The spectral variability hypothesis does not hold across landscapes

Remote Sensing of Environment

Volumn 192, Issue , 2017, Pages 114-125

  Schmidtlein, Sebastian ^a   Fassnacht, Fabian Ewald ^a  

^a KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

Author keywords

Biodiversity; Floristic survey; Plant species richness; Spatial non stationarity; SVH; Zoning effects

Indexed keywords

BIODIVERSITY; FORESTRY; MAPPING; RADIOMETERS;

CORRELATION ANALYSIS; FLORISTIC SURVEYS; MONITORING APPROACH; PLANT SPECIES RICHNESS; SPATIAL NON-STATIONARITY; SPATIAL VARIABILITY; SPECTRAL VARIABILITY; VASCULAR PLANT SPECIES;

PLANTS (BOTANY);

BIODIVERSITY; CORRELATION; DATA SET; FLORISTICS; MODIS; PIXEL; REFLECTANCE; SPATIAL VARIATION; SPECIES OCCURRENCE; SPECIES RICHNESS; SPECTRAL ANALYSIS; VASCULAR PLANT;

GERMANY;

TRACHEOPHYTA;

EID: 85013176271     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.01.036     Document Type: Article

References (46)

1. Bivand, R., Piras, G., Comparing implementations of estimation methods for spatial econometrics. J. Stat. Softw. 63:18 (2015), 1–36.
2. Bossard, M., Feranec, J., Otahel, J., CORINE land cover technical guide—addendum 2000. Technical Report No 40, 2000, European Environment Agency, Copenhagen (105 pp.).
3. Camathias, L., Bergamini, A., Küchler, M., Stofer, S., Baltensweiler, A., High-resolution remote sensing data improves models of species richness. Appl. Veg. Sci. 16 (2013), 539–551.
4. Carlson, K.M., Asner, G.P., Hughes, R.F., Ostertag, R., Martin, R.E., Hyperspectral remote sensing of canopy biodiversity in Hawaiian lowland rainforests. Ecosystems 10 (2007), 536–549.
5. Dungan, J., Perry, J.N., Dale, M.R.T., Legendre, P., Citron-Pousty, S., Fortin, M.-J., Jakomulska, A., Miriti, M., Rosenberg, M.S., A balanced view of scale in spatial statistical analysis. Ecography 25 (2002), 626–640.
6. Dutilleul, P., Modifying the t-test for assessing the correlation between two spatial processes. Biometrics 49 (1993), 305–314.
7. Feilhauer, H., Schmidtlein, S., Mapping continuous fields of forest alpha and beta diversity. Appl. Veg. Sci. 12:4 (2009), 429–439.
8. Féret, J.-B., Asner, G.P., Mapping tropical forest canopy diversity using high-fidelity imaging spectroscopy. Ecol. Appl. 24 (2014), 1289–1296.
9. Foody, G., Cutler, M., Tree biodiversity in protected and logged Bornean tropical rain forests and its measurement by satellite remote sensing. J. Biogeogr. 30 (2003), 1053–1066.
10. Foody, G., Cutler, M., Mapping the species richness and composition of tropical forests from remotely sensed data with neural networks. Ecol. Model. 195 (2006), 37–42.
11. Gould, W., Remote sensing of vegetation, plant species richness, and regional biodiversity hotspots. Ecol. Appl. 10:6 (2000), 1861–1870.
12. Hall, K., Johansson, L.J., Sykes, M.T., Reitalu, T., Larsson, K., Prentice, H.C., Inventorying management status and plant species richness in semi-natural grasslands using high spatial resolution imagery. Appl. Veg. Sci. 13 (2010), 221–233.
13. Hall, K., Reitalu, T., Sykes, M.T., Prentice, H.C., Spectral heterogeneity of QuickBird satellite data is related to fine-scale plant species spatial turnover in semi-natural grasslands. Appl. Veg. Sci. 15 (2012), 145–158.
