 Persistent land gain11956–73 Persistent land gain1,41973–75 Persistent land gain1,41975–77 Persistent land gain1,41977–85 Persistent land gain1,4

1985–88 Persistent land gain11988–90 Persistent land gain11990–95 Persistent land gain11995–98 Persistent land gain11998–99 Persistent land gain11999–2002 Persistent land gain12002–04 Persistent land gain12004–06 Persistent land gain12006–08 Persistent land gain12008–09 Persistent land gain12009–10 Persistent land gain12010–13 Persistent land gain1

2013–14 Persistent la2014–15 New land ar

Basin boundary 

1Gain is determined by the last d

transitioned from water to lan

throughout the period of obse

2Loss is determined by the last d

transitioned from land to wate

throughout the period of obse

3Because this date range has on

some of these effects may be 

4This date range contains at lea

the land/water data were crea

Multispectral Scanner System 
Land Area Change in Coastal Louisiana (1932 to 2016) 

By Brady R. Couvillion, Holly Beck, Donald Schoolmaster, and Michelle Fischer

Abstract

Coastal Louisiana wetlands are one of the most critically 

threatened environments in the United States. These wetlands 

are in peril because Louisiana currently experiences greater 

coastal wetland loss than all other States in the contiguous 

United States combined. The analyses of landscape change 

presented here have utilized historical surveys, aerial, and 

satellite data to quantify landscape changes from 1932 to 2016. 

Analyses show that coastal Louisiana has experienced a net 

change in land area of approximately -4,833 square kilometers 

(modeled estimate: -5,197 +/- 443 square kilometers) from 1932 

to 2016. This net change in land area amounts to a decrease 

of approximately 25 percent of the 1932 land area. Previous 

studies have presented linear rates of change over multidecadal 

time periods which unintentionally suggest that wetland change 

occurs at a constant rate, although in many cases, wetland 

change rates vary with time. A penalized regression spline 

technique was used to determine the model that best fit the data, 

rather than fitting the data with linear trends. Trend analyses 

from model fits indicate that coastwide rates of wetland change 

have varied from -83.5 +/- 11.8 square kilometers per year 

to -28.01 +/- 16.37 square kilometers per year. To put these 

numbers into perspective, this equates to long-term average 

loss rates of approximately an American football field’s worth 

of coastal wetlands within 34 minutes when losses are rapid to 

within 100 minutes at more recent, slower rates. Of note is the 

slowing of the rate of wetland change since its peak in the mid1970s. Not only have rates of wetland loss been decreasing since 

that time, a further rate reduction has been observed since 2010. 

Possible reasons for this reduction include recovery from lows 

affected by the hurricanes of 2005 and 2008, the lack of major 

storms in the past 8 years, a possible slowing of subsidence 

rates, the reduction in and relocation of oil and gas extraction 

and infrastructure since the peak of such activities in the late 

1960s, and restoration activities. In addition, many wetlands 

in more exposed positions in the landscape have already been 

lost. Most notable of the factors listed above is the lack of 

major storms over the past 8 years. The observed coastwide net 

“stability” in land area observed over the past 6–8 years does 

not imply that loss has ceased. Future disturbance events such 

as a major hurricane impact could change the trajectory of the 

rates. Sea-level rise is projected to increase at an exponential 

rate, and that would also expedite the rate of wetland loss.

Introduction

The U.S. Geological Survey (USGS) analyzed 

landscape changes in coastal Louisiana by determining 

land and water classifications for 21 datasets. Coastal 

Louisiana has been losing wetlands because of multiple 

compounding and interacting stressors including sea-level 

rise (SLR), subsidence, storms, sediment deprivation, oil and 

gas extraction and infrastructure, navigation infrastructure, 

saltwater intrusion, altered hydrology, and others (Penland 

and others, 2001). 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 from 1932 to 2016. The use of 21 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.

Study Area

The Louisiana coastal zone encompasses approximately 

37,780 square kilometers (km2

) of lowland plains, deltaic 

lobes, and open water (fig. 1). Coastal Louisiana wetlands are 

generally considered one of the most important environments 

in the United States because they support more than 30 

percent of the commercial fisheries in the United States, 5 

of the Nation’s top 20 ports are located in coastal Louisiana, 

and 20 percent of the Nation’s oil and gas comes from or is 

transported through these wetlands (Costanza and others, 

2008; Feagin and others, 2010; Gedan and others, 2011; 

NOAA, 2010; Twilley, 2007). This coast is also considered 

to be one of the most “at-risk” environments in the Nation 

because approximately a quarter of these wetlands have been 

lost in the past 84 years (Couvillion and others, 2011).

Coastal Louisiana was built by sedimentary material 

sourced from fluvial and tidally redistributed deposits. The 

bulk of these deposits were delivered via the Mississippi 

River as a result of upper catchment glaciation and melting 

associated with sea-level changes. As glaciers retreated (from 

about 12,000 until 6,000 years ago), meltwater inundated 

valleys and transported much of the upper catchment 

sediments to the lower catchment floodplains that compose 
2 Land Area Change in Coastal Louisiana (1932 to 2016)

CAMERON

PLAQUEMINES

ST BERNARD

IBERIA

TERREBONNE

VERMILION

ST MARY

LAFOURCHE

ST

TAMMANY

LIVINGSTON

ORLEANS

ST 

CHARLES

ASSUMPTION

ST JAMES

ST JOHN 

THE BAPTIST

Area enlarged

Path 24

Path 23

Path 22

Path 21 EXPLANATION

Modified Coastal Zone Boundary: 37,780 km2

Landsat Worldwide Reference System-2 (WRS-2)

