Дослідження використання методів ДЗЗ для моніторингу та картографування торфовищ
| dc.citation.epage | 211 | |
| dc.citation.issue | І(49) | |
| dc.citation.journalTitle | Сучасні досягнення геодезичної науки та виробництва : збірник наукових праць | |
| dc.citation.spage | 201 | |
| dc.contributor.affiliation | Волинський національний університет імені Лесі Українки | |
| dc.contributor.affiliation | Волинський національний університет імені Лесі Українки | |
| dc.contributor.affiliation | Волинський національний університет імені Лесі Українки | |
| dc.contributor.affiliation | Волинський національний університет імені Лесі Українки | |
| dc.contributor.affiliation | Національний університет “Львівська політехніка” | |
| dc.contributor.affiliation | Lesya Ukrainka Volyn National University | |
| dc.contributor.affiliation | Lesya Ukrainka Volyn National University | |
| dc.contributor.affiliation | Lesya Ukrainka Volyn National University | |
| dc.contributor.affiliation | Lesya Ukrainka Volyn National University | |
| dc.contributor.affiliation | Lviv Polytechnic National University | |
| dc.contributor.author | Расюн, В. | |
| dc.contributor.author | Волошин, В. | |
| dc.contributor.author | Рудик, О. | |
| dc.contributor.author | Мельник, О. | |
| dc.contributor.author | Вовк, А. | |
| dc.contributor.author | Rasyun, V. | |
| dc.contributor.author | Voloshyn, V. | |
| dc.contributor.author | Rudyk, O. | |
| dc.contributor.author | Melnyk, O. | |
| dc.contributor.author | Vovk, A. | |
| dc.coverage.placename | Львів | |
| dc.coverage.placename | Lviv | |
| dc.date.accessioned | 2025-11-11T13:01:52Z | |
| dc.date.created | 2025-05-21 | |
| dc.date.issued | 2025-05-21 | |
| dc.description.abstract | Взаємодія між гідрологічною динамікою, характеристиками рослинності та кругообігом вуглецю критично важлива для підтримки екосистем торфовищ і навколишнього середовища загалом. Дослідження таких екосис- тем можливе на різних рівнях, територіях із використанням окремих якісних і кількісних характеристик. Дані ДЗЗ надають широкий спектр інформації про об’єкти території як загалом, так і за окремими показниками. Такі дослідження екосистем із використанням даних ДЗЗ набули актуальності у світі, тому аналіз методів досліджень, згадуваних у сучасних публікаціях, – завдання своєчасне. Мета. Здійснити огляд літератури стосовно викорис- тання методів оброблення різночасових гіпер- та мультиспектральних даних різних систем ДЗЗ, радарних даних із синтезованою апертурою (SAR), даних LiDAR та даних безпілотних літальних апаратів (БПЛА) для монітори- нгу і картографування рослинності та біорізноманіття торфовищ у світі впродовж 2000–2024 рр. Методика. Для аналізу актуальних публікацій використано комбінації ключових термінів та їхніх синонімів, пов’язаних із тор- фовищами, дистанційним зондуванням та моніторингом Землі, у наукометричній базі Web of Science. Аналіз публікацій передбачав зосередження уваги на дослідженнях із використанням супутникових, бортових даних або даних БПЛА для картографування та моніторингу торфовищ. Отриманий набір праць проаналізовано для визна- чення основних напрямів досліджень торфовищ із використанням даних ДЗЗ. Результати. Розглянуто останні досягнення у технологіях дистанційного зондування, ураховуючи супутникові, повітряні дані та дані БПЛА, а також їх використання для картографування і моніторингу торфовищ. Аналіз охоплює оцінку ефективності цих методів для ідентифікації різних видів рослин, моніторингу стану рослинності та виявлення змін у біорізнома- нітті. Огляд зосереджено на можливостях дистанційного зондування для точного картографування біорізнома- ніття рослинного покриву торфовищ. У статті детально розглянуто проблеми та обмеження поточних підходів дистанційного зондування, а також пропозиції щодо майбутніх досліджень для покращення моніторингу торфо- вищ. Практична значущість. Розширюючи окреслені напрями досліджень, зусилля з моніторингу стану торфо- вищ ми спрямували на підвищення просторової та часової роздільної здатності даних за рахунок їх інтеграції з різних джерел. Ця інтеграція націлена на виявлення дрібних і швидких змін в ареалах торфовищ. Інший підхід – перехресна оцінка та розширення можливостей масштабування ареалів торфовищ. У цьому напрямі наведено результати картографування функціональних типів рослин (Plant Functional Types) і мікроформ за допомогою даних БПЛА, які показують, що характеристики рослинності істотно впливають на мінімальну просторову роз- дільну здатність даних ДЗЗ, необхідну для точного визначення мікроформ. Проаналізувавши дослідження карто- графування функціональних типів рослин (Plant Functional Types), ми визначили, що необхідна роздільна здат- ність даних ДЗЗ мінімум 0,25 м. | |
| dc.description.abstract | The interaction between hydrological dynamics, vegetation characteristics and carbon cycling is critical for the maintenance of peatland ecosystems and the environment in general. The study of such ecosystems is possible at different levels and territories using separate qualitative and quantitative characteristics. Remote sensing data provide a wide range of information about the objects of the territory both in general and by individual indicators. Such studies of ecosystems using remote sensing data have gained relevance in the world, so the analysis of such research methods mentioned in modern publications is a timely task. Objective. To review the literature on the use of methods for processing multitemporal hyperspectral and multispectral data from different remote sensing systems, synthetic aperture radar (SAR) data, LiDAR data, and UAV data for monitoring and mapping peatland vegetation and biodiversity in the world during 2000–2024. Methods. To analyse relevant publications, we used combinations of key terms and their synonyms related to peatlands, remote sensing and Earth monitoring in the Web of Science scientific and metric database. The analysis of publications included a focus on studies using satellite, on-board or unmanned aerial vehicle (UAV) data for peatland mapping and monitoring. This set of papers was analysed to identify the main areas of peatland