Research Article
BibTex RIS Cite

Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi

Year 2018, Volume: 33 Issue: 3, 887 - 904, 14.08.2018

Seniha Esen Yüksel , Emrah Oduncu

https://doi.org/10.17341/gazimmfd.416393

Abstract

Bu çalışmada hiperspektral veri kümesinde gölgede kalan alanların ışıma ve yansıma değerlerinin, bu alanlardaki gökyüzü açıklığı ile ilişkisi fiziksel bir model içinde incelenmiştir. Öncelikle hiperspektral veride gölgede kalan alanlar LiDAR verileri yardımıyla tespit edilmiştir ve yansıma ve ışıma değerleri çizdirilmiştir. Daha sonra, yine LiDAR verileri kullanılarak, gölgedeki piksellerin gökyüzü açıklığı hesaplanmıştır. Üçüncü olarak, Modtran yazılımı kullanılarak gökyüzü ışıması ve güneş ışıma değerleri ile ilgili parametreler elde edilmiştir. Son olarak da, bu parametreler ve gölgeden toplanan veriler, fiziksel ışıma modeline yerleştirilmiş ve etkileri incelenmiştir. Modtran sonuçları fiziksel ışıma modeline yerleştirildiğinde, gökyüzü açıklığı değerinin artmasına rağmen ışıma ve yansıma verilerinde gözlenen azalma; ışıma modelinde yakında bulunan nesnelerden saçılarak hedeften yansıyan fotonların gökyüzü açıklığından daha baskın olduğunu göstermektedir. Sonuç olarak, hem gerçek verilerde hem de ışıma modeli üzerinde yapılan çalışmalarda, ilgili alanların ışınım ve yayınım verileri incelendiğinde ve fiziksel model ile karşılaştırıldığında, gökyüzü açıklığının yeterince baskın bir eleman olmadığı, buna karşın, gölge alan çevresinde bulunan nesnelerden saçılarak yansıyanlar fotonların daha çok etkinlik gösterdiği gözlenmiştir.