Missing from 1932 and 1956 data: 1,494 km2 within modified Coastal Zone Boundary

Missing from 1932 data: 2,888 km2 within modified Coastal Zone Boundary

Missing from 1956 data: 2,383 km2 within modified Coastal Zone Boundary N

Figure 1. The study area in coastal Louisiana. The coastal zone boundary, the zone for which statistics were calculated, isolates coastal 

regions while excluding fastlands (defined as developed, agricultural, and other protected areas) from statistical analysis of coastal land 

change. Of particular note are the areas of non-overlapping data coverage in the 1932 and 1956 datasets (based on survey and aerial data) 

and in the 1973–2016 datasets (based on satellite imagery data). Because no data exist for these non-overlapping areas, an assumption of 

no change in those areas has been used for those time periods in the analyses (a reasonable assumption because a majority of these data 

voids occurs in areas dominated by forested wetlands, a habitat type known to have been particularly stable in past observations). Areas 

are presented in square kilometers (km2

).

coastal Louisiana today. Periodic floodwaters would carry 

these sediments, and as the floodwaters retreated, rich 

sediment left behind formed a vast expanse of fertile deltaic 

wetlands (Fisk and McFarlan, 1955). Hydrology continues to 

dictate the geomorphic structure and vegetation distribution 

of this landscape but in a drastically altered fashion. 

Flood-control structures including dams and levees were 

built, not only in Louisiana but throughout the Mississippi 

River catchment, particularly after the flood of 1927. The 

construction of these features has led to an overall decrease in 

the amount of sediment carried by the Mississippi River as a 

result of dam and levee construction throughout the drainage 

basin (Meade and others, 1990; Kesel and others, 1992). 

Anthropogenic controls also vary the distribution of sediment 

within the river by redirecting or altering the amount of 

sediment distribution at channel mouths, along channel banks, 

and across floodplains. These flood-control structures have 

contributed to a reduced capacity for sediment accretion and 

thereby reduced the ability of wetlands to maintain elevation 

in response to SLR and subsidence. 

Methodology

This study analyzed changes in the extent of land in 

coastal Louisiana by using 21 datasets summarizing land 

and water areas from 1932 to 2016 (table 1; figs. 2 and 3). 

The datasets were derived from multiple sources including 

(1) historical U.S. Army Corps of Engineers land loss 

data (1932) (Dunbar and others, 1990, 1992); (2) National 

Wetlands Inventory (NWI) data based on aerial photography 

(1956); (3) Landsat Multispectral Scanner (MSS) data 

(1973–79); (4) Landsat Thematic Mapper (TM) (1985–2010); 

and (5) Landsat Operational Land Imager (OLI) (2013–2016) 

satellite imagery classified into land and water categories. 

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 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 

fig. 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 be used with 

the implicit understanding of this assumption in areas lacking 

data in 1932 and 1956.

Preprocessing of all datasets included use of ERDAS 

IMAGINE AutoSync software (Hexagon Geospatial, 2016) 

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 
Methodology 3

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 68- by 83-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- and OLI-based data (native 30-m 

resolution). All satellite imagery data were then classified 

into land/water categories by using a methodology which 

makes use of a modified Normalized Difference Water Index 

(mNDWI) (Xu, 2005, 2006). The mNDWI enhances water 

features while cutting down on noise from land, vegetation, 

and soil (Xu, 2006). The mNDWI is seen in equation 1 below:

mNDWI = (Green-MIR)/(Green+MIR) (1)

Mid-infrared (MIR) is used because the wavelengths 

in this range, 1.55–1.75 micrometers, are particularly 

informative and discriminatory with regard to categorizing 

land and water. The green wavelength range is used as it 

maximizes reflectance of water and vegetation reflects MIR 

light more than green light (Xu, 2006). Initial mNDWI values 

were assigned to their appropriate land/water categories 

by thresholds. Supervised and unsupervised classification 

was then used to account for areas that may be incorrectly 

classified by the mNDWI alone. This step focuses on errorprone classes such as floating aquatic vegetation (FAV), 

shadows, and bridges. These areas were manually recoded to 

their appropriate land/water categories by expert analyses.

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) (table 2) of the data (Morton and others, 2005; Bernier 

and others, 2006). A composite coastal land-water dataset 

was developed from the source-classified satellite data for 

each time period and was then used to derive the land area by 

date, basin area, and coastal area (table 1). 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 consecutive 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. For this reason, 

recent land changes (2015 to early 2016) 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.” 

The resulting land area data were summarized by time 

period and by basin (fig. 3, table 1). Figures 2 and 3 display 

the long-term trend in land area over the period of observation. 

The function of change in land area over time was fit with 

a smoothing method called penalized regression splines by 

using the Mixed GAM Computation Vehicle (MGCV) package 

(Wood, 2000) on the R statistical platform (R Core Team, 

2014). This method fits land change as a set of polynomials 

in a piecewise-continuous fashion across the span of years. 

Trends computed from this spline technique are smoothed 

and, as such, generalize trends over time. The intent of this 

study is to provide long-term, coarse-scale rates of change, 

and therefore these change rates are not appropriate at finer 

spatial and temporal scales. The complexity smoothing spline, 

as determined by the dimensionality of its basis function, was 

set to a maximum of five, but its final value was determined by 

cross-validation to prevent overfitting. 

One of the assumptions of these modeling methods is 

that each data point provides equally precise information 

about the response variable. When this assumption is violated, 

there is non-zero covariance between the model error and the 

independent variables, which leads to biased estimates. These 

data clearly violate this assumption because of differences in 

data-collection methods. To account for differences in methods 

across years, points were weighted differently on the basis of 

expert opinion of the uncertainty inherent in each method. The 

weights affect how strongly each point contributes to estimates 

of total deviation. Data before 1973 were given half the weight 

of data after 1984. Data between 1973 and 1984 were given 

three-quarters weight of data after 1984. The goodness of fit 

is described by the coefficient of determination (R2) statistic. 

