a spatial-temporal analysis of wetland loss and ... · 1. develop improved wetland mapping and...

A Spatial-Temporal Analysis of Wetland Loss and

Vulnerability: Needs for Improved

Mapping and Monitoring of Wetland Dynamics for

Improved Resilience and Delivery of Ecosystem

Services in the Mid-Atlantic Region

In-Young Yeo a (with contribution from Quentin Stubbs a, e) M. Langb, C. Huanga, C. Jantzc, V. Thomasd, S. Princea, and M. Kearneya

a Department of Geographical Sciences, University of Maryland ; b USDA Forest Service Northern Research Station;

c Shippensburg University; d Virginia Tech; e USGS

Designing Sustainable Coastal Habitats

16-17 April 2013

Background: Wetlands in the CBW

The importance of

wetland systems are

recognized regionally,

nationally, and

internationally

(RAMSAR site).

The CBW has lost

over 60% of its

historic wetlands.

It is predicted that

existing wetlands are

at high risk for future

loss.

Risk Based on Historic Population/Construction

Data and 1980s NWI Wetland Density

Wetland Mapping Background Accurate, dynamic wetland maps can improve

society’s resilience to increasing

urbanization, population growth, and

climate change through

early detection

improved understanding of climate

change and LCLUC effects

enhanced management of wetlands to

target desired ecosystem services

Wetland hydroperiod (duration and

frequency of flooding and soil saturation at a

specified depth) is the most important abiotic

factor controlling wetland extent and function

Fall Spring

Hydroperiod

controls

Biota Vegetation

Water Quality

Soils

Wetland Mapping Background

Fundamental wetland data are lacking to conduct regional-scale

vulnerability assessment of wetlands and to identify hot spots, and key

drivers for wetland losses.

Available wetland maps are dated and do not represent wetland dynamics.

Water levels in wetlands can vary highly, in response to climate condition.

Rapid changes in land cover further confound wetland mapping in developing

areas.

Forested wetland maps are inaccurate, especially at moderate spatial

resolutions.

The vast majority of wetlands in the CBW are forested.

Forested wetlands continue to sustain high levels of loss.

Improved mapping of forested wetlands and wetland change is needed

to assess current impacts and vulnerabilities of wetlands to climate

and land cover change and to develop adaptation strategies.

1. Develop improved wetland mapping and change detection using remote-sensing data from multiple, complementary sensors at various temporal and spatial scales;

2. Study the socioeconomic, policy, and physical drivers of wetland change affecting wetland extent and function from regional to local scales, using existing data;

3. Assess the impacts of multiple environmental stressors (particularly the anthropogenic ones);

4. Quantify vulnerability of wetlands and wetland ecosystem services under multiple climate and land use change scenarios.

Research Objectives

The overall research design and

outcomes

(Part 1) Geospatial Analysis (obj 1) (Part 2) Impacts and Vulnerability

Assessment (obj 2&3)

(Part 3) Ecosystem Service Assessment (obj4)

Project benefits

Improved, consistent, recent wetland maps for

CBW – readily operational technique

Enhanced understanding of change drivers = greater

conservation of wetlands and ecosystem services

Near time tracking of wetland loss to enhance

regulatory abilities

Targeting for restoration and conservation

Improved parameterization of the Bay Model

Support for Ecosystem Markets

Greater understanding of climate change impacts

Progress and findings

Vulnerability Impact Assessment – regional

approach and case study

Innovation in mapping technique

Ecosystem service assessment – integrated

approach (literature review, numerical modeling,

and parameterization of existing model)

Vulnerability Impact Assessment: Wetland changes and their potential drivers – regional

assessment using existing dataset • What is the quantity of the wetland change over the last 30 years on

the Delmarva and CBW, measured by existing geospatial data sets?

• What physical and anthropocentric drivers of land use and land cover change are correlated with wetland loss?

• What information do the spatial and temporal distribution of wetland permits and wetland loss patterns provide regarding the influence of wetland change drivers and the impacts of the wetland permitting system?

• What wetlands, watersheds, and counties are most vulnerable to wetland loss due to physical, socioeconomic and policy drivers of wetland change?

(c)Wetland Loss (In Red)

between 1992-2006 (CCAP)

(d) Hot Spot and Point Density of Wetland Permits issued by the

State of MD, MDE

(b) Forest and Agricultural Conversion in the CBW between

1990 and 2000 (Jantz et al., 2005)

(a) Case study site

Regional assessment: land cover data

available on wetlands in the CBW The National Wetlands Inventory

Outlier Detection Analysis (Neilson et al.,

2008)

Land Cover Datasets

The National Land Cover Dataset

(NLCD)

The Coastal Change Analysis Program

(CCAP)

The Chesapeake Bay Watershed Land

Cover Data Series (CBLCD)

All of our Datasets cover the entire study

area, except for the CCAP

Area CCAP does cover accounts for

~98% of the wetlands in the study area.

