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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">scbook</journal-id><journal-title-group><journal-title xml:lang="ru">Биология растений и садоводство: теория, инновации</journal-title><trans-title-group xml:lang="en"><trans-title>Plant Biology and Horticulture: theory, innovation</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2712-7788</issn><publisher><publisher-name>Federal State Funded Institution of Science “The Labour Red Banner Order Nikitsky Botanical Gardens – National scientific Center of the RAS”</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.36305/2019-3-152-56-70</article-id><article-id custom-type="elpub" pub-id-type="custom">scbook-482</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭФИРОМАСЛИЧНЫЕ И ЛЕКАРСТВЕННЫЕ РАСТЕНИЯ</subject></subj-group></article-categories><title-group><article-title>Спектральные характеристики некоторых сельскохозяйственных культур в различные фенологические фазы вегетации</article-title><trans-title-group xml:lang="en"><trans-title>Spectral characteristics of some agricultural crops in different phenological phases of vegetation</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Табунщик</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Tabunschik</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Владимир Александрович Табунщик</p><p>299011, г. Севастополь </p><p> </p></bio><email xlink:type="simple">tabunshchyk@ya.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чекмарёва</surname><given-names>Т. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Chekmareva</surname><given-names>Т. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Татьяна Михайловна Чекмарёва</p><p>299011, г. Севастополь </p><p> </p></bio><email xlink:type="simple">aspirant@imbr-ras.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Горбунов</surname><given-names>Р. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Gorbunov</surname><given-names>R. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Роман Вячеславович Горбунов</p><p>299011, г. Севастополь </p></bio><email xlink:type="simple">karadag_station@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>ФГБУН ФИЦ «Институт биологии южных морей имени А.О. Ковалевского РАН»</institution><country>Russian Federation</country></aff><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>18</day><month>02</month><year>2020</year></pub-date><volume>0</volume><issue>152</issue><fpage>56</fpage><lpage>70</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Табунщик В.А., Чекмарёва Т.М., Горбунов Р.В., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Табунщик В.А., Чекмарёва Т.М., Горбунов Р.В.</copyright-holder><copyright-holder xml:lang="en">Tabunschik V.A., Chekmareva Т.M., Gorbunov R.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://scbook.elpub.ru/jour/article/view/482">https://scbook.elpub.ru/jour/article/view/482</self-uri><abstract><p>Для дешифрирования сельскохозяйственных культур в различные временные периоды необходимо обладать информацией о спектральной отражательной способности растений во время прохождения ими фенологических фаз вегетации. В работе предпринята попытка произвести оценку спектральной отражательной способности основных плодовых сельскохозяйственных культур и винограда в разные фенологические фазы вегетации с использованием космических снимков Sentinel-2 и программного комплекса ENVI. С помощью полевых методов исследования были подобраны участки, на которых произрастают персик, виноград, черешня, яблоня, слива, абрикос. Установлено, что посадка сельскохозяйственных культур выполнялась путем смешения сортов, с целью снижения риска получения дополнительных издержек в результате возможных неблагоприятных природных процессов и явлений. Для каждого участка получены и проанализированы максимальные, минимальные и средние значения коэффициента спектральной яркости в пределах 13 каналов космических снимков Sentinel-2. Космические снимки были выбраны за 07.04.2019, 27.04.2019 и 12.05.2019 года, как наиболее подходящие к периодам начала цветения (07.04.2019), окончания цветения (27.04.2019) и начала созревания плодов(12.05.2019), с минимальными значениями перекрытия облаками. Для устранения внешнего воздействия почвы в пределах каждого пикселя изображения был использован модуль линейного спектрального разделения программного комплекса ENVI, подобран эталонный фрагмент почвы и получены его спектральные характеристики, что позволило изобразить графики спектральных кривых рассматриваемых сельскохозяйственных культур в пределах каждого участка. Получить разграничение коэффициента спектральной яркости удалось не для всех участков, что связано с наличием дополнительных внешних элементов.