Effective degrees of freedom (edf) can be interpreted as being 

related to the degree of the polynomial fit of the spline (edf = 

1 is linear, edf = 2 is quadratic, and so on). We fit the models 

with and without weighting the data. As suspected, failing 

to weight the data resulted in overfitting. Specifically, nonweighted models were more complex (larger edf) and had 

higher R2 values but generated slightly larger out-of-sample 

prediction error on average. This suggests that weighting data 

successfully reduced bias and improved the robustness of 

the models.

Figures 2 and 3 display the change in land area over time, 

whereas figures 4 and 5 and table 3 display approximations of 

the rates of land area change over time. Rates of change were 

calculated from the fitted models by using finite-difference 

approximation. The uncertainty of the finite differences was 

calculated by posterior simulations. Each fitted model was 

simulated 10,000 times, and the finite-difference estimates of 

the rates were calculated by using the function derivSimulCI() 

(Simpson, 2016). The 15.9 and 84.1 percentiles (representing 

the expected value +/- 1 standard deviation) of each rate 

estimate were calculated and displayed on the graphs.
Table 1. Observed and modeled land area, including Standard Error (SE) in hydrologic basins and coastal Louisiana, 1932–2016. Units are in square kilom

Atchafalaya Delta Basin Barataria Basin Breton Sound Basin Calcasieu-Sabine Basin 

Julian date Land area (observed) Land area (modeled) SE Land area (observed) Land area (modeled) SE Land area (observed) Land area (modeled) SE Land area (observed) Land area (modeled) SE La

(o

1932 550.58 521.57 37.33 3,832.61 3,837.59 100.40 1,107.56 1,125.39 46.62 2,136.71 2,160.27 94.71 21956 511.70 514.08 21.01 3,580.92 3,629.09 76.41 974.02 1,025.31 26.36 2,099.23 1,929.75 54.67 21973.9 510.33 516.82 14.06 3,468.16 3,323.22 40.76 1,023.26 937.85 17.50 1,790.73 1,758.19 35.79 21975.7 545.24 517.82 13.54 3,172.13 3,282.24 38.65 900.69 927.70 16.83 1,807.18 1,743.12 34.35 21977.4 493.43 518.92 13.08 3,361.50 3,241.84 37.05 923.31 917.81 16.23 1,533.22 1,729.53 33.06 21985.1 483.82 525.67 11.16 2,977.82 3,047.84 31.52 864.71 869.40 13.83 1,593.98 1,676.63 28.02 21988.1 533.26 529.06 10.51 3,031.61 2,973.17 29.46 880.24 849.00 13.05 1,648.17 1,660.18 26.46 21990.8 515.21 532.43 9.98 2,859.62 2,909.55 27.90 810.68 829.96 12.43 1,707.41 1,647.40 25.29 21995.7 583.21 539.23 9.19 2,659.18 2,808.59 26.88 756.71 794.04 11.54 1,650.64 1,628.64 23.67 21998.2 468.64 542.97 8.88 2,829.30 2,766.69 26.94 811.51 775.19 11.15 1,544.00 1,620.92 22.96 11999.9 598.89 545.60 8.70 2,734.30 2,742.54 26.81 777.68 762.23 10.89 1,669.00 1,616.24 22.43 22002.2 548.25 549.23 8.52 2,802.67 2,715.65 26.10 788.86 744.55 10.58 1,631.37 1,610.50 21.69 22004.9 566.94 553.59 8.49 2,715.75 2,692.30 24.35 766.29 723.65 10.37 1,693.97 1,604.42 20.98 22006.8 554.23 556.70 8.65 2,683.07 2,680.72 22.88 684.02 708.89 10.44 1,619.11 1,600.42 20.88 12008.8 526.17 559.99 9.04 2,632.37 2,672.25 21.90 622.62 693.33 10.83 1,502.79 1,596.37 21.47 12009.8 568.12 561.65 9.33 2,618.09 2,669.21 21.97 628.07 685.55 11.17 1,473.35 1,594.38 22.11 12010.8 593.91 563.30 9.69 2,652.65 2,666.83 22.58 656.31 677.77 11.63 1,583.57 1,592.40 23.02 22013.9 619.64 568.45 11.23 2,656.36 2,662.38 28.31 647.23 653.65 13.68 1,605.89 1,586.31 27.43 22014.8 551.35 569.94 11.77 2,656.79 2,661.55 30.89 652.70 646.65 14.44 1,622.24 1,584.55 29.10 22015.8 553.12 571.60 12.42 2,679.08 2,660.72 34.08 646.26 638.87 15.34 1,621.26 1,582.59 31.11 12016.1 566.90 572.10 12.62 2,712.53 2,660.48 35.09 682.01 636.54 15.63 1,619.01 1,582.01 31.73 1
Table 1. Observed and modeled land area, including Standard Error (SE) in hydrologic basins and coastal Louisiana, 1932–2016. Units are in square kilo

Mississippi River Delta Basin Pontchartrain Basin Teche-Vermilion Basin Terrebonne Basin 

Julian

date

Land area 

(observed)

Land area 

(modeled)

SE Land area 

(observed)

Land area 

(modeled)

SE Land area 

(observed)

Land area 

(modeled)

SE Land area 

(observed)

Land area 

(modeled)

SE L

(o

1932 678.75 702.35 70.42 2,862.43 2,873.36 27.67 1,421.74 1,419.80 34.53 4,471.55 4,490.11 128.40 191956 626.31 486.15 51.80 2,689.07 2,722.32 18.42 1,347.43 1,377.98 24.12 4,191.70 4,246.20 91.66 18

