421
Jacquemoud S, Verhoef W, Baret F, Bacour C, Zarco-Tejada PJ, Asner GP, François C, Ustin SL
(2009) Prospect+ sail models: a review of use for vegetation characterization. Remote Sens
Environ 113:S56–S66
Johannsen CJ, Daughtry CS (2009) Surface reference data collection. In: Warner T, Nellis M,
Foody G (eds) The SAGE handbook of remote sensing. Sage Publications, London
Jonasson S (1988) Evaluation of the point intercept method for the estimation of plant biomass.
Oikos 52:101–106
Jones R (2009) Categories, borders and boundaries. Prog Hum Geogr 33:174–189
Jones HG, Vaughan RA (2010) Remote sensing of vegetation: principles, techniques, and applications. Oxford University Press, Oxford
Justice CO, Townshend JR (1981) Integrating ground data with remote sensing. In: Townshend
JRG (ed) Terrain analysis and remote sensing. Allen & Unwin, London
Kattenborn T, Eichel J, Fassnacht FE (2019) Convolutional neural networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution
UAV imagery. Sci Rep 9:17656
Kattge J, Diaz S, Lavorel S, Prentice I, Leadley P, Bönisch G, Garnier E, Westoby M, Reich PB,
Wright I (2011) Try–a global database of plant traits. Glob Chang Biol 17:2905–2935
Kincaid T, Olsen A (2016) Spsurvey: spatial survey design and analysis. R package version 3:3
Kruse F, Kierein-Young K, Boardman J (1990) Mineral mapping at cuprite, Nevada with a
63-channel imaging spectrometer. Photogramm Eng Remote Sens 56:83–92
Lopatin J, Fassnacht FE, Kattenborn T, Schmidtlein S (2017) Mapping plant species in mixed grassland communities using close range imaging spectroscopy. Remote Sens Environ 201:12–23
Martens H (2001) Reliable and relevant modelling of real world data: a personal account of the
development of pls regression. Chemom Intell Lab Syst 58:85–95
McCoy RM (2005) Field methods in remote sensing. The Guilford Press, New York
Milton EJ, Schaepman ME, Anderson K, Kneubühler M, Fox N (2009) Progress in field spectroscopy. Remote Sens Environ 113:S92–S109
Noda HM, Motohka T, Murakami K, Muraoka H, Nasahara KN (2013) Accurate measurement of
optical properties of narrow leaves and conifer needles with a typical integrating sphere and
spectroradiometer. Plant Cell Environ 36:1903–1909
Papritz A, Stein A (1999) Spatial prediction by linear kriging. In: Spatial statistics for remote sensing. Springer, Berlin, Heidelberg
Perez-Harguindeguy N, Diaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, Bret-Harte M
(2013) New handbook for standardised measurement of plant functional traits worldwide.
Australian J 800:167–234
Pettorelli N, Ryan S, Mueller T, Bunnefeld N, Jedrzejewska B, Lima M, Kausrud K (2011) The
normalized difference vegetation index (ndvi): unforeseen successes in animal ecology. Clim
Res 46:15–27
Pontius J, Hallett R, Martin M (2005) Using aviris to assess hemlock abundance and early decline
in the catskills, New York. Remote Sens Environ 97:163–173
Rouse JW Jr, Haas RH, Deering DW, Schell JA, Harlan JC (1974) Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. NASA/GSFC type III final
report, Greenbelt. Available from: https://ntrs.nasa.gov/search.jsp?R=19750020419
Sala OE, Jackson RB, Mooney HA, Howarth RW (2000) Methods in ecosystem science: progress,
tradeoffs, and limitations. Springer, New York
Schaepman ME (2007) Spectrodirectional remote sensing: from pixels to processes. Int J Appl
Earth Obs Geoinf 9:204–223
Schmidtlein S, Feilhauer H, Bruelheide H (2012) Mapping plant strategy types using remote sensing. J Veg Sci 23:395–405
Schweiger AK, Risch AC, Damm A, Kneubühler M, Haller R, Schaepman ME, Schütz M (2015a)
Using imaging spectroscopy to predict above-ground plant biomass in alpine grasslands grazed
by large ungulates. J Veg Sci 26:175–190
Schweiger AK, Schütz M, Anderwald P, Schaepman ME, Kneubühler M, Haller R, Risch AC
(2015b) Foraging ecology of three sympatric ungulate species - behavioural and resource maps
indicate differences between chamois, ibex and red deer. Mov Ecol 3:6
15 Spectral Field Campaigns: Planning and Data Collection
Jacquemoud S, Verhoef W, Baret F, Bacour C, Zarco-Tejada PJ, Asner GP, François C, Ustin SL
(2009) Prospect+ sail models: a review of use for vegetation characterization. Remote Sens
Environ 113:S56–S66
Johannsen CJ, Daughtry CS (2009) Surface reference data collection. In: Warner T, Nellis M,
Foody G (eds) The SAGE handbook of remote sensing. Sage Publications, London
Jonasson S (1988) Evaluation of the point intercept method for the estimation of plant biomass.