</p></abstract><trans-abstract xml:lang="en"><p>For deciphering crops from satellite images at different time periods, it is necessary to have information about the spectral reflectivity of plants during their passage through the phenological phases of vegetation. An attempt was made to evaluate the spectral reflectivity of the main fruit crops and grapes in different phenological phases of the growing season using Sentinel-2 satellite images and the ENVI software package. Field research methods, plots were selected on which peach, grapes, cherries, apple trees, plums, and apricots grow are used. It was established that planting crops was carried out by mixing cultivars in order to reduce the risk of additional costs as a result of possible adverse natural processes and phenomena. For each section, the maximum, minimum, and average values of the spectral brightness coefficient were obtained and analyzed within 13 bands of Sentinel-2 satellite images. Space images were selected for 04/07/2019, 04/27/2019 and 05/12/2019, as the most suitable for the periods of the beginning of flowering (04/07/2019), the end of flowering (04/27/2019) and the beginning of fruit ripening (12/05/2019), with minimal cloud overlap values. To eliminate the external influence of the soil within each pixel of the image, the linear spectral separation module of the ENVI software package was used, a reference soil fragment was selected and its spectral characteristics were obtained, which made it possible to depict graphs of the spectral curves of the crops under study within each section. It was not possible to obtain a distinction of the spectral brightness coefficient for all sections, which is associated with the presence of additional external elements.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>спектр</kwd><kwd>фенологическая фаза</kwd><kwd>вегетация</kwd><kwd>снимок</kwd><kwd>Крым</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Sentinel-2</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Бондур В.Г. Современные подходы к обработке больших потоков гиперспектральной и многоспектральной аэрокосмической информации // Исследование Земли из космоса. 2014. № 1. С. 4-17.</mixed-citation><mixed-citation xml:lang="en">Bondur V.G. Modern approaches to processing large flows of hyperspectral and multispectral aerospace information. Issledovaniye Zemli iz kosmosa. 2014. 1: 4-17.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Борзов C.M., Потатуркин О.И. Обнаружение выборочных рубок леса по данным дистанционных измерений высокого пространственного разрешения // Исследование Земли из космоса. 2014. № 4. С. 87.</mixed-citation><mixed-citation xml:lang="en">Borzov S.M., Potaturkin O.I. Detection of selective felling based on remote sensing data of high spatial resolution. Issledovaniye Zemli iz kosmosa. 2014. 4: 87</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Гусейнов Г. А., Смоктий О.И. Информационные свойства спектральных коэффициентов яркости и вегетационных индексов для калибровки аэрокосмических снимков // Труды СПИИРАН. 2005. Т. 2. № 2. С. 360-367.</mixed-citation><mixed-citation xml:lang="en">Huseynov G.A., Smokty O.I. Information properties of spectral brightness coefficients and vegetation indices for calibration of aerospace images // Trudy SPIIRAN. 2005. 2(2): 360-367</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Жирин B.M., Эйдлина С.П., Князева С.В. Опыт лесоводственного анализа последствий пожаров по космическим изображениям // Современные проблемы дистанционного зондирования Земли из космоса. 2013. Т. 10. № 3. С. 243-259.</mixed-citation><mixed-citation xml:lang="en">Zhirin V.M., Eidlina S.P., Knyazeva S. V. The experience of forestry analysis of the consequences of fires from space images // Sovremennyye problem distantsionnogo zondirovaniya Zemli iz kosmosa. 