1973.9 208.08 335.04 28.45 2,666.67 2,609.67 12.08 1,372.11 1,329.91 13.82 4,139.91 3,883.05 51.61 171975.7 244.16 326.14 26.99 2,587.61 2,598.35 11.51 1,367.83 1,323.47 13.13 3,961.86 3,838.01 48.99 161977.4 359.27 319.42 25.84 2,573.73 2,587.65 10.99 1,295.86 1,317.09 12.56 3,615.95 3,794.44 46.88 161985.1 315.01 308.05 21.85 2,536.17 2,539.19 8.90 1,275.20 1,286.24 10.54 3,433.10 3,593.55 39.45 151988.1 334.27 310.59 20.46 2,567.17 2,520.31 8.27 1,262.45 1,274.44 9.91 3,609.35 3,518.61 37.02 151990.8 357.39 315.08 19.45 2,514.53 2,503.32 7.83 1,237.77 1,264.54 9.46 3,425.47 3,455.23 35.30 151995.7 354.60 325.11 18.77 2,420.37 2,472.48 7.38 1,235.07 1,249.57 9.13 3,271.51 3,353.72 34.08 151998.2 295.37 329.39 18.75 2,491.55 2,456.75 7.35 1,255.36 1,243.95 9.07 3,281.10 3,309.97 33.93 141999.9 393.70 331.41 18.61 2,452.49 2,446.05 7.41 1,267.35 1,241.04 8.97 3,291.05 3,283.62 33.59 152002.2 346.00 332.60 18.06 2,446.46 2,431.58 7.59 1,258.42 1,238.35 8.67 3,351.74 3,252.32 32.53 152004.9 308.25 331.41 16.86 2,426.08 2,414.59 7.95 1,228.45 1,236.97 8.11 3,245.28 3,221.54 30.40 152006.8 274.49 328.83 15.91 2,362.91 2,402.63 8.27 1,236.53 1,237.05 7.71 3,215.95 3,203.29 28.80 142008.8 294.57 324.63 15.34 2,333.54 2,390.04 8.68 1,203.24 1,237.96 7.52 3,119.94 3,186.61 27.96 142009.8 281.50 322.02 15.44 2,339.36 2,383.75 8.90 1,219.41 1,238.67 7.61 3,119.51 3,179.07 28.24 142010.8 357.50 319.11 15.91 2,359.36 2,377.46 9.14 1,221.36 1,239.54 7.87 3,161.68 3,171.96 29.15 142013.9 306.83 308.79 19.88 2,364.85 2,357.95 9.94 1,289.79 1,242.86 9.77 3,213.18 3,151.80 36.31 142014.8 324.68 305.57 21.64 2,366.89 2,352.28 10.19 1,232.92 1,243.94 10.59 3,139.95 3,146.25 39.41 142015.8 315.79 301.96 23.80 2,364.48 2,345.99 10.48 1,234.85 1,245.14 11.59 3,142.53 3,140.14 43.23 142016.1 303.98 300.87 24.48 2,390.08 2,344.10 10.57 1,272.90 1,245.51 11.91 3,169.56 3,138.31 44.44 14
6 Land Area Change in Coastal Louisiana (1932 to 2016)

14,000

15,000

16,000

17,000

18,000

19,000

20,000

Coastal Louisiana

Year

Land area, in square kilometers

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

EXPLANATION

edf = 2.903

R2

 = 0.923

Penalized Regression Spline, 1932–2016

95 percent confidence band

Note:

Figure 2. Land area in coastal Louisiana, 1932–2016. (See table 1 for specific area measurements.) The red line 

represents a penalized regression spline which approximates the data. The blue dotted lines represent a 95-percent 

confidence interval. Effective degrees of freedom (edf) can be interpreted as being related to the degree of the 

polynomial fit of the spline (edf = 1 is linear, edf = 2 is quadratic, and so on). The goodness of fit is described by the 

coefficient of determination (R2) statistic.
laf170791_fig 03

500 550 600

Land area, in square kilometers

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Atchafalaya Delta

2,600 2,800 3,000 3,200 3,400 3,600 3,800Barataria

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

edf = 3.378R2 = 0.937

700 800 900 1000 1100Breton Sou

1930 1940 1950 1960 1970 19

edf = 2.008R2 = 0.897

1,500 1,600 1,700 1,800 1,900 2,000 2,100Calcasieu-Sabine

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Land area, in square kilometers edf = 2.206

R2 = 0.659

1,900 2,000 2,100 2,200 2,300 2,400 2,500 Mermentau edf = 1

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

R2 = 0.522

edf = 3.252

1930 1940 1950 1960 1970 19

200 300 400 500 600

Mississippi Riv

R2 = 0.609

2,400 2,500 2,600 2,700 2,800

Pontchartrain

Year

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

edf = 1

Land area, in square kilometers

R2 = 0.922

1,200 1,250 1,300 1,350 1,400

Teche Vermilion

Year

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

edf = 3.06R2 = 0.719

3,200 3,400 3,600 3,800 4,000 4,200 4,400Terrebonn

Year

1930 1940 1950 1960 1970 198

edf = 3.14R2 = 0.915

EXPLANATION

Penalized Regression Spline, 1932–201695 percent confidence band

edf = 1.77R2 = 0.245

Figure 3. Land area by hydrologic basin in coastal Louisiana, 1932–2016. (See table 1 for specific area measurements.) The red line represents a pewhich approximates the data. The blue dotted lines represent a 95-percent confidence interval. Effective degrees of freedom (edf) can be interpretedegree of the polynomial fit of the spline (edf = 1 is linear, edf = 2 is quadratic, and so on). The goodness of fit is described by the coefficient of deter
8 Land Area Change in Coastal Louisiana (1932 to 2016)

Table 2. Water levels at a selected gage (Station ID: 8761724, located near Grand Isle, Louisiana) on the date of acquisition for imagery 

used in the land area estimates. Elevations provided in meters (m) relative to station datum.

