Representation the Properties of the Central-Forest Reserve Southern Taiga Forest Soils in Remote Hyperspectral Measurements

M. Yu. Puzachenko; Пузаченко М. Ю.; A. S. Baibar; Байбар А. С.; Y. G. Puzachenko; Пузаченко Ю. Г.

doi:10.31857/S1026347023600887

Отображение свойств лесных почв южной Тайги Центрально-Лесного заповедника в дистанционных гиперспектральных измерениях

Авторы: Пузаченко М.Ю.¹, Байбар А.С.¹^,2, Пузаченко Ю.Г.¹
Учреждения:
1. Институт географии РАН
2. Институт проблем экологии и эволюции им. А.Н. Северцова РАН
Выпуск: № 8 (2023)
Страницы: 129-142
Раздел: ЛАНДШАФТНАЯ ЭКОЛОГИЯ
URL: https://journals.rcsi.science/1026-3470/article/view/231762
DOI: https://doi.org/10.31857/S1026347023600887
EDN: https://elibrary.ru/GULCEF
ID: 231762

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Аннотация

Исследовано отображение гранулометрического состава и цвета почвы по шкале Манселла, измеренных до глубины 135 см c интервалом 5 см на трансекте (длина 6 км) с шагом 20 м, в гиперспектральных данных прибора Гиперион (Hyperion) для 9 сроков измерений с января по сентябрь. Получено, что съемка за 24 мая наиболее связана со всеми рассматриваемыми характеристиками. Для гранулометрического состава наибольшие связи отмечаются для глубин 7–15, 45, 75 и 120 см; для оттенка цвета – 3–10 и 95–135 см; для яркости цвета – 7–15, 25–30 и 65–70 см; для насыщенности цвета – 7–10, 40–50, 75 и 100 см. Гранулометрический состав почвы наиболее связан с длинами волн 579–702 и 529 нм, оттенок цвета – 641–691 нм, яркость цвета – 569–702 и 518–539 нм, насыщенность цвета – 569–702, 508–529 и 732–763 нм.

Ключевые слова

гиперспектральное дистанционное зондирование, гранулометрический состав почв, цвет почв по шкале Манселла, дисперсионный анализ