2013. 10 (3): 243-259.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Исследование отражательной способности. M.: Гос. науч.-техн, горно-геол.нефт. изд-во, 1934. 84с.</mixed-citation><mixed-citation xml:lang="en">The study of reflectivity. Moscow: State scientific and technical mining geological oil Publishing House, 1934. 84 p.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Козодеров B.B., Кондранин T.B., Казанцев О.Ю., Бобылев В.И., Щербаков М.В., Борзяк В.В., Дмитриев Е.В., Егоров В.Д., Каменцев В.П., Беляков А.Ю., Логинов С.Б. Обработка и интерпретация данных гиперспектральных аэрокосмических измерений для дистанционной диагностики природно-техногенных объектов // Исследование Земли из космоса. 2009. № 2. С. 36-54.</mixed-citation><mixed-citation xml:lang="en">Kozoderov V.V., Kondranin T.V., Kazantsev О. Yu., Bobylev VI., Scherbakov M.V., Borzyak V.V., Dmitriev E.V., Egorov V.D., Kamentsev V.P., BelyakovA.Yu., Loginov S.B. Processing and interpretation of hyperspectral aerospace measurements for remote diagnostics of natural and technogenic objects. Issledovaniye Zemli iz kosmosa. 2009. 2: 36-54</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Козодеров В.В., Кондранин Т.В., Косолапов В.С., Головко В.А., Дмитриев Е.В. Восстановление объема фитомассы и других параметров состояния почвенно¬ растительного покрова по результатам обработки многоспектральных спутниковых изображений //Исследование Земли из космоса. 2007. № 1. С. 57-65.</mixed-citation><mixed-citation xml:lang="en">Kozoderov V.V., Kondranin T.V., Kosolapov V.S., Golovko V.A., Dmitriev E.V. Recovering the volume of phytomass and other parameters of the state of the land cover based on the processing of multispectral satellite images. Issledovaniye Zemli iz kosmosa. 2007. 1: 57-65</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Колесникова O.H., Черепанов А. С. Возможности ПК ENVI для обработки мультиспектральных и гиперспектральных данных // Геоматика. 2009. № 3. С. 24-27.</mixed-citation><mixed-citation xml:lang="en">Kolesnikova O.N., Cherepanov A.S. Possibilities ENVI for processing multispectral and hyperspectral data// Geomatika. 2009. 3: 24-27.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Кондратьев К.Я., Феченко П.П. Спектральная отражательная способность и распознавание растительности. Л.: Гидрометеоиздат, 1982. 216с.</mixed-citation><mixed-citation xml:lang="en">Kondratiev K.Ya., Fechenko P.P. Spectral reflectance and vegetation recognition. Leningrad: Gidrometeoizdat, 1982. 216 p.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Кринов Е.Л. Спектральная отражательная способность природных образований. М.: Изд. АНСССР, 1947. 272с.</mixed-citation><mixed-citation xml:lang="en">Krinov E.L. Spectral reflectance of natural formations. Moscow: Publishing USSR Academy of Sciences, 1947. 272 p.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Рачкулик B.H., Ситникова M.B. Отражательные свойства и состояние растительных покровов. Л: Гидрометеоиздат, 1981. 267с.</mixed-citation><mixed-citation xml:lang="en">Rachkulik V.N., Sitnikova M.V. Reflective properties and condition of vegetat/cw. Leningrad: Gidrometeoizdat, 1981. 267 p.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Чапурский Л.И. Отражательные свойства природных объектов в диапазоне 4002500 нм. Часть 1. Л.: МОСССР, 1986. 160с. [Chapursky L.I. Reflective properties of natural objects in the range of 400-2500 nm. Part 1. Leningrad: Ministry of Defense of the USSR, 1986. 160 p.]</mixed-citation><mixed-citation xml:lang="en">Chapursky L.I. Reflective properties of natural objects in the range of 400-2500 nm. Part 1. Leningrad: Ministry of Defense of the USSR, 1986. 160 p.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Шульц Г.Э. Общая фенология. Л.: Наука, 1981. 188с.</mixed-citation><mixed-citation xml:lang="en">Schulz G.E. General phenology. Leningrad: Nauka, 1981.188 p.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Adamowski K. Spectral density of a river flow time series // Journal of Hydrology. 1971. Vol. 14(1). pp. 43-52. doi: 10.1016/0022-1694(71)90091-6</mixed-citation><mixed-citation xml:lang="en">Adamowski K. Spectral density of a river flow time series // Journal of Hydrology. 