Path 21* Path 22* Path 23* Path 24*

Year Date Gauge

height (m)

Date Gauge

height (m)

Date Gauge

height (m)

Date Gauge

height (m)

1932 Variable Not Available Variable Not Available Variable Not Available Variable Not Available

1956 Variable Not Available Variable Not Available Variable Not Available Variable Not Available

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

1975.7 10/11/1975 Not Available 4/15/1975 Not Available 9/25/1975 Not Available 9/26/1975 Not Available

1977.4 7/2/1977 Not Available 6/3/1977 Not Available 1/23/1977 Not Available 4/6/1977 Not Available

1985.1 10/11/1985 2.07 1/19/1985 1.77 1/26/1985 1.81 12/3/1985 1.92

1988.1 12/4/1987 1.97 1/28/1988 1.53 12/2/1987 1.93 1/26/1988 1.82

1990.8 2/14/1991 1.82 11/1/1990 2.00 11/24/1990 1.95 10/30/1990 2.04

1995.7 10/7/1995 2.10 9/28/1995 2.09 10/5/1995 2.11 9/10/1995 2.08

1998.2 2/17/1998 1.84 2/24/1998 1.72 3/3/1998 1.87 3/10/1998 1.88

1999.9 11/27/1999 1.94 11/18/1999 1.97 11/16/1999 1.98 10/24/1999 2.05

2002.2 1/3/2002 1.83 2/27/2002 1.66 2/2/2002 1.82 1/8/2002 1.83

2004.9 10/15/2004 2.06 11/7/2004 1.97 10/13/2004 2.07 11/5/2004 2.01

2005.8 10/18/2005 2.05 10/25/2005 1.86 10/16/2005 2.03 10/23/2005 2.04

2006.8 1/25/2007 1.82 10/28/2006 1.99 11/4/2006 2.03 12/13/2006 1.90

2008.8 10/26/2008 2.08 10/1/2008 2.10 10/8/2008 2.10 9/29/2008 2.10

2009.8 11/14/2009 2.03 11/5/2009 2.04 11/12/2009 2.03 11/3/2009 2.05

2010.8 10/16/2010 1.99 10/7/2010 1.92 10/14/2010 1.94 10/5/2010 2.09

2013.9 10/24/2013 1.96 12/18/2013 1.76 2/27/2014 1.83 12/16/2013 1.80

2014.8 12/14/2014 1.90 11/19/2014 1.99 11/26/2014 1.81 11/1/2014 2.06

2015.8 10/14/2015 2.05 11/22/2015 2.02 12/15/2015 1.78 11/20/2015 1.99

2016.1 1/18/2016 1.88 2/10/2016 1.80 2/17/2016 1.88 2/8/2016 1.75
Methodology 9

EXPLANATION

Finite Difference Slope Approximation, 1932–2016

95 percent confidence band

Coastal Louisiana

Land area change rate, in square kilometers per year

-100

-80

-60

-40

-20

0

Year

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Figure 4. Finite-difference approximation of land area change rates through time in coastal Louisiana, 1932–2016; 

negative measurements indicate a net land loss rate, whereas positive measurements indicate net land gain rates. 

See table 3 for specific values.
laf170791_fig 05

EXPLANATION

Finite Difference Slope Approximation, 1932–201695 percent confidence band

Atchafalaya Delta

Land area loss rate,

in square kilometers per year

-2 -10123

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Barataria

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

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Breton So

-10 -9 -8 -7 -6 -5 -4 -3 -2

1930 1940 1950 1960 1970 19

Calcasieu/Sabine

-15 -10 -505

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Land area loss rate,

in square kilometers per year

Mermentau

-10 -8 -6 -4 -20

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Mississippi Riv

-15 -10 -505

1930 1940 1950 1960 1970 19

Pontchartrain

-10 -8 -6 -4 -20

Land area loss rate,

in square kilometers per year

Year

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Teche/Vermilion

-6 -4 -2024

Year

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020

Terrebon

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

Year

1930 1940 1950 1960 1970 19

Figure 5. Finite-difference approximation of land area change rates through time in coastal Louisiana by hydrologic basin (as defined by the LouisiaPlanning, Protection and Restoration Act Program, n.d.), 1932–2016; negative measurements indicate land loss, whereas positive measurements indicfor specific values.
Table 3. Finite-difference approximation estimates of long-term wetland change rates including standard error (SE) estimates for each hydrologic bfrom 1932 to 2016. Units are in square kilometers per year.