Keywords

Hiperspektral LiDAR ışıma gölge gökyüzü açıklığı

References

  • Richter R., “Hyperspectral Sensors for Military Applications”, DLR, German Aerospace Center Remote Sensing Data Center, OCT 2005.
  • Hege E. K. , O'Connell D., Johnson W. , Basty S. and Dereniak E. L. , “Hyperspectral imaging for astronomy and space surveillance”, SPIE Proceedings Vol. 5159, Imaging Spectrometry IX, January 2004.
  • Tuysuz, B., J. Urbina, and F. D. Lind. "Development of a passive VHF radar system using software defined radio for equatorial plasma instability studies." Radio Science 48.4 (2013): 416-426.
  • Njoku E. G., Entekhabi D., “Passive microwave remote sensing of soil moisture”, Journal of Hydrology 184 ,101-129, 1996
  • Choe E., Meer F., Ruitenbeek F., Werff H., Smeth B. and Kim K., “Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain”, Remote Sensing of Environment 112, 3222–3233, March 2009.
  • Eismann M.T., Hyperspectral remote sensing, SPIE Press Bellingham, 2012.
  • Kruse F. A., “Comparison of ATREM, ACORN, and FLAASH Atmospheric Corrections using Low-Altitude AVIRIS Data of Boulder, Colorado” In proceedings 13th JPL Airborne Geoscience Workshop, 2004.
  • Zhou J., Kwan C., and Ayhan B., "Hybrid In-Scene Atmospheric Compensation (H-ISAC) of hyperspectral images for high performance target detection." In Int. Symp. Spectral Sensing Research, Springfield, MO, USA, 2010.
  • Matteoli S., Ientilucci E. J., and Kerekes J. P., "Forward Modeling and Atmospheric Compensation in hyperspectral data: Experimental analysis from a target detection perspective." In 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, pp. 1-4. IEEE, 2009.
  • Lachérade S., Miesc C. and Boldo D., “ICARE: A physically-based model to correct atmospheric and geometric effects from high spatial and spectral remote sensing images over 3D urban areas”, Meteorol Atmos Phys (2008) 102: 209.
  • Boyaci M., Yuksel S.E., “Locating the shadow regions in LIDAR data: results on the SHARE 2012 dataset”, SPIE Defense and Security: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720K, May 2015.
  • Broadwater J., Banerjee A., “Improved atmospheric compensation of hyperspectral imagery using LIDAR”, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, Melbourne, VIC, 2013, pp. 2200-2203.
  • Hagstrom S., Broadwater J., “Atmospheric and shadow compensation of hyperspectral imagery using voxelized LIDAR”, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2959 – 2962, , 26-31 July 2015.
  • Sakarya U., Demirkesen C. and Teke M., “Unsharp masking filter based shadow-invariant feature extraction for hyperspectral signatures”, 2014 IEEE 22nd Signal Processing and Communications Applications Conference , pp. 293 – 296, April 25, 2014.
  • Omruuzun F., Ozisik Baskurt D., Daglayan H., and Yardimci Cetin Y.. "Shadow removal from VNIR hyperspectral remote sensing imagery with endmember signature analysis." In SPIE Sensing Technology and Applications, pp. 94821F-94821F, 2015.
  • Bernstein L.S., Gruninger J., Hoke M., Felde G. and Anderson G.P. et al, "Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery." In Proc. SPIE, vol. 4381, p. 461. 2001.
  • Friman O., Tolt G. and Ahlberg J., “Illumination and shadow compensation of hyperspectral images using a digital surface model and non-linear least squares estimation”, SPIE 8180, Image and Signal Processing for Remote Sensing XVII 81800Q, 27 October 2011.
  • Ientilucci E. J., “Leveraging LiDAR data to aid in hyperspectral image target detection in the radiance domain”, SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839007, May 9,2012.
  • Ientilucci E. J., “SHARE 2012: analysis of illumination differences on targets in hyperspectral imagery ”,SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 87430I, May 18, 2013.
  • Zhang Q., Pauca V. P., Plemmons R. J., and Nikic D. D.., “Detecting objects under shadows by fusion of hyperspectral and LiDAR data: A physical model approach”, Proc. 5th Workshop Hyperspectral Image Signal Process.: Evol. Remote Sens, 2013.
  • Ashton E. A., Wemett B. D., Leathers R. A., and Downes T. V., "A novel method for illumination suppression in hyperspectral images." In SPIE Defense and Security Symposium, pp. 69660C-69660C. International Society for Optics and Photonics, 2008.
  • Adler-Golden S. M., Matthew M. W., Anderson G. P., Felde G. W., and Gardner J. A., "Algorithm for de-shadowing spectral imagery." In International Symposium on Optical Science and Technology, pp. 203-210, 2002.
  • Schlapfer D., Richter R., and Damm A., "Correction Of Shadowing In Imaging Spectroscopy Data By Quantification Of The Proportion Of Diffuse Illumination," 8th SIG-IS EARSeL Imaging Spectroscopy Workshop, Nantes, 2013.
  • Roper T., Andrews M., "Shadow modelling and correction techniques in hyperspectral imaging," Electronics Letters 49.7 (2013): 458-460.
  • YuanliuX., Runsheng W., Suming Y., Shengwei L. and Bokun Y., “Atmospheric correction of hyperspectral data using Modtran model”, 16th National Symposium on Remote Sensing of China, Proceedings of the SPIE, 712306, 24 November 2008.
  • Berk A. et al., “Modtran5: 2006 update” in Proc. SPIE, Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331F , 8 May 2006.
  • Goforth M. A., Gilchrist G. W., Sirianni J.D. , “Cloud effects on thermal downwelling sky radiance ” Proc. SPIE 4710, Thermosense XXIV, 203, March 15, 2002.
  • SHARE2012 LIDAR 2012 http://www.rit.edu/cos/share2012/lidar.php ,Mart 1, 2017.
  • SHARE2012 SpecTIR 2012 http://www.rit.edu/cos/share2012/spectir.php, Mart 1, 2017.
  • Zakšek K, Oštir K, Kokalj Ž., “Sky-View Factor as a Relief Visualization Technique”, Remote Sensing., 3(2):398-415, 2011 .