research using remote sensing data. Results. The latest advances in remote sensing technologies, including satellite, airborne and UAV data, and their use for peatland mapping and monitoring are reviewed. The analysis includes an assessment of the effectiveness of these methods in identifying different plant species, monitoring vegetation conditions and detecting changes in biodiversity. The review focuses on the possibilities of remote sensing for accurate mapping of peatland vegetation biodiversity. The article discusses in detail the problems and limitations of current remote sensing approaches, as well as suggestions for future research to improve peatland monitoring. Practical significance. Expanding on the presented research areas, peatland monitoring efforts are focused on improving the spatial and temporal resolution of data by integrating them from different sources. This integration is aimed at detecting small and rapid changes in peatland habitats. Another approach is to cross-validate and improve the scaling capabilities of peatland areas. In this direction, we present the results of mapping plant functional types (Plant Functional Typess) and microforms using UAV data, which showed that vegetation characteristics significantly affect the required minimum spatial resolution of remote sensing data, which is necessary for accurate microform detection. The analysed studies of plant functional types (Plant Functional Types) mapping have shown that the required resolution of remote sensing data is at least 0.25 m | |
| dc.format.extent | 201-211 | |
| dc.format.pages | 11 | |
| dc.identifier.citation | Дослідження використання методів ДЗЗ для моніторингу та картографування торфовищ / Расюн В., Волошин В., Рудик О., Мельник О., Вовк А. // Сучасні досягнення геодезичної науки та виробництва : збірник наукових праць. — Львів : Видавництво Львівської політехніки, 2025. — № І(49). — С. 201–211. | |
| dc.identifier.citation2015 | Дослідження використання методів ДЗЗ для моніторингу та картографування торфовищ / Расюн В. та ін. // Сучасні досягнення геодезичної науки та виробництва : збірник наукових праць, Львів. 2025. № І(49). С. 201–211. | |
| dc.identifier.citationenAPA | Rasyun, V., Voloshyn, V., Rudyk, O., Melnyk, O., & Vovk, A. (2025). Doslidzhennia vykorystannia metodiv DZZ dlia monitorynhu ta kartohrafuvannia torfovyshch [Investigating the use of remote sensing methods for monitoring and mapping peatlands]. Modern Achievements of Geodesic Science and Industry(I(49)), 201-211. Lviv Politechnic Publishing House. [in Ukrainian]. | |
| dc.identifier.citationenCHICAGO | Rasyun V., Voloshyn V., Rudyk O., Melnyk O., Vovk A. (2025) Doslidzhennia vykorystannia metodiv DZZ dlia monitorynhu ta kartohrafuvannia torfovyshch [Investigating the use of remote sensing methods for monitoring and mapping peatlands]. Modern Achievements of Geodesic Science and Industry (Lviv), no I(49), pp. 201-211 [in Ukrainian]. | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/118539 | |
| dc.language.iso | uk | |
| dc.publisher | Видавництво Львівської політехніки | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Сучасні досягнення геодезичної науки та виробництва : збірник наукових праць, І(49), 2025 | |
| dc.relation.ispartof | Modern Achievements of Geodesic Science and Industry, І(49), 2025 | |
| dc.relation.references | Antala, M., Juszczak, R., van der Tol, C., & Rastogi, A. | |
| dc.relation.references | (2022). Impact of climate change-induced alterations in | |
| dc.relation.references | peatland vegetation phenology and composition on | |
| dc.relation.references | carbon balance. Science of The Total Environment,827, 154294. https://doi.org/10.1016/J.SCITOTENV.2022.154294 | |
| dc.relation.references | Arasumani, M., Thiel, F., Pham, V. D., Hellmann, C., | |
| dc.relation.references | Kaiser, M., & van der Linden, S. (2023). Advancing | |
| dc.relation.references | peatland vegetation mapping by spaceborne imaging | |
| dc.relation.references | spectroscopy. Ecological Indicators, 154, 110665.https://doi.org/10.1016/J.ECOLIND.2023.110665 | |
| dc.relation.references | Arroyo-Mora, J. P., Kalacska, M., Soffer, R., Ifimov, G., | |
| dc.relation.references | Leblanc, G., Schaaf, E. S., & Lucanus, O. (2018). | |
| dc.relation.references | Evaluation of phenospectral dynamics with Sentinel-2A using a bottom-up approach in a northern | |
| dc.relation.references | ombrotrophic peatland. Remote Sensing of Environment,216, 544–560. https://doi.org/10.1016/J.RSE.2018.07.021 | |
| dc.relation.references | Artz, R. R. E., Johnson, S., Bruneau, P., Britton, A. J., | |
| dc.relation.references | Mitchell, R. J., Ross, L., Donaldson-Selby, G., | |
| dc.relation.references | Donnelly, D., Aitkenhead, M. J., Gimona, A., & Poggio, L. (2019). The potential for modelling | |
| dc.relation.references | peatland habitat condition in Scotland using long-term | |
| dc.relation.references | MODIS data. Science of The Total Environment, 660,429–442. https://doi.org/10.1016/J.SCITOTENV.2018.12.327 | |
| dc.relation.references | Assiri, M., Sartori, A., Persichetti, A., Miele, C., Faelga, | |
| dc.relation.references | R. A., Blount, T., & Silvestri, S. (2023). Leaf Area | |
| dc.relation.references | Index and aboveground biomass estimation of an | |
| dc.relation.references | alpine peatland with a UAV multi-sensor approach. | |
| dc.relation.references | GIScience & Remote Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2270791 | |
| dc.relation.references | Ball, J., Gimona, A., Cowie, N., Hancock, M., Klein, D., | |
| dc.relation.references | Donaldson-Selby, G., & Artz, R. R. E. (2023). | |
| dc.relation.references | Assessing the Potential of using Sentinel-1 and 2 or | |
| dc.relation.references | high-resolution aerial imagery data with Machine | |
| dc.relation.references | Learning and Data Science Techniques to Model | |
| dc.relation.references | Peatland Restoration Progress – a Northern Scotland | |
| dc.relation.references | case study. International Journal of Remote Sensing,44(9), 2885–2911. https://doi.org/10.1080/01431161.2023.2209916 | |
