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Toprak Nemi İle Radarsat Geri Yansıtım Değerleri Arasındaki İlişkiler; Artvin-Merkez ve Gümüşhane-Karanlıkdere Orman Planlama Birimi Örnekleri

Year 2017, Volume: 17 Issue: 1, 36 - 44, 05.03.2017
https://doi.org/10.17475/kastorman.296199

Abstract

Bu çalışmanın amacı, Artvin-Merkez ve
Gümüşhane-Karanlıkdere planlama birimlerinde farklı yetişme özellikleri ve
farklı meşcere kapalılığına sahip örnek alanlardan elde edilen toprak nemi ile
Radarsat uydu görüntüsü kullanılarak her bir örnek alandan elde edilen geri
yansıtım değerleri arasındaki ilişkilerin belirlenmesidir. Artvin-Merkez
planlama biriminde kuru ve taze-tazece yetişme ortamları ile düşük ve bozuk
orman alanlarında toprak nemi ile geri yansıtım değerleri arasında sırasıyla
negatif ilişkiler bulunmuştur (
r=-0.85
ve r=-0.73).
Buna karşın, orta ve tam kapalı meşcerelerde
herhangi bir ilişki bulunamamıştır. Gümüşhane-Karanlıkdere planlama biriminde
ise çok kuru-kuru ve taze-tazece yetişme ortamları ile düşük ve bozuk orman
alanlarında toprak nemi ile geri yansıtım değerleri arasında sırasıyla pozitif
ilişkiler bulunmuştur (
r=0.78
ve r=0.83)

