استفاده از تصاویر ماهواره‌ای و داده‌های طیفی در برآورد مقدار کربن آلی خاک در جنگل‌های زاگرس میانی در خوزستان
محورهای موضوعی :
کشاورزی و محیط زیست
سعیده اسمی زاده
1
,
احمد لندی
2
,
حمید رضا متین فر
3
1 - دانشجوی دکتری گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، ایران.
2 - استاد گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، ایران. *(مسوول مکاتبات)
3 - استاد گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه لرستان، ایران.
تاریخ دریافت : 1397/02/05
تاریخ پذیرش : 1397/04/25
تاریخ انتشار : 1402/01/01
کلید واژه:
کربن آلی خاک,
ماهواره لندست,
روش رگرسیون گام به گام,
شاخص‌های گیاهی و رطوبتی,
چکیده مقاله :
زمینه و هدف: کربن آلی خاک (SOC) یکی از حیاتی ترین خصوصیات فیزیکی و شیمیایی خاک است که از تنزل و انهدام خاک جلوگیری به عمل می آورد. هدف از این مطالعه بررسی تغییرات مقدار SOC با استفاده از تکنیک سنجش از دور در مقایسه با روش های نمونه برداری مزرعه ای در جنگل های زاگرس میانی در استان خوزستان ایران در طول 2 دهه گذشته است.
روش بررسی: نمونه های خاک به منظور اندازه گیری مقدار SOC در آزمایشگاه به صورت تصادفی و از خاک سطحی (عمق cm 10-0) جمع آوری شد. آنالیز داده های دیجیتالی با استفاده از تصاویر به دست آمده از سنجنده های OLI ماهواره لندست 8 و ETM+ ماهواره لندست 7 در سال 2016 (سال نمونه برداری) به منظور تخمین سطوح ماده آلی سطحی خاک انجام یافت. هدف اصلی برقراری ارتباط میان کربن آلی خاک با نسبت های انعکاسی باندهای ماهواره لندست و شاخص های گیاهی و رطوبتی مانند NDVI، SAVI، BSCI، NDMI و NSMI بر اساس مقادیر SOC به دست آمده از نمونه های خاک مناطق جنگلی در کوه های زاگرس میانی بوده و بدین منظور این داده ها با روش های مختلف رگرسیون خطی مورد بررسی قرار گرفت.
یافته ها: در بهترین مدل متناسب از روش رگرسیون گام به گام مقدار R2 برای ماهواره لندست 8 برابر با 435/0 و برای ماهواره لندست 7 برابر با 501/0 به دست آمد و بر اساس این نتایج، بررسی تغییرات کربن آلی در سال های قبل صورت گرفت.
بحث و نتیجه گیری: نتایج نشان دهنده ارتباط معنی دار میان مواد آلی خاک و انعکاس های محدوده طیفی قرمز، مادون قرمز نزدیک و مادون قرمز کوتاه می باشد.
چکیده انگلیسی:
Background & Objective: Soil organic carbon (SOC) is one of the most important components of soil physical and chemical properties that prevented soil decay and destruction. The objective of the present study is the evaluation of SOC changes using the remote sensing technique compared with field methods at central Zagros forests in Khoozestan province in Iran over the past 2 decades.
Material and Methodology: The soil samples were collected randomly from the soil surface (0-10 cm depth) to estimate the SOC concentrations in the laboratory. Analysis of digital data by using Operational Land Imager (OLI) of satellite Landsat 8 and Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7 images in 2016 (the sampling year) was done to estimate surface organic carbon levels of soil. The main objective was to establish soil organic carbon relation with landsat different bands ratios and also herbal and moisture indexes such as NDVI, SAVI, BSCI, NDMI and NSMI corresponding to the SOC values obtained from soil samples of the forest areas in the central Zagros mountain, and for that purpose these data were evaluated using different linear regression methods.
Findings: The best fit model of stepwise regression method showed R2 value of 0.435 for landsat 8 and R2 value of 0.501 for landsat 7 and finally based on these results, evaluation of SOC changes occurred in previous years.
Discussion and conclusion: Results show the significant relationship between soil organic carbon and the reflectance in the Visible, Near-Infrared and Short-wave Infrared part of the spectrum.
منابع و مأخذ:
Craswell, E.T., Lefroy, R.D.B., 2001. The role and function of organic matter in tropical soils. Nutrient Cycling in Agro ecosystems, 61(1/2): 7-18.
Post, W.M., Izaurralde, R.C., Mann L.K., Bliss, N., 2001. Monitoring and verifying changes of organic carbon in soil. Climate Change, 51: 73-99.
