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Land Cover, Land Use of two Land Cover, Land Use of two bioluminescent bays in Puerto Ricobioluminescent bays in Puerto Ricobioluminescent bays in Puerto Ricobioluminescent bays in Puerto Rico
Undergraduate ResearchUndergraduate ResearchBy: Yadira Soto ViruetBy: Yadira Soto Viruet
Advisor: Fernando Gilbes Santaella, Ph.DAdvisor: Fernando Gilbes Santaella, Ph.D
OutlineOutline
IntroductionIntroductionIntroductionIntroductionObjectivesObjectivesSt dSt d AAStudyStudy AreaAreaMethodologyMethodologyResultResultDiscussionDiscussionDiscussionDiscussionConclusionConclusion
IntroductionIntroduction
LandLand aroundaround PuertoPuerto MosquitoMosquito BayBay inin ViequesVieques andandLandLand aroundaround PuertoPuerto MosquitoMosquito BayBay inin ViequesVieques andandLaLa PargueraParguera BioluminescenceBioluminescence BayBay inin Lajas,Lajas, PuertoPuertoRicoRico areare usedused toto produceproduce LandLand Use/Use/ LandLand CoverCovermapsmaps..
LandLand useuse isis defineddefined asas thethe useuse ofof landland byby humanshumans..
LandLand covercover isis designatesdesignates onlyonly thethe vegetationvegetation(natural(natural oror manman made)made)..
Examples: urban structures forest agricultureExamples: urban structures forest agricultureExamples: urban structures, forest, agriculture, Examples: urban structures, forest, agriculture, water resources, vegetations index and others. water resources, vegetations index and others.
The Land Use/Land Cover maps have the The Land Use/Land Cover maps have the capacity to illustrate the interaction betweencapacity to illustrate the interaction betweencapacity to illustrate the interaction between capacity to illustrate the interaction between human and the surroundings.human and the surroundings.
In Puerto Rico, general maps of Land Uses/Land In Puerto Rico, general maps of Land Uses/Land Cover were produced in 1999 for La Parguera Cover were produced in 1999 for La Parguera p gp gand Vieques Island. and Vieques Island.
Land Use/ Land Cover Maps, 1999Land Use/ Land Cover Maps, 1999
Linda Velez,1999
TheThe BioluminescenceBioluminescence isis thethe emissionemission ofof lightlight bybyTheThe BioluminescenceBioluminescence isis thethe emissionemission ofof lightlight bybylivingliving organismorganism ((PyrodiniumPyrodinium bahamense)bahamense)..
ConditionsConditions aidingaiding thethe accumulationaccumulation ofof thesetheseorganismsorganisms areare:: shallowshallow basinbasin withwith lowlow tidaltidal andando ga s so ga s s a ea e s a os a o basbas oo dada a da dnarrownarrow mouth,mouth, surroundedsurrounded byby mangrovesmangroves..
LaLa PargueraParguera BioluminescentBioluminescent BayBay hashas shownshown aadecreasedecrease inin itsits bioluminescencebioluminescence byby approximatelyapproximately8080%% duringduring recentrecent yearsyears comparedcompared withwith PuertoPuertoMosquitoMosquito BayBay..
ObjectivesObjectivesObjectivesObjectives
TheThe mainmain objectiveobjective ofof thisthis researchresearch waswas produceproduceandand comparecompare LandLand UseUse andand LandLand Cover,Cover, specificspecificpp ppmapsmaps forfor thethe twotwo bioluminescencebioluminescence baysbays;; usingusingRemoteRemote SensingSensing andand GISGIS toolstools..
Study AreaStudy AreaStudy AreaStudy Area
Adapted from Walker, 1997 IKONOS 1m
La Parguera Bioluminescence BayLa Parguera Bioluminescence Bay
Th h l f•The geomorphology of the area is the result of deformation of Limestone in earlyLimestone in early Cretaceous (Glynn, 1973).
•The bottom sediments are composed by fine mud, marine plants and mangrove leavesmangrove leaves.
