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Elements of Visual Image Interpretation

CHAPTER 5: Elements of Visual Image InterpretationREFERENCE: Remote Sensing of the Environment John R. Jensen (2007)Second EditionPearson Prentice HallReasons why photo/ Image Interpretation are powerful scientific tools: scale: aerial/regional perspective; three-dimensional depth perception; ability to obtain knowledge beyond our human Visual perception; ability to obtain a historical Image record to document OUR PERSPECTIVECHANGING OUR PERSPECTIVELA PARGUERA FROM A PLANELA PARGUERA FROM SPACET hematic MapperPUERTO RICO FROM THE SHUTTLEEVERYTHING IS ABOUT SCALESEARTH FROM SPACET hree-dimensional Depth PerceptionObtaining Knowledge Beyond our Human Visual PerceptionHistorical Image Record and Change Detection DocumentationElements of Image InterpretationElements of Image Interpretation -Tone and ColorElements of Image Interpretation -Tone and ColorGreenRedNear-infraredColor compos

Elements of Image Interpretation - Tone and Color Green Red Near-infrared Color composite RGB = green, red, near-infrared

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Transcription of Elements of Visual Image Interpretation

1 CHAPTER 5: Elements of Visual Image InterpretationREFERENCE: Remote Sensing of the Environment John R. Jensen (2007)Second EditionPearson Prentice HallReasons why photo/ Image Interpretation are powerful scientific tools: scale: aerial/regional perspective; three-dimensional depth perception; ability to obtain knowledge beyond our human Visual perception; ability to obtain a historical Image record to document OUR PERSPECTIVECHANGING OUR PERSPECTIVELA PARGUERA FROM A PLANELA PARGUERA FROM SPACET hematic MapperPUERTO RICO FROM THE SHUTTLEEVERYTHING IS ABOUT SCALESEARTH FROM SPACET hree-dimensional Depth PerceptionObtaining Knowledge Beyond our Human Visual PerceptionHistorical Image Record and Change Detection DocumentationElements of Image InterpretationElements of Image Interpretation -Tone and ColorElements of Image Interpretation -Tone and ColorGreenRedNear-infraredColor composite RGB = green, red.

2 Near-infraredElements of Image Interpretation -Tone and ColorGreenRedNear-infraredMid-infraredTr ue ColorFalse ColorElements of Image Interpretation -SizeElements of Image Interpretation -ShapeElements of Image Interpretation -TextureElements of Image Interpretation -PatternElements of Image Interpretation -ShadowElements of Image Interpretation -Height and DepthElements of Image Interpretation -Site, Situation and AssociationMethods of Search Use of Collateral Information Convergence of Evidence Use of the Multi-conceptCollateral InformationWORKING WITHDIGITAL DATAREFERENCE: Remote Sensing of the Environment John R.

3 Jensen (2007)Second EditionPearson Prentice HallPROCESSES AFECTING THE REMOTE SIGNALR eflected Bottom RadianceWater Column Reflected RadianceReflected Bottom RadianceWater Column Reflected RadianceFrom NEMO Inherent Optical Properties of the Water Bottom ReflectanceWhat we MeasureWhat we wantMEASURING THE RADIANCEDIGITAL IMAGINGP icture ElementsPIXELSPIXELMULTISPECTRAL PIXELSANALOG TO DIGITAL CONVERSIONSENSITIVITY OF THE SENSORSIGNAL TO NOISE RATIO (S/N)SPECTRAL SENSITIVITYDIGITAL VALUES Each digital value is recorded as a series of binary values known as bits. A bit (a contraction of binary digit) is the basic unit of information in computing and telecommunications; it is the amount of information stored by a digital device or other physical system that exists in one of two possible distinct states.

4 DIGITAL VALUES Each bit records an exponent of a power of 2, with the value of the exponent determined by the position of the bit in the sequence. Example: A system designed to record 7 bits for each digital value. This means that seven binary places are available to record the brightness sensed for each band of the 7 BITS SYSTEM1 + 2 + 4 + 8 + 16 + 32 + 64 + 128 + 256 + 512 + 10241 1 1 1 1 1 1 1 1 1 12021222324 25 26 27 28 29 210# Bits MDV1224384165326647128825695121010241120 48 RADIOMETRIC DIFFERENTIATION- Examination of any Image acquired by remote sensing ultimately depends upon detection of differences in the brightness of objects and the Resolution.

5 This is the sensitivity to small differences in the radiation of an observed object. MSS = 6 bits Landsat TM = 8 bits IKONOS 11 bits ERS SAR = 16 bits A KEY CONCEPT OF REMOTE SENSINGDATA FORMATSDATA FORMATSBand Interleaved by Pixel (BIP)DATA FORMATSBand Interleaved by Line (BIL)DATA FORMATSBand Sequential (BSQ)DIGITAL ANALYSISE jercicio #1: Explorando La PargueraEjercicio 2:Identificar lasdiferencias entrela imagen visible yla imagen infrarojade La 3: Principios de escala Examine el mapa topogr fico del 1966 de La Parguera y determine su escala Interprete Ia escala en Ia parte inferior de Ia p 3.

6 Principios de escala Use una regla y mida Ia distancia a trav s del rea de estudio de oeste a este. Cuantas pulgadas mide Ia distancia de oeste a este? Coloque Ia regIa sobre Ia barra de escala que representa Kil metros y determine:X Kil metros = X pulgadas Cuantos Kil metros mide a trav s del rea de estudio de oeste a este?Ejercicio 3: Principios de escala Repita las medidas a trav s del rea de estudio de norte a sur y determine: Cuantas pulgadas mide Ia distancia de norte a sur? Cuantos kil metros mide Ia distancia a trav s del rea de estudio de norte a sur?Ejercicio 4: Medidas de rea Utilice las medidas de distancia de norte a sur y de oeste a este y determine: Cu l es el rea, del rea de estudio, en pulgadas cuadradas?

7 Cu l es el rea, del rea de estudio, en Kil metros cuadrados?Informaci n: rea es la medida que se obtiene cuando se multiplica el largo por el 5: Medidas de Distancia Seleccione los dos mismos puntos en las im genes y determine la distancia en millas. Compare la imagen del 1991 y 2004.


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