1971. Vol. 14(1). pp. 43-52. doi: 10.1016/0022-1694(71)90091-6</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Ashish D., McClendon R.W., Hoogenboom G. Land use classification of multispectral aerial images using artificial neural networks // International Journal of Remote Sensing. 2009. Vol. 30(8). pp. 1989-2004. doi: 10.1080/01431160802549187</mixed-citation><mixed-citation xml:lang="en">Ashish D., McClendon R.W., Hoogenboom G. Land use classification of multispectral aerial images using artificial neural networks // International Journal of Remote Sensing. 2009. Vol. 30(8). pp. 1989-2004. doi: 10.1080/01431160802549187</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Asner G.P., Heidebrecht K.B. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations // International Journal of Remote Sensing. 2002. Vol. 23(19). pp. 3939-3958. doi:10.1080/01431160110115960</mixed-citation><mixed-citation xml:lang="en">Asner G.P., Heidebrecht K.B. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations // International Journal of Remote Sensing. 2002. Vol. 23(19). pp. 3939-3958. doi:10.1080/01431160110115960</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Call K.A., Hardy J. T., Wallin D. O. Coral reef habitat discrimination using multivariate spectral analysis and satellite remote sensing // International Journal of Remote Sensing. 2003. Vol. 24(13). pp. 2627-2639. doi: 10.1080/0143116031000066990</mixed-citation><mixed-citation xml:lang="en">Call K.A., Hardy J. T., Wallin D. O. Coral reef habitat discrimination using multivariate spectral analysis and satellite remote sensing // International Journal of Remote Sensing. 2003. Vol. 24(13). pp. 2627-2639. doi: 10.1080/0143116031000066990</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Hirano A., Madden M., Welch R. Hyperspectral image data for mapping wetland vegetation/ / Wetlands. 2003. Vol. 23 (2). pp. 436-448. doi: 10.1672/18-20</mixed-citation><mixed-citation xml:lang="en">Hirano A., Madden M., Welch R. Hyperspectral image data for mapping wetland vegetation/ / Wetlands. 2003. Vol. 23 (2). pp. 436-448. doi: 10.1672/18-20</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Jacquemoud S., Baret E , Hanocq J.F. Modeling spectral and bidirectional soil reflectance/ / Remote Sensing of Environment. 1992. Vol. 41 (2-3). pp. 123-132.</mixed-citation><mixed-citation xml:lang="en">Jacquemoud S., Baret E , Hanocq J.F. Modeling spectral and bidirectional soil reflectance/ / Remote Sensing of Environment. 1992. Vol. 41 (2-3). pp. 123-132.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Karami M., Rangzan K., Saberi A. Using GIS servers and interactive maps in spectral data sharing and administration: Case study of Ahvaz Spectral Geodatabase Platform (ASGP) // Computers &amp; Geosciences. 2013. Vol. 60. pp. 23-33. doi:10.1016/j.cageo.2013.06.007</mixed-citation><mixed-citation xml:lang="en">Karami M., Rangzan K., Saberi A. Using GIS servers and interactive maps in spectral data sharing and administration: Case study of Ahvaz Spectral Geodatabase Platform (ASGP) // Computers &amp; Geosciences. 2013. Vol. 60. pp. 23-33. doi:10.1016/j.cageo.2013.06.007</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Landsberg H.E., Kaylor R.E. Spectral analysis of long meteorological series // Journal of Interdisciplinary Cycle Research. 1976. vol. 7. no. 3. pp. 237-243.</mixed-citation><mixed-citation xml:lang="en">Landsberg H.E., Kaylor R.E. Spectral analysis of long meteorological series // Journal of Interdisciplinary Cycle Research. 1976. vol. 7. no. 3. pp. 237-243.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Lu D., Li G., Valladares G.S., Batistella M. Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RUSLE, remote sensing and GIS // Land Degradation &amp; Development. 2004. Vol. 15(5). pp. 499-512. doi:10.1002/ldr.634</mixed-citation><mixed-citation xml:lang="en">Lu D., Li G., Valladares G.S., Batistella M. Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RUSLE, remote sensing and GIS // Land Degradation &amp; Development. 