{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:50:12Z","timestamp":1774633812421,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:00:00Z","timestamp":1666051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing data comprise a valuable information source for many ecological landscape studies that may be under-utilized because of an overwhelming amount of processing methods and derived variables. These complexities, combined with a scarcity of quality control studies, make the selection of appropriate remote sensed variables challenging. Quality control studies are necessary to evaluate the predictive power of remote sensing data and also to develop parsimonious models underpinned by functional variables, i.e., cause rather than solely correlation. Cause-based models yield superior model transferability across different landscapes and ecological settings. We propose two basic guidelines for conducting such quality control studies that increase transferability and predictive power. The first is to favor predictors that are causally related to the response. The second is to include additional variables controlling variation in the property of interest and testing for optimum processing method and\/or scale. Here, we evaluated these principles in predicting ground vegetation cover, soil moisture and pH under challenging conditions with forest canopies hindering direct remote sensing of the ground. Our model using lidar data combined with natural resource maps explained most of the observed variation in soil pH and moisture, and somewhat less variation of ground vegetation cover. Soil pH was best predicted by topographic position, sediment type and site index (R2 = 0.90). Soil moisture was best predicted by topographic position, radiation load, sediment type and site index (R2 = 0.83). The best model for predicting ground vegetation cover was a combination of lidar-based estimates for light availability below canopy and forest type, including an interaction between these two variables (R2 = 0.65).<\/jats:p>","DOI":"10.3390\/rs14205207","type":"journal-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T00:58:51Z","timestamp":1666141131000},"page":"5207","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Predicting Habitat Properties Using Remote Sensing Data: Soil pH and Moisture, and Ground Vegetation Cover"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6335-2546","authenticated-orcid":false,"given":"Hanne","family":"Haugen","sequence":"first","affiliation":[{"name":"Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, 2480 Koppang, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7625-2816","authenticated-orcid":false,"given":"Olivier","family":"Devineau","sequence":"additional","affiliation":[{"name":"Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, 2480 Koppang, Norway"}]},{"given":"Jan","family":"Heggenes","sequence":"additional","affiliation":[{"name":"Department of Natural Sciences and Environmental Health, University of South-Eastern Norway, 3800 B\u00f8, Norway"}]},{"given":"Kjartan","family":"\u00d8stbye","sequence":"additional","affiliation":[{"name":"Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, 2480 Koppang, Norway"},{"name":"Department of Biosciences, Center for Ecological and Evolutionary Synthesis (CEES), University of Oslo, 0316 Oslo, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2698-651X","authenticated-orcid":false,"given":"Arne","family":"Linl\u00f8kken","sequence":"additional","affiliation":[{"name":"Department of Forestry and Wildlife Management, Inland Norway University of Applied Sciences, 2480 Koppang, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chuvieco, E. (2020). Fundamentals of Satellite Remote Sensing: An Environmental Approach, CRC Press. [3rd ed.].","DOI":"10.1201\/9780429506482"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"111626","DOI":"10.1016\/j.rse.2019.111626","article-title":"Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models","volume":"239","author":"Randin","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.ecolind.2015.01.007","article-title":"Remote sensing of ecosystem services: A systematic review","volume":"52","author":"Atkinson","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_4","first-page":"58","article-title":"On the use of Sentinel-2 for coastal habitat mapping and satellite-derived bathymetry estimation using downscaled coastal aerosol band","volume":"80","author":"Poursanidis","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2014.09.025","article-title":"The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps","volume":"156","author":"Ackers","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1111\/j.2041-210X.2011.00170.x","article-title":"Assessing transferability of ecological models: An underappreciated aspect of statistical validation","volume":"3","author":"Wenger","year":"2012","journal-title":"Methods Ecol. Evol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1007\/s11368-016-1573-4","article-title":"Topography-soil relationships in a hilly evergreen broadleaf forest in subtropical China","volume":"17","author":"Li","year":"2016","journal-title":"J. Soils Sediments"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"115280","DOI":"10.1016\/j.geoderma.2021.115280","article-title":"Use of multiple LIDAR-derived digital terrain indices and machine learning for high-resolution national-scale soil moisture mapping of the Swedish forest landscape","volume":"404","author":"Aagren","year":"2021","journal-title":"Geoderma"},{"key":"ref_9","first-page":"154","article-title":"Linking the depth-to-water topographic index to soil moisture on boreal forest sites in Alberta","volume":"62","author":"Oltean","year":"2016","journal-title":"For. