Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Emilio Chuvieco and Alfredo Huete Fundamentals of Satellite Remote.

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Presentation transcript:

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Emilio Chuvieco and Alfredo Huete Fundamentals of Satellite Remote Sensing – Chapter 4

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis ObjectivesMeans Scale Accuracy Project length Precision Costs Equipment # Images Methods Sensor The effective implementation of remote sensing into a project requires a series of decisions to meet proposed objectives with available resources.

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Interpretation approaches Classification. Generation of biophysical variables. Change detection. Spatial patterns. 3D Measurements.

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Land Cover Visual or digital interpretation Clasification Categorizing Borders

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Biophysical variables Y = f (ND i ), i=1,n (original variables and derived information). Inductive and deductive models. < 37° C ° C ° C ° C ° C > 57° C

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Change detection

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Spatial pattern Fragmentation Connectivity Shape Size

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis 3D Measurements from Lidar Riaño et al., 2003

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis MMU size (4 mm 2 ) Map scale Pixel size (After Robin, 1998) Relationship between resolution and the Minimum Mapping Unit size

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Scale It is related to: Spatial resolution: pixel size (4 mm 2 ). Legend / class typologies. Cost. Processing time (data volume).

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Two images of the Henares river in central Spain. The 15 m resolution of top image provides information about the river, while the 180 m of the bottom only detects it.

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Hierarchical classification: Corine land cover Source: European commission, CORINE guide

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Most common spatial resolutions Pixel size (m 2 )

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Covered area Area covered (km 2 )

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Cost – spatial resolution

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Digital-to-Analog Converter Negative Positive Film Positive Print ESA - EARTHNET LANDSAT-5 4/3/2 MAY Common formats of photographic products

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Digital Media Cartridges CD-ROM / DVD Internet  Sequential access  Low cost  Direct access  Low cost  Massive use.  Quick availability  Low transportation cost.

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Definition of Objectives Bibliographic Review Field workData Acquisition Interpretation Definition of Classes Accuracy Assessment Geo-referencing / Inventory Integration to GIS Interpretation of results Reconnaissance Calibration Generalized procedure for the interpretation of remote sensing imagery

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Spectro-radiometric measurements in the field are useful to select the most convenient sensor and spectral bands

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis Data collection in the field is important to interpret and calibrate satellite images and validate models used. Hemispheric photography for leaf area index estimations.

Chuvieco and Huete (2009): Fundamentals of Satellite Remote Sensing, Taylor and Francis MODIS image of a study region acquired the 19th of February, Includes the majority of Arizona, and parts of Nevada, California, Utah and the Northwest of Mexico