Oikos 52:101–106
Jones R (2009) Categories, borders and boundaries. Prog Hum Geogr 33:174–189
Jones HG, Vaughan RA (2010) Remote sensing of vegetation: principles, techniques, and applications. Oxford University Press, Oxford
Justice CO, Townshend JR (1981) Integrating ground data with remote sensing. In: Townshend
JRG (ed) Terrain analysis and remote sensing. Allen & Unwin, London
Kattenborn T, Eichel J, Fassnacht FE (2019) Convolutional neural networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution
UAV imagery. Sci Rep 9:17656
Kattge J, Diaz S, Lavorel S, Prentice I, Leadley P, Bönisch G, Garnier E, Westoby M, Reich PB,
Wright I (2011) Try–a global database of plant traits. Glob Chang Biol 17:2905–2935
Kincaid T, Olsen A (2016) Spsurvey: spatial survey design and analysis. R package version 3:3
Kruse F, Kierein-Young K, Boardman J (1990) Mineral mapping at cuprite, Nevada with a
63-channel imaging spectrometer. Photogramm Eng Remote Sens 56:83–92
Lopatin J, Fassnacht FE, Kattenborn T, Schmidtlein S (2017) Mapping plant species in mixed grassland communities using close range imaging spectroscopy. Remote Sens Environ 201:12–23
Martens H (2001) Reliable and relevant modelling of real world data: a personal account of the
development of pls regression. Chemom Intell Lab Syst 58:85–95
McCoy RM (2005) Field methods in remote sensing. The Guilford Press, New York
Milton EJ, Schaepman ME, Anderson K, Kneubühler M, Fox N (2009) Progress in field spectroscopy. Remote Sens Environ 113:S92–S109
Noda HM, Motohka T, Murakami K, Muraoka H, Nasahara KN (2013) Accurate measurement of
optical properties of narrow leaves and conifer needles with a typical integrating sphere and
spectroradiometer. Plant Cell Environ 36:1903–1909
Papritz A, Stein A (1999) Spatial prediction by linear kriging. In: Spatial statistics for remote sensing. Springer, Berlin, Heidelberg
Perez-Harguindeguy N, Diaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, Bret-Harte M
(2013) New handbook for standardised measurement of plant functional traits worldwide.
Australian J 800:167–234
Pettorelli N, Ryan S, Mueller T, Bunnefeld N, Jedrzejewska B, Lima M, Kausrud K (2011) The
normalized difference vegetation index (ndvi): unforeseen successes in animal ecology. Clim
Res 46:15–27
Pontius J, Hallett R, Martin M (2005) Using aviris to assess hemlock abundance and early decline
in the catskills, New York. Remote Sens Environ 97:163–173
Rouse JW Jr, Haas RH, Deering DW, Schell JA, Harlan JC (1974) Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. NASA/GSFC type III final
report, Greenbelt. Available from: https://ntrs.nasa.gov/search.jsp?R=19750020419
Sala OE, Jackson RB, Mooney HA, Howarth RW (2000) Methods in ecosystem science: progress,
tradeoffs, and limitations. Springer, New York
Schaepman ME (2007) Spectrodirectional remote sensing: from pixels to processes. Int J Appl
Earth Obs Geoinf 9:204–223
Schmidtlein S, Feilhauer H, Bruelheide H (2012) Mapping plant strategy types using remote sensing. J Veg Sci 23:395–405
Schweiger AK, Risch AC, Damm A, Kneubühler M, Haller R, Schaepman ME, Schütz M (2015a)
Using imaging spectroscopy to predict above-ground plant biomass in alpine grasslands grazed
by large ungulates. J Veg Sci 26:175–190
Schweiger AK, Schütz M, Anderwald P, Schaepman ME, Kneubühler M, Haller R, Risch AC
(2015b) Foraging ecology of three sympatric ungulate species - behavioural and resource maps
indicate differences between chamois, ibex and red deer. Mov Ecol 3:6
15 Spectral Field Campaigns: Planning and Data Collection