Advanced

Remote sensing phenology at European northern latitudes - From ground spectral towers to satellites

Jin, Hongxiao LU (2015)
Abstract (Swedish)
Popular Abstract in Swedish

Växters fenologi påverkar ekosystemens funktion och tjänster, och återkopplar till klimatet genom att påverka utbytet av kol, vatten och energi mellan atmosfär och ekosystem. Under de senaste decennierna har växternas fenologi studerats i allt större omfattning, men fortfarande är osäkerheten stor och enighet saknas om klimatets inverkan på fenologi och förändringar över tiden. Detta projekt syftar till att minska osäkerheterna genom att analysera marknära insamling av spektrala data, utveckla nya metoder för kalibrering av ljussensorer i fält, och utforska nya spektralindex för mer tillförlitlig uppskattning av växternas fenologi och klimatkänslighet i norra Europa med hjälp av fjärranalysdata.... (More)
Popular Abstract in Swedish

Växters fenologi påverkar ekosystemens funktion och tjänster, och återkopplar till klimatet genom att påverka utbytet av kol, vatten och energi mellan atmosfär och ekosystem. Under de senaste decennierna har växternas fenologi studerats i allt större omfattning, men fortfarande är osäkerheten stor och enighet saknas om klimatets inverkan på fenologi och förändringar över tiden. Detta projekt syftar till att minska osäkerheterna genom att analysera marknära insamling av spektrala data, utveckla nya metoder för kalibrering av ljussensorer i fält, och utforska nya spektralindex för mer tillförlitlig uppskattning av växternas fenologi och klimatkänslighet i norra Europa med hjälp av fjärranalysdata.

Vid fältstationer används ofta sensorer med lodrät eller sned vinkel för att mäta reflekterad strålning, men ofta är osäkerheten i mätningarna stor då nödvändig fältkalibrering av sensorerna saknas, och därigenom förbises hur olika växter påverkar den uppmätta reflektionen. Våra resultat tyder på att växternas reflektion följer en Cauchy-fördelning, modifierad av sensorns geometriska responsfunktion. Vi utvecklade en metod för fältkalibrering av spektralsensorer och visade hur denna metod ökar trovärdigheten av mätningarna gentemot mätningar gjorda med tillverkarnas standardkalibreringar.

Med mer trovärdiga reflektionsmätningar utvecklade vi ett fenologiskt vegetationsindex (PPI) som beräknas genom en strålningsekvation baserat på röd och nära-infraröd reflektion. PPI var linjärt korrelerad med trädensbladyteindex (LAI, leaf area index) och var bättre korrelerad med brutto- primärproduktion än andra vegetationsindex. PPI har speciellt stor potential för barrträdsdominerad boreal skog eftersom PPI är mindre känslig för påverkan av snö än andra vegetationsindex.

Vi uppskattade fenologin över norra Europa mellan 2000 och 2014 med PPI beräknat med s.k. BRDF-justerad reflektion från MODIS-sensorn. Vi utvärderade förändringar i växtsäsongens start (SOS), slut (EOS), längd (LOS) och PPI-integral och kunde påvisa signifikanta förändringar under de senaste 15 åren i större delen av norra Europa. I snitt var förändringen -0.39 dagar·år-1 för SOS, 0.48 dagar·år-1 för EOS, 0.87 dagar·år-1 för LOS, och 0.79%·år-1 för PPI-integralen. Fenologin var i de flesta områden signifikant påverkad av klimatet, i relation till temperatur; -3.43 dagar·°C-1 för SOS, 1.27 dagar·°C-1 för EOS, 3.16 dagar·°C-1 för LOS, och 2.29 %·°C-1 för PPI-integralen, och till nederbörd; 0.28 dagar∙cm-1 för SOS, 0.05 dagar∙cm-1 för EOS, 0.04 dagar∙cm-1 för LOS och 0.07%∙cm-1 för PPI-integralen. Dessa förändringar var signifikant relaterade till variationer över de senaste årtiondena av atmosfäriska cirkulationsmönster, såsom den Nordatlantiska oscillationen och den Arktiska oscillationen.

Metoderna som har utvecklats i detta projekt ökar trovärdigheten av spektralmätningar och minskar osäkerheten i estimerad fenologi och klimatkänslighet baserad på fjärranalysdata. (Less)
Abstract
Plant phenology exerts major influences on carbon, water, and energy exchanges between atmosphere and ecosystems, provides feedbacks to climate, and affects ecosystem functioning and services. Great efforts have been spent in studying plant phenology over the past decades, but there are still large uncertainties and disputations in phenology estimation, trends, and its climate sensitivities. This thesis aims to reduce these uncertainties through analyzing ground spectral sampling, developing methods for in situ light sensor calibration, and exploring a new spectral index for reliable retrieval of remote sensing phenology and climate sensitivity estimation at European northern latitudes.