14. Hernández-Stefanoni, J., Dupuy, J., Johnson, K., Birdsey, R., Tun-Dzul, F., Peduzzi, A., Caamal-Sosa, J.P., Sánchez-Santos, G., López-Merlín, D., Improving species diversity and biomass estimates of tropical dry forests using airborne LiDAR. Remote Sens. 6 (2014), 4741–4763.
15. Heumann, B.W., Hackett, R.A., Monfils, A.K., Testing the spectral diversity hypothesis using spectroscopy data in a simulated wetland community. Eco. Inform. 25 (2015), 29–34.
16. Higgins, M., Asner, G., Martin, R., Knapp, D., Anderson, C., Kennedy-Bowdoin, T., Saenz, R., Aguilar, A., Wright, S., Linking imaging spectroscopy and LiDAR with floristic composition and forest structure in Panama. Remote Sens. Environ. 154 (2014), 358–367.
17. Hijmans, R.J., van Etten, J., raster: Geographic Analysis and Modeling With Raster Data. R package version 2.0-12. 2012 ( http://CRAN.R-project.org/package=raster).
18. Kühn, I., Brandl, R., Klotz, S., The flora of German cities is naturally species rich. Evol. Ecol. Res. 6 (2004), 749–764.
19. Laurin, G.V., Chan, J.C.-W., Lindsell, J.A., Coomes, D.A., Guerriero, L., Del Frate, F., Miglietta, F., Valentini, R., Biodiversity mapping in a tropical West African forest with airborne hyperspectral data. PLoS ONE 9:6 (2014), 1–10.
20. Levin, N., Shmida, A., Levanoni, O., Tamari, H., Kark, S., Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices. Divers. Distrib. 13 (2007), 692–703.
21. Lopatin, J., Galleguillos, M., Fassnacht, F.E., Ceballos, A., Hernández, J., Using a multistructural object-based LiDAR approach to estimate vascular plant richness in Mediterranean forests with complex structure. IEEE Geosci. Remote Sens. Lett. 12:5 (2015), 1008–1012.
22. Lopatin, J., Dolos, K., Hernández, J., Galleguillos, M., Fassnacht, F.E., Comparing generalized linear models and random forest to model vascular plant species richness using LiDAR data in a natural forest in Central Chile. Remote Sens. Environ. 173 (2016), 200–210.
23. LP DAAC, https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod09a1, 2016 (last access 30 July 2016).
24. Mahecha, M.D., Schmidtlein, S., Revealing biogeographical patterns by nonlinear ordinations and derived anisotropic spatial filters. Glob. Ecol. Biogeogr. 17:2 (2008), 284–296.
25. Mairota, P., Cafarelli, B., Labadessa, R., Lovergine, F., Tarantino, C., Lucas, R.M., Nagendra, H., Didham, R.K., Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas. Int. J. Appl. Earth Obs. Geoinf. 37 (2015), 100–105.
26. Meynen, E., Schmithüsen, J., (eds.) Handbuch der naturräumlichen Gliederung Deutschlands, 1956–1962, Bundesanstalt für Landeskunde, Remagen/Bad Godesberg (9 issues in 8 volumes, 1 map 1:1,000,000).
27. Nagendra, H., Rocchini, D., Ghate, R., Sharma, B., Pareeth, S., Assessing plant diversity in a dry tropical forest: comparing the utility of Landsat and IKONOS satellite images. Remote Sens. 2 (2010), 478–496.
28. Netzwerk Phytodiversität Deutschland, Bundesamt für Naturschutz, Verbreitungsatlas der Farn- und Blütenpflanzen Deutschlands. 2013, Landwirtschaftsverlag, Münster.
29. Oindo, B.O., Skidmore, A.K., Interannual variability of NDVI and species richness in Kenya. Int. J. Remote Sens. 23:2 (2002), 285–298.