Temporal Extent

Each Dataset covers a range of different time periods, both yearly and seasonally. NWI – 1977 to 1998

NLCD – 1992 (unusable for wetlands), 2001, 2006

CCAP – 1992 (DE, MD, VA) 1996, 2001, 2006

CBLCD – 2001 baseline, 2006, 1992 and 1984 retroactively

ODA – 2000/2001 (baseline – NWI map)

Land Cover Mapping

Classification and Change Detection

All of the land cover products used Classification and Regression Tree (CART) approach

Change identification for updates

CCAP and CBLCD – MDA Federal’s Cross Correlation Analysis

NLCD – Multi-Index Integrated Change Analysis (MIICA)

Outlier Detection Method – major, minor, or no change in wetlands (using z score from Landsat spectra, similar to the cross correlation analysis) since NWI

Land Cover Mapping

All of these datasets incorporate ancillary data Not as specific about how data was used

DEM, NWI

NCLD uses extensive independent data to help map urban land cover Independently generated percent imperviousness layers,

NOAA city lights, tigerline roads

CCAP also uses an impervious surface layer and roads layer, but the roads are not as detailed in final map

NLCD uses a minimum mapping unit to preserve logic of land cover Urban land cover– 5 pixels

Agricultural land cover – 32 pixels

All other classes – 12 pixels

The CBLCD corrected for an overabundance of coastal emergent wetlands

Minimum mapping

unit and roads

example

Total Wetland Change by Land Cover

Product, 2001-2006 Area (Hectares) C-CAP NLCD CBLCD

Total Wetland Area

(2001)

785489.49 758100.60 779748.75

Total Wetland Area

(2006)

777587.58 750048.84 773297.19

Net Change -7901.91 -8051.76 -6451.56

Percent Change -1.00598 -1.06209 -0.82738

Wetland Loss

Development 1226.16 2367.27 1074.33

Agriculture 4188.15 2050.02 3564

Forest 669.69 3973.5 565.92

Grass/Scrub 769.23 2358.63 800.55

Bare 491.13 328.23 431.91

Water 2409.66 2334.24 2044.62

Total 9754.02 13411.89 8481.33

Wetland Gain

Development 28.44 0 2.34

Agriculture 68.67 1558.17 121.32

Forest 848.07 1950.66 872.91

Grass/Scrub 544.32 1032.93 486

Bare 34.83 25.83 34.2

Water 322.56 792.54 505.71

Total 1846.89 5360.13 2022.48

Net Change

Development -1197.72 -2367.27 -1071.99

Agriculture -4119.48 -491.85 -3442.68

Forest 178.38 -2022.84 306.99

Grass/Scrub -224.91 -1325.7 -314.55

Bare -456.3 -302.4 -397.71

Water -2087.1 -1541.7 -1538.91

Total -7907.13 -8051.76 -6458.85

Geographical distribution of

wetland changes

NWI 2007 Delaware Updates

The NWI has been updated for the year of 2007

The FWS released a status and trends report

covering 1992-2007, based on the NWI update

Comparison of the CCAP and CBLCD over 1992-

2006 with the FWS 1992-2007 report

FWS Report Comparison

FWS report (2007) 83,877 acres emergent wetland

72,839 acres of estuarine emergent wetland

10,938 acres of palustrine emergent wetland

225,546 acres of forested wetland

CCAP (2006) 83,453 acres emergent wetland

75,532 acres estuarine emergent

7,921 acres palustrine emergent

174,001 acres forested wetland

CBLCD (2006) 79,445 emergent wetlands

176,068 Forested wetlands

CCAP and FWS agreement on emergent wetlands indication that CBLCD overcorrected for emergent wetlands?

Spatial agreement between Land

Cover and NWI

• ~71% of NWI polygons agree with the

location wetlands in CCAP and CBLCD

• CCAP agrees with any NWI polygon: 83%

Emergent wetlands agree with NWI (86% for

estuarine), 65% Forested wetlands, 38%

Scrub/Shrub wetlands

• CBLCD agrees with any NWI polygon: 85%

emergent wetlands, 61% forested wetlands

FWS Report Comparison on

change (1992-2007)

Total Wetland Change: FWS Report – 3893.4 acres lost, 767.5 acres gained

CCAP – 8453.87 acres lost, 1821.64 acres gained

CBLCD – 7085.5 acres lost, 514.84 acres gained

FWS Change Estuarine wetland loss to – 84% open water, 11% intertidal

unconsolidated shore

Palustrine wetland loss to – 32% Agriculture, 32% Development, 18% Altered/Barren land