Список литературы

Пузаченко М.Ю., Пузаченко Ю.Г., Козлов Д.Н., Федяева М.В. Картографирование мощности органогенного и гумусового горизонтов лесных почв и болот южнотаежного ландшафта (юго-запад Валдайской возвышенности) на основе трехмерной модели рельефа и дистанционной информации (Landsat 7) // Исследование Земли из космоса, 2006. № 4. С. 70–79.
Asner G.P. Biophysical and biochemical sources of variability in canopy reflectance // Remote Sensing of Environment, 1998. V. 64. P. 234–253.
Asner G.P., Martin R.E., Ford A.J., Metcalfe D.J., Liddell M.J. Leaf chemical and spectral diversity in Australian tropical forests // Ecological App. 2009. V. 19(1). P. 236–253.
Asner G.P., Martin R.E., Knapp D.E., Tupayachi R., Anderson C., Carranza L., Martinez P., Houcheime M., Sinca, F.P. Weiss spectroscopy of canopy chemicals in humid tropical forests // Remote Sensing of Environment, 2011. V. 115. P. 3587–3598.
Blackburn G.A., Steele C.M. Towards the remote sensing of Matorral vegetation physiology: relationships between spectral reflectance, pigment, and biophysical characteristics of semiarid bushland canopies // Remote Sensing of Environment, 1999. V. 70. P. 278–292.
Brauns F.E., Brauns D.A. The chemistry of lignin. N.Y.: Academic Press., 1960. 703 p.
Carter G.A., Knapp A.K. Leaf optical properties in higher plants. Linking spectral characteristics to stress and chlorophyll concentration // Am. J. Botany, 2001. V. 88(4). P. 677–684.
Das B.S., Sarathjith M.C., Santra P., Sahoo R.N., Srivastava R., Routray A., Ray S.S. Hyperspectral remote sensing: opportunities, status and challenges for rapid soil assessment in India // Special section: hyperspectral remote sensing current science, 2015. V. 108(5). P. 860–868.
Daughtry, C., Hunt E., McMurtrey J. Crop Residue Cover Using Shortwave Infrared Reflectance // Remote Sensing of Environment, 2004. V. 90. P. 126–134.
DeTar W.R., Chesson J.H., Penner J.V., Ojala J.C. Detection of soil properties with airborne hyperspectral measurements of bare fields // Am. Soc. of Agricultural and Biological Engineers, 2008. V. 51(2). P. 463–470.
Field Book for Describing and Sampling Soils. Version 3.0. National Soil Survey Center. Natural Resources Conservation Service. U.S. Department of Agriculture, 2012. 298 p.
Field manual for describing terrestrial ecosystems. -2nd ed. Co-Published by Research Branch B.C. Ministry of Forests and Range, B.C. Ministry of Environment Province of British Columbia, 2010. 266 p.
Fourty T., Baret F., Jacquemoud S., Schmuck G., Verdebout J. Leaf optical properties and biochemical composition // Remote Sensing of Environment, 1996. V. 56. P. 104–117.
Gomez C., Gholizadeh A., Borùvka L., Lagacherie P. Using legacy soil data for standardizing predictions of topsoil clay content obtained from vnir/swir hyperspectral airborne images. The International Archives of the Photogrammetry // Remote Sensing and Spatial Information Sci. ISPRS Geospatial Week 2015. V. XL-3/W3. P. 439–444.
Gmur S., Vogt D., Zabowski D., Moskal L.M. Hyperspectral Analysis of Soil Nitrogen, Carbon, Carbonate, and Organic Matter Using Regression Trees // Sensors. 2012. V. 12. P. 10639–10658.
Hively W.D., McCarty G.W., James B. Reeves III J.B., Lang M.W., Oesterling R.A., Delwiche S.R. Use of Airborne Hyperspectral Imagery to Map Soil Properties in Tilled Agricultural Fields // Applied and Environmental Soil Science, Hindawi Publishing Corporation. 2011. V. 2011. 13 p.
Kiang N.Y., Govindjee J.S., Blankenship R.E. Spectral signatures of photosynthesis // Rev. of earth organisms. Astrobiology, 2007. V. 7(1). P. 223–251.
Konen M.E., Burras C.L., Sandor J.A. Organic Carbon, Texture, and Quantitative Color Measurement Relationships for Cultivated Soils in North Central Iowa Published // Soil Sci. Soc. Am. J. 2003. V. 67. P. 1823–1830.
McKenzie N.J., Grundy M.J., Webster R., Ringrose-Voase A.J. Guidelines for surveying soil and land resources – 2nd ed. Australian Soil and Land Survey Handbook Series. Melbourne: CSIRO Publishing, 2008. 557 p.
Moritsuka N., Matsuoka K., Katsura K., Sano S., Yanai J. Soil color analysis for statistically estimating total carbon, total nitrogen and active iron contents in Japanese agricultural soils Soil Science and Plant Nutrition // Japanese Society of Soil Science and Plant Nutrition, 2014. V. 60. P. 475–485.
Munsell Soil Color Charts, Revised Edition. N.Y.: Gretagmacbeth Division of Kollmorgen Instruments Corp. 1994.
Neill S., Gould K.S. Optical properties of leaves in relation to anthocyanin concentration and distribution // Canadian J. Botany, 1999. V. 77. P. 1777–1782.
Jay S. Pearlman Hyperion Validation Report. Boeing Report Number 03-ANCOS-001. Phantom Works. The Boeing Company Kent, WA 98032 NASA/GSFC, 2003.
Soil Taxonomy. A Basic System of Soil Classification for Making and Interpreting Soil Surveys Second Edition, United States Department of Agriculture Agriculture Handbook Natural Resources Conservation Service, 1999. № 436. 886 p.
Shum M., Lavkulich L.M. Use of sample color to estimate oxidized Fe content in mine waste rock // Environmental Geology, 1999. V. 37(4). P. 281–289.
Summers D. Discriminating and mapping soil variability with hyperspectral reflectance data. Thesis presented for the degree of PhD, Faculty of Science, School of Earth and Environmental Science, The University of Adelaide, 2009. 122 p.
Thien S.J. A flow diagram for teaching texture by feel analysis // J. of Agronomic Education, 1979. V. 8. P. 54–55.
Viscarra Rossel R.A., Minasny B., Roudier P., McBratney A.B. Colour space models for soil science // Geoderma, 2006. V. 133. P. 320–337.
Viscarra Rossela R.A., Fouada Y., Walter C. Using a digital camera to measure soil organic carbon and iron contents // Biosystems engineering, 2008. V. 100. P. 149–159.
Wills S.A., Burras C.L., Sandor J.A. Prediction of soil organic carbon content using field and laboratory measurements of soil colour // Soil Sci. Soc. of Am. J. 2007. V. 71(2). P. 380–388.
Wójtowicz M., Wójtowicz A., Piekarczyk J. Application of remote sensing methods in agriculture // Communications in Biometry and Crop Sci. 2016. V. 11. P. 31–50.
Luo Z., Yaolin L., Jian W., Jing W. Quantitative mapping of soil organic material using field spectrometer and hyperspectral remote sensing // The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008. V. XXXVII. Part B8. P. 901–906.