Year 2018, Volume: 33 Issue: 3, 887 - 904, 14.08.2018

Seniha Esen Yüksel , Emrah Oduncu

https://doi.org/10.17341/gazimmfd.416393

Abstract

References

  • Richter R., “Hyperspectral Sensors for Military Applications”, DLR, German Aerospace Center Remote Sensing Data Center, OCT 2005.
  • Hege E. K. , O'Connell D., Johnson W. , Basty S. and Dereniak E. L. , “Hyperspectral imaging for astronomy and space surveillance”, SPIE Proceedings Vol. 5159, Imaging Spectrometry IX, January 2004.
  • Tuysuz, B., J. Urbina, and F. D. Lind. "Development of a passive VHF radar system using software defined radio for equatorial plasma instability studies." Radio Science 48.4 (2013): 416-426.
  • Njoku E. G., Entekhabi D., “Passive microwave remote sensing of soil moisture”, Journal of Hydrology 184 ,101-129, 1996
  • Choe E., Meer F., Ruitenbeek F., Werff H., Smeth B. and Kim K., “Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain”, Remote Sensing of Environment 112, 3222–3233, March 2009.
  • Eismann M.T., Hyperspectral remote sensing, SPIE Press Bellingham, 2012.
  • Kruse F. A., “Comparison of ATREM, ACORN, and FLAASH Atmospheric Corrections using Low-Altitude AVIRIS Data of Boulder, Colorado” In proceedings 13th JPL Airborne Geoscience Workshop, 2004.
  • Zhou J., Kwan C., and Ayhan B., "Hybrid In-Scene Atmospheric Compensation (H-ISAC) of hyperspectral images for high performance target detection." In Int. Symp. Spectral Sensing Research, Springfield, MO, USA, 2010.
  • Matteoli S., Ientilucci E. J., and Kerekes J. P., "Forward Modeling and Atmospheric Compensation in hyperspectral data: Experimental analysis from a target detection perspective." In 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, pp. 1-4. IEEE, 2009.
  • Lachérade S., Miesc C. and Boldo D., “ICARE: A physically-based model to correct atmospheric and geometric effects from high spatial and spectral remote sensing images over 3D urban areas”, Meteorol Atmos Phys (2008) 102: 209.
  • Boyaci M., Yuksel S.E., “Locating the shadow regions in LIDAR data: results on the SHARE 2012 dataset”, SPIE Defense and Security: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720K, May 2015.
  • Broadwater J., Banerjee A., “Improved atmospheric compensation of hyperspectral imagery using LIDAR”, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, Melbourne, VIC, 2013, pp. 2200-2203.
  • Hagstrom S., Broadwater J., “Atmospheric and shadow compensation of hyperspectral imagery using voxelized LIDAR”, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2959 – 2962, , 26-31 July 2015.
  • Sakarya U., Demirkesen C. and Teke M., “Unsharp masking filter based shadow-invariant feature extraction for hyperspectral signatures”, 2014 IEEE 22nd Signal Processing and Communications Applications Conference , pp. 293 – 296, April 25, 2014.
  • Omruuzun F., Ozisik Baskurt D., Daglayan H., and Yardimci Cetin Y.. "Shadow removal from VNIR hyperspectral remote sensing imagery with endmember signature analysis." In SPIE Sensing Technology and Applications, pp. 94821F-94821F, 2015.
  • Bernstein L.S., Gruninger J., Hoke M., Felde G. and Anderson G.P. et al, "Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery." In Proc. SPIE, vol. 4381, p. 461. 2001.
  • Friman O., Tolt G. and Ahlberg J., “Illumination and shadow compensation of hyperspectral images using a digital surface model and non-linear least squares estimation”, SPIE 8180, Image and Signal Processing for Remote Sensing XVII 81800Q, 27 October 2011.
  • Ientilucci E. J., “Leveraging LiDAR data to aid in hyperspectral image target detection in the radiance domain”, SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839007, May 9,2012.
  • Ientilucci E. J., “SHARE 2012: analysis of illumination differences on targets in hyperspectral imagery ”,SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 87430I, May 18, 2013.
  • Zhang Q., Pauca V. P., Plemmons R. J., and Nikic D. D.., “Detecting objects under shadows by fusion of hyperspectral and LiDAR data: A physical model approach”, Proc. 5th Workshop Hyperspectral Image Signal Process.: Evol. Remote Sens, 2013.
  • Ashton E. A., Wemett B. D., Leathers R. A., and Downes T. V., "A novel method for illumination suppression in hyperspectral images." In SPIE Defense and Security Symposium, pp. 69660C-69660C. International Society for Optics and Photonics, 2008.
  • Adler-Golden S. M., Matthew M. W., Anderson G. P., Felde G. W., and Gardner J. A., "Algorithm for de-shadowing spectral imagery." In International Symposium on Optical Science and Technology, pp. 203-210, 2002.
  • Schlapfer D., Richter R., and Damm A., "Correction Of Shadowing In Imaging Spectroscopy Data By Quantification Of The Proportion Of Diffuse Illumination," 8th SIG-IS EARSeL Imaging Spectroscopy Workshop, Nantes, 2013.
  • Roper T., Andrews M., "Shadow modelling and correction techniques in hyperspectral imaging," Electronics Letters 49.7 (2013): 458-460.
  • YuanliuX., Runsheng W., Suming Y., Shengwei L. and Bokun Y., “Atmospheric correction of hyperspectral data using Modtran model”, 16th National Symposium on Remote Sensing of China, Proceedings of the SPIE, 712306, 24 November 2008.
  • Berk A. et al., “Modtran5: 2006 update” in Proc. SPIE, Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331F , 8 May 2006.
  • Goforth M. A., Gilchrist G. W., Sirianni J.D. , “Cloud effects on thermal downwelling sky radiance ” Proc. SPIE 4710, Thermosense XXIV, 203, March 15, 2002.
  • SHARE2012 LIDAR 2012 http://www.rit.edu/cos/share2012/lidar.php ,Mart 1, 2017.
  • SHARE2012 SpecTIR 2012 http://www.rit.edu/cos/share2012/spectir.php, Mart 1, 2017.
  • Zakšek K, Oštir K, Kokalj Ž., “Sky-View Factor as a Relief Visualization Technique”, Remote Sensing., 3(2):398-415, 2011 .
There are 30 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler
Authors

