<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<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">nature</journal-id><journal-title-group><journal-title xml:lang="ru">Природопользование</journal-title><trans-title-group xml:lang="en"><trans-title>Nature Management</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2079-3928</issn><publisher><publisher-name>Институт природопользования НАН Беларуси</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">nature-87</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>ГЕОГРАФИЯ. ГЕОЭКОЛОГИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>GEOGRAPHY. GEOECOLOGY</subject></subj-group></article-categories><title-group><article-title>Выявление структуры землепользования в зоне влияния Солигорского калийного комбината по данным дистанционного зондирования</article-title><trans-title-group xml:lang="en"><trans-title>Identification of land use structure in the zone of influence of the Soligorsk potash plant based on remote sensing data</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>Цзян</surname><given-names>Чэнь</given-names></name><name name-style="western" xml:lang="en"><surname>Jiang</surname><given-names>Chen</given-names></name></name-alternatives><bio xml:lang="ru"><p>Цзян Чэнь – аспирант факультета географии и геоинформатики</p><p>ул. Ленинградская, 16, 220030, г. Минск</p></bio><bio xml:lang="en"><p>Jiang Chen – Post Graduate Student</p><p>16, Leningradskaya Str., 220030, Minsk</p></bio><email xlink:type="simple">sweenei1j@gmail.com</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>Червань</surname><given-names>А. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Chervan</surname><given-names>A. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Червань Александр Николаевич – кандидат сельскохозяйственных наук, доцент, заведующий кафедрой почвоведения и геоинформационных систем факультета географии и геоинформатики</p><p>ул. Ленинградская, 16, 220030, г. Минск</p></bio><bio xml:lang="en"><p>Chervan Alexander Nikolaevich – Ph. D. (Agriculture), Associate Professor, Head of Department of Soil Science and Geoinformatic, Faculty of Geography and Geoinformatic</p><p>16, Leningradskaya Str., 220030, Minsk</p></bio><email xlink:type="simple">ChervanAlex@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Белорусский государственный университет</institution></aff><aff xml:lang="en"><institution>Belarusian State University</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>30</day><month>10</month><year>2025</year></pub-date><volume>0</volume><issue>1</issue><fpage>51</fpage><lpage>63</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Цзян Ч., Червань А.Н., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Цзян Ч., Червань А.Н.</copyright-holder><copyright-holder xml:lang="en">Jiang C., Chervan A.N.</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://www.nature-journal.by/jour/article/view/87">https://www.nature-journal.by/jour/article/view/87</self-uri><abstract><p>Исследована структура землепользования в горнодобывающем районе Солигорского калийного комбината в Беларуси по данным дистанционного зондирования (ДДЗ) для учета процессов деградации земельных и почвенных ресурсов. Выполнен анализ пространственно-временных характеристик пяти групп видов земель (пахотных, лесных, луговых земель, болот и водоемов) с использованием четырех вегетационных индексов (нормализованного индекса растительности NDVI, зеленого нормализованного индекса растительности GNDVI, почвенно-регулируемого индекса растительности SAVI и зеленого хлорофиллового индекса GCI). Исследование проводилось по 9 территориальным блокам в программной среде ArcGIS. Результаты позволили уточнить модели дешифрирования структуры землепользования на основе долевого участия групп видов земель. Оценена динамика вегетативных индексов в течение