Mallah Nokandeh, S., Homaee, M., Noroozi, A., 2014. Investigation on feasibility of estimating soil organic matter using Hyperion hyperspectral imagery in Ivanekey and Urmia. Watershed Engineering and Management, Vol. 6, Issue 3. (In Persian)
Danesh, M., Bahrami, H.A., Noroozi, A.A., 2011. A synchronous investigation of soil geometric mean particle diameter and lime, using remote sensing technology (case study: Pol-e-Dokhtar, the southwest of Lorestan province, Iran). J. Agr. Sci. Tech, 12, 479-494.
Stephens, S.C., Rasmussen, V.P., Ramsey, R.D., Whitesides, R.E., Searle, G.S., Newhall, R.L., 2005. Remote sensing organic carbon in soil. USU/NASA SGEP Projects; available online (15-09-05), www.extnasa.usu.edu/link_pages/downloads/remote_sensing_carbon.pdf.
Ben-Dor, E., Patkin, K., Banin, A., Karnieli, A., 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel. Int. J. Remote Sens., 23(6): 1043-1062.
Dematte, M.J.A., Epiphanio, N.J.C., Formaggio, A.R., 2003. Influence of organic matter and iron oxides on the spectral reflectance of tropical soils. Bragantia, 62(3): 451-464.
Shirazi, M., Zehtabian, Gh., Alavipanah, S.K., 2010. Applicability of IRS Satellite Images for Surveying Water, Soil and Vegetation Cover Condition of Najm Abad Region, Savojbolagh. Journal of Natural Environmental, Iranian Journal of Natural Resources, Vol. 63, No. 1, pp.33-51. (In Persian)
Mohamadi, J., 2006. Pedometer. Vol. 2 (Spatial statistics). Pelk Publications, p. 453. (In Persian)
Hanquet, B., Sirjacobs, D., Destain, M.F., Frankinet, M., Verbrugge, J.C., 2004. Analysis of soil variability measured with a soil strength sensor. Precision Agriculture, 5(3): 227-246.
Ladoni, M., 2009. Estimating soil organic carbon from soil reflectance: a review. Springer Science+Business Media.
Henderson, T.L., Baumgardner, M.F., Franzmeier, D.P., Stott, D.E., Coster, D.C., 1992. High dimensional reflectance analysis of soil organic matter. Soil Science Society of America Journal, 56: 865–872.
Soan, Y.B., Gardner, W.D., Mishonov, A.V., Richardson, M.J., 2013. Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico. J. Earth Syst. Sci, 118, 1-10.
Hummel, J.W., Sudduth, K.A., Hollinger, S.E., 2001. Soil moisture and organic matter prediction of surface and subsurface soils using an NIR soil sensor. Comput. Electron. Agr., 32(2): 149-165.
Walkley, A., Black, I.A., 1934. An examination of the Degtjareff method for determining organiccarbon in soils: effect of variations in digestion conditions and of inorganic soil constituents. SoilScience, 63: 251-263.
Matinfar, H.R., Alavi Panah, S.K., Rafiei Emam, A., 2010. Remotely sensed data evaluation on soil spectral properties in arid regions. Iranian journal of Range and Desert Reseach, Vol. 16 No. (4). (In Persian)
Angstrum, 1925. Reflectance properties of soils. In: adv. In agronomy, 38: 1-44.
Ben-Dor, E., Banin, A., 1995. Near-infrared analysisas a rapid method to simultaneously evaluateseveral soil properties. Soil Science Society of America Journal, 59, pp.364-372.
Sheklabadi, M., Khademi, H., Karimian Eghbal, M., Nourbakhsh, F., 2007. Effect of climate and long term grazing exclusion on selected soil biological quality indicators in rangelandas of centeral Zagros. Agricultural Sciences and Natural Resources, 41: 103-115. (In Persian)
Bagherifam, S., Karimi, A.R., Lakzian, A., Izanloo, E., 2013. Effects of land use management on soil organic carbon, particle size distribution and aggregate stability along hillslope in semi-arid areas of northern Khorasan. Journal of Water and Soil Conservation, Vol. 20(4).(In Persian)
Shataee, Sh., Hossein Ali zadeh, M., Ayoubi, Sh., 2007. Study on the potential of ETM+ spectral data in assessing soil surface organic matter (Case study: a part of rangelands of Mehr watershed Sabzevar, Iran). Journal of Rangeland, No. 1, pp.67-78. (In Persian)
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Craswell, E.T., Lefroy, R.D.B., 2001. The role and function of organic matter in tropical soils. Nutrient Cycling in Agro ecosystems, 61(1/2): 7-18.
