Three decades of remote sensing analysis of forest decline related to climate change

a bibliometric study

Authors

DOI:

https://doi.org/10.18172/cig.5639

Keywords:

scientometrics, forest mortality, UAV, global warming, forest resources

Abstract

Climate change is predicted to lead to increasingly intense and hotter droughts, causing physiological weakness followed by forest decline in many regions of the world. Long- and short-range remote sensing (satellites and unmanned aerial vehicles, commonly called drones) can sense drought-induced changes in vegetation. Although several studies have addressed forest decline events, none have analyzed the forest decline attributable to climate change using remote sensing in a concise manner. A bibliometric analysis was carried out to characterize the scientific production reported in the Web of Science repository. The search descriptors were a combination of keywords related to forest decline and remote sensing. The results showed 278 articles published between 1989 and 2021 in 92 journals, with an average annual increase of 31%. A total of 29 nodes and 220 scientific collaboration links were located, mainly led by researchers from USA, Germany and China. Keyword analysis using World-TreeMap reflected the association of different key forest decline phenomena such as drought stress and climate change. Although the use of satellite information to study and understand forest decline has been reported for just over three decades, the most notable feature of the present research was the limited role of drones with only 5 studies. This reveals an area of opportunity to take advantage of the main strengths of drones, i.e., spatial and temporal resolution, low cost compared to manned flights, and centimeter accuracy. Therefore, it is strongly recommended to increase studies to improve the use of multispectral sensors, thermal and LiDAR technology for long-term monitoring of forest decline related to climate change.

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References

Afuye, G.A., Kalumba, A.M., Busayo, E.T., Orimoloye, I. R., 2022. A bibliometric review of vegetation response to climate change. Environmental Science and Pollution Research 29(13), 18578-18590. https://doi.org/10.1007/s11356-021-16319-7

Allen, C.D., Breshears, D.D., McDowell, N.G., 2015. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere 6(8). https://doi.org/10.1890/ES15-00203.1

Allen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.H. (Ted), Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J.-H., Allard, G., Running, S. W., Semerci, A., Cobb, N., 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecology and Management 259(4), 660-684. https://doi.org/10.1016/j.foreco.2009.09.001

Anderegg, W.R.L., Anderegg, L.D.L., 2013. Hydraulic and carbohydrate changes in experimental drought-induced mortality of saplings in two conifer species. Tree Physiology 33(3), 252-260. https://doi.org/10.1093/treephys/tpt016

Anderegg, W.R.L., Martinez-Vilalta, J., Cailleret, M., Camarero, J.J., Ewers, B.E., Galbraith, D., Gessler, A., Grote, R., Huang, C., Levick, S.R., Powell, T.L., Rowland, L., Sánchez-Salguero, R., Trotsiuk, V., 2016. When a Tree Dies in the Forest: Scaling Climate-Driven Tree Mortality to Ecosystem Water and Carbon Fluxes. Ecosystems 19(6), 1133-1147. https://doi.org/10.1007/s10021-016-9982-1

Anderson, L.O., Malhi, Y., Aragão, L.E., Ladle, R., Arai, E., Barbier, N., Phillips, O., 2010. Remote sensing detection of droughts in Amazonian Forest canopies. New Phytologist 187(3), 733-750. https://doi.org/10.1111/j.1469-8137.2010.03355.x

Aria, M., Cuccurullo, C., 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007

Baeza, A., Martin, R.E., Stephenson, N.L., Das, A.J., Hardwick, P., Nydick, K., Mallory, J., Slaton, M., Evans, K., Asner, G.P., 2021. Mapping the vulnerability of giant sequoias after extreme drought in California using remote sensing. Ecological Applications 31(7), e02395. https://doi.org/10.1002/eap.2395

Belter, C.W., 2015. Bibliometric indicators: opportunities and limits. Journal of the Medical Library Association 103(4), 219-221. https://doi.org/10.3163/1536-5050.103.4.014

Beniston, M., 2003. Climatic Change in Mountain Regions: A Review of Possible Impacts. Climatic Change 59(1), 5-31. https://doi.org/10.1023/A:1024458411589

Breidenich, C., Magraw, D., Rowley, A., Rubin, J. W., 1998. The Kyoto Protocol to the United Nations Framework Convention on Climate Change. American Journal of International Law 92(2), 315-331. https://doi.org/10.2307/2998044

Bright, B.C., Hicke, J.A., Hudak, A.T., 2012. Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery. Remote Sensing of Environment 124, 270-281. https://doi.org/10.1016/j.rse.2012.05.016