вегетативного периода. Коэффициенты детерминации (R2) индексов для лесных, пахотных и луговых земель составили ряд NDVI (0,78–0,82) &gt; GNDVI (0,75–0,80) &gt; SAVI (0,73–0,79) &gt; GCI (0,69–0,77). Пространственный анализ по индексам NDVI и GNDVI указывает на существенное влияние содержания влаги в почве в границах луговых земель, роль интенсивности сельскохозяйственной деятельности на пахотных землях, а также недостаточную чувствительность индекса SAVI для дешифрирования водоемов и болот. Анализ динамики индексов NDVI, GNDVI, SAVI и GCI позволил оценить пространственную неоднородность землепользования в горнодобывающем районе для последующего анализа процессов деградации земельных и почвенных ресурсов.</p></abstract><trans-abstract xml:lang="en"><p>The spatiotemporal characteristics of five land use types – arable land, forests, meadows, wetlands and water bodies – over an area of 8100 km2 in the influence zone of the Soligorsk Potash Plant in Belarus using four vegetation indices (NDVI, GNDVI, SAVI and GCI) based on Sentinel-2A remote sensing data (March – September 2023) are analyzed in the article. The study was conducted on nine territorial blocks in the ArcGIS environment with the accuracy of land type interpretation using the weighted average method for 900 representative plots. The obtained results made it possible to refine the models for interpreting land use structure based on the share of land types, as well as the dynamics of vegetation indices during the growing season. The coefficients of determination (R2) of the four vegetation indices for forest, arable and meadow lands are as follows: NDVI (0.78–0.82) &gt; GNDVI (0.75–0.80) &gt; SAVI (0.73–0.79) &gt; GCI (0.69–0.77). Spatial analysis of the NDVI and GNDVI indices specifies a significant influence of soil moisture within the boundaries of meadow lands, the role of agricultural intensity on arable lands and insufficient sensitivity of the SAVI index for interpreting water bodies and wetlands. The research results made it possible to assess the spatial heterogeneity of land use in the mining region for subsequent analysis of land and soil resource degradation processes.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>вегетационные индексы</kwd><kwd>дешифрирование</kwd><kwd>землепользование</kwd><kwd>вид земель</kwd><kwd>деградация почв</kwd></kwd-group><kwd-group xml:lang="en"><kwd>vegetation indices</kwd><kwd>decoding</kwd><kwd>land use</kwd><kwd>land type</kwd><kwd>soil degradation</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">黄土高原露天煤矿复垦土壤−植被系统恢复力及协同—权衡关系 / 陈浮, 朱燕峰, 骆占斌, 等 // 煤炭学报. – 2024. – Vol. 49, № 11. – P. 4950–4602. = Устойчивость почвенно-растительной системы и синергетические эффекты при рекультивации открытых угольных шахт на лёссовом плато / Чэнь Фу, Чжу Яньфэн, Ло Чжаньбинь [и др.] // Журнал по изучению каменного угля. – 2024. – Vol. 49, № 11. – P. 4950–4602. – DOI: 10.13225/j.cnki.jccs.2024.0326.</mixed-citation><mixed-citation xml:lang="en">Chen Fu, Zhu Yanfeng, Luo Zhanbin, e. a. Soil-Vegetation System Resilience and Synergies – Trade-Offs in Reclaiming Surface Coal Mines on The Loess Plateau. Journal of Chian Coal Science, 2024, vol. 49, рр. 4950–4602. DOI: 10.13225/j.cnki.jccs.2024.0326. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Study on the influence of mining disturbance on the variation characteristics of vegetation index: A case study of Lingwu Mining Area / Guo Yachao, Huang Yanli, Li Junmeng [et. al.] // Environmental Development. – 2023. – Vol. 45. – DOI: 10.1016/j.envdev.2023.100811.</mixed-citation><mixed-citation xml:lang="en">Yachao Guo, Yanli Huang, Junmeng Li, Shenyang Ouyang, Laiwei Wu, Wenyue Qi. Study on the influence of mining disturbance on the variation characteristics of vegetation index: A case study of Lingwu Mining Area. Environmental Development, 2023, vol. 45. DOI: 10.1016/j.envdev.2023.100811.