| dc.relation.references | Beyer, F., Jurasinski, G., Couwenberg, J., & Grenzdörffer, | |
| dc.relation.references | G. (2019). Multisensor data to derive peatland | |
| dc.relation.references | vegetation communities using a fixed-wing unmanned | |
| dc.relation.references | aerial vehicle. International Journal of Remote | |
| dc.relation.references | Sensing, 40(24), 9103–9125. https://doi.org/10.1080/01431161.2019.1580825 | |
| dc.relation.references | Bourgeau-Chavez, L. L., Endres, S., Powell, R., Battaglia, | |
| dc.relation.references | M. J., Benscoter, B., Turetsky, M., Kasischke, E. S., | |
| dc.relation.references | & Banda, E. (2016). Mapping boreal peatland | |
| dc.relation.references | ecosystem types from multitemporal radar and optical | |
| dc.relation.references | satellite imagery. Https://Doi.Org/10.1139/Cjfr-2016-0192, 47(4), 545–559. https://doi.org/10.1139/CJFR-2016-0192 | |
| dc.relation.references | Cole, B., McMorrow, J., & Evans, M. (2014). Spectral | |
| dc.relation.references | monitoring of moorland plant phenology to identify a | |
| dc.relation.references | temporal window for hyperspectral remote sensing of | |
| dc.relation.references | peatland. ISPRS Journal of Photogrammetry and | |
| dc.relation.references | Remote Sensing, 90, 49–58. https://doi.org/10.1016/J.ISPRSJPRS.2014.01.010 | |
| dc.relation.references | Connolly, J., Holden, N. M., Connolly, J., Seaquist, J. W., | |
| dc.relation.references | & Ward, S. M. (2011). Detecting recent disturbance on | |
| dc.relation.references | Montane blanket bogs in the Wicklow Mountains, | |
| dc.relation.references | Ireland using the MODIS enhanced vegetation index. | |
| dc.relation.references | International Journal of Remote Sensing, 32(9), 2377–2393. https://doi.org/10.1080/01431161003698310 | |
| dc.relation.references | Czapiewski, S., & Szumińska, D. (2022). An overview of | |
| dc.relation.references | remote sensing data applications in peatland research | |
| dc.relation.references | based on works from the period 2010–2021. Land,11(1), 24. https://doi.org/10.3390/LAND11010024/S1 | |
| dc.relation.references | Erudel, T., Fabre, S., Houet, T., Mazier, F., & Briottet, X. | |
| dc.relation.references | (2017). Criteria Comparison for Classifying Peatland | |
| dc.relation.references | Vegetation Types Using In Situ Hyperspectral | |
| dc.relation.references | Measurements. Remote Sensing, 9(7). https://doi.org/10.3390/rs9070748 | |
| dc.relation.references | FAO. Peatland Mapping and Monitoring: Recommendations | |
| dc.relation.references | and Technical Overview. (2020). FAO.https://doi.org/https://doi.org/10.4060/ca8200en | |
| dc.relation.references | Franke, J., Keuck, V., & Siegert, F. (2012). Assessment of | |
| dc.relation.references | grassland use intensity by remote sensing to support | |
| dc.relation.references | conservation schemes. Journal for Nature Conservation,20(3), 125–134. https://doi.org/10.1016/J. | |
| dc.relation.references | JNC.2012.02.001 | |
| dc.relation.references | Frick, A., Steffenhagen, P., Zerbe, S., Timmermann, T., & | |
| dc.relation.references | Schulz, K. (2011). Monitoring of the Vegetation | |
| dc.relation.references | Composition in Rewetted Peatland with Iterative | |
| dc.relation.references | Decision Tree Classification of Satellite Imagery. | |
| dc.relation.references | Photogrammetrie - Fernerkundung - Geoinformation,2011(3), 109–122. https://doi.org/10.1127/1432-8364/2011/0076 | |
| dc.relation.references | Garisoain, R., Delire, C., Decharme, B., Ferrant, S., | |
| dc.relation.references | Granouillac, F., Payre-Suc, V., & Gandois, L. (2023). | |
| dc.relation.references | A Study of Dominant Vegetation Phenology in a | |
| dc.relation.references | Sphagnum Mountain Peatland Using In Situ and | |
| dc.relation.references | Sentinel-2 Observations. Journal of Geophysical | |
| dc.relation.references | Research: Biogeosciences, 128(10), e2023JG007403.https://doi.org/10.1029/2023JG007403 | |
| dc.relation.references | Harris, A., Charnock, R., & Lucas, R. M. (2015). | |
| dc.relation.references | Hyperspectral remote sensing of peatland floristic | |
| dc.relation.references | gradients. Remote Sensing of Environment, 162, 99–111. https://doi.org/10.1016/J.RSE.2015.01.029 | |
| dc.relation.references | Hilbert, D. W., Roulet, N., & Moore, T. (2000). Modelling | |
| dc.relation.references | and analysis of peatlands as dynamical systems. | |
| dc.relation.references | Journal of Ecology, 88(2), 230–242. https://doi.org/10.1046/J.1365-2745.2000.00438.X | |
| dc.relation.references | Julia´, J., Cabezas, J., Galleguillos, M., Valdé S, A., | |
| dc.relation.references | Fuentes, J. P., Rez, C. P., Perez-Quezada, J. F., Cabezas, | |
| dc.relation.references | C. :, Galleguillos, M., Valdés, A., Fuen-tes, J. P., | |
| dc.relation.references | Pérez, C., Perez-Quezada, J. F., & Peters, D. P. C.(2015). Evaluation of impacts of management in an | |
| dc.relation.references | anthropogenic peatland using field and remote sensing | |
| dc.relation.references | data. Ecosphere, 6(12), 1–24. https://doi.org/10.1890/ES15-00232.1 | |
| dc.relation.references | Kalacska, M., Lalonde, M., & Moore, T. R. (2015). | |
| dc.relation.references | Estimation of foliar chlorophyll and nitrogen content in | |
| dc.relation.references | an ombrotrophic bog from hyperspectral data: Scaling | |
| dc.relation.references | from leaf to image. Remote Sensing of Environment,169, 270–279. https://doi.org/10.1016/J.RSE.2015.08.012 | |
| dc.relation.references | Karlson, M., Gålfalk, M., Crill, P., Bousquet, P., Saunois, | |
| dc.relation.references | M., & Bastviken, D. (2019). Delineating northern | |
| dc.relation.references | peatlands using Sentinel-1 time series and terrain | |
| dc.relation.references | indices from local and regional digital elevation | |
| dc.relation.references | models. Remote Sensing of Environment, 231, 111252. | |
| dc.relation.references | https://doi.org/10.1016/J.RSE.2019.111252 | |
| dc.relation.references | Kattenborn, T., Fassnacht, F. E., Pierce, S., Lopatin, J., | |