Bright, B.C., Hudak, A.T., Meddens, A.J.H., Egan, J.M., Jorgensen, C.L., 2020. Mapping Multiple Insect Outbreaks across Large Regions Annually Using Landsat Time Series Data. Remote Sensing 12(10). https://doi.org/10.3390/rs12101655

Brovkina, O., Cienciala, E., Surový, P., Janata, P., 2018. Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands. Geo-Spatial Information Science 21(1), 12-20. https://doi.org/10.1080/10095020.2017.1416994

Chambers, J.Q., Magnabosco, M.D., Alan, D.V., Joerg, T., Dar, R., Niro, H., 2013. The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape. Proceedings of the National Academy of Sciences 110(10), 3949-3954. https://doi.org/10.1073/pnas.1202894110

Choat, B., Brodribb, T.J., Brodersen, C.R., Duursma, R.A., López, R., Medlyn, B.E., 2018. Triggers of tree mortality under drought. Nature 558(7711), 531-539. https://doi.org/10.1038/s41586-018-0240-x

Cohen, W.B., Yang, Z., Stehman, S., Schroeder, T.A., Bell, D.M., Masek, J.G., Huang, C., Meigs, G.W., 2016. Forest disturbance across the conterminous United States from 1985-2012: The emerging dominance of forest decline. Forest Ecology and Management 360, 242-252. https://doi.org/10.1016/j.foreco.2015.10.042

Collins, J.B., Woodcock, C.E., 1996. An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data. Remote Sensing of Environment 56(1), 66-77. https://doi.org/10.1016/0034-4257(95)00233-2

Colomina, I., Molina, P., 2014. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing 92, 79-97. https://doi.org/10.1016/j.isprsjprs.2014.02.013

Dainelli, R., Toscano, P., di Gennaro, S.F., Matese, A., 2021. Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework. Forests 12(3). https://doi.org/10.3390/f12030327

Dash, J.P., Pearse, G.D., Watt, M.S., 2018. UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health. Remote Sensing 10(8). https://doi.org/10.3390/rs10081216

Dash, J.P., Watt, M.S., Pearse, G.D., Heaphy, M., Dungey, H.S., 2017. Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak. ISPRS Journal of Photogrammetry and Remote Sensing 131, 1-14. https://doi.org/10.1016/j.isprsjprs.2017.07.007

Ellegaard, O., Wallin, J. A., 2015. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics 105(3), 1809-1831. https://doi.org/10.1007/s11192-015-1645-z

Fort, M., 2015. Impact of climate change on mountain environment dynamics: An introduction. Journal of Alpine Research 103, 2-7. https://doi.org/10.4000/rga.2877

Furniss, T.J., Kane, V.R., Larson, A.J., Lutz, J.A., 2020. Detecting tree mortality with Landsat-derived spectral indices: Improving ecological accuracy by examining uncertainty. Remote Sensing of Environment 237, 111497. https://doi.org/10.1016/j.rse.2019.111497

Gallardo-Salazar, J.L., Carrillo-Aguilar, D.M., Pompa-García, M., Aguirre-Salado, C.A., 2021. Multispectral indices and individual-tree level attributes explain forest productivity in a pine clonal orchard of Northern Mexico. Geocarto International 1-13. https://doi.org/10.1080/10106049.2021.1886341

Gallardo-Salazar, J.L., Pompa-García, M., Aguirre-Salado, C., López-Serrano, P., Meléndez-Soto, A. 2020. Drones: technology with a promising future in forest management. Revista Mexicana de Ciencias Forestales 11(61). https://doi.org/10.29298/rmcf.v11i61.794

Gheitury, M., Heshmati, M., Noroozi, A., Ahmadi, M., Parvizi, Y., 2020. Monitoring mortality in a semiarid forest under the influence of prolonged drought in Zagros region. International Journal of Environmental Science and Technology 17(11), 4589-4600. https://doi.org/10.1007/s13762-020-02638-8

Glänzel, W., 2001. National characteristics in international scientific co-authorship relations. Scientometrics 51(1), 69-115. https://doi.org/10.1023/A:1010512628145

Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202, 18-27. https://doi.org/10.1016/j.rse.2017.06.031

Guada, G., Camarero, J.J., Sánchez-Salguero, R., Cerrillo, R.M.N., 2016. Limited Growth Recovery after Drought-Induced Forest Dieback in Very Defoliated Trees of Two Pine Species. Frontiers in Plant Science 7. https://doi.org/10.3389/fpls.2016.00418

Hajek, P., Link, R.M., Nock, C.A., Bauhus, J., Gebauer, T., Gessler, A., Kovach, K., Messier, C., Paquette, A., Saurer, M., Scherer-Lorenzen, M., Rose, L., Schuldt, B., 2022. Mutually inclusive mechanisms of drought-induced tree mortality. Global Change Biology 28(10), 3365-3378. https://doi.org/10.1111/gcb.16146

