149
Carter GA, Knapp AK, Anderson JE, Hoch GA, Smith MD (2005) Indicators of plant species richness in AVIRIS spectra of a mesic grassland. Remote Sens Environ 98:304–316
Chappelle EW, Kim MS, McMurtrey JE III (1992) Ratio analysis of reflectance spectra (RARS):
an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b,
and carotenoids in soybean leaves. Remote Sens Environ 39(3):239–247
Chastain RA, Fisk H, Ellenwood JR, Sapio FJ, Ruefenacht B, Finco MV, Thomas V (2015) Nearreal time delivery of MODIS-based information on forest disturbances. In: Time-sensitive
remote sensing. Springer, New York, pp 147–164
Chen J (1996) Evaluation of vegetation indices and a modified simple ratio for boreal applications.
Can J Remote Sens 22(3):229–242
Cheng Y-B, Zarco-Tejada PJ, Riano D, Rueda CA, Ustin SL (2006) Estimating vegetation water
content with hyperspectral data for different canopy scenarios: relationships between AVIRIS
and MODIS indexes. Remote Sens Environ 105(2006):354–366
Coates AR, Dennison PE, Roberts DA, Roth KL (2015) Monitoring the impacts of severe drought
on southern California chaparral species using hyperspectral and thermal infrared imagery.
Remote Sens 7(11):14276–14291
Congalton RG (2001) Accuracy assessment and validation of remotely sensed and other spatial
information. Int J Wildland Fire 10(3–4):321–328
Cook BD, Corp LW, Nelson RF, Middleton EM, Morton DC, McCorkel JT, Masek JG, Ranson KJ,
Ly V, Montesano PM (2013) NASA Goddard's Lidar, Hyperspectral and Thermal (G-LiHT)
airborne imager. Remote Sens Environ 5:4045–4066
D’ambrosio N, Szabo K, Lichtenthaler H (1992) Increase of the chlorophyll fluorescence
ratio F690/F735 during the autumnal chlorophyll breakdown. Radiat Environ Biophys
31(1):51–62
Datt B (1998) Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a + b, and total carotenoid content in eucalyptus leaves. Remote Sens Environ 66:111–121
Datt B (1999) Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves. Int
J Remote Sens 20(14):2741–2759
Daughtry CST, Walthall CL, Kim MS, de Colstoun EB, McMurtrey JE (2000) Estimating corn leaf
chlorophyll concentration from leaf and canopy reflectance. Remote Sens Environ 74(2):229–239.
https://doi.org/10.1016/s0034-4257(00)00113-9
Deblonde G, Cihlar J (1993) A multiyear analysis of the relationship between surface environmental variables and NDVI over the Canadian landmass. Remote Sens Rev 7:151–177
Degerickx J, Roberts DA, McFadden JP, Hermy M, Somers B (2018) Urban tree health assessment
using airborne hyperspectral and LiDAR imagery. Int J Appl Earth Obs Geoinf 73:26–38
Ellison AM, Barker-Plotkin AA, Foster DR, Orwig DA (2010) Experimentally testing the role of
foundation species in forests: the Harvard Forest Hemlock Removal Experiment. Methods Ecol
Evol 1(2):168–179. https://doi.org/10.1111/j.2041-210X.2010.00025.x
Elvidge CD, Chen Z (1995) Comparison of broad-band and narrow-band red and near-infrared
vegetation indices. Remote Sens Environ 54(1):38–48
Elvidge CD, Lyon RJ (1985) Estimation of the vegetation contribution to the 1 65/2 22 μm ratio
in airborne thematic-mapper imagery of the Virginia Range, Nevada. Int J Remote Sens
6(1):75–88
Epanchin-Niell RS, Hastings A (2010) Controlling established invaders: integrating economics
and spread dynamics to determine optimal management. Ecol Lett 13(4):528–541
Fassnacht KS, Cohen WB, Spies TA (2006) Key issues in making and using satellite-based maps
in ecology: a primer. For Ecol Manag 222:167–181
Filella I, Penuelas J (1994) The red edge position and shape as indicators of plant chlorophyll
content, biomass, and hydric status. Int J Remote Sens 15(7):1459–1470
Gamon JA, Serrano L, Surfus JS (1997) The photochemical reflectance index: an optical indicator
of photosynthetic radiation use efficiency across species, functional types, and nutrient levels.