2004. Vol. 15(5). pp. 499-512. doi:10.1002/ldr.634</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Luck-Vogel M., Mbolambi C., Rautenbach K., Adams J., van Niekerk L. Vegetation mapping in the St Lucia estuary using very high-resolution multispectral imagery and LiDAR // South African Journal of Botany. 2006. Vol. 107. pp. 188-199. doi:10.1016/j.sajb.2016.04.010</mixed-citation><mixed-citation xml:lang="en">Luck-Vogel M., Mbolambi C., Rautenbach K., Adams J., van Niekerk L. Vegetation mapping in the St Lucia estuary using very high-resolution multispectral imagery and LiDAR // South African Journal of Botany. 2006. Vol. 107. pp. 188-199. doi:10.1016/j.sajb.2016.04.010</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Lunetta RS., Ediriwickrema J., Hames J., Johnson D.M., Lyon J.G., Me Kerrow A., Pilant A. A Quantitative Assessment of a Combined Spectral and GIS Rule-Based LandCover Classification in the Neuse River Basin of North Carolina // Photogrammetric Engineering &amp; Remote Sensing. 2009. Vol. 69(3). pp. 299-310. doi:10.14358/pers.69.3.299</mixed-citation><mixed-citation xml:lang="en">Lunetta RS., Ediriwickrema J., Hames J., Johnson D.M., Lyon J.G., Me Kerrow A., Pilant A. A Quantitative Assessment of a Combined Spectral and GIS Rule-Based LandCover Classification in the Neuse River Basin of North Carolina // Photogrammetric Engineering &amp; Remote Sensing. 2009. Vol. 69(3). pp. 299-310. doi:10.14358/pers.69.3.299</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Mayaux P., Bartholome E., Fritz S., Belward, A. A new land-cover map of Africa for the year 2000 // Journal of Biogeography. 2004. Vol. 31(6). pp. 861-877. doi: 10.1111/j.13652699.2004.01073.x.</mixed-citation><mixed-citation xml:lang="en">Mayaux P., Bartholome E., Fritz S., Belward, A. A new land-cover map of Africa for the year 2000 // Journal of Biogeography. 2004. Vol. 31(6). pp. 861-877. doi: 10.1111/j.13652699.2004.01073.x.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Molleri G. S. F , Kampel, M., de Moraes Novo E. M. L. Spectral classification of water masses under the influence of the Amazon River plume // Acta Oceanologica Sinica. 2010. Vol. 29(3). pp. 1-8. doi:10.1007/sl3131-010-0031-l</mixed-citation><mixed-citation xml:lang="en">Molleri G. S. F , Kampel, M., de Moraes Novo E. M. L. Spectral classification of water masses under the influence of the Amazon River plume // Acta Oceanologica Sinica. 2010. Vol. 29(3). pp. 1-8. doi:10.1007/sl3131-010-0031-l</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Parrish D.F., Derber J.C. The National Meteorological Center's spectral statisticalinterpolation analysis system // Monthly Weather Review. 1992. vol. 120. no. 8. pp. 17471763.</mixed-citation><mixed-citation xml:lang="en">Parrish D.F., Derber J.C. The National Meteorological Center's spectral statisticalinterpolation analysis system // Monthly Weather Review. 1992. vol. 120. no. 8. pp. 17471763.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Rivero R. G., Grunwald S., BinfordM. W., Osborne, T. Z. Integrating spectral indices into prediction models of soil phosphorus in a subtropical wetland // Remote Sensing of Environment. 2009. Vol. 113(11). pp. 2389-2402. doi:10.1016/j.rse.2009.07.015</mixed-citation><mixed-citation xml:lang="en">Rivero R. G., Grunwald S., BinfordM. W., Osborne, T. Z. Integrating spectral indices into prediction models of soil phosphorus in a subtropical wetland // Remote Sensing of Environment. 2009. Vol. 113(11). pp. 2389-2402. doi:10.1016/j.rse.2009.07.015</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Roberts D.A., Ustin S.L., Ogunjemiyo S., Greenberg J., Dobrowski S.Z., Chen J., Hinckley T.M. Spectral and Structural Measures of Northwest Forest Vegetation at Leaf to Landscape Scales//Ecosystems. 2004. Vol. 7(5). doi:10.1007/sl0021-004-0144-5</mixed-citation><mixed-citation xml:lang="en">Roberts D.A., Ustin S.L., Ogunjemiyo S., Greenberg J., Dobrowski S.Z., Chen J., Hinckley T.M. Spectral and Structural Measures of Northwest Forest Vegetation at Leaf to Landscape Scales//Ecosystems. 2004. Vol. 7(5). doi:10.1007/sl0021-004-0144-5</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Salih A.A. M., Ganawa E.-T, Elmahl A.A. Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery // The Egyptian Journal of Remote Sensing and Space Science. 