the yellowstone project talk...

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Remote sensing of riparian resources: Remote sensing of riparian resources: ethical considerations and the role of geographersethical considerations and the role of geographers

W. Andrew MarcusW. Andrew MarcusDepartment of GeographyDepartment of Geography

University of OregonUniversity of Oregon

Probe1 1 meter data, 8/03/99Probe1 1 meter data, 8/03/99MNF Image by W. A. MarcusMNF Image by W. A. Marcus

Collaborators and FundingCollaborators and Funding

•• Richard Aspinall, Montana State UniversityRichard Aspinall, Montana State University

•• Mark Fonstad, Texas State UniversityMark Fonstad, Texas State University

•• Carl Legleiter, UC Santa BarbaraCarl Legleiter, UC Santa Barbara•• Chuck Robertson, Idaho State UniversityChuck Robertson, Idaho State University

•• Photos: Carter Photos: Carter GowlGowl•• Field Assistants: Rob Field Assistants: Rob AhlAhl, Jim Rasmussen, Jim Rasmussen

Talk OrganizationTalk Organization

•• The Yellowstone projectThe Yellowstone project•• field area and methodsfield area and methods

•• mapping results: Inmapping results: In--stream habitats, stream habitats, depths, woody debris, vegetation, depths, woody debris, vegetation, wetlands & algaewetlands & algae

•• future researchfuture research•• My journey into ethical realmsMy journey into ethical realms

•• legal constraintslegal constraints•• military applicationsmilitary applications•• resource managementresource management

The Yellowstone ProjectThe Yellowstone ProjectOverarching goal: determine if HSRH imagery can be used to Overarching goal: determine if HSRH imagery can be used to map key environmental variables in complex stream settings.map key environmental variables in complex stream settings.

Soda Butte Creek, 9ssg68, Oct 10, 1999Soda Butte Creek, 9ssg68, Oct 10, 1999

From Wright et al., 2000From Wright et al., 2000

Remote mapping of streamsRemote mapping of streams

Some Personal HistorySome Personal History

MetalsMetals

ConcernsConcernsabout applications about applications

Talk OrganizationTalk Organization

•• The Yellowstone projectThe Yellowstone project•• field area and methodsfield area and methods

•• mapping results: Inmapping results: In--stream habitats, stream habitats, depths, woody debris, vegetation, depths, woody debris, vegetation, wetlands & algaewetlands & algae

•• My journey into ethical realmsMy journey into ethical realms•• legal constraintslegal constraints•• military applicationsmilitary applications•• resource managementresource management

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Advances due to fine spectral resolutionAdvances due to fine spectral resolution

cottonwood

sediment

doug fir

water

128128bandsbands

The ProbeThe Probe--1 hyperspectral sensor and 1 hyperspectral sensor and spectra from the Lamar River, WYspectra from the Lamar River, WY

Greater spectral resolution Greater spectral resolution detects subtle featuresdetects subtle features

pc 3,2,1pc 3,2,1

pc 12,11,10pc 12,11,10

pc 9,8,7pc 9,8,7

pc 6,5,4pc 6,5,4

true colortrue color

Advances due to high spatial resolutionAdvances due to high spatial resolution–– even from space!even from space!

TM (30 m)TM (30 m)

AVIRIS (17 m)AVIRIS (17 m)

Probe1 (8 m)Probe1 (8 m)

Probe1 (5 m)Probe1 (5 m)

IKONOS (0.85 m)IKONOS (0.85 m)

Animation byAnimation byRichard AspinallRichard Aspinall


Field Area and Field Area and Collection of HSHR ImageryCollection of HSHR Imagery

Field Sites: NE YellowstoneField Sites: NE Yellowstone

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Lamar River

Soda Butte Creek

33rdrd

orderorder

44 thth

orderorder

55thth

orderorder

Cache Creek

Landscapes: Lower Soda Butte CreekLandscapes: Lower Soda Butte Creek

Landscapes: Lamar RiverLandscapes: Lamar River Methods: spectral data collectionMethods: spectral data collection