30. Oldeland, J., Wesuls, D., Rocchini, D., Schmidt, M., Jürgens, N., Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?. Ecol. Indic. 10 (2010), 390–396.
31. Palmer, M.W., Wohlgemuth, T., Earls, P., Arévalo, J.R., Thompson, S.D., Opportunities for long-term ecological research at the Tallgrass Prairie Preserve, Oklahoma. Lajtha, K., Vanderbilt, K., (eds.) Cooperation in Long Term Ecological Research in Central and Eastern, 2000.
32. Palmer, M.W., Earls, P.G., Hoagland, B.W., White, P.S., Wohlgemuth, T., Quantitative tools for predicting species lists. Environmetrics 13 (2002), 121–137.
33. Rocchini, D., Effects of spatial and spectral resolution in estimating ecosystem α-diversity by satellite imagery. Remote Sens. Environ. 111 (2007), 423–434.
34. Rocchini, D., Chiarucci, A., Loiselle, S.A., Testing the spectral variation hypothesis by using satellite multispectral images. Acta Oecol. 26 (2004), 117–120.
35. Rocchini, D., Balkenhol, N., Carter, G.A., Foody, G.M., Gillespie, T.W., He, K.S., Kark, S., Levin, N., Lucas, K., Luoto, M., Nagendra, H., Oldeland, J., Ricotta, C., Southworth, J., Neteler, M., Remotely sensed spectral heterogeneity as a proxy of species diversity: recent advances and open challenges. Eco. Inform. 5 (2010), 318–329.
36. Rocchini, D., Dadalt, L., Delucchi, L., Neteler, M., Palmer, M.W., Disentangling the role of remotely sensed spectral heterogeneity as a proxy for North American plant species richness. Community Ecol. 15 (2014), 37–43.
37. Salomonson, V.V., Barnes, W., Maymon, P.W., Montgomery, H.E., Ostrow, H., MODIS: advanced facility instrument for studies of the Earth as a system. IEEE Trans. Geosci. Remote Sens. 27 (1989), 145–153.
38. Schmidtlein, S., Sassin, J., Mapping of continuous floristic gradients in grassland using hyperspectral imagery. Remote Sens. Environ. 92 (2004), 126–138.
39. Simonson, W., Allen, H., Coomes, D., Use of an airborne LiDAR system to model plant species composition and diversity of Mediterranean oak forests. Conserv. Biol. 26 (2012), 840–850.
40. Skidmore, A.K., Pettorelli, N., Coops, N.C., Geller, G.N., Hansen, M., Lucas, R., Mücher, C.A., 'Connor, B., Paganini, Pereira, H.M., Schaepman, M.E., Turner, W., Wang, T., Wegmann, M., Environmental science: agree on biodiversity metrics to track from space. Nature 523:7561 (2015), 403–405.
41. Ustin, S.L., Gamon, J.A., Remote sensing of plant functional types. New Phytol. 186 (2010), 795–816.
42. Viedma, O., Torres, I., Pérez, B., Moreno, J.M., Modeling plant species richness using reflectance and texture data derived from QuickBird in a recently burned area of Central Spain. Remote Sens. Environ. 119 (2012), 208–221.
43. Wang, K., Franklin, S.E., Guo, X., Cattet, M., Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists. Sensors 10:11 (2010), 9647–9667.
44. Waser, L.T., Stofer, S., Schwarz, M., Küchler, M., Ivtis, E., Scheidegger, C., Prediction of biodiversity—regression of lichen species richness on remote sensing data. Community Ecol. 5:1 (2004), 121–133.
45. Whittaker, R.H., Vegetation of the Siskiyou Mountains, Oregon and California. Ecol. Monogr. 30 (1960), 279–338.
46. Wilson, J.B., Peet, R.K., Dengler, J., Pärtel, M., Plant species richness: the world records. J. Veg. Sci. 23 (2012), 796–802.