2017. Vol. 20, S21-S29. doi:10.1016/j.ejrs.2016.12.008</mixed-citation><mixed-citation xml:lang="en">Salih A.A. M., Ganawa E.-T, Elmahl A.A. Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery // The Egyptian Journal of Remote Sensing and Space Science. 2017. Vol. 20, S21-S29. doi:10.1016/j.ejrs.2016.12.008</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Sanyal J., Lu X.X. Remote sensing and GIS-based flood vulnerability assessment of human settlements: a case study of Gangetic West Bengal, India // Hydrological Processes. 2005. Vol. 19(18). pp. 3699-3716. doi:10.1002/hyp.5852</mixed-citation><mixed-citation xml:lang="en">Sanyal J., Lu X.X. Remote sensing and GIS-based flood vulnerability assessment of human settlements: a case study of Gangetic West Bengal, India // Hydrological Processes. 2005. Vol. 19(18). pp. 3699-3716. doi:10.1002/hyp.5852</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Small C. Estimation of urban vegetation abundance by spectral mixture analysis // International Journal of Remote Sensing. 2001. Vol. 22(7). pp. 1305-1334.</mixed-citation><mixed-citation xml:lang="en">Small C. Estimation of urban vegetation abundance by spectral mixture analysis // International Journal of Remote Sensing. 2001. Vol. 22(7). pp. 1305-1334.</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Smith M. J., Pain C.F. Applications of remote sensing in geomorphology // Progress in Physical Geography. 2009. Vol. 33(4). pp. 568-582. doi: 10.1177/0309133309346648</mixed-citation><mixed-citation xml:lang="en">Smith M. J., Pain C.F. Applications of remote sensing in geomorphology // Progress in Physical Geography. 2009. Vol. 33(4). pp. 568-582. doi: 10.1177/0309133309346648</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Tabunshchyk V.A., Petlukova E.A., Hytrin M.O. The use of Satellite Imagery Sentinel 2 for Analysis of Land Used in Agriculture (for Example Razdolnensky District of the Republic of Crimea) // Proceedings of the T.I. Vyazemsky Karadag scientific station Nature Reserve of the RAS. 2018. no 1. pp. 43-57.</mixed-citation><mixed-citation xml:lang="en">Tabunshchyk V.A., Petlukova E.A., Hytrin M.O. The use of Satellite Imagery Sentinel 2 for Analysis of Land Used in Agriculture (for Example Razdolnensky District of the Republic of Crimea) // Proceedings of the T.I. Vyazemsky Karadag scientific station Nature Reserve of the RAS. 2018. no 1. pp. 43-57.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Tansey K., Chambers I., Anstee A., Denniss A., Lamb A. Object-oriented classification of very high resolution airborne imagery for the extraction of hedgerows and field margin cover in agricultural areas // Applied Geography. 2009. Vol. 29(2). pp. 145-157. doi:10.1016/j.apgeog.2008.08.004</mixed-citation><mixed-citation xml:lang="en">Tansey K., Chambers I., Anstee A., Denniss A., Lamb A. Object-oriented classification of very high resolution airborne imagery for the extraction of hedgerows and field margin cover in agricultural areas // Applied Geography. 2009. Vol. 29(2). pp. 145-157. doi:10.1016/j.apgeog.2008.08.004</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Yuan F. Land cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling // International Journal of Remote Sensing. 2008. Vol. 29(4). pp. 1169-1184. doi: 10.1080/01431160701294703</mixed-citation><mixed-citation xml:lang="en">Yuan F. Land cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling // International Journal of Remote Sensing. 2008. Vol. 29(4). pp. 1169-1184. doi: 10.1080/01431160701294703</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">YuanM., Dickens-Micozzi M., MagsigM.A. Analysis of Tornado Damage Tracks from the 3 May Tornado Outbreak Using Multispectral Satellite Imagery // Weather and Forecasting. 2002. Vol. 17(3). pp. 382-398. doi :10.1175/15200434(2002)017&lt;0382:aotdtf&gt;2.0.co;2.</mixed-citation><mixed-citation xml:lang="en">YuanM., Dickens-Micozzi M., MagsigM.A. Analysis of Tornado Damage Tracks from the 3 May Tornado Outbreak Using Multispectral Satellite Imagery // Weather and Forecasting. 2002. Vol. 17(3). pp. 382-398. doi :10.1175/15200434(2002)017&lt;0382:aotdtf&gt;2.0.co;2.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