| dc.relation.references | Grime, J. P., & Schmidtlein, S. (2017). Linking plant | |
| dc.relation.references | strategies and plant traits derived by radiative transfer | |
| dc.relation.references | modelling. Journal of Vegetation Science, 28(4), 717–727. https://doi.org/10.1111/JVS.12525 Knoth, C., Klein, B., Prinz, T., & Kleinebecker, T. (2013). | |
| dc.relation.references | Unmanned aerial vehicles as innovative remote sensing | |
| dc.relation.references | platforms for high-resolution infrared imagery to | |
| dc.relation.references | support restoration monitoring in cut-over bogs. | |
| dc.relation.references | Applied Vegetation Science, 16(3), 509–517.https://doi.org/10.1111/AVSC.12024 | |
| dc.relation.references | Lees, K. J., Quaife, T., Artz, R. R. E., Khomik, M., | |
| dc.relation.references | & Clark, J. M. (2018). Potential for using remote sensing | |
| dc.relation.references | to estimate carbon fluxes across northern peatlands – A | |
| dc.relation.references | review. Science of The Total Environment, 615, 857–874.https://doi.org/10.1016/J.SCITOTENV.2017.09.103 | |
| dc.relation.references | Lourenco, M., Fitchett, J. M., & Woodborne, S. (2023). | |
| dc.relation.references | Peat definitions: A critical review. Progress in | |
| dc.relation.references | Physical Geography, 47(4), 506–520. https://doi.org/10.1177/03091333221118353/ASSET/IMAGES/LARGE/10.1177_03091333221118353-FIG1.JPEG | |
| dc.relation.references | McMorrow, J. M., Cutler, M. E. J., Evans, M. G., & Al- | |
| dc.relation.references | Roichdi, A. (2004). Hyperspectral indices for | |
| dc.relation.references | characterizing upland peat composition. International | |
| dc.relation.references | Journal of Remote Sensing, 25(2), 313–325.https://doi.org/10.1080/0143116031000117065 | |
| dc.relation.references | McPartland, M. Y., Falkowski, M. J., Reinhardt, J. R., | |
| dc.relation.references | Kane, E. S., Kolka, R., Turetsky, M. R., Douglas, | |
| dc.relation.references | T. A., Anderson, J., Edwards, J. D., Palik, B., | |
| dc.relation.references | & Montgomery, R. A. (2019). Characterizing Boreal | |
| dc.relation.references | Peatland Plant Composition and Species Diversity with | |
| dc.relation.references | Hyperspectral Remote Sensing. Remote Sensing 2019, | |
| dc.relation.references | Vol. 11, Page 1685, 11(14), 1685. https://doi.org/10.3390/RS11141685 | |
| dc.relation.references | Merchant, M. A., Adams, J. R., Berg, A. A., Baltzer, J. L., | |
| dc.relation.references | Quinton, W. L., & Chasmer, L. E. (2017). | |
| dc.relation.references | Contributions of C-Band SAR Data and Polarimetric | |
| dc.relation.references | Decompositions to Subarctic Boreal Peatland | |
| dc.relation.references | Mapping. IEEE Journal of Selected Topics in Applied | |
| dc.relation.references | Earth Observations and Remote Sensing, 10(4), 1467–1482. https://doi.org/10.1109/JSTARS.2016.2621043 | |
| dc.relation.references | Middleton, M., Närhi, P., Arkimaa, H., Hyvönen, E., | |
| dc.relation.references | Kuosmanen, V., Treitz, P., & Sutinen, R. (2012). | |
| dc.relation.references | Ordination and hyperspectral remote sensing approach | |
| dc.relation.references | to classify peatland biotopes along soil moisture and | |
| dc.relation.references | fertility gradients. Remote Sensing of Environment, 124,596–609. https://doi.org/10.1016/J.RSE.2012.06.010 | |
| dc.relation.references | Millard, K., Kirby, P., Nandlall, S., Behnamian, A., | |
| dc.relation.references | Banks, S., & Pacini, F. (2020). Using Growing-Season | |
| dc.relation.references | Time Series Coherence for Improved Peatland Mapping: | |
| dc.relation.references | Comparing the Contributions of Sentinel-1 and | |
| dc.relation.references | RADARSAT-2 Coherence in Full and Partial Time | |
| dc.relation.references | Series. Remote Sensing 2020, Vol. 12, Page 2465,12(15), 2465. https://doi.org/10.3390/RS12152465 | |
| dc.relation.references | Minasny, B., Adetsu, D. V., Aitkenhead, M., Artz, R. R. E., | |
| dc.relation.references | Baggaley, N., Barthelmes, A., Beucher, A., Caron, J., | |
| dc.relation.references | Conchedda, G., Connolly, J., Deragon, R., Evans, C., | |
| dc.relation.references | Fadnes, K., Fiantis, D., Gagkas, Z., Gilet, L., Gimona, A., | |
| dc.relation.references | Glatzel, S., Greve, M. H., … Zak, D. (2023). Mapping | |
| dc.relation.references | and monitoring peatland conditions from global to field | |
| dc.relation.references | scale. Biogeochemistry 2023 167:4, 167(4), 383–425. | |
| dc.relation.references | https://doi.org/10.1007/ S10533-023-01084-1 | |
| dc.relation.references | Minasny, B., Berglund, Ö., Connolly, J., Hedley, C., de | |
| dc.relation.references | Vries, F., Gimona, A., Kempen, B., Kidd, D., Lilja, H., | |
| dc.relation.references | Malone, B., McBratney, A., Roudier, P., O’Rourke, S., | |
| dc.relation.references | Rudiyanto, Padarian, J., Poggio, L., ten Caten, A., | |
| dc.relation.references | Thompson, D., Tuve, C., & Widyatmanti, W. (2019). | |
| dc.relation.references | Digital mapping of peatlands – A critical review. | |
| dc.relation.references | Earth-Science Reviews, 196, 102870. https://doi.org/10.1016/J.EARSCIREV.2019.05.014 | |
| dc.relation.references | Montanarella, L., R.J.A, J., & R, H. (2006). The | |
| dc.relation.references | distribution of peatland in Europe. Mires and Peat, 1. | |
| dc.relation.references | Pflugmacher, D., Krankina, O. N., & Cohen, W. B. (2007). | |
| dc.relation.references | Satellite-based peatland mapping: Potential of the | |
| dc.relation.references | MODIS sensor. Global and Planetary Change, 56 (3–4),248–257. https://doi.org/10.1016/J.GLOPLACHA.2006.07.019 | |
| dc.relation.references | Räsänen, A., Juutinen, S., Kalacska, M., Aurela, M., | |
| dc.relation.references | Heikkinen, P., Mäenpää, K., Rimali, A., & Virtanen, T.(2020). Peatland leaf-area index and biomass | |
| dc.relation.references | estimation with ultra-high resolution remote sensing. | |
| dc.relation.references | GIScience & Remote Sensing, 57(7), 943–964.https://doi.org/10.1080/15481603.2020.1829377 | |
| dc.relation.references | Räsänen, A., Juutinen, S., Tuittila, E. S., Aurela, M., & | |