Scale 1,2000 (Volckmann, 1984)
Puerto Mosquito BayPuerto Mosquito Bayq yq y
Scale 1,2000 (USGS Maps,2001)
• The geology of Vieques consists in intrusive rocks with carbonate sediments, the bottom sediments are composed by clay.
• QTu – Sedimentary deposits undivided Marine limestone.
MethodologyMethodologyEnvironment for Visualizing Images (ENVI)Environment for Visualizing Images (ENVI)
Geographic Information System (GIS) Geographic Information System (GIS)
IKONOS sensor provides spatial resolution at 1 IKONOS sensor provides spatial resolution at 1 meter and in multispectral mode, it provides meter and in multispectral mode, it provides imagery at 4 m spatial in four spectral bands.imagery at 4 m spatial in four spectral bands.
The images was displayed using all available The images was displayed using all available bands; red, green, blue (RGB) and infrared band bands; red, green, blue (RGB) and infrared band (IR)(IR)(IR). (IR).
IKONOS, 1m
IKONOS, 1m
(Campbell, 2002)
(Campbell, 2002)
Supervised classificationSupervised classificationParallelepipedParallelepipedParallelepipedParallelepipedMinimum DistanceMinimum DistanceMahalanobis DistanceMahalanobis DistanceMahalanobis DistanceMahalanobis DistanceMaximum LikelihoodMaximum Likelihood
C f i M t i th dC f i M t i th dConfusion Matrix methodConfusion Matrix methodusing ground truth image and ROI’s.using ground truth image and ROI’s.
H d l i f tiH d l i f ti USGS bli ti filUSGS bli ti filHydrology informationHydrology information, USGS publication files, USGS publication files
Regions of InterestRegions of Interest (ROI’s)(ROI’s)• The process of using known pixels identity to classifyunknown pixel identityunknown pixel identity.
Index of Vegetation (NDVI)Index of Vegetation (NDVI)
NDVI= Infrared (IR)-Red (R) / Infrared (IR)+ Red (R)
ResultsResultsResultsResults
Maximum LikehoodMaximum LikehoodAssumes that the statistics for each class in each band are normally distributed and calculates the probability that a given pixel belongs to a specificpixel belongs to a specific class.
(Campbell, 2002)
Minimum DistanceMinimum Distance
Uses the mean vectors of each ROI’s and calculates the Euclidean distance from each unknownfrom each unknown pixel to the mean vector for each class.
(Campbell, 2002)
Parallelepiped classificationParallelepiped classificationRanges of values within training data to definetraining data to define regions within a multidimensional data space.
(Campbell, 2002)
Mahalanobis DistanceMahalanobis Distance
Mahalanobis Distance classification is a direction sensitive distance classifier that uses statistics for each class.class.
Minimum DistanceMinimum Distance
Mahalanobis DistanceMahalanobis Distance
Maximum LikehoodMaximum Likehood
Distribution of ClassesDistribution of Classes
Distribution of Classes % L P Bi l i B
Distribution of Classes % La Parguera Bioluminescence Bay
12%,1%
Puerto Mosquito Bay
11%
5%
9%
55%
57%27%
23%27%
Index of VegetationIndex of Vegetation
Darker green color represent more density of vegetation
Validation processValidation processAccuracy is calculated by the sum of the number of pixels classified correctly divided by the sum of all the pixels in the entire ground truth classes.
Confusion matrix for La Parguera Bioluminescence BayConfusion matrix for La Parguera Bioluminescence BayGround Truth ROI’s, was 99% Ground Truth ROI’s, was 99% Kappa coefficient was 0.80. Kappa coefficient was 0.80. The Kappa coefficient is a measure of the proportional The Kappa coefficient is a measure of the proportional improvement by the 36 classifier over a purely random improvement by the 36 classifier over a purely random
i t f li t f lassignment of classes. assignment of classes.
Puerto Mosquito Bay Puerto Mosquito Bay G d T th ROI’ 90%G d T th ROI’ 90%Ground Truth ROI’s 90%Ground Truth ROI’s 90%Kappa Coefficient was 0.5Kappa Coefficient was 0.5
f G %f G %The confusion matrix, using Ground Truth Image, was 100% The confusion matrix, using Ground Truth Image, was 100% and the kappa coefficient was 1 for both bays. and the kappa coefficient was 1 for both bays.