Post, W.M., Izaurralde, R.C., Mann L.K., Bliss, N., 2001. Monitoring and verifying changes of organic carbon in soil. Climate Change, 51: 73-99.
Mallah Nokandeh, S., Homaee, M., Noroozi, A., 2014. Investigation on feasibility of estimating soil organic matter using Hyperion hyperspectral imagery in Ivanekey and Urmia. Watershed Engineering and Management, Vol. 6, Issue 3. (In Persian)
Danesh, M., Bahrami, H.A., Noroozi, A.A., 2011. A synchronous investigation of soil geometric mean particle diameter and lime, using remote sensing technology (case study: Pol-e-Dokhtar, the southwest of Lorestan province, Iran). J. Agr. Sci. Tech, 12, 479-494.
Stephens, S.C., Rasmussen, V.P., Ramsey, R.D., Whitesides, R.E., Searle, G.S., Newhall, R.L., 2005. Remote sensing organic carbon in soil. USU/NASA SGEP Projects; available online (15-09-05), www.extnasa.usu.edu/link_pages/downloads/remote_sensing_carbon.pdf.
Ben-Dor, E., Patkin, K., Banin, A., Karnieli, A., 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel. Int. J. Remote Sens., 23(6): 1043-1062.
Dematte, M.J.A., Epiphanio, N.J.C., Formaggio, A.R., 2003. Influence of organic matter and iron oxides on the spectral reflectance of tropical soils. Bragantia, 62(3): 451-464.
Shirazi, M., Zehtabian, Gh., Alavipanah, S.K., 2010. Applicability of IRS Satellite Images for Surveying Water, Soil and Vegetation Cover Condition of Najm Abad Region, Savojbolagh. Journal of Natural Environmental, Iranian Journal of Natural Resources, Vol. 63, No. 1, pp.33-51. (In Persian)
Mohamadi, J., 2006. Pedometer. Vol. 2 (Spatial statistics). Pelk Publications, p. 453. (In Persian)
Hanquet, B., Sirjacobs, D., Destain, M.F., Frankinet, M., Verbrugge, J.C., 2004. Analysis of soil variability measured with a soil strength sensor. Precision Agriculture, 5(3): 227-246.
Ladoni, M., 2009. Estimating soil organic carbon from soil reflectance: a review. Springer Science+Business Media.
Henderson, T.L., Baumgardner, M.F., Franzmeier, D.P., Stott, D.E., Coster, D.C., 1992. High dimensional reflectance analysis of soil organic matter. Soil Science Society of America Journal, 56: 865–872.
Soan, Y.B., Gardner, W.D., Mishonov, A.V., Richardson, M.J., 2013. Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico. J. Earth Syst. Sci, 118, 1-10.
Hummel, J.W., Sudduth, K.A., Hollinger, S.E., 2001. Soil moisture and organic matter prediction of surface and subsurface soils using an NIR soil sensor. Comput. Electron. Agr., 32(2): 149-165.
Walkley, A., Black, I.A., 1934. An examination of the Degtjareff method for determining organiccarbon in soils: effect of variations in digestion conditions and of inorganic soil constituents. SoilScience, 63: 251-263.
Matinfar, H.R., Alavi Panah, S.K., Rafiei Emam, A., 2010. Remotely sensed data evaluation on soil spectral properties in arid regions. Iranian journal of Range and Desert Reseach, Vol. 16 No. (4). (In Persian)
Angstrum, 1925. Reflectance properties of soils. In: adv. In agronomy, 38: 1-44.
Ben-Dor, E., Banin, A., 1995. Near-infrared analysisas a rapid method to simultaneously evaluateseveral soil properties. Soil Science Society of America Journal, 59, pp.364-372.
Sheklabadi, M., Khademi, H., Karimian Eghbal, M., Nourbakhsh, F., 2007. Effect of climate and long term grazing exclusion on selected soil biological quality indicators in rangelandas of centeral Zagros. Agricultural Sciences and Natural Resources, 41: 103-115. (In Persian)
Bagherifam, S., Karimi, A.R., Lakzian, A., Izanloo, E., 2013. Effects of land use management on soil organic carbon, particle size distribution and aggregate stability along hillslope in semi-arid areas of northern Khorasan. Journal of Water and Soil Conservation, Vol. 20(4).(In Persian)
Shataee, Sh., Hossein Ali zadeh, M., Ayoubi, Sh., 2007. Study on the potential of ETM+ spectral data in assessing soil surface organic matter (Case study: a part of rangelands of Mehr watershed Sabzevar, Iran). Journal of Rangeland, No. 1, pp.67-78. (In Persian)