Atchafalaya Delta Basin Barataria Breton Sound Calcasieu 

Year Change rate

per year

1 SE

low

1 SE

high

Change rate

per year

1 SE

low

1 SE

high

Change rate

per year

1 SE

low

1 SE

high

Change rate

per year

1 SE

low

1 SE

high

Chang

per 

1932 -0.40 -1.69 0.88 -6.82 -13.28 -0.16 -4.05 -5.82 -2.31 -9.45 -13.26 -5.51 -1956 -0.13 -0.97 0.71 -12.43 -15.14 -9.75 -4.42 -5.48 -3.34 -9.92 -12.21 -7.67 -1973 0.47 -0.26 1.16 -21.66 -25.56 -17.87 -5.47 -6.41 -4.48 -8.72 -10.91 -6.55 -1975 0.57 -0.13 1.23 -22.89 -26.53 -19.41 -5.66 -6.57 -4.71 -8.33 -10.46 -6.25 -1977 0.67 -0.01 1.31 -24.01 -27.31 -20.79 -5.86 -6.74 -4.93 -7.90 -9.95 -5.90 -1985 1.06 0.43 1.67 -25.34 -27.96 -22.71 -6.65 -7.47 -5.81 -5.91 -7.74 -4.10 -1988 1.19 0.57 1.80 -24.36 -27.04 -21.66 -6.93 -7.74 -6.11 -5.11 -6.89 -3.33 -1990 1.27 0.66 1.87 -23.25 -25.95 -20.50 -7.10 -7.90 -6.29 -4.59 -6.34 -2.83 -1995 1.44 0.85 2.04 -18.96 -21.49 -16.40 -7.44 -8.23 -6.66 -3.45 -5.12 -1.80 -1998 1.52 0.93 2.12 -15.51 -17.68 -13.31 -7.59 -8.36 -6.83 -2.91 -4.51 -1.32 -1999 1.54 0.94 2.15 -14.27 -16.35 -12.17 -7.63 -8.40 -6.85 -2.76 -4.35 -1.17 -2002 1.60 0.95 2.24 -10.51 -12.53 -8.49 -7.71 -8.56 -6.88 -2.39 -4.10 -0.67 -2004 1.62 0.93 2.32 -8.11 -10.39 -5.85 -7.75 -8.67 -6.84 -2.21 -4.13 -0.33 -2006 1.64 0.89 2.40 -5.93 -8.67 -3.23 -7.77 -8.77 -6.77 -2.09 -4.26 0.01 -2008 1.65 0.83 2.47 -4.05 -7.35 -0.84 -7.78 -8.88 -6.67 -2.02 -4.44 0.33 -2009 1.65 0.80 2.50 -3.25 -6.83 0.22 -7.78 -8.93 -6.63 -2.00 -4.55 0.46 -2010 1.66 0.78 2.53 -2.56 -6.41 1.15 -7.78 -8.98 -6.59 -1.98 -4.66 0.56 -2013 1.66 0.73 2.59 -1.18 -5.55 3.05 -7.78 -9.07 -6.51 -1.96 -4.86 0.82 -2014 1.66 0.72 2.61 -0.96 -5.42 3.35 -7.78 -9.08 -6.50 -1.96 -4.90 0.85 -2015 1.66 0.72 2.61 -0.85 -5.34 3.51 -7.78 -9.09 -6.49 -1.96 -4.92 0.87 -
Table 3. Finite-difference approximation estimates of long-term wetland change rates including standard error (SE) estimates for each hydrologic bafrom 1932 to 2016. Units are in square kilometers per year.—Continued Mississippi River Delta Basin Pontchartrain Basin Teche/Vermilion Basin Terrebonne Basin 

Year Change rate per year 1 SE low 1 SE high Change rate per year 1 SE low 1 SE high Change rate per year 1 SE low 1 SE high Change rate per year 1 SE low 1 SE high Chang

per 

1932 -8.71 -13.09 -4.38 -6.29 -6.69 -5.88 -1.57 -3.61 0.45 -7.62 -15.30 0.00 -521956 -9.61 -11.44 -7.78 -6.29 -6.69 -5.88 -2.09 -2.99 -1.19 -15.25 -18.58 -11.84 -671973 -5.91 -8.43 -3.34 -6.29 -6.69 -5.88 -3.38 -4.54 -2.22 -24.29 -28.73 -19.82 -821975 -4.84 -7.18 -2.45 -6.29 -6.69 -5.88 -3.59 -4.69 -2.50 -25.10 -29.26 -20.91 -831977 -3.70 -5.85 -1.47 -6.29 -6.69 -5.88 -3.80 -4.81 -2.78 -25.76 -29.60 -21.89 -831985 0.26 -1.51 2.07 -6.29 -6.69 -5.88 -4.02 -4.88 -3.18 -25.61 -28.84 -22.43 -781988 1.31 -0.49 3.14 -6.29 -6.69 -5.88 -3.83 -4.70 -2.98 -24.33 -27.62 -21.14 -741990 1.79 -0.04 3.65 -6.29 -6.69 -5.88 -3.60 -4.48 -2.75 -23.14 -26.46 -19.89 -701995 2.02 0.31 3.74 -6.29 -6.69 -5.88 -2.71 -3.52 -1.93 -19.28 -22.35 -16.27 -591998 1.49 -0.04 2.99 -6.29 -6.69 -5.88 -1.99 -2.70 -1.29 -16.51 -19.19 -13.82 -521999 1.21 -0.24 2.64 -6.29 -6.69 -5.88 -1.72 -2.41 -1.05 -15.55 -18.14 -12.99 -502002 0.17 -1.23 1.57 -6.29 -6.69 -5.88 -0.91 -1.59 -0.24 -12.73 -15.31 -10.16 -432004 -0.62 -2.21 0.96 -6.29 -6.69 -5.88 -0.40 -1.17 0.37 -11.01 -13.88 -8.14 -392006 -1.42 -3.30 0.46 -6.29 -6.69 -5.88 0.08 -0.81 0.97 -9.49 -12.84 -6.12 -352008 -2.18 -4.40 0.06 -6.29 -6.69 -5.88 0.49 -0.56 1.55 -8.21 -12.17 -4.26 -322009 -2.52 -4.93 -0.09 -6.29 -6.69 -5.88 0.67 -0.46 1.81 -7.68 -11.96 -3.43 -312010 -2.82 -5.39 -0.24 -6.29 -6.69 -5.88 0.82 -0.38 2.03 -7.23 -11.79 -2.66 -302013 -3.45 -6.35 -0.53 -6.29 -6.69 -5.88 1.13 -0.22 2.49 -6.34 -11.45 -1.20 -282014 -3.55 -6.50 -0.58 -6.29 -6.69 -5.88 1.18 -0.19 2.56 -6.20 -11.41 -0.96 -282015 -3.61 -6.59 -0.60 -6.29 -6.69 -5.88 1.21 -0.18 2.60 -6.12 -11.37 -0.84 -28
Discussion 13

Results

Land Area Changes 

These analyses show that coastal Louisiana has 

experienced a net land area change of approximately -4,833 km2

(modeled estimate: -5,197 +/- 443 km2) from 1932 to 2016 

(fig. 2, table 1), roughly the size of the land area of the State of 

Delaware. This net change in land area amounts to a decrease 

of approximately 25 percent of the 1932 land area. Although 

this decrease in net land area is pervasive throughout much of 

the coast and the time period analyzed, the land area of recent 

data points (2013–16) is approximately equivalent and, in some 

cases, slightly greater than that of the 2010 estimate (Couvillion 

and others, 2011). 