Hammond, W.M., Williams, A.P., Abatzoglou, J.T., Adams, H.D., Klein, T., López, R., Sáenz-Romero, C., Hartmann, H., Breshears, D. D., Allen, C.D., 2022. Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests. Nature Communications 13(1), 1761. https://doi.org/10.1038/s41467-022-29289-2

Hernández-Clemente, R., Navarro-Cerrillo, R. M., Suárez, L., Morales, F., Zarco-Tejada, P.J., 2011. Assessing structural effects on PRI for stress detection in conifer forests. Remote Sensing of Environment 115(9), 2360-2375. https://doi.org/10.1016/j.rse.2011.04.036

Hicke, J.A., Logan, J., 2009. Mapping whitebark pine mortality caused by a mountain pine beetle outbreak with high spatial resolution satellite imagery. International Journal of Remote Sensing 30(17), 4427-4441. https://doi.org/10.1080/01431160802566439

Hirsch, J.E. 2005. An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences 102(46), 16569-16572. https://doi.org/10.1073/pnas.0507655102

Homer, C., Dewitz, J., Jin, S., Xian, G., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., Stehman, S., Auch, R., Riitters, K., 2020. Conterminous United States land cover change patterns 2001-2016 from the 2016 National Land Cover Database. ISPRS Journal of Photogrammetry and Remote Sensing 162, 184-199. https://doi.org/10.1016/j.isprsjprs.2020.02.019

Hood, W. W., Wilson, C.S., 2001. The Literature of Bibliometrics, Scientometrics, and Informetrics. Scientometrics 52(2), 291. https://doi.org/10.1023/A:1017919924342

Huang, C., Anderegg, W.R.L., 2012. Large drought-induced aboveground live biomass losses in southern Rocky Mountain aspen forests. Global Change Biology 18(3), 1016-1027. https://doi.org/10.1111/j.1365-2486.2011.02592.x

Huang, C., Anderegg, W.R.L., Asner, G.P., 2019. Remote sensing of forest die-off in the Anthropocene: From plant ecophysiology to canopy structure. Remote Sensing of Environment 231, 111233. https://doi.org/10.1016/j.rse.2019.111233

Huang, C., Asner, G.P., Barger, N.N., Neff, J.C., Floyd, M.L., 2010. Regional aboveground live carbon losses due to drought-induced tree dieback in piñon-juniper ecosystems. Remote Sensing of Environment 114(7), 1471-1479. https://doi.org/10.1016/j.rse.2010.02.003

Huang, S., Tang, L., Hupy, J.P., Wang, Y., Shao, G., 2021. A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forestry Research 32(1), 1-6. https://doi.org/10.1007/s11676-020-01155-1

Iglhaut, J., Cabo, C., Puliti, S., Piermattei, L., O’Connor, J., Rosette, J., 2019. Structure from Motion Photogrammetry in Forestry: a Review. Current Forestry Reports 5(3), 155-168. https://doi.org/10.1007/s40725-019-00094-3

Jay, L., Josue, M.-A., John, D., Kathleen, S., 2018. Lessons from California’s 2012-2016 Drought. Journal of Water Resources Planning and Management 144(10), 04018067. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000984

Jiao, W., Wang, L., McCabe, M.F., 2021. Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future. Remote Sensing of Environment 256, 112313. https://doi.org/10.1016/j.rse.2021.112313

Justice, C.O., Townshend, J.R.G., Vermote, E.F., Masuoka, E., Wolfe, R.E., Saleous, N., Roy, D.P., Morisette, J.T., 2002. An overview of MODIS Land data processing and product status. Remote Sensing of Environment 83(1), 3-15. https://doi.org/10.1016/S0034-4257(02)00084-6

Klein, T., Torres-Ruiz, J.M., Albers, J.J., 2022. Conifer desiccation in the 2021 NW heatwave confirms the role of hydraulic damage. Tree Physiology 42(4), 722-726. https://doi.org/10.1093/treephys/tpac007

Lenssen, N.J.L., Schmidt, G.A., Hansen, J.E., Menne, M.J., Persin, A., Ruedy, R., Zyss, D., 2019. Improvements in the GISTEMP Uncertainty Model. Journal of Geophysical Research: Atmospheres 124(12), 6307-6326. https://doi.org/10.1029/2018JD029522

Li, K., Rollins, J., Yan, E., 2018a. Web of Science use in published research and review papers 1997-2017: a selective, dynamic, cross-domain, content-based analysis. Scientometrics 115(1), 1-20. https://doi.org/10.1007/s11192-017-2622-5