References

  • Ahmad S., Kalra A., Stephen H. 2010. Estimating soil moisture using remote sensing data: a machine learning approach. Advances in Water Resources, 33(1), 69-80.
  • Altun L., Başkent E.Z., Bakkaoğlu M., Günlü A., Kadıoğulları A.İ. 2008. Comparing methods for determining forest sites: a case study in Gümüşhane-Karanlıkdere forest. European Journal of Forest Research, 127, 395-406.
  • Altun L., Baskent E.Z., Gunlu A, Kadioğullari A.İ. 2008. Classification and mapping forest sites using geographic information system (GIS): a case study in Artvin Province. Environ. Monitor. Assess. , 137, 149-161.
  • Anonymous. 2001a. Artvin meteorology station climate data.
  • Anonymous. 2001b. Gumushane meteorology station climate data.
  • Baghdadi N, Cerdan O, Zribi M, Auzet V, Darboux F, El Hajj M, Bou Kheir R. 2008. Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling. Hydrol. Proc, 22, 9-20.
  • Bakkaloğlu, M. 2003. Classification and mapping of forest sites in Gumushane-Karanlıkdere Forest District. PhD thesis, Karadeniz Technical University, The Graduate School of Natural and Applied Sciences, 177 p, Trabzon.
  • Balik Sanli F, Kurucu Y, Esetlili M.T., Saygın A. 2008. Soil moisture estimation from radarsat-1, asar and palsar data in agricultural fields of Menemen Plane of Western Turkey. XXIst ISPRS Congress, 3-11 July, Beijing, China.
  • Bertuzzi P, Chanzy A, Vidal-Madjar D, Autret A. 1992, The use of microwave backscatter model for retrieving soil moisture over bare soil. International Journal of Remote Sensing, 13, 2653–2668.
  • Bhagat VS. 2009. Use of Landsat ETM+ data for detection of potential areas for Afforestation. International Journal of Remote Sensing, 30, 2607–2617.
  • Bindlish R, Barros A.P. 2000. Multifrequency soil moisture inversion from SAR measurements with the use of IEM, Remote Sens. Environ., 71, 61– 88.
  • Dieguez-Aranda U, Grandas-Arias J.A., Alvarez-Gonzalez J.G., Von Gadow K.2006. Site quality curves for Birch stands in North-Western Spain. Silva Fenn, 40(4), 631-644.
  • Dobson M.C., Ulaby, F.T. 1986, Active microwave soil moisture research. IEEE Transactions on Geoscience and Remote Sensing, 24, 23–36.
  • Engman E.T., Chauhan, N. 1995. Status of microwave soil moisture measurements with remote sensing. Remote Sens. Environ., 51, 189-198.
  • Erdas. 2002. Erdas Field Guide sixth edition. Erdas LLC, Atlanta, Georgia.
  • Eric S. Kasischke, Laura L. Bourgeau-Chavez, Allison R. Rober, Kevin H. Wyatt, James M. Waddington, Merritt R. Turetsky. 2009. Effects of soil moisture and water depth on ERS SAR backscatter measurements from an Alaskan wetland complex. Remote Sensing of Environment, 113, 1868-1873.
  • Glenn N.F., Carr J.R. 2003. The use of geostatistics in relating soil moisture to Radarsat-1 SAR data obtained over the Great Basin, Nevada, USA, Comput. Geosci., 29 , 577–586.
  • Günlü A., Başkent E.Z., Kadıoğulları A.İ., Altun L. 2009. Forest site classification using Landsat 7 ETM Data: A case study of Maçka-Ormanüstü Forest, Turkey. Environ. Monitor. Assess, 151, 93-104.
  • He B., Xing M., Bai X. 2014. A Synergistic methodology for soil moisture estimation in an Alpine Prairie using radar and optical satellite data. Remote Sensing, 6(11), 10966-10985.
  • Hutchinson J.M.S. 2003. Estimating near-surface soil moisture using active microwave satellite imagery and optical sensor inputs. Trans. Am. Soc. Agric. Eng., 46(2), 225-236.
  • Hymer D.C., Moran M.S., Keefer T.O. 2000. Soil moisture evaluation using a hydrologic model and calibrated sensor network. Soil Sci. Soc. Am. J. 64, 319–326.
  • Lillesand M.T., Kiefer W.K. 2000. Remote Sensing and Image Interpretation, John Wiley and Sons, New York.
  • Mattikalli M.N., Engman E.T., Ahuja, L.R., Jackson T.J. 1998. Mirowave remote sensing of soil moisture for estimation of pro. le soil property. International Journal of Remote Sensing, 19, 1751–1767.
  • Moeremans B., Dautrebande S. 2000. Soil moisture evaluation using multi-temporal synthetic aperture radar (SAR) in semiarid rangeland. Agriculture and Forest Meteorology, 105, 69-80.
  • Musaoglu N, 1999. Possibilities of determining the types of tree stocks in the forest and the units of growing sites by means of satellite images obtained from the electro-optıcal and active microwave sensors, Ph.D., Istanbul Technical University, Graduate School of Natural And Applıed Scıence, İstanbul.
  • Notarnicola C., Angiulli M., Posa F. 2006. Use of radar and optical remotely sensed data for soil moisture retrieval over vegetated areas. IEEE Transactions on Geoscience and Remote Sensing, 44, 925–935.
  • Pan Y., Birdsey R., Hom J., Mccullough K., Clark K. 2006, Improved estimates of net primary productivity from MODIS satellite data at regional and local scales. Ecological Applications, 16, 125–132.
  • Rowell D.L. 1994, Soil Science: Methods and Applications (Harlow: Longman Group).
  • Sahebi M.R., Bonn F., Gwyn Q.H.J. 2003. Estimation of the moisture content of bare soil from Radarsat-1 SAR using simple empirical modals. International Journal of Remote Sensing, 24, 2575-2582.
  • Shimada M., Isoguchi O., Tadono T., Higuchi R., Isono K. 2007. Palsar calval summary and update, Proc. IGARSS, pp. 3593.
  • SPSS Institute Inc. SPSS Base 15.0 User’s Guide, 2007
  • Ulaby F.T., Moore R.K., Fung A.K. 1986. Microwave remote sensing: active and passive; Artech House: Boston, MA, Vol. III.
  • Ulaby F.T., Dubois P.C., Van Zyl J. 1996. Radar mapping of surface soil moisture. J. Hydrol. 184, 57–84.

Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units

Year 2017, Volume: 17 Issue: 1, 36 - 44, 05.03.2017
https://doi.org/10.17475/kastorman.296199

Abstract

The
purpose of this study was to determine the relationships between soil moisture
and backscattering coefficient values calculated for each sampling plot and
compare with soil moisture in different forest sites and crown closure classes
using Radarsat satellite images in Artvin-Merkez and Gümüşhane-Karanlıkdere
forest planning units. Results indicate that in low coverage and degraded
forest areas in dry and fresh-moderate fresh forest sites in Artvin forest
planning unit, the relations between soil moisture and backscatter coefficient
values were negatively correlated with r=-0.85 and r=-0.73, respectively.
However, there was no relationship between backscatter coefficient values and
soil moisture in medium crown coverage and full coverage stands.  Similarly, at low coverage and degraded
forest areas in very dry-dry and fresh-moderate fresh forest sites in
Gümüşhane-Karanlıkdere forest planning unit were positively correlated high and
significant r=0.78 and r=0.83, respectively