The Probe1 sensor:The Probe1 sensor:

•• 128 bands at 12 to 16 128 bands at 12 to 16 nm resolutionnm resolution

•• spectral range from 440 spectral range from 440 to 2,543 nmto 2,543 nm

•• 512 m image width at 1 512 m image width at 1 m resolutionm resolution

•• VERYVERY expensive expensive ($25,000/day rental)($25,000/day rental)

Probe1, misc9, Aug 4, 1999Probe1, misc9, Aug 4, 1999

Methods: Helicopter platformMethods: Helicopter platformTo collect 1To collect 1--m resolution data, the Probe1 m resolution data, the Probe1 sensor was mounted on a helicopter and sensor was mounted on a helicopter and flown 600 m above the ground surface.flown 600 m above the ground surface.

..

J. Boardman, Probe1, misc6, 08/04/99J. Boardman, Probe1, misc6, 08/04/99

The helicopter platform created unique problems:The helicopter platform created unique problems:

•• more vibration, pitch, yaw and roll than fixed wing aircraft more vibration, pitch, yaw and roll than fixed wing aircraft

•• gyroscope overcompensation led to serious image swirlgyroscope overcompensation led to serious image swirl

•• rotor blades reflected GPS signal, causing loss of coordinate darotor blades reflected GPS signal, causing loss of coordinate da tata

•• greater difficulty in coregistering field maps to imagery and GIgreater difficulty in coregistering field maps to imagery and GIS dataS data

Aug 4, 1999, misc5Aug 4, 1999, misc5

99080308b, Lamar River99080308b, Lamar RiverAug3. 1999Aug3. 1999

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Riparian features examinedRiparian features examinedRiparian variables examined:Riparian variables examined:

•• inin--stream habitats (riffles, pools, glides)stream habitats (riffles, pools, glides)•• stream depthsstream depths•• large woody debrislarge woody debris•• vegetation cover typesvegetation cover types•• amphibian habitatamphibian habitat

All these variables:All these variables:•• are key to habitat managementare key to habitat management•• are sensitive to human impacts are sensitive to human impacts

•• are difficult to map at watershed scales with are difficult to map at watershed scales with groundground--based methodsbased methods


Mapping inMapping in--stream habitatsstream habitats

InIn--stream habitatsstream habitats

Eddy drop zone Eddy drop zone (fine sediment(fine sedimentaccumulation)accumulation)

GlideGlide

High gradientHigh gradientriffle (whiteriffle (whitewater)water)

Low gradient riffleLow gradient riffle(no white water)(no white water)

Scour poolScour pool

Round Prairie, 9srp104, October, 1999Round Prairie, 9srp104, October, 1999

Methods: field mapping forMethods: field mapping forimage training and validationimage training and validation

Morphologic units, stream depth, Morphologic units, stream depth, substrate size, and vegetation communsubstrate size, and vegetation commun--ities and species were mapped directly ities and species were mapped directly to 1 m images to insure coregistrationto 1 m images to insure coregistration

J. Rasmussen, Aug, 1999 (misc12)J. Rasmussen, Aug, 1999 (misc12) C. Legleiter, Aug, 1999 (misc13)C. Legleiter, Aug, 1999 (misc13)

Lamar River

9sul03,9sul03,Nov16, 1999Nov16, 1999

Field map of morphologic units Field map of morphologic units with 3 pixel buffer zone removedwith 3 pixel buffer zone removed

9mul89mul8--26, Aug 26, 199926, Aug 26, 1999

Image 99080309Image 99080309

PC images: The power of hyperspectral PC images: The power of hyperspectral Take raw imageTake raw image

Mask to calculate Mask to calculate covarcovar--ianceiance statistics for waterstatistics for water

Create pc data that highlight Create pc data that highlight withinwithin--stream variationsstream variations

