Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

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Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

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

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; 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:: BRDF CORRECTION ON AVHRR IMAGERY FOR SPAIN H. Heisig

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 on a nomenclature of 44 classes that are hierarchically organised into three levels (CORINE Land Cover Report, 2000). These data were reprojected to fit projection and cell size of the AVHRR imagery. The original land cover types were aggregated into 14 land cover classes to represent major structural and surface cover combinations. For each aggregated land cover class between 60 and 100 sampling points were defined. Minimum distance to pixels of other classes was 5 pixels, minimizing thus the effect of transition pixels. For these sampling points the median reflectance value from a 3*3 window were sampled. Table | lists the agglomerated CORINE Land Cover classes and their relative fraction of the surface of Spain. Aggregated | Comprises classes % class coverage 12 12: Non irrigated arable land 23.08 13 13: Irrigated arable land 7:33 15: Vine yards 16: Fruit trees and berry plantations 17 17: Olive grows 3.13 20 18: Pastures 8.39 19: Annual with permanent crops 20: Complex cultivation patterns 21 21: Agriculture with natural 523 vegetation 22 22: Agro forestry areas 4.73 23 23: Broad leafed forests 6.88 24 24: Coniferous forests 9.00 25 25: Mixed forests 2.11 26 26: Natural grassland 5.54 27 27: Moors and heathland 3.54 28 28: Sclerophyllous vegetation 10.27 29 29: Transitional woodland shrub 6.45 31 31: Bare rock 2.42 32: Sparsely vegetated areas 0 All other classes (mainly 1.70 settlements) Table 1: CORINE Land Cover classes and relative fraction of surface 2.5 Temporal and angular sampling Data were sampled from cloud mask processed datasets from throughout the study period. Between 1000 and 2000 observations per aggregated land cover class were obtained. Alternatively to cloud mask processing, data might have been sampled from cloud free composites. 2.6 Model inversion and statistic parameters For model inversion, the CCRS kindly provided its MIB (Model Inversion of BRDF) software tool. For the linear models, the MIB works on a matrix inversion based procedure. For the NTAM, the modified Powell’s minimization method is used to calculate the non-linear least squares fit in an iterative procedure (Latifovic et al., 2003). Statistic parameters used in the MIB are: 42 ae» . . 2 - e The coefficient of determination R* defined by: 8° 2 = 1 R = M where: 1 N 8° = N >b, m (acht 5? 1 N 2 1 N 2 obs = N > (04) E N 2. (aJ) i=1 i= e The standard error of the estimate (se) defined by: 2 Sb, = De] where: Po», = Observed reflectance p = modelled reflectance N = number of observations 3. RESULTS AND DISCUSSION The CORINE Land Cover class 17 (olive grows), maybe the most emblematic land cover for Spain, was chosen to demonstrate the quality of the regression. In figure 2 modelled and observed reflectance are displayed for the sampling data in the NIR channel. 1052 observations were collected from NOAA 15 data and 852 observations originate from NOAA 16 data. The data from the two sensors were inverted together. They are displayed in different colours only for better legibility. 0,3 ; [0] i D 025 | & | S 0,2 = © 0.15 + NOAA 15 © = NOAA 16 > 0,1 4 o TS osse), 05 | E | 0 ud 0 0,1 0,2 0,3 0,4 observed reflectance Figure 2: Observed and modelled reflectances for olive grows The statistic results of the inverse mode are very satisfying. Figure 3 displays the coefficient of determination for the different aggregated land cover classes. The mean coefficient of determination for all land cover classes is 0.79 for the VIS and 0.83 for the NIR channel. Homogeneous land cover classes, e.g. class 17: olive grows and class 24: coniferous forest, are generally only slightly better modelled than more heterogeneous classes. For the latter ones, the classes 12, arable land, and 20, complex cultivation patterns may be named as examples. This shows well how the NTAM accounts for the varying amount of green leaf area within one vegetation class.

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