Li, Y., Flowerdew, J., Cargill, M., 2018b. Teaching English for Research Publication Purposes to science students in China: A case study of an experienced teacher in the classroom. Journal of English for Academic Purposes 35, 116-129. https://doi.org/10.1016/j.jeap.2018.07.006

Lin, Q., Huang, H., Wang, J., Huang, K., Liu, Y., 2019. Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar. In Remote Sensing (Vol. 11, Issue 21). https://doi.org/10.3390/rs11212540

Liu, L., Wang, Z., Wang, Y., Zhang, Y., Shen, J., Qin, D., Li, S., 2019. Trade-off analyses of multiple mountain ecosystem services along elevation, vegetation cover and precipitation gradients: A case study in the Taihang Mountains. Ecological Indicators 103, 94-104. https://doi.org/10.1016/j.ecolind.2019.03.034

Lu, R., Du, Y., Yan, L., Xia, J., 2019. A methodological review on identification of tree mortality and their applications. Chinese Science Bulletin 64, 2395-2409. https://doi.org/10.1360/N972019-00199

Martin, R.E., Asner, G.P., Francis, E., Ambrose, A., Baxter, W., Das, A.J., Vaughn, N.R., Paz-Kagan, T., Dawson, T., Nydick, K., Stephenson, N.L., 2018. Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought. Forest Ecology and Management 419-420, 279-290. https://doi.org/10.1016/j.foreco.2017.12.002

McDowell, N., Pockman, W.T., Allen, C.D., Breshears, D.D., Cobb, N., Kolb, T., Plaut, J., Sperry, J., West, A., Williams, D.G., Yepez, E. A., 2008. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytologist 178(4), 719-739. https://doi.org/10.1111/j.1469-8137.2008.02436.x

Meddens, A.J.H., Hicke, J.A., Vierling, L.A., Hudak, A.T., 2013. Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery. Remote Sensing of Environment 132, 49-58. https://doi.org/10.1016/j.rse.2013.01.002

Meigs, G.W., Kennedy, R.E., Cohen, W.B., 2011. A Landsat time series approach to characterize bark beetle and defoliator impacts on tree mortality and surface fuels in conifer forests. Remote Sensing of Environment 115(12), 3707-3718. https://doi.org/10.1016/j.rse.2011.09.009

Michaelian, M., Hogg, E.H., Hall, R.J., Arsenault, E., 2011. Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest. Global Change Biology 17(6), 2084-2094. https://doi.org/10.1111/j.1365-2486.2010.02357.x

Naud, L., Måsviken, J., Freire, S., Angerbjörn, A., Dalén, L., Dalerum, F. 2019. Altitude effects on spatial components of vascular plant diversity in a subarctic mountain tundra. Ecology and Evolution 9(8), 4783-4795. https://doi.org/10.1002/ece3.5081

Nydick, K.R., Stephenson, N.L., Ambrose, A.R., Asner, G.P., Baxter, W.L., Das, A.J., Dawson, T., Martin, R.E., Paz-Kagan, T., 2018. Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section. Forest Ecology and Management 419-420, 249-256. https://doi.org/10.1016/j.foreco.2018.03.028

OECD. (2022, May 12). Gross domestic spending on R&D (indicator). https://doi.org/10.1787/d8b068b4-en

Ogaya, R., Liu, D., Barbeta, A., Peñuelas, J., 2020. Stem Mortality and Forest Dieback in a 20-Years Experimental Drought in a Mediterranean Holm Oak Forest. Frontiers in Forests and Global Change 2. https://doi.org/10.3389/ffgc.2019.00089

Patience, G.S., Patience, C.A., Blais, B., Bertrand, F., 2017. Citation analysis of scientific categories. Heliyon 3(5), e00300. https://doi.org/10.1016/j.heliyon.2017.e00300

Peng, H., Jia, Y., Zhan, C., Xu, W., 2020. Topographic controls on ecosystem evapotranspiration and net primary productivity under climate warming in the Taihang Mountains, China. Journal of Hydrology 581, 124394. https://doi.org/10.1016/j.jhydrol.2019.124394

Pörtner, H.O., Roberts, D.C., Adams, H., Adler, C., Aldunce, P., Ali, E., Ara Begum, R., Betts, R., Bezner Kerr, R., Biesbroek, R., Birkmann, J., Bowen, K., Castellanos, E., Cissé, G., Constable, A., Cramer, W., Dodman, D., Eriksen, S.H., Fischlin, A., … Zaiton Ibrahim, Z. 2022. Climate change 2022: impacts, adaptation, and vulnerability. IPCC. https://edepot.wur.nl/565644