Mask of mapped unitsMask of mapped units

PC bands 8,4,1 PC bands 8,4,1

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InIn--stream habitat mapping accuraciesstream habitat mapping accuraciesLamar River, WY: 5Lamar River, WY: 5thth Order StreamOrder Stream

Ground Truth (percent)

Classification

eddy drop zones

riffles

pools

glides

eddy drop zones 84.8 4.1 2.1 1.3 riffles 3.5 75.9 2.6 3.9 pools 11.6 11.1 90.5 7.9

glides .2 8.9 4.8 86.8 Total 100 100 100 100

Overall accuracy = 9432/11,033 = Overall accuracy = 9432/11,033 = 85.5%85.5%Kappa = Kappa = 0.740.74

Data for supervised classification on pc bands 1Data for supervised classification on pc bands 1--25, 1 m 25, 1 m imagery with buffered morphologic unitsimagery with buffered morphologic units

Results of 4 Unit Stream ClassificationResults of 4 Unit Stream Classification

RifflesRiffles

GlidesGlides

PoolsPoolsEddy drop zoneEddy drop zone

1 meter classification1 meter classificationField mapField map

Classification Results inClassification Results in33rdrd, 4, 4thth and 5and 5thth Order StreamsOrder Streams

0.740.74

0.280.28

0.520.52

0.350.35

KappaKappapoolspoolsglidesglidesrifflesriffleseddy eddy drop drop zoneszones

6767676775755252343433Cooke CityCooke City

8585878791917676858555Lamar RiverLamar River

71717878737362629944FootbridgeFootbridge

7171666684845555444444Round PrairieRound Prairie

Overall Overall AccurAccur--acyacy (%)(%)

Producer’s Accuracy Producer’s Accuracy (%)(%)Stream Stream

orderorderLocationLocation

Discussion: Reasons for varying results in Discussion: Reasons for varying results in 33rdrd, 4, 4thth and 5and 5thth order streamsorder streams

Image 9scc04, Oct 4, 1999Image 9scc04, Oct 4, 1999

Cooke City Reach, 3Cooke City Reach, 3 rdrd OrderOrder

Image 9srp104, Oct 4, 1999Image 9srp104, Oct 4, 1999

Round Prairie Reach, Round Prairie Reach, 44thth OrderOrder

Footbridge Reach, 4Footbridge Reach, 4thth OrderOrder

Image 9sfb79, Sept, 1999Image 9sfb79, Sept, 1999

Lamar River,Lamar River,55 thth OrderOrder

Image 9sul05, Nov., 1999Image 9sul05, Nov., 1999

Soda Butte Creek, 9msb10Soda Butte Creek, 9msb10--4, Oct, 4, 19994, Oct, 4, 1999

Are HSHR maps better than field maps? Are HSHR maps better than field maps?

low gradient rifflelow gradient riffleglideglidepoolpoolrunrun

high gradient rifflehigh gradient riffle

eddy drop zoneeddy drop zone

Classification mapClassification map


Stream DepthsStream Depths

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Stream depthStream depthWater depth is a key control on aquatic habitat and is a Water depth is a key control on aquatic habitat and is a variable in most hydrologic and geomorphic models.variable in most hydrologic and geomorphic models.

Continuous depth variations cause point measurements Continuous depth variations cause point measurements to miss much of the natural variationto miss much of the natural variation ..

Soda Butte Creek, 9ssg53, Oct 10, 1999Soda Butte Creek, 9ssg53, Oct 10, 1999

Jim Rasmussen, misc14, Aug, 1999Jim Rasmussen, misc14, Aug, 1999

Reflectance is a function of:Reflectance is a function of:•• depthdepth•• andand turbulenceturbulence•• andand substrate substrate

Soda Butte Crk, July, 1999, Untitled 1Soda Butte Crk, July, 1999, Untitled 1-- 22

Stratifying by morphologic Stratifying by morphologic unit should therefore help unit should therefore help to normalize the relation of to normalize the relation of depth to reflectance. depth to reflectance.

