XXII ISPRS Congress 2012: Technical Commission VII

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Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/6: REMOTE SENSING DATA FUSION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: SYNTHETIC APERTURE RADAR (SAR) AND OPTICAL IMAGERY DATA FUSION: CROP YIELD ANALYSIS IN SOUTHEAST ASIA S. M. Parks

Document type:: Multivolume work

Structure type:: Chapter

loaded into SARscape in ENVI using the ASAR product standard format reader. The processing of the multi- temporal ASAR APS data involved several steps including: l. Data import of the original ESA datasets. 2. Data multilooking (number of looks: 1 and 5 respectively in azimuth and range), Data coregistration. 4. Data multitemporal Filtering (using a De Grandi method). 5. Extraction of SRTM-3 version 4 DEMs for use with geocoding. 6. Data geocoding with radiometric calibration and normalization (using a grid size 25 m to match the resolution of the ASAR data). Ww These steps roughly consist of image calibration or conversion to the radar backscattering coefficient sigma nought (co), image registration or geocoding, and image spatial filtering (Nguyen, Armando, Thuy, Young, Trung, & Bouvet, 2009). Image calibration consists of correcting SAR images for incidence angle effect and for replica pulse power variations to derive physical values (Nguyen, Armando, Thuy, Young, Trung, & Bouvet, 2009). The processed SAR datasets were then fused with Landsat ETM+ scenes from 2011, and ENVI was used to classify the images in order to quantify the area covered by the rice Crops. 3. RESULTS The processed SAR images for each of the dates during the growing season are represented in Figure 1 below. The rice crops are represented by the darker areas at the beginning of the growing season (Figure 1a) as the backscatter coefficient for water is lower. Once the plants emerge from the water, the backscatter coefficient gets higher and these areas become brighter in the images from August through October (Figure 1: b), c) and d)). As the crops mature and are harvested starting in November (Figure 1: e), the areas begin to appear darker again. k Bs a) July 2011 September 2011 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia “ e) November 2011 Figure 1. Processed SAR Multi-temporal Images; HH Polarization After the ENVISAT ASAR data was processed, SARscape in ENVI was used to produce an RGB color composites using HH and HV bands in order to improve the visualization of the objects in the images. In the series of RGB color composites shown in Figure 2 below, red = (input 1 - input 2) / (input 1 + input 2), green = input 2, and blue = input 1. This type of color composite enhances the differences in the backscatter results of the rice crops during different periods of the growing season. The forests (green) are more easily distinguished from the rice crop fields (red to purple depending on water content). ) July 2011 c) September 2011 d) October 2011 - €) November 2011. Figure 2. Processed SAR Multi-temporal Images; Color Composites In the ETM+ image from Figure 3 below, at the end of the growing season in November, the light green areas represent the forested areas, the pink/purple areas represent the fields where the rice has been harvested, and the blue areas represent water.

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