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.rse.2014.01.028","article-title":"Subcanopy Solar Radiation model: Predicting solar radiation across a heavily vegetated landscape using LiDAR and GIS solar radiation models","volume":"154","author":"Bode","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9149","DOI":"10.1002\/ece3.5462","article-title":"Estimating below-canopy light regimes using airborne laser scanning: An application to plant community analysis","volume":"9","author":"Zellweger","year":"2019","journal-title":"Ecol. Evol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1002\/2016GL068189","article-title":"Demonstrating soil moisture remote sensing with observations from the UK TechDemoSat-1 satellite mission","volume":"43","author":"Chew","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1111\/j.1365-2664.2004.00875.x","article-title":"Capercaillie breeding success in relation to forest habitat and predator abundance","volume":"41","author":"Baines","year":"2004","journal-title":"J. Appl. Ecol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"669784","DOI":"10.3389\/fmicb.2021.669784","article-title":"Habitat, Snow-Cover and Soil pH, Affect the Distribution and Diversity of Mortierellaceae Species and Their Associations to Bacteria","volume":"12","author":"Telagathoti","year":"2021","journal-title":"Front. Microbiol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1007\/s11368-015-1070-1","article-title":"Soil pH determines the alpha diversity but not beta diversity of soil fungal community along altitude in a typical Tibetan forest ecosystem","volume":"15","author":"Wang","year":"2015","journal-title":"J. Soils Sediments"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/femsec\/fiv148","article-title":"Soil moisture and chemistry influence diversity of ectomycorrhizal fungal communities associating with willow along an hydrologic gradient","volume":"92","author":"Erlandson","year":"2016","journal-title":"FEMS Microbiol. Ecol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1890\/1540-9295(2005)003[0421:UVAAFE]2.0.CO;2","article-title":"Understory Vegetation as a Forest Ecosystem Driver: Evidence from the Northern Swedish Boreal Forest","volume":"3","author":"Nilsson","year":"2005","journal-title":"Front. Ecol. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4892","DOI":"10.1038\/s41467-020-18631-1","article-title":"Soil moisture dominates dryness stress on ecosystem production globally","volume":"11","author":"Liu","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.1016\/j.scitotenv.2016.04.004","article-title":"Spatial patterns and environmental constraints on ecosystem services at a catchment scale","volume":"572","author":"Emmett","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_20","unstructured":"Weil, R.R., Brady, N.C., and Weil, R.R. (2017). The Nature and Properties of Soils, Pearson. [5th ed.]."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.geoderma.2007.05.013","article-title":"Topographical influences on soil properties in boreal forests","volume":"141","author":"Seibert","year":"2007","journal-title":"Geoderma"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.foreco.2007.09.038","article-title":"Influence of tree species on understory vegetation diversity and mechanisms involved\u2014A critical review for temperate and boreal forests","volume":"254","author":"Barbier","year":"2008","journal-title":"For. Ecol. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1111\/brv.12119","article-title":"Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests: Spermatophytes and forest functioning","volume":"90","author":"Augusto","year":"2015","journal-title":"Biol. Rev. Camb. Philos. Soc."},{"key":"ref_24","unstructured":"Amaro, A., Reed, D., and Soares, P. (2003). Modelling Forest Systems, CABI."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1139\/X10-203","article-title":"Site index of Sitka spruce (Picea sitchensis) in relation to different measures of site quality in Ireland","volume":"41","author":"Farrelly","year":"2011","journal-title":"Rev. Can. De Rech. For."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5794869","DOI":"10.1155\/2019\/5794869","article-title":"The Role of Soil pH in Plant Nutrition and Soil Remediation","volume":"2019","author":"Neina","year":"2019","journal-title":"Appl. Environ. Soil Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1146\/annurev.earth.30.091201.140434","article-title":"SCALING OF SOIL MOISTURE: A Hydrologic Perspective","volume":"30","author":"Western","year":"2002","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_28","unstructured":"Oke, T.R. (1987). Boundary Layer Climates, Routledge. [2nd ed.]."},{"key":"ref_29","unstructured":"Lid, J., Lid, D.T., Elven, R., and Alm, T. (2005). Norsk Flora, Samlaget. [7th ed.]."