Depth results, Lamar RiverDepth results, Lamar River

Multiple regression of pc scores (x) Multiple regression of pc scores (x) vsvs depth (ydepth (y)

But… sample size issues are significantBut… sample size issues are significant

In-stream habitat Number of sites

Number of pc's included in regression

Adjusted R2

Eddy drop zone 17 4 93.8%High gradient riffle 35 6 67.0%Low gradient riffle 11 6 91.7%Pool 5 1 72.3%Rough water runs 10 3 82.5%Runs 9 4 93.1%Glides 17 11 98.6%

Methods: The HABMethods: The HAB--1 model1 model

Basis for model:Basis for model:•• Manning equationManning equation•• Jarret’sJarret’s roughnessroughness•• Q, S and W are measuredQ, S and W are measured

Key assumptions:Key assumptions:•• roughness estimate is reasonableroughness estimate is reasonable•• triangle approximation: triangle approximation: DDmaxmax = 2*= 2*DDavgavg•• avgavg depth depth αα avgavg reflectance signal (implies depth reflectance signal (implies depth driving all variations in reflectance)driving all variations in reflectance)

.

TEST SECTION TEST SECTION DN’sDN’s HABHAB--1 Depths1 Depths

Darkest DN Max DepthDarkest DN Max Depth

Average DN Average DN AvgAvg DepthDepth

Brightest DN Shallow DepthBrightest DN Shallow Depth

(relates to…)

Repeat with multiple XRepeat with multiple X--sections to produce sections to produce A wellA well--defined Depthdefined Depth--toto--DN relationshipDN relationship

Applying the HABApplying the HAB--1 Model:1 Model:•• estimate estimate DDavgavg and and DDmaxmax at multiple cross sectionsat multiple cross sections•• determine determine avgavg, max, min reflectances at cross sections, max, min reflectances at cross sections•• regress reflectance (x) regress reflectance (x) vsvs depth (y)depth (y)•• apply regression to remainder of remote sensing image apply regression to remainder of remote sensing image

Methods: The HABMethods: The HAB--1 model1 model

Smooth water transects Smooth water transects (green)(green)

Rough water transectsRough water transects (yellow)(yellow)

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Results: TM5 band 3 Results: TM5 band 3 vsvs DepthDepth

HABHAB--1 depth 1 depth vsvs measured depthmeasured depth

Band 3 Band 3 vsvs HABHAB--1 estimated depth1 estimated depth

Discussion: Are the depths accurate? Discussion: Are the depths accurate? rr22 = 0.34, seems low, but = 0.34, seems low, but

•• general trend captured (slope general trend captured (slope ≅≅ 1, y int. 1, y int. ≅≅ 0)0)•• cross sections seem real:cross sections seem real:

IKONOS Image of Lamar& Soda Butte System, YNP August 7, 2001

HABHAB--1 Cross1 Cross--SectionsSections

XS 1

XS 2

XS 3

XS 4

XS 5

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Reasons for misclassificationReasons for misclassification

•• natural variations within a feature typenatural variations within a feature type

•• “false” turbulence“false” turbulence

•• viewing angle relative to sun angle viewing angle relative to sun angle

•• variations in background (mixed pixels)variations in background (mixed pixels)

•• obstructions (e.g., trees, woody debris)obstructions (e.g., trees, woody debris)

•• inconsistent field mappinginconsistent field mapping

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Soda Butte Crk, Silver Gate, Oct, 1999 (9ssg57)Soda Butte Crk, Silver Gate, Oct, 1999 (9ssg57)

Variations within a feature typeVariations within a feature type

Soda Butte Crk, Round Prairie, Oct, 1999 (9srp96)Soda Butte Crk, Round Prairie, Oct, 1999 (9srp96)

Pools with varying substrate Pools with varying substrate and surface turbulenceand surface turbulence

