et al., (1990) using the TIMS showed that 15–30 min between overflights is sufficient
time difference to obtain measurable and useful changes in forest canopy temperature due to the change in incoming solar radiation. The mean spatially averaged
temperature for the surface elements at the times of imaging is estimated from
T = 1= n
P
T p
À
Á
, where each T p is the temperature of a pixel in the thermal image
and n is the number of pixels of the surface element. The TRN provides an
analytical framework for studying the effects of surface thermal response for large
spatial resolution map scales that can be aggregated for input to coarser scales as
needed by climate models. The utility of TRN is that (1) it is a functional classifier
of land cover types; (2) it provides an initial surface characterization for input to
various climate models; (3) it is a physically based measurement; (4) it can be
determined completely from a pixel by pixel measurement or for a polygon from a
landscape feature which represents a group of pixels; and (5) surface topography
and orientation of observation are not handicaps where adequate digital elevation
data are available. The TRN can be used as an aggregate expression of both
environmental energy fluxes and surface properties such as forest canopy structure
and biomass, age, and physiological condition as well as urban structures and
material types. A similar index, the thermal buffer capacity (TBC), was later
proposed by Aerts et al. (2004) as a dissipation indicator:
TBC =
t 2 − t 1
T s t 2 − T s t 1
=
Dt
DT s
3.8.3 Ecological Complexity and Ecological Health
The use of ecosystem exergy theory with thermal remote sensing observations is
beginning to be used to study other ecosystems throughout the world. Maes et al.
(2011) used a series of DAIS (digital airborne imaging spectrometer) images collected
over various forests, orchards, croplands, grazing lands, and urban areas in Northern
and Central Belgium. They found that TRN and TBC have the highest discriminative
power of all dissipative indices and were particularly suited for distinguishing
differences in latent heat flux among the vegetation types. They also determined
that TBC and TRN were the dissipation indicators that were least influenced by
prevailing meteorological conditions.
Additional work by Lin et al. (2009) used TRN, TBC, and R n /K* to quantify
plant community self-organization in a tropical seasonal rainforest, an artificial
tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M.
King & H. Robinson communities aged 13 years and 1 year. These transects
sampled the typical vegetation complexity and land use in Xishuangbanna,
southwestern China. They concluded that these thermodynamic indices could
discriminate differences in complexity among ecosystems studied both in the
dry and wet seasons.
Norris et al. (2012) studied the application of ecological thermodynamics theory to
ecosystem climate change adaptation and resilience. They concluded that using
52
THERMAL INFRARED REMOTE SENSING FOR ANALYSIS OF LANDSCAPE
time difference to obtain measurable and useful changes in forest canopy temperature due to the change in incoming solar radiation. The mean spatially averaged
temperature for the surface elements at the times of imaging is estimated from
T = 1= n
P
T p
À
Á
, where each T p is the temperature of a pixel in the thermal image
and n is the number of pixels of the surface element. The TRN provides an
analytical framework for studying the effects of surface thermal response for large
spatial resolution map scales that can be aggregated for input to coarser scales as
needed by climate models. The utility of TRN is that (1) it is a functional classifier
of land cover types; (2) it provides an initial surface characterization for input to
various climate models; (3) it is a physically based measurement; (4) it can be
determined completely from a pixel by pixel measurement or for a polygon from a
landscape feature which represents a group of pixels; and (5) surface topography
and orientation of observation are not handicaps where adequate digital elevation
data are available. The TRN can be used as an aggregate expression of both
environmental energy fluxes and surface properties such as forest canopy structure
and biomass, age, and physiological condition as well as urban structures and
material types. A similar index, the thermal buffer capacity (TBC), was later
proposed by Aerts et al. (2004) as a dissipation indicator:
TBC =
t 2 − t 1
T s t 2 − T s t 1
=
Dt
DT s
3.8.3 Ecological Complexity and Ecological Health
The use of ecosystem exergy theory with thermal remote sensing observations is
beginning to be used to study other ecosystems throughout the world. Maes et al.
(2011) used a series of DAIS (digital airborne imaging spectrometer) images collected
over various forests, orchards, croplands, grazing lands, and urban areas in Northern
and Central Belgium. They found that TRN and TBC have the highest discriminative
power of all dissipative indices and were particularly suited for distinguishing
differences in latent heat flux among the vegetation types. They also determined
that TBC and TRN were the dissipation indicators that were least influenced by
prevailing meteorological conditions.
Additional work by Lin et al. (2009) used TRN, TBC, and R n /K* to quantify
plant community self-organization in a tropical seasonal rainforest, an artificial
tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M.
King & H. Robinson communities aged 13 years and 1 year. These transects
sampled the typical vegetation complexity and land use in Xishuangbanna,
southwestern China. They concluded that these thermodynamic indices could
discriminate differences in complexity among ecosystems studied both in the
dry and wet seasons.
Norris et al. (2012) studied the application of ecological thermodynamics theory to
ecosystem climate change adaptation and resilience. They concluded that using
52
THERMAL INFRARED REMOTE SENSING FOR ANALYSIS OF LANDSCAPE