The model which best approximated the coastwide net 

land area change is similar to that of a third order polynomial 

(edf = 2.903) (R2=0.923) (fig. 2). Within these data, 2005 and 

2008 land area data from hurricane-induced effects are evident 

as low outliers. Also evident is a perceived “stability” in 

coastwide net land area in recent years. 

All basins, with the exception of Atchafalaya Delta 

Basin, have experienced a net decrease in wetland area during 

the period of observation (1932–2016) (fig. 3). In terms of 

total area, Terrebonne Basin has experienced the greatest 

decrease in wetland area (-1,302 km2 observed; -1,352 +/- 

136 km2 modeled), followed by Barataria Basin (-1,120 km2

observed; -1,177 +/- 106 km2 modeled), Calcasieu-Sabine 

Basin (-517 km2 observed; -578 +/- 100 km2 modeled), 

Mermentau Basin (-488 km2 observed; -500 +/- 90 km2

modeled), Pontchartrain Basin (-472 km2 observed; -529 

+/- 30 km2 modeled), Breton Sound Basin (-426 km2 observed; 

-489 +/- 49 km2 modeled), Mississippi River Delta Basin 

(-375 km2 observed; -401 +/- 75 km2 modeled), and TecheVermilion Basin (-149 km2

 observed; -174 +/- 37 km2 modeled) 

(table 1). Atchafalaya Delta Basin experienced an increase 

(+16 km2 observed; +51 +/- 39 km2 modeled) in total land area 

across the entire period of record (table 1). As a percent of 

starting area, Mississippi River Delta Basin has experienced 

the greatest percentage decrease in wetland area (-55 percent 

observed; -57 percent modeled), followed by Breton Sound 

Basin (-38 percent observed; -43 percent modeled), Barataria 

Basin (-29 percent observed; -31 percent modeled), Terrebonne 

Basin (-29 percent observed; -30 percent modeled), CalcasieuSabine Basin (-24 percent observed; -27 percent modeled), 

Mermentau Basin (-20 percent observed and modeled), 

Pontchartrain Basin (-17 percent observed; -18 percent 

modeled), and Teche-Vermilion Basin (-10 percent observed; 

-12 percent modeled). Atchafalaya Delta Basin was the only 

basin to experience an increase (+3 percent observed; +9 

percent modeled) in land area, as a percentage of starting area, 

across the entire period of record (table 1).

Change in Land Change Rates through Time

Trend analyses from model fits indicate that coastwide 

rates of wetland change have varied from -83.5 +/- 11.8 square 

kilometers per year to -28.01 +/- 16.37 square kilometers per 

year. Excluding the high rates of wetland loss due to the 2005 

and 2008 hurricanes (Katrina, Rita, Gustav, and Ike), recent 

wetland loss rates have decreased from the peak loss rates 

observed in the 1970s which are known to have exceeded 

80 square kilometers per year (km2/yr) (Britsch and Dunbar, 

1993; Barras and others, 1994, 2003). This analysis indicates 

wetland change rates averaged -83 km2/yr during the 1973–78 

time period, followed by a steady reduction in the rate since 

that time (fig. 4). Britsch and Dunbar (1993) and Barras and 

others (2008) observed a similar trend of decreasing loss 

after 1978.

The rate of wetland change in most basins has changed 

drastically over the period of record. Only two basins, 

Mermentau and Pontchartrain, were best fit by a linear model 

(edf = 1), suggesting that the rate of change has not changed 

significantly over the period of record in those basins (fig. 5). 

The remaining basins were best fit by non-linear functions. 

Barataria, Terrebonne, and Teche-Vermilion Basins follow 

a similar pattern to that of the coastwide trend of loss rates 

increasing to a peak in the late 1970s, followed by a reduction 

in loss rates since that time. In Breton Sound Basin, wetland 

loss rates have continued to increase and have only recently 

begun to suggest a decrease in that rate (fig. 5). CalcasieuSabine Basin experienced the highest rates of wetland loss 

prior to the 1970s, with rates slowly decreasing since that 

time, with the exception of hurricane-induced losses in 2005 

and 2008. The Mississippi River Delta Basin experienced a 

reduction in wetland loss rate since the 1960s, reaching a point 

of wetland gain, only to be followed by a negative trend due 

to the effects of Hurricane Katrina in 2005 (Barras, 2006). 

Finally, the Atchafalaya Delta Basin experienced an increasing 

land area trend (positive land change slope) since 1961 (fig. 5). 

Prior to 1961, this basin was initially on a negative trajectory; 

however, following the opening of the Wax Lake Outlet in 

1942, sediment deposition increased, and a subaerial active 

delta emerged after the flood of 1973.

Discussion 

The spatial and temporal patterns of wetland change 

observed in this assessment reveal a dynamic landscape 

changing as a result of the complex and often interactive 

effects of natural and human-induced processes. Coastwide 

total net land area suggests an increase in land area by 2015 

as compared to the previous estimate in 2010 (Couvillion 

and others, 2011); however, these values are well within the 

standard error associated with the datasets and, as such, are 

not necessarily indicative of a true change in the long-term 

trend. This increase in coastwide net land area may not yet 
14 Land Area Change in Coastal Louisiana (1932 to 2016)

be interpreted as “gain” because the persistence of said areas 

has yet to be assessed and much of this may be interpreted 

as recovery from the ephemeral lows associated with the 

hurricanes of 2005 and 2008; however, specific areas of gain 

can be detected in the dataset, many of which are showing 

persistence throughout the newly added data points. 

It is important to note that there is a difference between 

net land area change (figs. 2 and 3, table 1) and persistent 

losses and gains (mapped dataset) and long term trends (figs. 4 

and 5, table 3). Classification of an area as “loss” or “gain” is 

dependent on persistence criteria, where 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 

effect occurs because persistent losses in a particular location 

can be offset by transitory gains in another.