Reflectance variations from turbulenceReflectance variations from turbulence

Downstream hydraulic riffle

Downstream hydraulic riffle

Up valley wind creating

Up valley wind creating

waves on a glidewaves on a glide

““False” turbulenceFalse” turbulence

Viewing angle relative to sunViewing angle relative to sun

Looking down at same time Looking down at same time and site (arrows show same and site (arrows show same transect)transect)

Looking towards sunLooking towards sun

Soda Butte Crk,Silver Gate, Oct 1999 (9ssg54)Soda Butte Crk,Silver Gate, Oct 1999 (9ssg54)

Soda Butte Crk,Silver Gate, Oct 1999 (9ssg55)Soda Butte Crk,Silver Gate, Oct 1999 (9ssg55)

Mixed pixels Mixed pixels

Soda Butte Crk, Oct 1999 (9srp94)Soda Butte Crk, Oct 1999 (9srp94)

One pixelOne pixel

Obstructed view of stream

pool

Logsover pool 1069 nm reflectance

(highlights woody debris)

493

nm r

efle

ctan

ce

Reflectance of Mapped Pool Sites

Pure pool spectra

Spectra for logs overhangingpool

Discussion: The power of visualization Discussion: The power of visualization

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Woody Debris Woody Debris Large woody debrisLarge woody debris

Wood Wood alters stream morphology, stores sediment and organic alters stream morphology, stores sediment and organic debris, provides fish cover, and debris, provides fish cover, and provides habitat and nutrients for provides habitat and nutrients for invertebrates. Mapping woody debris is a pain.invertebrates. Mapping woody debris is a pain.

Soda Butte near Amphitheatre Crk, P001314, June, 2000Soda Butte near Amphitheatre Crk, P001314, June, 2000

Field Map of Woody DebrisField Map of Woody DebrisLamar River, Aug., 1999Lamar River, Aug., 1999

Matched Filter Mapping of Woody DebrisMatched Filter Mapping of Woody Debris

Woody debrisWoody debris(orange)(orange)

False color mageFalse color mageby J. Rasmussenby J. Rasmussen

Proportion of wood in each pixel,Proportion of wood in each pixel,red = high, green red = high, green -- medium, blue = lowmedium, blue = low

Matched filter imageMatched filter imageby J. Boardmanby J. Boardman

Overall classification accuracy = 82%Overall classification accuracy = 82%


Amphibian HabitatAmphibian HabitatAlgae and wetlandsAlgae and wetlands

•• key for many species, including amphibianskey for many species, including amphibians

•• frequently small (< several mfrequently small (< several m22), widely dispersed, ), widely dispersed, and missed by standard photos, maps, and groundand missed by standard photos, maps, and ground--based surveys.based surveys.

•• Census techniques areCensus techniques areneeded that guide us toneeded that guide us topotential habitat in apotential habitat in afast, efficient manner. fast, efficient manner.

Algae site 17, Cache Creek, WY, Aug, 2000Algae site 17, Cache Creek, WY, Aug, 2000Photos by Chuck PetersonPhotos by Chuck Peterson

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Initial Wetland ResultsInitial Wetland Results

Matched filter image by W.A. Marcus and Matched filter image by W.A. Marcus and Chuck PetersonChuck PetersonProbe 1 5 m imagery from Aug 25, 1999Probe 1 5 m imagery from Aug 25, 1999

Intentional Intentional overpredictionoverprediction (errors of (errors of commission) to avoid missing any commission) to avoid missing any amphibian habitat. In a preliminary amphibian habitat. In a preliminary survey, no wetland sites were missed out survey, no wetland sites were missed out of 15 visited. Three new amphibian sites of 15 visited. Three new amphibian sites were found.were found.

#5#5

#6#6

Imagery led us to find wetlands in Imagery led us to find wetlands in unexpected sitesunexpected sites

Cache Creek, WY, August 2000Cache Creek, WY, August 2000Photo by Chuck PetersonPhoto by Chuck Peterson

Spectral Angle Mapping of AlgaeSpectral Angle Mapping of AlgaeS.A.M. requires that the user define theS.A.M. requires that the user define thethreshold at which the feature is “found.”threshold at which the feature is “found.”