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1080\/07352680600819286","article-title":"Understory Vegetation Dynamics of North American Boreal Forests","volume":"25","author":"Hart","year":"2006","journal-title":"Crit. Rev. Plant Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1093\/jpe\/rtr005","article-title":"Ecohydrological advances and applications in plant-water relations research: A review","volume":"4","author":"Asbjornsen","year":"2011","journal-title":"Plant Ecol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1005987807596","article-title":"Plant-soil interactions in temperate grasslands","volume":"42","author":"Burke","year":"1998","journal-title":"Biogeochemistry"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1111\/j.1061-2971.2004.0325.x","article-title":"Factors Controlling Vegetation Establishment and Water Erosion on Motorway Slopes in Valencia, Spain","volume":"12","author":"Bochet","year":"2004","journal-title":"Restor. Ecol."},{"key":"ref_34","unstructured":"(2022, January 14). Natur i Norge. Available online: https:\/\/artsdatabanken.no\/NiN."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1111\/geb.13164","article-title":"Towards a systematics of ecodiversity: The EcoSyst framework","volume":"29","author":"Halvorsen","year":"2020","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_36","unstructured":"Ellenberg, H., and Leuschner, C. (2010). Vegetation Mitteleuropas mit den Alpen, Ulmer Verlag."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Best, E.P.H., and Haeck, J. (1983). Principles of Bio-Indication. Ecological Indicators for the Assessment of the Quality of Air, Water, Soil, and Ecosystems, Springer.","DOI":"10.1007\/978-94-009-6322-1"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1007\/s11258-012-0056-y","article-title":"Microtopographic heterogeneity constrains alpine plant diversity, Glacier National Park, MT","volume":"213","author":"Rose","year":"2012","journal-title":"Plant Ecol."},{"key":"ref_39","unstructured":"Kartverket (2017). NDH Lifjell-M\u00e6lefjellSauherad-Notodden 2 pkt 2017, Kartverket."},{"key":"ref_40","unstructured":"Kartverket (2022, June 03). NDH Notodden-SauheradHjartdal 5pkt 2017, Available online: https:\/\/hoydedata.no\/LaserInnsyn2\/."},{"key":"ref_41","unstructured":"Kartverket (2022, June 03). NDH Lier-R\u00f8yken-HurumSvelvik 5 pkt 2017, Available online: https:\/\/hoydedata.no\/LaserInnsyn2\/."},{"key":"ref_42","unstructured":"Boehner, J., and Conrad, O. (2022, May 05). SAGA-GIS Module Library Documentation (v2.2.2). Available online: https:\/\/saga-gis.sourceforge.io\/saga_tool_doc\/2.2.2\/ta_hydrology_15.html."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/S0734-189X(84)80011-0","article-title":"The extraction of drainage networks from digital elevation data","volume":"28","author":"Mark","year":"1984","journal-title":"Comput. Vis. Graph. Image Processing"},{"key":"ref_44","unstructured":"Gallant, J.C., and Wilson, J.P. (2000). Terrain Analysis: Principles and Applications, Wiley."},{"key":"ref_45","first-page":"13","article-title":"Spatial prediction of soil attributes using terrain analysis and climate regionalisation","volume":"115","author":"Boehner","year":"2006","journal-title":"Goettinger Geogr. Abh."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1672\/0277-5212(2007)27[846:MWACOT]2.0.CO;2","article-title":"Mapping Wetlands: A Comparison of Two Different Approaches for New Brunswick, Canada","volume":"27","author":"Murphy","year":"2007","journal-title":"Wetl. (Wilmington N.C.)"},{"key":"ref_47","unstructured":"Weiss, A.D. (2001). Topographic Position and Landforms Analysis, The Nature Conservancy."},{"key":"ref_48","unstructured":"ESRI (2022, June 01). Area Solar Radiation (Spatial Analyst). Available online: https:\/\/desktop.arcgis.com\/en\/arcmap\/latest\/tools\/spatial-analyst-toolbox\/area-solar-radiation.htm."},{"key":"ref_49","unstructured":"NGU (2016). Produktark: L\u00f8smasser N50\/N250, NGU."},{"key":"ref_50","unstructured":"Heldal, T., and Torgersen, E. (2020). Milj\u00f8variabel Kalkinnhold i Berggrunn: Metode for \u00e5 Etablere Nasjonale Dataset, Norges Geologiske Unders\u00f8kelser (NGU)."},{"key":"ref_51","unstructured":"NIBIO (2019). AR5 Klassifikasjonssystem: Klassifisering av Arealressurser, NIBIO."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.rse.2013.09.006","article-title":"Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data","volume":"140","author":"Dalponte","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.geoderma.2012.09.009","article-title":"The utility of remotely-sensed vegetative and terrain covariates at different spatial resolutions in modelling soil and watertable depth (for digital soil mapping)","volume":"193\u2013194","author":"Taylor","year":"2013","journal-title":"Geoderma"},{"key":"ref_54","first-page":"1","article-title":"R_Core_Team. nlme: Linear and Nonlinear Mixed Effects Models","volume":"3","author":"Pinheiro","year":"2022","journal-title":"R Package Version"},{"key":"ref_55","unstructured":"Harrell, F.E. (2022). Package \u2018Rms\u2019, Vanderbilt University."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Venables, W.N., and Ripley, B.D. (2002). Modern Applied Statistics with S, Springer Science & Business Media.","DOI":"10.1007\/978-0-387-21706-2"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.2307\/2532457","article-title":"Assessing proportionality in the proportional odds model for ordinal logistic regression","volume":"46","author":"Brant","year":"1990","journal-title":"Biometrics"},{"key":"ref_58","first-page":"1","article-title":"Beta Regression in R","volume":"34","author":"Francisco","year":"2010","journal-title":"J. Stat. Softw."