CCAP change Estuarine wetland loss to – 53% open water, 18% cultivated land, 8%

Development

Palustrine wetland loss to – 52% cultivated land, 16% scrub shrub, 14% forest, 5% development

Earlier land cover products (1992) are not reliable? (under-investigation- land cover vs. land use/cover)

NWI and Outlier Detection

Analysis The Outlier Detection Analysis was developed by

Nielsen et. al.(2008) as an update to the NWI, using

multiseasonal Landsat ETM+ images from 2000

Identify hotspots & estimate total amount of

wetland changes at different scales

Validation exercise resulted in an 89.9 percent

accuracy assessment with a Kappa score of 0.779.

The method accurately identified areas of

wetland change 89.9 percent of the time;

There is substantial agreement between model

predictions of wetland change and on-the-

ground evidence for change.

Reliably discerned “no change” in wetland pixels

from “minor change,” and “minor” from “major”

change.

Change types in

ODA analysis

Wetland Change in the Chesapeake

Nielsen, E. M., S. D. Prince & G. T. Koeln (2008)

Upper

Potomac

Blackwater

NWR

Norfolk

Upper Potomac—few wetlands

> majority are palustrine (99.7%)

> 8% show major change

> 12% show minor change

> 80% show no change

Blackwater—many wetlands

> majority are palustrine (55%)

> 45% estuarine




Norfolk—moderate wetlands, high change

> majority are palustrine (65%)

> 35% estuarine




NWI Aggregation

Upper Potomac, shows wetland

change

> 20 HUC-11 watersheds

> 9.53 km^2 of wetlands

> 2 show major change

> 7 show minor change

> 11 show no change

Blackwater, minimal change


> 219 km^2 of wetlands

> none show major change

> 1 shows minor change

> 6 show no change

Norfolk, minimal change


> 74 km^2 of wetlands

> none show major change

> 1 shows minor change

No Change

Change

Minor Change

HUC-11 Watersheds

HUC-11

Aggregations

Upper Potomac

> Loudoun, VA and

Mongtomery, MD

> 45% of pixels show change

> 10% major, 35% minor

Blackwater

> Dorchester County, MD

> 14% of pixels show change

> All minor

Norfolk

> Cities of Norfolk, Portsmouth,

portions of Suffolk

> very few (<1%) wetland pixels

show change

No Change Minor Change Major Change

County

Aggregations

NWI Categories

and Wetland Area

HUC-11

Watersheds and

Counties

Physiographic

Provinces

Preliminary Results

Net Wetland Loss between 1992-2006 (Acres) Watershed (HUC-8) NLCD CCAP CBCLCD Pocomoke-W Lower Delmarva 204.19 -8.42 -6.55 Nanticoke 39.02 -5.48 -6.13 Tangier 46.71 -5.18 -5.48 Chincoteague 53.38 -5.07 -4.41 E Lower Delmarva 19.50 -2.79 -2.57 Broadkill-Smyrna 16.94 -2.31 -1.80 Choptank 33.40 -1.82 -1.59 Chester-Sassafras 48.34 -1.14 -0.90 Brandywine Christina 10.65 -1.03 -0.99

Wetland Loss between

1992-2006 (CCAP)

Wetland Loss (In Red)


Decennial Census Total Housing Units

per Acre at HUC 8 Watershed Scale

Wetland Loss (In Red)


Hot Spot and Point Density of Wetland Permits issued by the State of MD, MDE

2. Developing Technologies & Techniques

Landsat historic record (1984-Present)

Advanced geometric and radiometric correction

Knowledge from North American Forest Dynamics

Project: Vegetation Change Tracker (Co-I Huang)

0

2

4

6

8

10

12

85 87 89 91 93 95 97 99

Year (19xx)

IFZ

Masking and

normalization Masking and




normalization

LTSS

Masks

Time series

analysis

Disturbance

products

Indices

Yearly Information on Vegetation Change from 1984- Present

2.Developing Technologies &

Techniques

Wetness Change Tracker!

Monitoring hydroperiod in

response to weather and

land cover change

DEM based topographic

wetness indices

complement optical data

Implications for climate

change

Monitoring the Connection between Weather and Hydroperiod

with Landsat Based Wetness Trends through Time

Note that different trends in wetland gains are probably due to natural

versus human based drivers and differences amongst human based

restoration implementation practices.