References

  • Ahmad S., Kalra A., Stephen H. 2010. Estimating soil moisture using remote sensing data: a machine learning approach. Advances in Water Resources, 33(1), 69-80.
  • Altun L., Başkent E.Z., Bakkaoğlu M., Günlü A., Kadıoğulları A.İ. 2008. Comparing methods for determining forest sites: a case study in Gümüşhane-Karanlıkdere forest. European Journal of Forest Research, 127, 395-406.
  • Altun L., Baskent E.Z., Gunlu A, Kadioğullari A.İ. 2008. Classification and mapping forest sites using geographic information system (GIS): a case study in Artvin Province. Environ. Monitor. Assess. , 137, 149-161.
  • Anonymous. 2001a. Artvin meteorology station climate data.
  • Anonymous. 2001b. Gumushane meteorology station climate data.
  • Baghdadi N, Cerdan O, Zribi M, Auzet V, Darboux F, El Hajj M, Bou Kheir R. 2008. Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling. Hydrol. Proc, 22, 9-20.
  • Bakkaloğlu, M. 2003. Classification and mapping of forest sites in Gumushane-Karanlıkdere Forest District. PhD thesis, Karadeniz Technical University, The Graduate School of Natural and Applied Sciences, 177 p, Trabzon.
  • Balik Sanli F, Kurucu Y, Esetlili M.T., Saygın A. 2008. Soil moisture estimation from radarsat-1, asar and palsar data in agricultural fields of Menemen Plane of Western Turkey. XXIst ISPRS Congress, 3-11 July, Beijing, China.
  • Bertuzzi P, Chanzy A, Vidal-Madjar D, Autret A. 1992, The use of microwave backscatter model for retrieving soil moisture over bare soil. International Journal of Remote Sensing, 13, 2653–2668.
  • Bhagat VS. 2009. Use of Landsat ETM+ data for detection of potential areas for Afforestation. International Journal of Remote Sensing, 30, 2607–2617.
  • Bindlish R, Barros A.P. 2000. Multifrequency soil moisture inversion from SAR measurements with the use of IEM, Remote Sens. Environ., 71, 61– 88.
  • Dieguez-Aranda U, Grandas-Arias J.A., Alvarez-Gonzalez J.G., Von Gadow K.2006. Site quality curves for Birch stands in North-Western Spain. Silva Fenn, 40(4), 631-644.
  • Dobson M.C., Ulaby, F.T. 1986, Active microwave soil moisture research. IEEE Transactions on Geoscience and Remote Sensing, 24, 23–36.
  • Engman E.T., Chauhan, N. 1995. Status of microwave soil moisture measurements with remote sensing. Remote Sens. Environ., 51, 189-198.
  • Erdas. 2002. Erdas Field Guide sixth edition. Erdas LLC, Atlanta, Georgia.
  • Eric S. Kasischke, Laura L. Bourgeau-Chavez, Allison R. Rober, Kevin H. Wyatt, James M. Waddington, Merritt R. Turetsky. 2009. Effects of soil moisture and water depth on ERS SAR backscatter measurements from an Alaskan wetland complex. Remote Sensing of Environment, 113, 1868-1873.
  • Glenn N.F., Carr J.R. 2003. The use of geostatistics in relating soil moisture to Radarsat-1 SAR data obtained over the Great Basin, Nevada, USA, Comput. Geosci., 29 , 577–586.
  • Günlü A., Başkent E.Z., Kadıoğulları A.İ., Altun L. 2009. Forest site classification using Landsat 7 ETM Data: A case study of Maçka-Ormanüstü Forest, Turkey. Environ. Monitor. Assess, 151, 93-104.
  • He B., Xing M., Bai X. 2014. A Synergistic methodology for soil moisture estimation in an Alpine Prairie using radar and optical satellite data. Remote Sensing, 6(11), 10966-10985.
  • Hutchinson J.M.S. 2003. Estimating near-surface soil moisture using active microwave satellite imagery and optical sensor inputs. Trans. Am. Soc. Agric. Eng., 46(2), 225-236.
  • Hymer D.C., Moran M.S., Keefer T.O. 2000. Soil moisture evaluation using a hydrologic model and calibrated sensor network. Soil Sci. Soc. Am. J. 64, 319–326.
  • Lillesand M.T., Kiefer W.K. 2000. Remote Sensing and Image Interpretation, John Wiley and Sons, New York.
  • Mattikalli M.N., Engman E.T., Ahuja, L.R., Jackson T.J. 1998. Mirowave remote sensing of soil moisture for estimation of pro. le soil property. International Journal of Remote Sensing, 19, 1751–1767.
  • Moeremans B., Dautrebande S. 2000. Soil moisture evaluation using multi-temporal synthetic aperture radar (SAR) in semiarid rangeland. Agriculture and Forest Meteorology, 105, 69-80.
  • Musaoglu N, 1999. Possibilities of determining the types of tree stocks in the forest and the units of growing sites by means of satellite images obtained from the electro-optıcal and active microwave sensors, Ph.D., Istanbul Technical University, Graduate School of Natural And Applıed Scıence, İstanbul.
  • Notarnicola C., Angiulli M., Posa F. 2006. Use of radar and optical remotely sensed data for soil moisture retrieval over vegetated areas. IEEE Transactions on Geoscience and Remote Sensing, 44, 925–935.
  • Pan Y., Birdsey R., Hom J., Mccullough K., Clark K. 2006, Improved estimates of net primary productivity from MODIS satellite data at regional and local scales. Ecological Applications, 16, 125–132.
  • Rowell D.L. 1994, Soil Science: Methods and Applications (Harlow: Longman Group).
  • Sahebi M.R., Bonn F., Gwyn Q.H.J. 2003. Estimation of the moisture content of bare soil from Radarsat-1 SAR using simple empirical modals. International Journal of Remote Sensing, 24, 2575-2582.
  • Shimada M., Isoguchi O., Tadono T., Higuchi R., Isono K. 2007. Palsar calval summary and update, Proc. IGARSS, pp. 3593.
  • SPSS Institute Inc. SPSS Base 15.0 User’s Guide, 2007
  • Ulaby F.T., Moore R.K., Fung A.K. 1986. Microwave remote sensing: active and passive; Artech House: Boston, MA, Vol. III.
  • Ulaby F.T., Dubois P.C., Van Zyl J. 1996. Radar mapping of surface soil moisture. J. Hydrol. 184, 57–84.
There are 33 citations in total.