},{"key":"ref_59","unstructured":"R Core Team (2021). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_60","unstructured":"Barton, K. (2022, January 14). Mu-MIn: Multi-model inference. Available online: https:\/\/www.scirp.org\/(S(i43dyn45teexjx455qlt3d2q))\/reference\/ReferencesPapers.aspx?ReferenceID=753578."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1093\/bioinformatics\/bty633","article-title":"ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R","volume":"35","author":"Paradis","year":"2019","journal-title":"Bioinformatics"},{"key":"ref_62","unstructured":"Hartig, F., and Lohse, L. (2022). DHARMa: Residual Diagnostics for Hierarchical (Multi-Level\/Mixed) Regression Models."},{"key":"ref_63","unstructured":"Greenwell, B., McCarthy, A., Boehmke, B., and Liu, D. (2022, January 14). sure: Surrogate Residuals for Ordinal and General Regression Models. Available online: https:\/\/cran.r-project.org\/web\/packages\/DHARMa\/vignettes\/DHARMa.html."},{"key":"ref_64","unstructured":"L\u00fcdecke, D. (2021). sjPlot: Data Visualization for Statistics in Social Science. R Package, 1308357."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1080\/11956860.2004.11682828","article-title":"Soil parent material may control forest floor properties more than stand type or stand age in mixedwood boreal forests","volume":"11","author":"Lamarche","year":"2004","journal-title":"\u00c9coscience (St. -Foy)"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/0169-1317(90)90018-K","article-title":"The pH of clay suspensions in the field and laboratory, and methods of measurement of their pH","volume":"5","author":"Keller","year":"1990","journal-title":"Appl. Clay Sci."},{"key":"ref_67","unstructured":"J\u00f8rgensen, P., S\u00f8rensen, R., and Haldorsen, S. (1997). Kvart\u00e6rgeologi, Landbruksforl.. [2nd ed.]."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.catena.2016.01.020","article-title":"Effect of parent material on soil acidity and carbon content in soils under silver fir (Abies alba Mill.) stands in Poland","volume":"140","author":"Gruba","year":"2016","journal-title":"Catena (Giess.)"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1002\/esp.4301","article-title":"Modelling soil moisture in a high-latitude landscape using LiDAR and soil data","volume":"43","author":"Kemppinen","year":"2018","journal-title":"Earth Surf. Processes Landf."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Zhang, Y.-Y., Wu, W., and Liu, H. (2019). Factors affecting variations of soil pH in different horizons in hilly regions. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0218563"},{"key":"ref_71","unstructured":"Reuter, H.I., Lado, L.R., Hengl, T., and Montanarella, L. (2008). Continental-Scale Digital Soil Mapping Using European Soil Profile Data: Soil PH., University of Hamburg."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"114663","DOI":"10.1016\/j.geoderma.2020.114663","article-title":"Microtopography shapes soil pH in flysch regions across Switzerland","volume":"380","author":"Baltensweiler","year":"2020","journal-title":"Geoderma"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3623","DOI":"10.5194\/hess-18-3623-2014","article-title":"Evaluating digital terrain indices for soil wetness mapping\u2014A Swedish case study","volume":"18","author":"Aagren","year":"2014","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"(2019). Bollands\u00e5s; \u00d8rka; Dalponte; Gobakken; N\u00e6sset. Modelling Site Index in Forest Stands Using Airborne Hyperspectral Imagery and Bi-Temporal Laser Scanner Data. Remote Sens. (Basel Switz.), 11.","DOI":"10.3390\/rs11091020"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1029\/1998WR900065","article-title":"Observed spatial organization of soil moisture and its relation to terrain indices","volume":"35","author":"Western","year":"1999","journal-title":"Water Resour. Res."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s11258-008-9566-z","article-title":"The Effect of Light Conditions on Herbs, Bryophytes and Seedlings of Temperate Mixed Forests in \u0150rs\u00e9g, Western Hungary","volume":"204","author":"Tinya","year":"2009","journal-title":"Plant Ecol."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Hagemeier, M., and Leuschner, C. (2019). Leaf and Crown Optical Properties of Five Early-, Mid- and Late-Successional Temperate Tree Species and Their Relation to Sapling Light Demand. Forests, 10.","DOI":"10.3390\/f10100925"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s00704-010-0361-0","article-title":"Comparison between open-site and below-canopy climatic conditions in Switzerland for different types of forests over 10 years (1998\u20132007)","volume":"105","author":"Renaud","year":"2010","journal-title":"Theor. Appl. Climatol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5207\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:56:18Z","timestamp":1760144178000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5207"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,18]]},"references-count":78,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14205207"],"URL":"https:\/\/doi.org\/10.3390\/rs14205207","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,18]]}}}