| dc.relation.references | Virtanen, T. (2019). Comparing ultra-high spatial | |
| dc.relation.references | resolution remote-sensing methods in mapping | |
| dc.relation.references | peatland vegetation. Journal of Vegetation Science,30(5), 1016–1026. https://doi.org/10.1111/JVS.12769 | |
| dc.relation.references | Schaepman-Strub, G., Limpens, J., Menken, M., | |
| dc.relation.references | Bartholomeus, H. M., & Schaepman, M. E. (2009). | |
| dc.relation.references | Towards spatial assessment of carbon sequestration in | |
| dc.relation.references | peatlands: Spectroscopy based estimation of fractional | |
| dc.relation.references | cover of three plant functional types. Biogeosciences,6(2), 275–284. https://doi.org/10.5194/BG-6-275-2009 | |
| dc.relation.references | Schmidtlein, S., Feilhauer, H., & Bruelheide, H. (2012). | |
| dc.relation.references | Mapping plant strategy types using remote sensing. | |
| dc.relation.references | Journal of Vegetation Science, 23(3), 395–405.https://doi.org/10.1111/J.1654-1103.2011.01370.X | |
| dc.relation.references | Steenvoorden, J., Bartholomeus, H., & Limpens, J. (2023). | |
| dc.relation.references | Less is more: Optimizing vegetation mapping in | |
| dc.relation.references | peatlands using unmanned aerial vehicles (UAVs). | |
| dc.relation.references | International Journal of Applied Earth Observation | |
| dc.relation.references | and Geoinformation, 117, 103220. https://doi.org/10.1016/J.JAG.2023.103220 | |
| dc.relation.references | Steenvoorden, J., & Limpens, J. (2023). Upscaling | |
| dc.relation.references | peatland mapping with drone-derived imagery: impact | |
| dc.relation.references | of spatial resolution and vegetation characteristics. | |
| dc.relation.references | GIScience & Remote Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2267851 | |
| dc.relation.references | Stuart, M. B. , Davies, M. Hobbs, M. J. Mcgonigle, A. J. S., | |
| dc.relation.references | Stuart, M. B., Davies, M., Hobbs, M. J., Mcgonigle, | |
| dc.relation.references | A. J. S., & Willmott, J. R. (2022). Peatland Plant | |
| dc.relation.references | Spectral Response as a Proxy for Peat Health, Analysis | |
| dc.relation.references | Using Low-Cost Hyperspectral Imaging Techniques. | |
| dc.relation.references | Remote Sensing 2022, Vol. 14, p. 3846, 14(16), 3846. | |
| dc.relation.references | https://doi.org/10.3390/RS14163846 Torabi Haghighi, A., Menberu, M. W., Darabi, H., | |
| dc.relation.references | Akanegbu, J., & Kløve, B. (2018). Use of remote | |
| dc.relation.references | sensing to analyse peatland changes after drainage | |
| dc.relation.references | for peat extraction. Land Degradation & | |
| dc.relation.references | Development, 29(10), 3479–3488.https://doi.org/10.1002/LDR.3122 | |
| dc.relation.references | White, L., Millard, K., Banks, S., Richardson, M., Pasher, J., | |
| dc.relation.references | & Duffe, J. (2017). Moving to the RADARSAT | |
| dc.relation.references | Constellation Mission: Comparing Synthesized Compact | |
| dc.relation.references | Polarimetry and Dual Polarimetry Data with Fully | |
| dc.relation.references | Polarimetric RADARSAT-2 Data for Image | |
| dc.relation.references | Classification of Peatlands. Remote Sensing 2017, Vol. 9,p. 573, 9(6), 573. https://doi.org/10.3390/RS9060573 | |
| dc.relation.references | Zhou, Z., Li, Z., Waldron, S., & Tanaka, A. (2019). InSAR | |
| dc.relation.references | Time Series Analysis of L-Band Data for | |
| dc.relation.references | Understanding Tropical Peatland Degradation and | |
| dc.relation.references | Restoration. Remote Sensing 2019, Vol. 11, p. 2592,11(21), 2592. https://doi.org/10.3390/RS11212592 | |
| dc.relation.referencesen | Antala, M., Juszczak, R., van der Tol, C., & Rastogi, A. (2022). Impact of climate change-induced alterations in peatland | |
| dc.relation.referencesen | vegetation phenology and composition on carbon balance. Science of The Total Environment, 827, 154294. | |
| dc.relation.referencesen | https://doi.org/10.1016/J.SCITOTENV.2022.154294 | |
| dc.relation.referencesen | Arasumani, M., Thiel, F., Pham, V. D., Hellmann, C., Kaiser, M., & van der Linden, S. (2023). Advancing peatland | |
| dc.relation.referencesen | vegetation mapping by spaceborne imaging spectroscopy. Ecological Indicators, 154, 110665. | |
| dc.relation.referencesen | https://doi.org/10.1016/ J.ECOLIND.2023.110665 | |
| dc.relation.referencesen | Arroyo-Mora, J. P., Kalacska, M., Soffer, R., Ifimov, G., Leblanc, G., Schaaf, E. S., & Lucanus, O. (2018). Evaluation of | |
| dc.relation.referencesen | phenospectral dynamics with Sentinel-2A using a bottom-up approach in a northern ombrotrophic peatland. Remote | |
| dc.relation.referencesen | Sensing of Environment, 216, 544–560. https://doi.org/10.1016/J.RSE.2018.07.021 | |
| dc.relation.referencesen | Artz, R. R. E., Johnson, S., Bruneau, P., Britton, A. J., Mitchell, R. J., Ross, L., Donaldson-Selby, G., Donnelly, D., | |
| dc.relation.referencesen | Aitkenhead, M. J., Gimona, A., & Poggio, L. (2019). The potential for modelling peatland habitat condition in | |
| dc.relation.referencesen | Scotland using long-term MODIS data. Science of The Total Environment, 660, 429–442. | |
| dc.relation.referencesen | https://doi.org/10.1016/J.SCITOTENV. 2018.12.327 | |
| dc.relation.referencesen | Assiri, M., Sartori, A., Persichetti, A., Miele, C., Faelga, R. A., Blount, T., & Silvestri, S. (2023). Leaf Area Index and | |
| dc.relation.referencesen | aboveground biomass estimation of an alpine peatland with a UAV multi-sensor approach. GIScience & Remote | |
| dc.relation.referencesen | Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2270791 | |
| dc.relation.referencesen | Ball, J., Gimona, A., Cowie, N., Hancock, M., Klein, D., Donaldson-Selby, G., & Artz, R. R. E. (2023). Assessing the | |
| dc.relation.referencesen | Potential of using Sentinel-1 and 2 or high-resolution aerial imagery data with Machine Learning and Data Science | |
| dc.relation.referencesen | Techniques to Model Peatland Restoration Progress – a Northern Scotland case study. International Journal of | |