Oecologia 112(4):492–501
6 Remote Sensing for Early, Detailed, and Accurate Detection of Forest Disturbance…
Carter GA, Knapp AK, Anderson JE, Hoch GA, Smith MD (2005) Indicators of plant species richness in AVIRIS spectra of a mesic grassland. Remote Sens Environ 98:304–316
Chappelle EW, Kim MS, McMurtrey JE III (1992) Ratio analysis of reflectance spectra (RARS):
an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b,
and carotenoids in soybean leaves. Remote Sens Environ 39(3):239–247
Chastain RA, Fisk H, Ellenwood JR, Sapio FJ, Ruefenacht B, Finco MV, Thomas V (2015) Nearreal time delivery of MODIS-based information on forest disturbances. In: Time-sensitive
remote sensing. Springer, New York, pp 147–164
Chen J (1996) Evaluation of vegetation indices and a modified simple ratio for boreal applications.
Can J Remote Sens 22(3):229–242
Cheng Y-B, Zarco-Tejada PJ, Riano D, Rueda CA, Ustin SL (2006) Estimating vegetation water
content with hyperspectral data for different canopy scenarios: relationships between AVIRIS
and MODIS indexes. Remote Sens Environ 105(2006):354–366
Coates AR, Dennison PE, Roberts DA, Roth KL (2015) Monitoring the impacts of severe drought
on southern California chaparral species using hyperspectral and thermal infrared imagery.
Remote Sens 7(11):14276–14291
Congalton RG (2001) Accuracy assessment and validation of remotely sensed and other spatial
information. Int J Wildland Fire 10(3–4):321–328
Cook BD, Corp LW, Nelson RF, Middleton EM, Morton DC, McCorkel JT, Masek JG, Ranson KJ,
Ly V, Montesano PM (2013) NASA Goddard's Lidar, Hyperspectral and Thermal (G-LiHT)
airborne imager. Remote Sens Environ 5:4045–4066
D’ambrosio N, Szabo K, Lichtenthaler H (1992) Increase of the chlorophyll fluorescence
ratio F690/F735 during the autumnal chlorophyll breakdown. Radiat Environ Biophys
31(1):51–62
Datt B (1998) Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a + b, and total carotenoid content in eucalyptus leaves. Remote Sens Environ 66:111–121
Datt B (1999) Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves. Int
J Remote Sens 20(14):2741–2759
Daughtry CST, Walthall CL, Kim MS, de Colstoun EB, McMurtrey JE (2000) Estimating corn leaf
chlorophyll concentration from leaf and canopy reflectance. Remote Sens Environ 74(2):229–239.
https://doi.org/10.1016/s0034-4257(00)00113-9
Deblonde G, Cihlar J (1993) A multiyear analysis of the relationship between surface environmental variables and NDVI over the Canadian landmass. Remote Sens Rev 7:151–177
Degerickx J, Roberts DA, McFadden JP, Hermy M, Somers B (2018) Urban tree health assessment
using airborne hyperspectral and LiDAR imagery. Int J Appl Earth Obs Geoinf 73:26–38
Ellison AM, Barker-Plotkin AA, Foster DR, Orwig DA (2010) Experimentally testing the role of
foundation species in forests: the Harvard Forest Hemlock Removal Experiment. Methods Ecol
Evol 1(2):168–179. https://doi.org/10.1111/j.2041-210X.2010.00025.x
Elvidge CD, Chen Z (1995) Comparison of broad-band and narrow-band red and near-infrared
vegetation indices. Remote Sens Environ 54(1):38–48
Elvidge CD, Lyon RJ (1985) Estimation of the vegetation contribution to the 1 65/2 22 μm ratio
in airborne thematic-mapper imagery of the Virginia Range, Nevada. Int J Remote Sens
6(1):75–88
Epanchin-Niell RS, Hastings A (2010) Controlling established invaders: integrating economics
and spread dynamics to determine optimal management. Ecol Lett 13(4):528–541
Fassnacht KS, Cohen WB, Spies TA (2006) Key issues in making and using satellite-based maps
in ecology: a primer. For Ecol Manag 222:167–181
Filella I, Penuelas J (1994) The red edge position and shape as indicators of plant chlorophyll
content, biomass, and hydric status. Int J Remote Sens 15(7):1459–1470
Gamon JA, Serrano L, Surfus JS (1997) The photochemical reflectance index: an optical indicator
of photosynthetic radiation use efficiency across species, functional types, and nutrient levels.
Oecologia 112(4):492–501
6 Remote Sensing for Early, Detailed, and Accurate Detection of Forest Disturbance…