Pranckutė, R., 2021. Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World. Publications 9(1). https://doi.org/10.3390/publications9010012

Queiroz, M.M., Ivanov, D., Dolgui, A., Fosso Wamba, S., 2020. Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of Operations Research 319, 1159-1196. https://doi.org/10.1007/s10479-020-03685-7

Ripple, W.J., Wolf, C., Newsome, T.M., Barnard, P., Moomaw, W.R., 2020. World Scientists’ Warning of a Climate Emergency. BioScience 70(1), 8-12. https://doi.org/10.1093/biosci/biz088

RStudio (2022). RStudio: Integrated Development for R. http://www.rstudio.com/

Sáenz-Romero, C., Mendoza-Maya, E., Gómez-Pineda, E., Blanco-García, A., Endara-Agramont, A.R., Lindig-Cisneros, R., López-Upton, J., Trejo-Ramírez, O., Wehenkel, C., Cibrián-Tovar, D., Flores-López, C., Plascencia-González, A., Vargas-Hernández, J.J., 2020. Recent evidence of Mexican temperate forest decline and the need for ex situ conservation, assisted migration, and translocation of species ensembles as adaptive management to face projected climatic change impacts in a megadiverse country. Canadian Journal of Forest Research 50(9), 843-854. https://doi.org/10.1139/cjfr-2019-0329

Stereńczak, K., Mielcarek, M., Kamińska, A., Kraszewski, B., Piasecka, Ż., Miścicki, S., Heurich, M., 2020. Influence of selected habitat and stand factors on bark beetle Ips typographus (L.) outbreak in the Białowieża Forest. Forest Ecology and Management 459, 117826. https://doi.org/10.1016/j.foreco.2019.117826

Stevens, M., 2016. 102 million dead California trees ‘unprecedented in our modern history,’officials say. Los Angeles Times. https://doi.org/http://www.latimes.com/local/lanow/la-me-dead-trees-20161118-story.html

Verma, P., Ghosh, P.K., 2022. The economics of Forest Carbon Sequestration: A Bibliometric Analysis. Research Square. https://doi.org/10.21203/rs.3.rs-1236338/v1

Williams P, Allen C.D., Macalady A.K., 2013. Temperature as a potent driver of regional forest drought stress and tree mortality. Nature Climate Change 3, 292-297. https://doi.org/10.1038/nclimate1693

Wu, X., Liu, H., Li, X., Liang, E., Beck, P.S.A., Huang, Y., 2016. Seasonal divergence in the interannual responses of Northern Hemisphere vegetation activity to variations in diurnal climate. Scientific Reports 6(1), 19000. https://doi.org/10.1038/srep19000

Wulder, M.A., Loveland, T.R., Roy, D. P., Crawford, C.J., Masek, J.G., Woodcock, C.E., Allen, R. G., Anderson, M.C., Belward, A.S., Cohen, W.B., Dwyer, J., Erb, A., Gao, F., Griffiths, P., Helder, D., Hermosilla, T., Hipple, J.D., Hostert, P., Hughes, M.J., Huntington, J., Zhu, Z., 2019. Current status of Landsat program, science, and applications. Remote Sensing of Environment 225, 127-147. https://doi.org/10.1016/j.rse.2019.02.015

Yao, H., Qin, R., Chen, X., 2019. Unmanned Aerial Vehicle for Remote Sensing Applications—A Review. Remote Sensing 11(12). https://doi.org/10.3390/rs11121443

Youn, B.Y., Song, H.J., Yang, K., Cheon, C., Ko, Y., Jang, B.H., Shin, Y.C., Ko, S.G., 2021. Bibliometric Analysis of Integrative Medicine Studies from 2000 to 2019. The American Journal of Chinese Medicine 49(04), 829-841. https://doi.org/10.1142/S0192415X21500397

Zhu, Z., 2017. Change detection using Landsat time series: A review of frequencies, preprocessing, algorithms, and applications. ISPRS Journal of Photogrammetry and Remote Sensing 130, 370-384. https://doi.org/10.1016/j.isprsjprs.2017.06.013

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04-05-2023

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Gallardo-Salazar JL, Sáenz-Romero C, Lindig-Cisneros R, López-Toledo L, Blanco-García JA, Endara-Agramont Ángel R. Three decades of remote sensing analysis of forest decline related to climate change: a bibliometric study. CIG [Internet]. 2023 May 4 [cited 2024 Apr. 24];49(1):69-87. Available from: https://publicaciones.unirioja.es/ojs/index.php/cig/article/view/5639

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