| dc.relation.referencesen | Remote Sensing, 44(9), 2885–2911. https://doi.org/10.1080/01431161.2023.2209916 | |
| dc.relation.referencesen | Beyer, F., Jurasinski, G., Couwenberg, J., & Grenzdörffer, G. (2019). Multisensor data to derive peatland vegetation | |
| dc.relation.referencesen | communities using a fixed-wing unmanned aerial vehicle. International Journal of Remote Sensing, 40(24), 9103–9125. https://doi.org/10.1080/01431161.2019.1580825 | |
| dc.relation.referencesen | Bourgeau-Chavez, L. L., Endres, S., Powell, R., Battaglia, M. J., Benscoter, B., Turetsky, M., Kasischke, E. S., & Banda, E.(2016). Mapping boreal peatland ecosystem types from multitemporal radar and optical satellite imagery. | |
| dc.relation.referencesen | Https://Doi.Org/10.1139/Cjfr-2016-0192, 47(4), 545–559. https://doi.org/10.1139/CJFR-2016-0192 | |
| dc.relation.referencesen | Cole, B., McMorrow, J., & Evans, M. (2014). Spectral monitoring of moorland plant phenology to identify a temporal | |
| dc.relation.referencesen | window for hyperspectral remote sensing of peatland. ISPRS Journal of Photogrammetry and Remote Sensing, 90,49–58. https://doi.org/10.1016/J.ISPRSJPRS.2014.01.010 | |
| dc.relation.referencesen | Connolly, J., Holden, N. M., Connolly, J., Seaquist, J. W., & Ward, S. M. (2011). Detecting recent disturbance on | |
| dc.relation.referencesen | Montane blanket bogs in the Wicklow Mountains, Ireland using the MODIS enhanced vegetation index. International | |
| dc.relation.referencesen | Journal of Remote Sensing, 32(9), 2377–2393. https://doi.org/10.1080/01431161003698310 | |
| dc.relation.referencesen | Czapiewski, S., & Szumińska, D. (2022). An overview of remote sensing data applications in peatland research based on | |
| dc.relation.referencesen | works from the period 2010–2021. Land, 11(1), 24. https://doi.org/10.3390/LAND11010024/S1 | |
| dc.relation.referencesen | Erudel, T., Fabre, S., Houet, T., Mazier, F., & Briottet, X. (2017). Criteria Comparison for Classifying Peatland | |
| dc.relation.referencesen | Vegetation Types Using In Situ Hyperspectral Measurements. Remote Sensing, 9(7). https://doi.org/10.3390/rs9070748 | |
| dc.relation.referencesen | FAO. Peatland Mapping and Monitoring: Recommendations and Technical Overview. (2020). FAO.https://doi.org/https://doi.org/10.4060/ca8200en | |
| dc.relation.referencesen | Franke, J., Keuck, V., & Siegert, F. (2012). Assessment of grassland use intensity by remote sensing to support | |
| dc.relation.referencesen | conservation schemes. Journal for Nature Conservation, 20(3), 125–134. https://doi.org/10.1016/J.JNC.2012.02.001 | |
| dc.relation.referencesen | Frick, A., Steffenhagen, P., Zerbe, S., Timmermann, T., & Schulz, K. (2011). Monitoring of the Vegetation Composition | |
| dc.relation.referencesen | in Rewetted Peatland with Iterative Decision Tree Classification of Satellite Imagery. Photogrammetrie - | |
| dc.relation.referencesen | Fernerkundung - Geoinformation, 2011(3), 109–122. https://doi.org/10.1127/1432-8364/2011/0076 | |
| dc.relation.referencesen | Garisoain, R., Delire, C., Decharme, B., Ferrant, S., Granouillac, F., Payre-Suc, V., & Gandois, L. (2023). A Study of | |
| dc.relation.referencesen | Dominant Vegetation Phenology in a Sphagnum Mountain Peatland Using In Situ and Sentinel-2 Observations. | |
| dc.relation.referencesen | Journal of Geophysical Research: Biogeosciences, 128(10), e2023JG007403. https://doi.org/10.1029/2023JG007403 | |
| dc.relation.referencesen | Harris, A., Charnock, R., & Lucas, R. M. (2015). Hyperspectral remote sensing of peatland floristic gradients. Remote | |
| dc.relation.referencesen | Sensing of Environment, 162, 99–111. https://doi.org/10.1016/J.RSE.2015.01.029 | |
| dc.relation.referencesen | Hilbert, D. W., Roulet, N., & Moore, T. (2000). Modelling and analysis of peatlands as dynamical systems. Journal of | |
| dc.relation.referencesen | Ecology, 88(2), 230–242. https://doi.org/10.1046/J.1365-2745.2000.00438.X | |
| dc.relation.referencesen | Julia´, J., Cabezas, J., Galleguillos, M., Valdé S, A., Fuentes, J. P., Rez, C. P., Perez-Quezada, J. F., Cabezas, C. , | |
| dc.relation.referencesen | Galleguillos, M., Valdés, A., Fuentes, J. P., Pérez, C., Perez-Quezada, J. F., & Peters, D. P. C. (2015). Evaluation of | |
| dc.relation.referencesen | impacts of management in an anthropogenic peatland using field and remote sensing data. Ecosphere, 6(12), 1–24. | |
| dc.relation.referencesen | https://doi.org/10.1890/ES15-00232.1 | |
| dc.relation.referencesen | Kalacska, M., Lalonde, M., & Moore, T. R. (2015). Estimation of foliar chlorophyll and nitrogen content in an | |
| dc.relation.referencesen | ombrotrophic bog from hyperspectral data: Scaling from leaf to image. Remote Sensing of Environment, 169, 270–279. https://doi.org/10.1016/J.RSE.2015.08.012 | |
| dc.relation.referencesen | Karlson, M., Gålfalk, M., Crill, P., Bousquet, P., Saunois, M., & Bastviken, D. (2019). Delineating northern peatlands | |
| dc.relation.referencesen | using Sentinel-1 time series and terrain indices from local and regional digital elevation models. Remote Sensing of | |
| dc.relation.referencesen | Environment, 231, 111252. https://doi.org/10.1016/J.RSE.2019.111252 | |
| dc.relation.referencesen | Kattenborn, T., Fassnacht, F. E., Pierce, S., Lopatin, J., Grime, J. P., & Schmidtlein, S. (2017). Linking plant strategies | |
| dc.relation.referencesen | and plant traits derived by radiative transfer modelling. Journal of Vegetation Science, 28(4), 717–727. | |
| dc.relation.referencesen | https://doi.org/10.1111/JVS.12525 | |
| dc.relation.referencesen | Knoth, C., Klein, B., Prinz, T., & Kleinebecker, T. (2013). Unmanned aerial vehicles as innovative remote sensing | |
| dc.relation.referencesen | platforms for high-resolution infrared imagery to support restoration monitoring in cut-over bogs. Applied Vegetation | |
| dc.relation.referencesen | Science, 16(3), 509–517. https://doi.org/10.1111/AVSC.12024 | |
| dc.relation.referencesen | Lees, K. J., Quaife, T., Artz, R. R. E., Khomik, M., & Clark, J. M. (2018). Potential for using remote sensing to estimate | |