The user should therefore have The user should therefore have knowledge about the landscapeknowledge about the landscape

for feature ID to work.for feature ID to work.

SAM rule images by W.A. MarcusSAM rule images by W.A. MarcusProbe1 1 m data, Aug 03, 1999Probe1 1 m data, Aug 03, 1999

The algae training siteThe algae training site

Initial Algae ResultsInitial Algae Results

75% correct 75% correct classificaclassifica--tiontion out of 20 sites out of 20 sites visited. Found 4 new visited. Found 4 new amphibian sites in algae amphibian sites in algae areas.areas.

Site 18Site 18Probe1 1 m imagery, Aug 3, 1999Probe1 1 m imagery, Aug 3, 1999Matched filter image by W.A. Marcus and C. PetersonMatched filter image by W.A. Marcus and C. Peterson

Photos by C. PetersonPhotos by C. Peterson


Vegetation MappingVegetation Mapping

Riparian Vegetation Riparian Vegetation

Riparian vegetation:Riparian vegetation:•• provides habitat for terrestrial and aquatic organismsprovides habitat for terrestrial and aquatic organisms•• stabilizes streams banksstabilizes streams banks•• is sensitive to disturbanceis sensitive to disturbance

Classical surveyClassical surveytechniques can betechniques can betime consuming andtime consuming andlocally destructive.locally destructive.

Hitching Post Willow Grid, P705Hitching Post Willow Grid, P705Soda Butte Creek, Aug, 1999Soda Butte Creek, Aug, 1999

Conifer 100%Conifer 100%

Sedge Sedge 96.6%96.6%

DecidDecid.. 100%100%

ThistleThistle 93.1%93.1%

AverageAverage 97.4%97.4%

% correct% correct

30 sites visited for 30 sites visited for each categoryeach category

Work by Kerry Halligan, YERCWork by Kerry Halligan, YERC

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Summary: high definition measurementSummary: high definition measurement

Overall Accuracies:Overall Accuracies:InIn--stream habitats:stream habitats: 76% 76% –– 91% 91% Depths:Depths: 67% 67% –– 99%99%Woody debris:Woody debris: 82%82%Algae:Algae: 75%75%Wetlands:Wetlands: 100%100%Vegetation:Vegetation: 93% 93% -- 100%100%

low gradient rifflelow gradient riffleglideglidepoolpoolrunrun

high gradient rifflehigh gradient riffle

eddy drop zoneeddy drop zone

Classification mapClassification map

Ethical ConcernsEthical ConcernsAdvances in remote mapping of riparian settings Advances in remote mapping of riparian settings –– with with examples from Yellowstone: examples from Yellowstone:

•• ability of high resolution imagery to “reveal all”ability of high resolution imagery to “reveal all”•• broad spatial coverage of spacebroad spatial coverage of space--based platformsbased platforms

•• ease of accessease of accessPerils of exposing natural resources and potential ethical Perils of exposing natural resources and potential ethical dilemmas:dilemmas:

•• unfriendly useunfriendly use•• exploitationexploitation

•• destruction of wildernessdestruction of wildernessWork to promote ethical uses of remote sensing data:Work to promote ethical uses of remote sensing data:

•• existing guidelinesexisting guidelines•• future roles for geographersfuture roles for geographers

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Mapping depth with 0.85Mapping depth with 0.85--m satellite m satellite imagery, Soda Butte Creek, WYimagery, Soda Butte Creek, WY

IKONOS analysis by Mark FonstadIKONOS analysis by Mark Fonstad

IKONOS (0.85 m)

High definition imagery from space, over the internetHigh definition imagery from space, over the internet