2. Innovative Mapping Technique Mapping forested wetlands and their change dynamics in response to

variable weather conditions (Landsat based approach)

Spectral

Index Formula Reference

NDVI (Band 4 – Band 3) / (Band

4 + Band 3) Rouse et al., 1974

NDWI-

1

(Band 4 – Band 5) / (Band

4 + Band 5) Gao, 1996

NDWI-

2

(Band 3 – Band 5) / (Band

3 + Band 5)

Rogers &

Kearney, 2004

TCWG

D TCW - TCG In this study

TCA Arctan (TCG / TCB ) Powell et al., 2010

IVR Band 5 / Band 2 Ozesmi & Bauer,

2002

IR (Band 5 – Band 7) / (Band

5 + Band 7) Ruan et al., 2007

Data pre-processing

Mapping inundation

dynamics

Landsat corrected

by LEDAPS

Landsat surface

reflectance

LiDAR 1 m

inundation

map

LiDAR

intensity

data

2007 Landsat reflectance

& spectral indices

2007 LiDAR 30 m

inundation

percentage map

Landsat-based

inundation model

2005, 2007, 2009 &

2010 Landsat Images

Predicted inundation percentage maps in

2005, 2007, 2009 & 2010

Spatial

aggregation

Model calibration,

validation & post-

adjustment

Model development

(Stepwise Regression Tree)

Fall Spring

Highly variable wetland hydrology

Spectral mixture with vegetation and soil



Feb. 2005 b. Mar. 2007 c.

Mar. 2007 d. Mar., 2009

(1) Results from reference image (2007, normal year)

(2) Results from other target years (2005, 2009, 2010)

Subpixel Inundation Percent (2009)

a. b.

c. SPOT imagery on Apr., 2005 d. SPOT imagery on Apr., 2010



a. Feb. 2005 b. Mar. 2007 c. Mar. 2009 d. Mar., 2010

(A) Inundation percentage maps for the catchment

(B) Total inundated area vs. the Palmer

seasonal drought index

(C) Total inundated area vs. Stream

discharge data

2. Innovative Mapping Technique Topographic metrics for improved mapping of forested wetlands

(LiDAR-based approach)

(A) Study site

(B) The overall design of the methodology

(C)Topographic index vs. products and forested

wetlands (a) the local terrain normalized relief; (b) enhanced topographic

wetness index (ETWI); (c)the relief enhance topographic wetness

index; (d) LiDAR intensity during a dry spring (e) LiDAR intensity

during average spring ; (f) false color near infrared aerial photograph

(collected coincident to e)

3. Ecosystem Service Assessment

Wetland function: Integrated approach 1. Regional Assessment for the CBW: use of regional models and existing

dataset and literature to assess the ability of wetlands to improve water quality

- Currently, regional water quality models (SPARROW, Chesapeake Bay

Watershed Model) for the CBW do not simulate natural wetland processes.

- Wetland function is based on the removal efficiency and it only applies to a

specific type of wetlands (e.g., constructed wetlands).

- We are in the process of compiling literature and field data to evaluate the

range of nutrient removal efficiency of wetlands, key functional drivers

affecting the removal efficiencies, and their applicability for the CBW

2. Simulation based approach at the local watershed: Choptank Watershed

- We are evaluating the effectiveness and accuracy of watershed process

model (Soil and Water Assessment Tool, SWAT) to simulate natural wetland

processes and its water quality improvement benefits at the watershed

scale.

(A) Study site (B) Calibration and validation of SWAT model

Thank you!

For additional information please contact In-Young at [email protected]

Physical Indicators

Variables

• Climate Change Data (Acquired)

– Palmer Drought Severity Index

– Temperature

– Precipitation

– Source: NOAA

• Sea Level Rise (Acquired)

– Mean Eustatic Sea level

– Inundation frequency

– Sources: SLAMM & PSMSL

• Hydrogeomorphology (HGM)

– Elevation and soil type (Acquired)

– Sources: USGS and USDA RCS

Indices (To be calculated)

HGM/LLWW

Slope

Proximity (Distance)

Wetland Loss

Land Cover Type

Areas: Urban and Protected

Density

Edges

Anthropogenic Indicators

Variables Demographics

Population Growth Housing Density Sources: US Census, Brown

University, and CBP (Acquired)

Wetland Permitting Records Total quantity of Permits Density of permits (by acre)

National Regional Letter of Permission Specific

Sources (Acquired) Federal:

US Army Corps of Engineers

State: MD MDE, VIMS, DE DNREC

Indices (To be calculated)

• Proximity (Distance) – Wetland permits

• land cover types

• pixels and patches of wetland loss

• urban areas

• shoreline

• protected areas

• Proportions – Wetland permits by

wetland type

– By population

– By housing density

a spatial-temporal analysis of wetland loss and ... · 1. develop improved wetland mapping and...

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