| dc.relation.referencesen | carbon fluxes across northern peatlands – A review. Science of The Total Environment, 615, 857–874. | |
| dc.relation.referencesen | https://doi.org/10.1016/J.SCITOTENV.2017.09.103 | |
| dc.relation.referencesen | Lourenco, M., Fitchett, J. M., & Woodborne, S. (2023). Peat definitions: A critical review. Progress in Physical | |
| dc.relation.referencesen | Geography, 47(4), 506–520. https://doi.org/10.1177/03091333221118353/ASSET/IMAGES /LARGE/10.1177_03091333221118353-FIG1.JPEG | |
| dc.relation.referencesen | McMorrow, J. M., Cutler, M. E. J., Evans, M. G., & Al-Roichdi, A. (2004). Hyperspectral indices for characterizing | |
| dc.relation.referencesen | upland peat composition. International Journal of Remote Sensing, 25(2), 313–325. https://doi.org/10.1080/0143116031000117065 | |
| dc.relation.referencesen | McPartland, M. Y., Falkowski, M. J., Reinhardt, J. R., Kane, E. S., Kolka, R., Turetsky, M. R., Douglas, T. A., | |
| dc.relation.referencesen | Anderson, J., Edwards, J. D., Palik, B., & Montgomery, R. A. (2019). Characterizing Boreal Peatland Plant | |
| dc.relation.referencesen | Composition and Species Diversity with Hyperspectral Remote Sensing. Remote Sensing 2019, Vol. 11, Page 1685,11(14), 1685. https://doi.org/10.3390/RS11141685 | |
| dc.relation.referencesen | Merchant, M. A., Adams, J. R., Berg, A. A., Baltzer, J. L., Quinton, W. L., & Chasmer, L. E. (2017). Contributions of CBand | |
| dc.relation.referencesen | SAR Data and Polarimetric Decompositions to Subarctic Boreal Peatland Mapping. IEEE Journal of Selected | |
| dc.relation.referencesen | Topics in Applied Earth Observations and Remote Sensing, 10(4), 1467–1482. https://doi.org/10.1109/JSTARS.2016.2621043 | |
| dc.relation.referencesen | Middleton, M., Närhi, P., Arkimaa, H., Hyvönen, E., Kuosmanen, V., Treitz, P., & Sutinen, R. (2012). Ordination and | |
| dc.relation.referencesen | hyperspectral remote sensing approach to classify peatland biotopes along soil moisture and fertility gradients. | |
| dc.relation.referencesen | Remote Sensing of Environment, 124, 596–609. https://doi.org/10.1016/J.RSE.2012.06.010 | |
| dc.relation.referencesen | Millard, K., Kirby, P., Nandlall, S., Behnamian, A., Banks, S., & Pacini, F. (2020). Using Growing-Season Time Series | |
| dc.relation.referencesen | Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 | |
| dc.relation.referencesen | Coherence in Full and Partial Time Series. Remote Sensing 2020, Vol. 12, Page 2465, 12(15), 2465. https://doi.org/10.3390/RS12152465 | |
| dc.relation.referencesen | Minasny, B., Adetsu, D. V., Aitkenhead, M., Artz, R. R. E., Baggaley, N., Barthelmes, A., Beucher, A., Caron, J., | |
| dc.relation.referencesen | Conchedda, G., Connolly, J., Deragon, R., Evans, C., Fadnes, K., Fiantis, D., Gagkas, Z., Gilet, L., Gimona, A., | |
| dc.relation.referencesen | Glatzel, S., Greve, M. H., … Zak, D. (2023). Mapping and monitoring peatland conditions from global to field scale. | |
| dc.relation.referencesen | Biogeochemistry 2023 167:4, 167(4), 383–425. https://doi.org/10.1007/S10533-023-01084-1 | |
| dc.relation.referencesen | Minasny, B., Berglund, Ö., Connolly, J., Hedley, C., de Vries, F., Gimona, A., Kempen, B., Kidd, D., Lilja, H., Malone, B., | |
| dc.relation.referencesen | McBratney, A., Roudier, P., O’Rourke, S., Rudiyanto, Padarian, J., Poggio, L., ten Caten, A., Thompson, D., | |
| dc.relation.referencesen | Tuve, C., & Widyatmanti, W. (2019). Digital mapping of peatlands – A critical review. Earth-Science Reviews, 196,102870. https://doi.org/10.1016/J.EARSCIREV.2019.05.014 | |
| dc.relation.referencesen | Montanarella, L., R. J. A., J., & R., H. (2006). The distribution of peatland in Europe. Mires and Peat, 1. | |
| dc.relation.referencesen | Pflugmacher, D., Krankina, O. N., & Cohen, W. B. (2007). Satellite-based peatland mapping: Potential of the MODIS | |
| dc.relation.referencesen | sensor. Global and Planetary Change, 56(3–4), 248–257. https://doi.org/10.1016/J.GLOPLACHA.2006.07.019 | |
| dc.relation.referencesen | Räsänen, A., Juutinen, S., Kalacska, M., Aurela, M., Heikkinen, P., Mäenpää, K., Rimali, A., & Virtanen, T. (2020). | |
| dc.relation.referencesen | Peatland leaf-area index and biomass estimation with ultra-high resolution remote sensing. GIScience & Remote | |
| dc.relation.referencesen | Sensing, 57(7), 943–964. https://doi.org/10.1080/15481603.2020.1829377 | |
| dc.relation.referencesen | Räsänen, A., Juutinen, S., Tuittila, E. S., Aurela, M., & Virtanen, T. (2019). Comparing ultra-high spatial resolution | |
| dc.relation.referencesen | remote-sensing methods in mapping peatland vegetation. Journal of Vegetation Science, 30(5), 1016–1026.https://doi.org/10.1111/JVS.12769 | |
| dc.relation.referencesen | Schaepman-Strub, G., Limpens, J., Menken, M., Bartholomeus, H. M., & Schaepman, M. E. (2009). Towards spatial | |
| dc.relation.referencesen | assessment of carbon sequestration in peatlands: Spectroscopy based estimation of fractional cover of three plant | |
| dc.relation.referencesen | functional types. Biogeosciences, 6(2), 275–284. https://doi.org/10.5194/BG-6-275-2009 | |
| dc.relation.referencesen | Schmidtlein, S., Feilhauer, H., & Bruelheide, H. (2012). Mapping plant strategy types using remote sensing. Journal of | |
| dc.relation.referencesen | Vegetation Science, 23(3), 395–405. https://doi.org/10.1111/J.1654-1103.2011.01370.X | |
| dc.relation.referencesen | Steenvoorden, J., Bartholomeus, H., & Limpens, J. (2023). Less is more: Optimizing vegetation mapping in peatlands | |
| dc.relation.referencesen | using unmanned aerial vehicles (UAVs). International Journal of Applied Earth Observation and Geoinformation,117, 103220. https://doi.org/10.1016/J.JAG.2023.103220 | |
| dc.relation.referencesen | Steenvoorden, J., & Limpens, J. (2023). Upscaling peatland mapping with drone-derived imagery: impact of spatial | |
| dc.relation.referencesen | resolution and vegetation characteristics. GIScience & Remote Sensing, 60(1). https://doi.org/10.1080/15481603.2023.2267851 | |
