The use of geospatial technologies to monitor surface water Department of Zoology, UNH Cooperative Extension Center for Freshwater Biology, University.

The use of geospatial technologies to monitor surface water

Department of Zoology, UNH Cooperative ExtensionCenter for Freshwater Biology, University of New Hampshire

NEAEB Annual Meeting, March 29-31, 2006

Shane Bradt

• What are geospatial technologies?

• “Hypothetical” situations for using GST to monitor surface waters

• Where did these ideas come from?

• Any other ideas . . .

Geographic Positioning System (GPS)

Geographic Information System (GIS)

Remote Sensing (RS)

How does GPS work?How does GPS work?

Earth

Space

1. The receiver picks up the signals from the satellites

GPS

How does GPS work?How does GPS work?

Earth

Space

2. Travel time of signal from satellite used to calculate distance

0.075 sec = 14,000 mi

0.059 sec = 11,000 mi

0.07

0 se

c =

13,0

00 m

i

0.065 sec = 12,000 mi

3. Receiver triangulates to determine position of the receiver

GPS

How does GPS work?How does GPS work?

3. Receiver triangulates to determine position of the receiver

GPS

How does GPS work?How does GPS work?

3. Receiver triangulates to determine position of the receiver

GPS

How does GPS work?How does GPS work?

3. Receiver triangulates to determine position of the receiver

GPS

How does GPS work?How does GPS work?

3. Receiver triangulates to determine position of the receiver

You are

here!

GPS

Geographic Positioning System (GPS)Points, Lines, Areas

Chemical, Physical and

Biological Activities

RS

Visual representation Thematic representation

RS

Geographic Positioning System (GPS)

Remote Sensing (RS)

Points, Lines, Areas

Imagery, Topography

Remote SensingGPS

GIS Data Sources

Paper Maps

GIS

What makes GIS work?

• GIS SOFTWARE - Stack different data layers• GIS SOFTWARE - Knows how features are

related to each other spatially

GIS

Geographic Positioning System (GPS)

Geographic Information System (GIS)

Remote Sensing (RS)

Points, Lines, Areas

Imagery, Topography

Points, Lines, Areas, Imagery, Topography

Spatial information linked to tabular data

Be aware of error inherent in data

Questions you need to ask yourself

• What is your goal? – Monitor many lakes over long time scales

• What features would you like to monitor?– Water clarity

• How frequently do you need measurements?– Several times a year

• What is the spatial scale you need?– 30 meters

• What is your goal? – Monitor many lakes over long time scales

• What features would you like to monitor?– Water clarity

• How frequently do you need measurements?– Several times a year

• What is the spatial scale you need?– 30 meters

“Hypothetical” situation #1

Long term change – Secchi disk depth

Landsat TM

GISGPSRS

Long term change – Secchi disk depth

Landsat TM

GISGPSRS

Long term change – Secchi disk depth

Landsat TM

GISGPSRS

• What is your goal? – Detail water quality a single large lake

• What features would you like to monitor?– Chlorophyll

• How frequently do you need measurements?– Once

• What is the spatial scale you need?– 1 km

“Hypothetical” situation #2

(g l-1)

GISGPSShort term: chlorophyll

Chl 2 Chl 3

Short term: chlorophyll

Chl 1

MODIS

GISGPSRS

Long term: chlorophyll GISGPSRS

2 Jun 05

Chlorophyll data from lake collections

Method for determiningchlorophyll from satellite

18 May 05 7 Jun 05 9 Jun 05 14 Jun 05 17 Jun 0526 May 0513 May 058 May 05

• What is your goal? – A RS method to detect many water quality features

• What features would you like to monitor?– Chlorophyll, CDOM, cyanobacteria, sediments

• How frequently do you need measurements?– Variable

• What is the spatial scale you need?– Small as possible

“Hypothetical” situation #3

Wavelength (nm)

400 450 500 550 600 650 700 750

Ref

lect

ance

0

2

4

6

8

10

12FB-12 FB-1 S-1 S-14

DRS on-lake

GPSRSShort term: chl, phyco, CDOM, sediments

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

400 425 450 475 500 525 550 575 600 625 650 675 700 725

Wavelength (nm)

Rrs

PhycocyaninFluorescence

ScatteringCDOM

Chlorophyll a PhycocyaninFluorescence

ScatteringCDOM

Chlorophyll a

Chl a = 61.9 g l-1

SDD = 0.6 mCDOM = 28.4 CPU

Chl a = 1.4 g l-1

SDD = 6.4 mCDOM = 7.4 CPU

Short term: chl, phyco, CDOM, sediments GPSRS

Wavelength (nm)

400 450 500 550 600 650 700 750

Ref

lect

ance

0

1

2

3

4

5

6

7

8

Wavelength (nm)

400 450 500 550 600 650 700 750

Re

fle

cta

nc

e

0

2

4

6

8

10

12

Wavelength (nm)

400 450 500 550 600 650 700 750

Re

fle

cta

nc

e

0

2

4

6

8

10

Wavelength (nm)

400 450 500 550 600 650 700 750R

efl

ec

tan

ce

0

2

4

6

8

10

12

Short term: chl, phyco, CDOM, sediments GISGPSRS

• What is your goal? – Describe watershed characteristics for a water body

• What features would you like to monitor?– Watershed extent, landcover, soils, topography

• How frequently do you need measurements?– Every few years

• What is the spatial scale you need?– Depends on feature

“Hypothetical” situation #4

Topography: DEM GISRS

Hillshade: DEM GISRS

Topography: DEM GISRS

Watershed: DEM GISRS

Slope: DEM GISRS

Severe slope: DEM GISRS

Landcover: Landsat GISRS GPS

Impervious surfaces: Landsat GISRS

Impervious surfaces: Landsat GISRS

Soils: Soil Surveys GIS

Where did I get these ideas?• Introduction:

– UNH Cooperative Extension – Myself, Jeff Schloss

• Hypothetical #1: Monitor water clarity in many lakes – Upper Midwest Regional Earth Science Applications Center

(Minnesota, Michigan and Wisconsin)

• Hypothetical #2: Monitor chlorophyll in a large lake– My PhD research, USGS Salt Lake City, Utah State University

• Hypothetical #3: RS method of describing lakes– My PhD research, University of Nebraska Lincoln, EPA Region 1

• Hypothetical #4: Describing watershed features– UNH Cooperative Extension GIS course – Watershed Analysis using Spatial Analyst in ArcGIS 9.1

Where did I get these ideas?• Introduction:

– UNH Cooperative Extension – Myself, Jeff Schloss

• Hypothetical #1: Monitor water clarity in many lakes – Upper Midwest Regional Earth Science Applications Center

(Minnesota, Michigan and Wisconsin)

• Hypothetical #2: Monitor chlorophyll in a large lake– My PhD research, USGS Salt Lake City, Utah State University

• Hypothetical #3: RS method of describing lakes– My PhD research, University of Nebraska Lincoln, EPA Region 1

• Hypothetical #4: Describing watershed features– UNH Cooperative Extension GIS course – Watershed Analysis using Spatial Analyst in ArcGIS 9.1

Your turn . . .