Application of Remote Sensing Technique in Soil Carbon Storage Researches
Received date: 2004-10-01
Revised date: 2005-03-01
Online published: 2005-05-25
As the main parts of terrestrial carbon pool, soil carbon pools play an important role in global carbon balance. They are essential to understand the soil carbon cycling for the prediction of future atmospheric CO2 concentration and understanding the structure and function of soil ecosystem. Applications of remote sensing in the study of terrestrial carbon cycle open up an effective way for simulating terrestrial ecosystem process. Remote sensing of soil carbon storage is critical to understand climate change and terrestrial carbon cycle. Beginning with the Landsat-MSS data in early 1970s, spaceborne multispectral measurements from a variety of sensors have been extensively used for carrying out soil surveys. In the paper, combining many latest studies, we summarized the applications of remote sensing in soil carbon storage. First, the feasibility of using remotely sensed data to study soil carbon storage is discussed. The applications of remote sensing in estimating soil carbon storage, including remotely sensed aerial photograph, vegetation index and soil reflectance spectrum are reviewed next. Finally, the development tendency in soil carbon storage researches using remote sensing technology is specified concisely. With the link of carbon cycle model, remote sensing technique and GIS, simulating carbon cycle process in large scale will be the main research trend.
Key words： remote sensing; soil carbon storage; soil organic matter; vegetation index
ZHANG Wenjuan, WANG Shaoqiang, CHANG Hua, YU Guirui . Application of Remote Sensing Technique in Soil Carbon Storage Researches[J]. PROGRESS IN GEOGRAPHY, 2005 , 24(3) : 118 -126 . DOI: 10.11820/dlkxjz.2005.03.014
[1] 胡著智, 王慧麟, 陈钦峦. 遥感技术与地学应用: 绪论. 南京: 南京大学出版社, 1999, 1~5.
[2] Dwivedi, R S. Soil Resources Mapping: A Remote Sensing Perspective. Remote Sensing Reviews, 2001, 20: 89~122.
[3] 浦瑞良, 宫 鹏. 高光谱遥感及其应用:高光谱遥感数据在其它方面的应用研究. 北京: 高等教育出版社, 2000, 99~122.
[4] Kristof S J, Baumgardner M F, Weismiller A, Davis S. Applications of multispectral reflectance studies of soils: Pre-Landsat, Proceedings of the International Symposium on Machine Processing of Remotely Sensed Data. West Lafayette, Indiana, USA-61, 1978, p.52.
[5] Wight G G, Birnie R V. Detection of surface soil variation using high resolution satellite data: Results from the UK Spot simulation investigation. International Journal of Remote Sensing, 1986, 7: 757~ 766.
[6] Johnson W M. Soil classification and the design of soil surveys. In: Swindale L D (Ed). Soil Resources Data for Agricultural Development. Hawaii Agricultural Experiment Station. College of Tropical Agriculture. University of Hawaii. 1978.
[7] Chen F, Kissel D E, West L T, Adkins W. Field-Scale Mapping of Surface Soil Organic Carbon Using Remotely Sensed Imagery. Soil Sci. Soc. Am. J, 2000, 64: 746~ 753.
[8] Frazier B E, Cheng Y. Remote Sensing of soils in the Eastern Palouse region with Landsat Thematic Mapper. Remote Sensing of Environment, 1989, 28: 317~ 325.
[9] Frazier B E, Jarvis C R. A Landsat-TM ratio transformation to show soil variation. Agronomy Abstracts, American Society of Agronomy. Madison, Wisconsin, USA, 1990, p. 291.
[10] Baumgardner M F, Silva L F, Beihl L L, Stoner E R. Reflectance properties of soils. Advances in Agronomy, 1985, 38: 1~ 44.
[11] Wang shaoqiang, Xu jun, Zhou chenghu. Using remote sensing to estimate the change of carbon storage: a case study in the estuary of Yellow River delta. International journal of remote sensing. 2002, Vol.23, No.8,1565~ 1580.
[12] Michael Gluck, Gebhard Banko, Wolfgang Vrzal. Harnessing Remote Sensing to Accomplish Full Carbon Accounting: Workshop Report. International Institute for Applied Systems Analysis, 2002, 9~10.
[13] Merry C J, Levine E R. Methods to assess soil carbon using remote sensing techniques. In: Lal R, Kimble J, Levine E, Stewart B A (eds.), Assessment methods for soil carbon. CRC Press, Boca Raton, FL, 1995, 265~274.
[14] Smith J A, Ranson K J, Williams D L, Levine E R, Goltz M S, Katz R. A sensor fusion field optical experiment in forest ecosystem dynamics. SPIE Int. Symposium of Optical and Engineering Photonics in Aerospace Engineering. Orlando, FL. 1990, Vol. 1300.