| dc.relation.referencesen | Stuart, M. B. , Davies, M. , Hobbs, M. J. , Mcgonigle, A. J. S. , Stuart, M. B., Davies, M., Hobbs, M. J., Mcgonigle, A. J. S., | |
| dc.relation.referencesen | & Willmott, J. R. (2022). Peatland Plant Spectral Response as a Proxy for Peat Health, Analysis Using Low-Cost | |
| dc.relation.referencesen | Hyperspectral Imaging Techniques. Remote Sensing 2022, Vol. 14, p. 3846, 14(16), 3846. https://doi.org/10.3390/RS14163846 | |
| dc.relation.referencesen | Torabi Haghighi, A., Menberu, M. W., Darabi, H., Akanegbu, J., & Kløve, B. (2018). Use of remote sensing to analyse | |
| dc.relation.referencesen | peatland changes after drainage for peat extraction. Land Degradation & Development, 29(10), 3479–3488. | |
| dc.relation.referencesen | https://doi.org/10.1002/LDR.3122 | |
| dc.relation.referencesen | White, L., Millard, K., Banks, S., Richardson, M., Pasher, J., & Duffe, J. (2017). Moving to the RADARSAT | |
| dc.relation.referencesen | Constellation Mission: Comparing Synthesized Compact Polarimetry and Dual Polarimetry Data with Fully | |
| dc.relation.referencesen | Polarimetric RADARSAT-2 Data for Image Classification of Peatlands. Remote Sensing 2017, Vol. 9, p. 573, 9(6),573. https://doi.org/10.3390/RS9060573 | |
| dc.relation.referencesen | Zhou, Z., Li, Z., Waldron, S., & Tanaka, A. (2019). InSAR Time Series Analysis of L-Band Data for Understanding | |
| dc.relation.referencesen | Tropical Peatland Degradation and Restoration. Remote Sensing 2019, Vol. 11, p. 2592, 11(21), 2592. | |
| dc.relation.referencesen | https://doi.org/10.3390/RS11212592 | |
| dc.relation.uri | https://doi.org/10.1016/J.SCITOTENV.2022.154294 | |
| dc.relation.uri | https://doi.org/10.1016/J.ECOLIND.2023.110665 | |
| dc.relation.uri | https://doi.org/10.1016/J.RSE.2018.07.021 | |
| dc.relation.uri | https://doi.org/10.1016/J.SCITOTENV.2018.12.327 | |
| dc.relation.uri | https://doi.org/10.1080/15481603.2023.2270791 | |
| dc.relation.uri | https://doi.org/10.1080/01431161.2023.2209916 | |
| dc.relation.uri | https://doi.org/10.1080/01431161.2019.1580825 | |
| dc.relation.uri | Https://Doi.Org/10.1139/Cjfr-2016-0192 | |
| dc.relation.uri | https://doi.org/10.1139/CJFR-2016-0192 | |
| dc.relation.uri | https://doi.org/10.1016/J.ISPRSJPRS.2014.01.010 | |
| dc.relation.uri | https://doi.org/10.1080/01431161003698310 | |
| dc.relation.uri | https://doi.org/10.3390/LAND11010024/S1 | |
| dc.relation.uri | https://doi.org/10.3390/rs9070748 | |
| dc.relation.uri | https://doi.org/https://doi.org/10.4060/ca8200en | |
| dc.relation.uri | https://doi.org/10.1016/J | |
| dc.relation.uri | https://doi.org/10.1127/1432-8364/2011/0076 | |
| dc.relation.uri | https://doi.org/10.1029/2023JG007403 | |
| dc.relation.uri | https://doi.org/10.1016/J.RSE.2015.01.029 | |
| dc.relation.uri | https://doi.org/10.1046/J.1365-2745.2000.00438.X | |
| dc.relation.uri | https://doi.org/10.1890/ES15-00232.1 | |
| dc.relation.uri | https://doi.org/10.1016/J.RSE.2015.08.012 | |
| dc.relation.uri | https://doi.org/10.1016/J.RSE.2019.111252 | |
| dc.relation.uri | https://doi.org/10.1111/JVS.12525 | |
| dc.relation.uri | https://doi.org/10.1111/AVSC.12024 | |
| dc.relation.uri | https://doi.org/10.1016/J.SCITOTENV.2017.09.103 | |
| dc.relation.uri | https://doi.org/10.1177/03091333221118353/ASSET/IMAGES/LARGE/10.1177_03091333221118353-FIG1.JPEG | |
| dc.relation.uri | https://doi.org/10.1080/0143116031000117065 | |
| dc.relation.uri | https://doi.org/10.3390/RS11141685 | |
| dc.relation.uri | https://doi.org/10.1109/JSTARS.2016.2621043 | |
| dc.relation.uri | https://doi.org/10.1016/J.RSE.2012.06.010 | |
| dc.relation.uri | https://doi.org/10.3390/RS12152465 | |
| dc.relation.uri | https://doi.org/10.1007/ | |
| dc.relation.uri | https://doi.org/10.1016/J.EARSCIREV.2019.05.014 | |
| dc.relation.uri | https://doi.org/10.1016/J.GLOPLACHA.2006.07.019 | |
| dc.relation.uri | https://doi.org/10.1080/15481603.2020.1829377 | |
| dc.relation.uri | https://doi.org/10.1111/JVS.12769 | |
| dc.relation.uri | https://doi.org/10.5194/BG-6-275-2009 | |
| dc.relation.uri | https://doi.org/10.1111/J.1654-1103.2011.01370.X | |
| dc.relation.uri | https://doi.org/10.1016/J.JAG.2023.103220 | |
| dc.relation.uri | https://doi.org/10.1080/15481603.2023.2267851 | |
| dc.relation.uri | https://doi.org/10.3390/RS14163846 | |
| dc.relation.uri | https://doi.org/10.1002/LDR.3122 | |
| dc.relation.uri | https://doi.org/10.3390/RS9060573 | |
| dc.relation.uri | https://doi.org/10.3390/RS11212592 | |
| dc.relation.uri | https://doi.org/10.1016/ | |
| dc.relation.uri | https://doi.org/10.1016/J.SCITOTENV | |
| dc.relation.uri | https://doi.org/10.1016/J.JNC.2012.02.001 | |
| dc.relation.uri | https://doi.org/10.1177/03091333221118353/ASSET/IMAGES | |
| dc.relation.uri | https://doi.org/10.1007/S10533-023-01084-1 | |
| dc.rights.holder | © Національний університет „Львівська політехніка“, 2025; © Західне геодезичне товариство, 2025 | |
| dc.subject | дистанційне зондування Землі | |
| dc.subject | ДЗЗ | |
| dc.subject | методи ДЗЗ | |
| dc.subject | дані ДЗЗ | |
| dc.subject | гіпер- та мультиспектральні дані | |
| dc.subject | радарні дані із синтезованою апертурою (SAR) | |
| dc.subject | дані LiDAR | |
| dc.subject | дані БПЛА | |
| dc.subject | картографування торфовищ | |
| dc.subject | моніторинг торфовищ | |
| dc.subject | аналіз ареалів торфовищ | |
| dc.subject | аналіз біорізноманіття торфовищ | |
| dc.subject | remote sensing | |
| dc.subject | remote sensing methods | |
| dc.subject | remote sensing data | |
| dc.subject | hyper- and multispectral data | |
| dc.subject | synthetic aperture radar (SAR) data | |
| dc.subject | LiDAR data | |
| dc.subject | UAV data | |
| dc.subject | peatland mapping | |
| dc.subject | peatland monitoring | |
| dc.subject | peatland habitat analysis | |
| dc.subject | peatland biodiversity analysis | |
| dc.subject.udc | 528.3 | |
| dc.title | Дослідження використання методів ДЗЗ для моніторингу та картографування торфовищ | |
| dc.title.alternative | Investigating the use of remote sensing methods for monitoring and mapping peatlands | |
| dc.type | Article |