Details

Journal Section Articles
Authors

Alkan Günlü

Emin Zeki Başkent

Publication Date March 5, 2017
Published in Issue Year 2017 Volume: 17 Issue: 1

Cite

APA Günlü, A., & Başkent, E. Z. (2017). Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units. Kastamonu University Journal of Forestry Faculty, 17(1), 36-44. https://doi.org/10.17475/kastorman.296199
AMA Günlü A, Başkent EZ. Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units. Kastamonu University Journal of Forestry Faculty. March 2017;17(1):36-44. doi:10.17475/kastorman.296199
Chicago Günlü, Alkan, and Emin Zeki Başkent. “Relationships Between Soil Moisture and RADARSAT Derived Backscattering Coefficient Values: A Case Studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units”. Kastamonu University Journal of Forestry Faculty 17, no. 1 (March 2017): 36-44. https://doi.org/10.17475/kastorman.296199.
EndNote Günlü A, Başkent EZ (March 1, 2017) Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units. Kastamonu University Journal of Forestry Faculty 17 1 36–44.
IEEE A. Günlü and E. Z. Başkent, “Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units”, Kastamonu University Journal of Forestry Faculty, vol. 17, no. 1, pp. 36–44, 2017, doi: 10.17475/kastorman.296199.
ISNAD Günlü, Alkan - Başkent, Emin Zeki. “Relationships Between Soil Moisture and RADARSAT Derived Backscattering Coefficient Values: A Case Studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units”. Kastamonu University Journal of Forestry Faculty 17/1 (March 2017), 36-44. https://doi.org/10.17475/kastorman.296199.
JAMA Günlü A, Başkent EZ. Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units. Kastamonu University Journal of Forestry Faculty. 2017;17:36–44.
MLA Günlü, Alkan and Emin Zeki Başkent. “Relationships Between Soil Moisture and RADARSAT Derived Backscattering Coefficient Values: A Case Studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units”. Kastamonu University Journal of Forestry Faculty, vol. 17, no. 1, 2017, pp. 36-44, doi:10.17475/kastorman.296199.
Vancouver Günlü A, Başkent EZ. Relationships between Soil Moisture and RADARSAT derived Backscattering Coefficient Values: a case studies in Artvin-Merkez and Gümüşhane-Karanlıkdere Forest Planning Units. Kastamonu University Journal of Forestry Faculty. 2017;17(1):36-44.

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