This analysis has fostered an ability to examine 

variability in rates of wetland change through time by fitting 

data with non-linear models. Most of the models fit the 

coastwide and basin-level land area change data well, with 

a couple of notable exceptions. In the Atchafalaya Delta 

Basin, a basin in which water levels are known to greatly 

influence assessments, the R2 of the model is 0.245 (fig. 3). 

Mississippi River Delta Basin, another basin in which water 

levels affect our ability to assess land area, also had one of 

the lower R2 values (R2 = 0.609) (fig. 3). The two Chenier 

Plain basins, Calcasieu-Sabine (R2 = 0.659) and Mermentau 

(R2 = 0.522), contain several water-control structures and are 

therefore also subject to variability. Barataria, Breton Sound, 

Pontchartrain, and Terrebonne Basins all have an R2 value at 

or exceeding 0.9.

This analysis has shown decreasing rates of wetland 

loss after the 1970s. The possible causes of this decline in 

land change rate are as numerous as the causes of wetland 

change itself. One of the first possible causes relates to the 

loss of wetlands. Trends have shown that as wetlands are lost, 

there are fewer wetlands remaining to be lost, and as such, 

the rate of wetland loss will decrease. Although there is still 

a substantial area of wetlands remaining, at some point the 

influence of this artifact should be considered. Similarly, many 

of the wetlands in the most precarious locations have already 

been lost. What remains are wetlands in less “at-risk” positions 

in the landscape which are consequently less vulnerable and 

contribute to this reduction in loss rate; however, even stable 

wetlands may be impacted by a single event or cumulative 

episodic events over time (Morton and Barras, 2011).

The lack of major storms since 2008 is likely the most 

influential factor causing the decrease in net loss rates. This 

period of relative calm has led to fewer disturbances in the 

form of wave energy, thereby reducing erosion-induced losses. 

The storm hiatus also allowed vegetation to colonize new 

areas of shallow water bodies or to reestablish once vegetated 

areas. Some of these areas may have begun life as FAV but 

may have since attached to the substrate (Russell, 1942). 

Oil and gas extraction in the Louisiana coastal zone 

began in 1926 and peaked in 1969 (Ko and Day, 2004). 

Infrastructure, such as canals, pipelines, and other features, 

contributes to wetland loss not only through direct removal 

of material but also by altering hydrologic flow. This altered 

hydrology can lead to indirect effects such as the propagation of 

wave energy and salinity into interior wetland areas. Following 

this peak, oil and gas activities started to move from the shallow 

wetland areas in one of two directions: inland or far offshore. 

As a result of this shift, Morton and others (2005) concluded 

that the decrease in the rate of land loss in Barataria Basin was 

attributable to a decrease in the rate of hydrocarbon production 

in that area after 1974. 

Another contributing factor involves a reduction in 

tectonic activity and subsidence due to active faulting 

(Dokka, 2006; Kolker and others, 2011). The extent to which 

submergence due to natural versus anthropologically influenced 

subsidence is poorly understood. Regardless of the causes, 

some evidence is beginning to point toward a reduction in 

the rate of subsidence. Kolker and others (2011) observed 

a decrease in subsidence rates which corresponds with the 

decrease in the rate of wetland loss. 

Finally, restoration activities, such as marsh creation and 

barrier island nourishments, can be observed in the datasets 

which constitute this analysis. Although these projects may 

have small effects in the coastwide total land area numbers, in 

specific areas, they have substantially changed the composition 

and configuration of the local landscape. These projects are 

in many cases building new land or sustaining existing land, 

again contributing to a reduction in loss rates. It is important 

to note that the effects of restoration projects are not always 

visible in the persistent change map because areas which were 

lost and then regained as a result of restoration do not meet the 

persistent change criteria. 

Conclusions

This assessment provides a comprehensive analysis 

of historical trends and rates of land area change in coastal 

Louisiana from 1932 to 2016. The primary improvements over 

past efforts are an improved statistical analysis allowing for 

the observation of rates other than linear and the inclusion of 

additional datasets for assessing coastal wetland change since 

2010 (Couvillion and others, 2011). This dataset provides the 

ability to better quantify the amount of wetland loss and the 

time period in which it was lost. This information will allow 

gradual loss patterns to be distinguished from losses due to 

episodic events such as hurricanes. The observed spatial and 

temporal patterns reveal a dynamic landscape changing as a 

result of the complex and often interactive effects of natural and 

human-induced processes.

The temporal frequency of land change provided by this 

study allows for further investigation of 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 will support the development of strategies 

to adapt to our changing environment.
References Cited 15

While recent trends have shown a reduction in the rate 

of wetland loss, it is important to note that past trends are not 

necessarily indicative of future change. Future disturbance 

events such as a major hurricane impact could change the 

trajectory of the rates. Sea-level rise is projected to increase 

at an exponential rate, and that would also expedite the rate of 

wetland loss. (IPCC, 2013; Doyle and others, 2015).

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Publishing support provided by

Lafayette Publishing Service Center

For more information concerning this publication contact:

Director, USGS, Wetland and Aquatic Research Center

700 Cajundome Blvd. Lafayette, LA 70506

https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc

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Atchafalaya Bay

Atchafalaya River

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Blanche Bay

West Cote 

Blanche Bay

Vermilion Bay

Wax Lake Outlet

Marsh

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Gulf Intracoastal Waterway

Lac des 

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LF OF MEXICO

Wax Lake Delta

Atchafalaya Delta

Intracoastal

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Montegut

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Lost Lake Four League

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Terrebonne Ba

Couvillion and others—Land Area Change in Coastal Louisiana (1932 to 2016)—Scientific Investigations Map 3381

ISBN 978-1-4113-4151-7

9 7 81411 341517

ISSN 2329-1311 (print)

ISSN 2329-132X (online)

https://doi.org/10.3133/sim3381