Seniha Esen Yüksel

Emrah Oduncu This is me

Publication Date August 14, 2018
Submission Date January 2, 2017
Acceptance Date April 2, 17
Published in Issue Year 2018 Volume: 33 Issue: 3

Cite

APA Yüksel, S. E., & Oduncu, E. (2018). Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33(3), 887-904. https://doi.org/10.17341/gazimmfd.416393
AMA Yüksel SE, Oduncu E. Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi. GUMMFD. August 2018;33(3):887-904. doi:10.17341/gazimmfd.416393
Chicago Yüksel, Seniha Esen, and Emrah Oduncu. “Gölgelik Alanlarda komşu Nesnelerin ışımaya Olan Etkisinin gerçek Veriler Ve Fiziksel ışıma Modeli üzerinden Incelenmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 33, no. 3 (August 2018): 887-904. https://doi.org/10.17341/gazimmfd.416393.
EndNote Yüksel SE, Oduncu E (August 1, 2018) Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 33 3 887–904.
IEEE S. E. Yüksel and E. Oduncu, “Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi”, GUMMFD, vol. 33, no. 3, pp. 887–904, 2018, doi: 10.17341/gazimmfd.416393.
ISNAD Yüksel, Seniha Esen - Oduncu, Emrah. “Gölgelik Alanlarda komşu Nesnelerin ışımaya Olan Etkisinin gerçek Veriler Ve Fiziksel ışıma Modeli üzerinden Incelenmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 33/3 (August 2018), 887-904. https://doi.org/10.17341/gazimmfd.416393.
JAMA Yüksel SE, Oduncu E. Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi. GUMMFD. 2018;33:887–904.
MLA Yüksel, Seniha Esen and Emrah Oduncu. “Gölgelik Alanlarda komşu Nesnelerin ışımaya Olan Etkisinin gerçek Veriler Ve Fiziksel ışıma Modeli üzerinden Incelenmesi”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 33, no. 3, 2018, pp. 887-04, doi:10.17341/gazimmfd.416393.
Vancouver Yüksel SE, Oduncu E. Gölgelik alanlarda komşu nesnelerin ışımaya olan etkisinin gerçek veriler ve fiziksel ışıma modeli üzerinden incelenmesi. GUMMFD. 2018;33(3):887-904.