Satellite imagery Satellite imagery potentially available at potentially available at 0.75 to 4 m resolution for 0.75 to 4 m resolution for entire ecosystem entire ecosystem ––over the internetover the internet

IKONOS 3.8 m imagery

New technology and techniques enable:New technology and techniques enable:

•• greater mapping accuracy at finer spatial resolutions greater mapping accuracy at finer spatial resolutions than ever beforethan ever before

•• application and use of the high definition products at application and use of the high definition products at watershed, landscape and regional scaleswatershed, landscape and regional scales

•• global access to the high definition, regional imagery global access to the high definition, regional imagery and mapsand maps


Applications and perils of exposing natural resources:Applications and perils of exposing natural resources:

•• military applications and potential unfriendly usemilitary applications and potential unfriendly use•• resource mapping and potential exploitationresource mapping and potential exploitation

•• potential destruction of the wildernesspotential destruction of the wildernessThe key question: to reveal, or not to reveal?The key question: to reveal, or not to reveal?

Exposing natural resources: potential ethical dilemmasExposing natural resources: potential ethical dilemmas

Algae site 17, Cache Creek, WY, Aug, 2000Algae site 17, Cache Creek, WY, Aug, 2000

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Military trafficability analysisMilitary trafficability analysis

Unfriendly use of high resolution image productsUnfriendly use of high resolution image products

Pools (in blue), too deep for crossing

Rapids (in white): Passable for vehicles, but too swift for foot traffic

Fine grained sediment (in yellow), might bog down vehicles

Glides (in green) are shallow, hard bottomed areas good for both foot and vehicle traffic

Best Crossing

Unfriendly use of image productsUnfriendly use of image products

1111--20202121--30303131--4040

00--10 cm10 cm5151--60606161--70707171--100100

4141--50 cm50 cm

>100 cm>100 cm

FlowFlow

nasty neighbornasty neighbor

downstream neighbordownstream neighbor

boun

dary

boun

dary

Stream inventory and managementStream inventory and management

FISH!!!!!!FISH!!!!!!

Private and commercial use of image productsPrivate and commercial use of image products

Resource inventoryResource inventory

#5#5

#6#6

Imagery led us to find wetlands in Imagery led us to find wetlands in unexpected sitesunexpected sites

Matched filter image by W.A. MarcusMatched filter image by W.A. MarcusProbe 1 5 m imagery from Aug 25, 1999Probe 1 5 m imagery from Aug 25, 1999

In a preliminary survey, 1In a preliminary survey, 1--m imagery m imagery identified 35 new algae or wetland sites. identified 35 new algae or wetland sites. Seven new amphibian sites were found in Seven new amphibian sites were found in backcountry wilderness.backcountry wilderness.

Resource management and Resource management and commercial exploitationcommercial exploitation

Matched filter image by W.A. Marcus, C PetersonMatched filter image by W.A. Marcus, C PetersonProbe 1 5 m imagery from Aug 25, 1999Probe 1 5 m imagery from Aug 25, 1999

Chuck’s Toads and Frogs Chuck’s Toads and Frogs Wilderness Adventures!Wilderness Adventures!

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The destruction of wildernessThe destruction of wilderness

Aldo Leopold: Aldo Leopold:

“..speaking geographically, the end of “..speaking geographically, the end of the Unknown is at hand. Is it to be the Unknown is at hand. Is it to be expected that it shall be lost from expected that it shall be lost from human experience without something human experience without something likewise being lost from human likewise being lost from human character?”character?”

Where can we turn for Where can we turn for specificspecific guidelines on ethical guidelines on ethical use of remote sensing for natural resource mapping?use of remote sensing for natural resource mapping?

Ethics: “The science of moral duty…, the science of the ideal Ethics: “The science of moral duty…, the science of the ideal ends of human action.”ends of human action.”

Underlying premise: moral actions promote the well being of Underlying premise: moral actions promote the well being of one or more living creatures, without harming othersone or more living creatures, without harming others

For remote sensing, Estep, 1973, p. 363: Goal is “providing a For remote sensing, Estep, 1973, p. 363: Goal is “providing a decent condition of living for all the peoples of the earth.”decent condition of living for all the peoples of the earth.”