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">中国矿区土地退化因素调查：概念、类型与方法 / 李海东, 沈渭涛, 司万童，等 // 生态与农村环境学报. – 2015. – Vol. 31, № 4. – P. 445–451. = Исследование факторов деградации земель в горнодобывающих районах Китая: концепции, виды и методы / Ли Хайдун, Шэнь Вэйтао, Си Вантун, Ян Цинву // Экология и сельская среда. – 2015. – Vol. 31, № 4. – P. 445–451. – DOI: 10.11934/j.issn.1673-4831.2015.04.001.</mixed-citation><mixed-citation xml:lang="en">Li Haidong, Shen Weishou, Si Wantong, Yan Qingwu. Investigation of Driving Factors of Land Degradation in Mine Areas in China: Concept, Types and Approaches. Journal of Ecology and Rural Environment, 2015, vol. 3, рр. 445–451. DOI: 10.11934/j.issn.1673-4831.2015.04.001. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Климат и средняя погода круглый год в Солигорск : [сайт]. – Миннеаполис, 2024. – URL: https://ru.weatherspark.com/y/95110/%D0%9E%D0%B1%D1%8B%D1%87%D0%BD%D0%B0%D1%8F-%D0%BF%D0%BE%D0%B3%D0%BE%D0%B4%D0%B0-%D0%B2-%D0%A1%D0%BE%D0%BB%D0%B8%D0%B3%D0%BE%D1%80%D1%81%D0%BA-%D0%91%D0%B5%D0%BB%D0%B0%D1%80%D1%83%D1%81%D1%8C-%D0%B2%D0%B5%D1%81%D1%8C-%D0%B3%D0%BE%D0%B4 (дата обращения: 01.03.2025).</mixed-citation><mixed-citation xml:lang="en">Klimat i srednyaya pogoda kruglyj god v Soligorske [Climate and average weather all year round in Soligorsk]. 2025. Available at: https://ru.weatherspark.com/y/95110/%D0%9E%D0%B1%D1%8B%D1%87%D0%BD%D0%B0%D1%8F%D0%BF%D0%BE%D0%B3%D0%BE%D0%B4%D0%B0%D0%B2%D0%A1%D0%BE%D0%BB%D0%B8%D0%B3%D0%BE%D1%80%D1%81%D0%BA%D0%91%D0%B5%D0%BB%D0%B0%D1%80%D1%83%D1%81%D1%8C%D0%B2%D0%B5%D1%81%D1%8C-%D0%B3%D0%BE%D0%B4 (accessed 1 December 2025). (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Официальный сайт Республики Беларусь : [сайт]. – Минск, 2009–2025. – URL: https://www.belarus.by/ru/ business/brands-of-belarus (дата обращения: 01.03.2025).</mixed-citation><mixed-citation xml:lang="en">Oficial'nyj sajt Respubliki Belarus' [Official Website of the Republic of Belarus]. 2025. Available at: https://www.belarus.by/cn/business/brands-of-belarus (accessed 1 December 2025). (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">白俄罗斯钾盐资源禀赋与投资环境分析 / 张宇轩, 李旭拓， 刘明义, 等 // 西北地址. – 2022. – Vol. 55, № 3. – P. 306–317. = Анализ обеспеченности калийными ресурсами и инвестиционной среды в Беларуси / Чжан Юйсюань, Ли Сютуо, Лю Минъи [и др.] // Северо-западная геология. – 2022. – Vol. 55, № 3. – P. 306–317.</mixed-citation><mixed-citation xml:lang="en">Zhang Yuxuan, Li Xutuo, Liu Mingyi, Gao Yongwei, Zhang Dandan. Analysis of Potash Resource Endowment and Investment Environment in Belarus. Northwestern Geology, vol. 5, рр. 306–317. DOI: 10.19751/j.cnki.61-1149/p.2022.03.025. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">我国盐湖浮选提钾技术及机理 / 惠庆华, 权朝明, 张慧芳, 等 // 应用化工. – 2021. – Vol. 50, № 12. – P. 3414–3419. = Технология и механизм извлечения калия флотацией в соленом озере Китая / Хуэй Цинхуа, Цюань Чжаомин, Чжан Хуэйфань [и др.] // Прикладная химия. – 2021. – Vol. 50, № 12. – P. 3414–3419. – DOI: doi.org/10.16581/j.cnki.issn1671-3206.2021.12.007.</mixed-citation><mixed-citation xml:lang="en">Hui Qinghua, Quan Zhaoming, Zhang Huifang, e. a. Potassium extraction technology and mechanism by flotation in China's salt lake. Applied Chemical Industry, 2021, vol. 50, рр. 3414–3419. DOI: doi.org/10.16581/j.cnki.issn1671-3206.2021.12.007. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Zhao Bochao. Spatial distribution of soils by salinization level in soligorsk district of Belarus / Zhao Bochao, Chervan Alexander // Почвенно-земельные ресурсы. – 2024. – Vol. 1. – P. 5–12.</mixed-citation><mixed-citation xml:lang="en">Zhao Bochao, Chervan A. N. Spatial distribution of soils by salinization level in Soligorsk district of Belarus. Soil and Land Resources, 2024, vol. 1, рр. 5–12.