[15] Levine E R, Ranson K J, Smith J, Williams D, Knox R G, Shugart H, Urban D, Lawrence W. Forest ecosystem dynamics: linking forest succession, soil process, and radiation models. Ecological Modeling, 1993, 65: 199~ 219.
[16] Levine E R, Knox R G, Lawrence W T. Relationships between soil properties and vegetation at the Northern Experimental forest, Howland, Maine. Remote Sensing of Environment. 1994.
[17] Levine E R, Kimes D. Predicting soil carbon in Mollisols using networks. In: Soil Processes and the Greenhouse Effect (Ed. By, Lal R, Kimble J M, Follet R F, Stewart B A), CRC Press, Boca Raton, FL, USA, 1998, 473~484.
[18] Ott, L. An Introduction to Statistical Methods and Data Analysis. PWS-Kent Publishing Co., Boston, MA. 1988.
[19] Conover, W B. Practical Nonparametric Statistics. 2nd Ed., John Wiley & Sons, NY. 1980.
[20] Mattikalli N M, Engman E T, Ahuja L R, Jackson T J. Microwave remote sensing of soil moisture for estimation of profile soil property. INT. J. Remote Sensing, 1998, 19(9):1751~1767.
[21] Nelson D W, Sommers L E. Total carbon, organic carbon and organic matter. In: Sparks D L, Page A L, Helmike P A, Loeppert R H, Softanpour P N, Tabatabai M A, Johnston C T, Summer M E (Eds.). Methods of Soil Analysis. Part3. SSSA and ASA, Madison, WI, 1996, 983~ 997.
[22] Reeves III J, McCarty G, Mimmo T. The potential of diffuse reflectance spectroscopy for the determination of carbon inventories in soils. Environmental Pollution, 2002, 116(3): 277~ 284.
[23] 安德罗尼科夫 B·Λ著, 王深法译. 土壤研究的遥感方法:土壤的红外和微波遥感研究法. 成都: 成都科技大学出版社, 1998, 173~181.
[24] 徐彬彬. 土壤剖面的反射光谱研究. 土壤,2000, 第6期, 281~287.
[25] Stone E R, Baungardner M F. Characteristic variations in reflectance of surface soils. Soil Sci. Soc. Am. J., 1981, 45: 1161~1165.
[26] Swain P H, Davis S M. Remote Sensing: The Quantitative Approach, McGraw-Hill, New York, 1978, p396.
[27] Latz K, Weismiller R A, Van Scoyoc G E, Baumgardner M F. Characteristics from Thematic Mapper data of a cropped organic-inorganic landscape. Soil Science Society of America Journal, 1984, 52: 1100~1134.
[28] Baumgardner N F, Kristof S J, Johannsen C J, Zachary A L. Effects of organic matter on the multispectral properties of soils. Proceedings Indiana Academy of Science, 1970, 79: 413~422.
[29] Coleman T L, Agbu P A, Montgomery O L, Gao T, Prasad S. Spectral band selection for quantifying selected properties in highly weathered soils. Soil Science, 1991, 151(5): 355~361.
[30] Ludwig B, Khanna P K. Use of Near Infrared Spectroscopy to determine inorganic and organic carbon fractions in soil and litter. In: Lal R, Kimble J, Levine E, Stewart B A (eds.), Assessment methods for soil carbon. CRC Press, Boca Raton, FL, 2001, 361~370.
[31] McCarty G W, Reeves III J B. Development of rapid instrumental methods for measuring soil organic carbon. In: Lal R, Kimble J, Levine E, Stewart B A (eds.), Assessment methods for soil carbon. CRC Press, Boca Raton, FL, 2001, 371~380.
[32] Martin P D, Malley D F, Manning G, Fuller L. Determination of soil organic carbon and nitrogen at the field level using near-infrared spectroscopy. Can. J. Soil Sci., 2002, 82: 413~422.
[33] Sudduth K A, Hummel J W. Soil organic matter, CEC and moisture sensing with a portable NIR spectrophotometer. Trans. ASAE. 1993, 36:185~193.
[34] Workman Jr, J J. NIR spectroscopy calibration basics. In: Burns D A, Ciurczak E W (Eds.), Handbook of Near-Infrared Analysis. Marcel Dekker, New York, 1992, 247~280.
[35] 陈庆强, 沈承德, 易惟熙, 彭少麟, 李志安. 土壤碳循环研究进展. 地球科学进展, 1998, 13(6): 555~563.
[36] 尹殿奎, 冯君, 杨志超. 长春市主要土壤类型光谱特性的研究. 吉林农业大学学报, 1998, 20(3): 57~59.
[37] 吴昀昭, 田庆久, 季峻峰, 陈骏, 惠凤鸣. 土壤光学遥感的理论、方法及应用. 遥感信息, 2003, 1: 40~47.
[38] 耿元波, 董云社, 孟维奇. 陆地碳循环研究进展. 地理科学进展, 2000, 19(4)： 297~306
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