Ethical remote sensing of natural resourcesEthical remote sensing of natural resources

Most professional codes focus on:Most professional codes focus on:•• quality of workquality of work

•• unfair competitionunfair competition•• intellectual propertyintellectual property

•• strengthening profession strengthening profession •• accessibility/privacyaccessibility/privacy

•• enforcement mechanisms and consequencesenforcement mechanisms and consequencesURISA, April, 2003 also has a social welfare emphasis:URISA, April, 2003 also has a social welfare emphasis:

•• work should be objective, clear, honestwork should be objective, clear, honest•• promote broad involvement and use of findingspromote broad involvement and use of findings

•• speak out about issuesspeak out about issues

Professional CodesProfessional CodesLegal Guidelines to Use of Remote SensingLegal Guidelines to Use of Remote Sensing

Sources to guide us:Sources to guide us:•• legislation legislation (not useful)(not useful)•• regulationregulation (nope)(nope)•• case lawcase law (some help)(some help)•• international treatiesinternational treaties (some help)(some help)

U.S. Case Law and PrivacyU.S. Case Law and PrivacyThe 4The 4thth Amendment prohibits unreasonable search by the Amendment prohibits unreasonable search by the

government (but not by other parties for commercial or government (but not by other parties for commercial or financial purposes)financial purposes)

Precedent is confusing:Precedent is confusing:•• Katz v. U.S., 1967 (the public phone booth case)Katz v. U.S., 1967 (the public phone booth case)

•• Dow v. U.S., 1981 (the air photo case) Dow v. U.S., 1981 (the air photo case) •• Oliver v. U.S., 1984 Oliver v. U.S., 1984 -- “an individual may not legitimately “an individual may not legitimately

demand privacy for activities conducted out of doors and demand privacy for activities conducted out of doors and in fields”in fields”

•• FLIR and recent casesFLIR and recent casesBut all this only applies to private propertyBut all this only applies to private property

International AgreementsInternational Agreements

Key guides:Key guides:

•• UN Declaration of Human Rights ( “Freedom to UN Declaration of Human Rights ( “Freedom to seek receive, and impart information and ideas seek receive, and impart information and ideas through any media and regardless of frontiers”) through any media and regardless of frontiers”)

•• UN Open Skies Policy (satellites are free to roam)UN Open Skies Policy (satellites are free to roam)

Consequence is open information for:Consequence is open information for:

•• entities with resources and expertiseentities with resources and expertise

•• groups/individuals with open internet accessgroups/individuals with open internet access

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Role of Geographers in Remote Sensing EthicsRole of Geographers in Remote Sensing Ethics

We can promote ethical use of remote sensing for mapping We can promote ethical use of remote sensing for mapping natural resources by:natural resources by:

•• Bringing a humanistic perspective to the engineering Bringing a humanistic perspective to the engineering dominated world of remote sensing (remote sensing is dominated world of remote sensing (remote sensing is more than techniques)more than techniques)

•• Providing creative avenues to engage in ethical thinking Providing creative avenues to engage in ethical thinking

•• Publishing on ethical uses of remote sensingPublishing on ethical uses of remote sensing

•• Promoting new laws, regulations and policies that apply Promoting new laws, regulations and policies that apply to remote sensing to remote sensing

•• Engaging in certification efforts and development of Engaging in certification efforts and development of ethical standards in professional societiesethical standards in professional societies

More immediate contributionsMore immediate contributions

Adopting ethics guiding human geography investigations to Adopting ethics guiding human geography investigations to remote sensing of natural resources:remote sensing of natural resources:

•• concepts of census data useconcepts of census data use

•• ethics guiding interviewsethics guiding interviews

•• human subject clearancehuman subject clearance

•• teachingteaching

the yellowstone project talk...

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