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">钾长石提钾技术进展 / 张晓慢,雍倩禧,祁梦瑶, 等 // 矿产保护与利用. – 2020. – Vol. 4. – P. 172–178. = Status and Prospect of Potassium Extracting from Potassium Feldspar / Чжан Сяома, Юн Цяньси, Ци Мэнъяо [и др.] // Сохранение и использование минеральных ресурсов. – 2020. – Vol. 4. – P. 172–178.</mixed-citation><mixed-citation xml:lang="en">Zhang Xiaoman, Yong Qianxi, Qi Mengyao, Sun Zhifu, Cao Peiyi, Peng Weijun. Status and Prospect of Potassium Extracting from Potassium Feldspar. Conservation and Utilization of Mineral Resources, 2020, vol. 40, no. 4, рр. 172–178. DOI: 10.13779/j.cnki.issn1001-0076.2020.04.021. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Взгляды Европы на Землю : [сайт]. – Брюссель, 2014–2025. – URL: https://www.copernicus.eu/en (дата обращения: 01.03.2025).</mixed-citation><mixed-citation xml:lang="en">Vzglyady Evropy na Zemlyu [Copernicus Eurpes eyes on Earth]. 2025. Available at: https://www.copernicus.eu/en (accessed 1 December 2025). (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Gitelson, Anatoly A. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for nondestructive chlorophyll assessment in higher plant leaves / Anatoly A. Gitelson, Yuri Gritz, Mark N. Merzlyak // Journal of Plant Physiology. – 2003. – Vol. 160, № 3. – P. 271–282. – DOI: doi.org/10.1078/0176-1617-00887.</mixed-citation><mixed-citation xml:lang="en">Anatoly A. Gitelson, Yuri Gritz. Mark N. Merzlyak. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology, 2003, vol. 16, рр. 271–282. DOI: doi.org/10.1078/0176-1617-0088.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">基于高分一号卫星数据的冬小麦叶片ＳＰＡＤ值遥感估 / 李粉, 王力, 刘京， 等 // 农业机械学报. – 2015. – Vol. 46, № 9. – P. 273–281. = Оценка величины SPAD для листьев пшеницы с помощью дистанционного зондирования на основе данных GF-1 / Ли Фенлинг, Ван Ли, Лю Цзин, Чанг Цинжуй // Труды Китайского общества сельскохозяйственной техники. – 2015. – Vol. 46, № 9. – P. 273–281. – DOI: doi.org/10.6041/j.issn.1000-1298.2015.09.040.</mixed-citation><mixed-citation xml:lang="en">Li Fenling, Wang Li, Liu Jing, Chang Qingrui. Remote Sensing Estimation of SPAD Value for Wheat Leaf Based on GF-1 Data. Transactions of the Chinese Society for Agricultural Machinery, 2015, vol. 4, рр. 273–281. DOI: 10.6041/j.issn.1000-1298.2015.09.040. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">王正兴. 植被指数研究进展: 从 AVHRR-NDVI 到 MODIS-EVI / 王正兴, 刘闯. // 生态学报. – 2003. – Vol. 23, № 5. – P. 979–987. = Ван Чжэнсин. Прогресс в исследовании индекса растительности: от AVHRR-NDVI до MODISEVI / Ван Чжэнсин, Лю Чжуань // Китайский экологический акт. – 2003. – Vol. 23, № 5. – P. 979–987.</mixed-citation><mixed-citation xml:lang="en">Wang Zhengxing, Liu Chuang, Huete Alfredo. Progress in Vegetation Index Research: From AVHRR-NDVI to MODIS-EVI. Acta Ecologica Sinica, 2003, vol. 2, рр. 979–987. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">郭玉川. 基于MODIS的干旱区植被覆盖度反演及植被指数优选 / 郭玉川, 何英, 李霞 // 国土资源遥感. – 2011. – Vol. 2. – P. 115–118. = Го Юйчуань. Инверсия растительного покрова и оптимизация вегетационного индекса в засушливых районах на основе MODIS / Го Юйчуань, Хэ Ин, Ли Ся // Дистанционное зондирование земли и ресурсов. – 2011. – Vol. 2. – P. 115–118.</mixed-citation><mixed-citation xml:lang="en">Guo Yuchuan, He Ying, Li Xia. Vegetation coverage inversion and vegetation index optimization in arid areas based on MODIS. Remote Sensing of Land and Resources, 2011, vol. 2, рр. 115–118. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Akhona Madasa. Application of geospatial indices for mapping land cover/use change detection in a mining area / Akhona Madasa, Israel R. Orimoloye, Olusola O. Ololade // Journal of African Earth Sciences. – 2021. – Vol. 175. – P. 104–108. – DOI: doi.org/10.1016/j.jafrearsci.2021.104108.