DiscussionDiscussionSupervised classification, the analyst has control of Supervised classification, the analyst has control of the selected classes depending of the purpose ofthe selected classes depending of the purpose ofthe selected classes depending of the purpose of the selected classes depending of the purpose of the researchthe research..
All supervised classifications, were tested to All supervised classifications, were tested to d t i th b t t l f hd t i th b t t l f hdetermine the best spectral response for each determine the best spectral response for each image and classification method.image and classification method.
For La Parguera Bioluminescence Bay the For La Parguera Bioluminescence Bay the percentage distribution were similar in the twopercentage distribution were similar in the twopercentage distribution were similar in the two percentage distribution were similar in the two bays, except for urban or built up.bays, except for urban or built up.
InIn LaLa PargueraParguera BioluminescenceBioluminescence BayBay hashas moremoreinteractioninteraction withwith anthropogenicanthropogenic activitiesactivities thanthanPuertoPuerto MosquitoMosquito BayBayPuertoPuerto MosquitoMosquito BayBay..
ItIt ii i ibli ibl tt ii th tth t LL PPItIt isis visiblevisible toto recognizerecognize thatthat LaLa PargueraPargueraBioluminescenceBioluminescence BayBay hashas lessless densitydensity ofofvegetationvegetation thanthan PuertoPuerto MosquitoMosquito BayBayvegetationvegetation thanthan PuertoPuerto MosquitoMosquito BayBay..
TheThe geologicalgeological characteristiccharacteristic taketake anan importantimportantrolerole forfor thethe distributiondistribution andand imputeimpute ofof sedimentssedimentsthatthat effecteffect intointo thethe baybaythatthat effecteffect intointo thethe baybay..
ConclusionConclusionThe capacity to recognize and updates these land use The capacity to recognize and updates these land use and land cover areas are important tools development of and land cover areas are important tools development of
i iti f th t d f f t hi iti f th t d f f t hpriorities for the management and for future research.priorities for the management and for future research.
The fact that the presence of the urban or anthropogenicThe fact that the presence of the urban or anthropogenicThe fact that the presence of the urban or anthropogenic The fact that the presence of the urban or anthropogenic activities affects the bioluminescent bays, also contribute activities affects the bioluminescent bays, also contribute to reduce the bioluminescentto reduce the bioluminescent. .
Human activities have a substantial impact on the Human activities have a substantial impact on the hydrology characteristic of the bay also the sedimenthydrology characteristic of the bay also the sedimenthydrology characteristic of the bay, also the sediment hydrology characteristic of the bay, also the sediment impute to the bay has been variable due to human impute to the bay has been variable due to human activities.activities.
The destruction of vegetation and the transit of The destruction of vegetation and the transit of boats can also affect the bayboats can also affect the bayboats can also affect the bay. boats can also affect the bay.
For future research is suggested used olderFor future research is suggested used olderFor future research, is suggested used older For future research, is suggested used older images and make supervised classification to images and make supervised classification to determine changes in time and vegetation.determine changes in time and vegetation.
The IKONOS sensor is a great tool to obtain The IKONOS sensor is a great tool to obtain i ith hi h lit l ifi ti d i di ith hi h lit l ifi ti d i dimages with high quality, classification and index images with high quality, classification and index of vegetation was possible using the spectral of vegetation was possible using the spectral information available in the images.information available in the images.information available in the images.information available in the images.
Webpage: http://gersview.uprm.edu/website/Webpage: http://gersview.uprm.edu/website/p g p g pp g p g p
AcknowledgmentsAcknowledgments
I want to thank Dr. Fernando Gilbes Santaella forI want to thank Dr. Fernando Gilbes Santaella for support and help in working on this research. Thanks William Hernández to provide the USGS pinformation and support me.This project was funded by University of Puerto p j y yRico, Sea Grant College Program.
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