</mixed-citation><mixed-citation xml:lang="en">Akhona Madasa, Israel R. Orimoloye, Olusola O. Ololade. Application of geospatial indices for mapping land cover/use change detection in a mining area. J. of African Earth Sciences, 2021, vol. 175, рр. 104–108. DOI: doi.org/10.1016/j.jafrearsci.2021.104108.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Bascietto Marco. Spatial Variations of Vegetation Index from Remote Sensing Linked to Soil Colloidal Status / Bascietto Marco, Enrico Santangelo, Claudio Beni // Land. – 2021. – Vol. 10, № 1. – P. 80. – DOI: https://doi.org/10.3390/land10010080.</mixed-citation><mixed-citation xml:lang="en">Bascietto Marco, Enrico Santangelo, Claudio Beni. Spatial Variations of Vegetation Index from Remote Sensing Linked to Soil Colloidal Status. Land, 2021, vol. 1, рр. 80. DOI: doi.org/10.3390/land10010080.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Orimoloye, I. R. Spatial evaluation of land-use dynamics in gold mining area using remote sensing and GIS technology / I. R Orimoloye, O. O. Ololade // International Journal of Environmental Science and Technology. – 2020. – Vol. 17, № 11. – P. 4465–4480. – DOI: 10.1007/s13762-020-02789-8.</mixed-citation><mixed-citation xml:lang="en">Orimoloye R., Ololade O. O. Spatial evaluation of land-use dynamics in gold mining area using remote sensing and GIS technology. International J. of Environmental Science and Technology, 2020, vol. 1, рр. 4465–4480. DOI: 10.1007/s13762-020-02789-8.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">基于 Landsat 8 和随机森林的青海门源天然草地地上生物量遥感估 / 赵翊含, 侯蒙京, 冯琦, 等. // 草业学报. – 2022. – Vol. 31, № 7. – P. 1–14. = Оценка с помощью дистанционного зондирования надземной биомассы естественных пастбищ в Мэньюане, Цинхай, на основе данных Landsat 8 и случайных лесов / Чжао Ихань, Хоу Мэнцзин, Фэн Цишэн [и др.] // Журнал пастбищной науки. – 2022. – Vol. 31, № 7. – P. 1–14.</mixed-citation><mixed-citation xml:lang="en">Zhao Yihan, Hou Mengjing, Feng Qisheng, e. a. Remote sensing estimation of aboveground biomass of natural grassland in Menyuan, Qinghai based on Landsat 8 and random forests. J. of Grassland Science, 2022, vol. 3, pp. 1–14. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">植物物种多样性无人机高光谱遥感反演研究 / 唐希颖, 李化哲,崔丽娟, 等 // 地球信息科学. – 2024. – Vol. 26, № 8. – P. 1954–1974. = Инверсия видового разнообразия водно-болотных растений с использованием гиперспектральных данных БПЛА / Тан Сиин, Ли Хуачжэ, Цуй Лицзюань [и др.] // Журнал геоинформационных наук. – 2024. – Vol. 26, № 8. – P. 1954–1974. – DOI: 10.12082/dqxxkx.2024.240055.</mixed-citation><mixed-citation xml:lang="en">Tang Xiying, Li Huazhe, Cui Lijuan, Zhao Xinsheng, Zhai Xiajie, Lei Yinru, Li Jing, Wang Jinzhi, Li Wei. Inversion of Wetland Plant Species Diversity Using UAV Hyperspectral Data. J. of Earth Information Science, 2024, vol. 2, pp. 1954–1974. DOI: 10.12082/dqxxkx.2024.240055. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">廖程浩. MODIS数据水体识别指数的识别效果比较分析 / 廖程浩,刘雪华 // 国土资源遥感. – 2008. – Vol. 4. – P. 22–27. = Ляо Чэньхао. Сравнительный анализ эффективности индексов идентификации водных объектов по данным MODIS / Ляо Чэньхао, Liu Xuehua // Дистанционное зондирование земельных ресурсов. – 2008. – Vol. 4. – P. 22–27.</mixed-citation><mixed-citation xml:lang="en">Liao Chenghao, Liu Xuehua. Comparative analysis of the identification effectiveness of water body identification indices from MODIS data. Remote sensing of land resources, 2008, vol. 4, pp. 22–27. (in Chinese)</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Геоморфологическая карта // Национальный атлас Беларуси. – Минск : Белкартография, 2002. – С. 67.</mixed-citation><mixed-citation xml:lang="en">Geomorfologicheskaya karta [Geomorphological map]. Natsional'nyi atlas Belarusi = National Atlas of Belarus. Minsk, Belkatografiya Publ., 2002, pp. 67. (in Russian)</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>