The ground spectral towers use light sensors... (More)
Plant phenology exerts major influences on carbon, water, and energy exchanges between atmosphere and ecosystems, provides feedbacks to climate, and affects ecosystem functioning and services. Great efforts have been spent in studying plant phenology over the past decades, but there are still large uncertainties and disputations in phenology estimation, trends, and its climate sensitivities. This thesis aims to reduce these uncertainties through analyzing ground spectral sampling, developing methods for in situ light sensor calibration, and exploring a new spectral index for reliable retrieval of remote sensing phenology and climate sensitivity estimation at European northern latitudes.

The ground spectral towers use light sensors of either nadir or off-nadir viewing to measure reflected radiation, yet how plants in the sensor view contribute differently to the measured signals, and necessary in situ calibrations are often overlooked, leading to great uncertainties in ground spectral sampling of vegetation. It was found that the ground sampling points in the sensor view follow a Cauchy distribution, which is further modulated by the sensor directional response function. We proposed in situ light sensor calibration methods and showed that the user in situ calibration is more reliable than manufacturer’s lab calibration when our proposed calibration procedures are followed.

By taking the full advantages of more reliable and standardized reflectance, we proposed a plant phenology vegetation index (PPI), which is derived from a radiative transfer equation and uses red and near infrared reflectance. PPI shows good linearity with canopy green leaf area index, and is correlated with gross primary productivity, better than other vegetation indices in our test. With suppressed snow influences, PPI shows great potentials for retrieving phenology over coniferous-dominated boreal forests.

PPI was used to retrieve plant phenology from MODIS nadir BRDF-adjusted reflectance at European northern latitudes for the period 2000-2014. We estimated the trend of start of growing season (SOS), end of growing season (EOS), length of growing season (LOS), and the PPI integral for the time span, and found significant changes in most part of the region, with an average rate of -0.39 days·year-1 in SOS, 0.48 days·year-1 in EOS, 0.87 days·year-1 in LOS, and 0.79%·year-1 in the PPI integral over the past 15 years. We found that the plant phenology was significantly affected by climate in most part of the region, with an average sensitivity to temperature: SOS at -3.43 days·°C-1, EOS at 1.27 days·°C-1, LOS at 3.16 days·°C-1, and PPI integral at 2.29 %·°C-1, and to precipitation: SOS at 0.28 days∙cm-1, EOS at 0.05 days∙cm-1, LOS at 0.04 days∙cm-1, and PPI integral at -0.07%∙cm-1. These phenology variations were significantly related to decadal variations of atmospheric circulations, including the North Atlantic Oscillation and the Arctic Oscillation.

The methods developed in this thesis can help to improve the reliability of long-term field spectral measurements and to reduce uncertainties in remote sensing phenology retrieval and climate sensitivity estimation. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Stenberg, Pauline, Department of Forest Sciences, University of Helsinki
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Remote sensing, climate sensitivity., calibration, ground spectral tower, Plant phenology index (PPI), northern latitude
pages
174 pages
publisher
Department of Physical Geography and Ecosystem Science, Lund University
defense location
Världen auditorium,Sölvegatan 12, 22362, Lund
defense date
2015-06-11 10:00
ISBN
978-91-85793-49-5
language
English
LU publication?
yes
id
85831574-d517-41c1-99ab-bef8dd66b24f (old id 5366415)
date added to LUP
2015-05-20 10:56:28
date last changed
2016-09-19 08:45:08
@phdthesis{85831574-d517-41c1-99ab-bef8dd66b24f,
  abstract     = {Plant phenology exerts major influences on carbon, water, and energy exchanges between atmosphere and ecosystems, provides feedbacks to climate, and affects ecosystem functioning and services. Great efforts have been spent in studying plant phenology over the past decades, but there are still large uncertainties and disputations in phenology estimation, trends, and its climate sensitivities. This thesis aims to reduce these uncertainties through analyzing ground spectral sampling, developing methods for in situ light sensor calibration, and exploring a new spectral index for reliable retrieval of remote sensing phenology and climate sensitivity estimation at European northern latitudes.<br/><br>
The ground spectral towers use light sensors of either nadir or off-nadir viewing to measure reflected radiation, yet how plants in the sensor view contribute differently to the measured signals, and necessary in situ calibrations are often overlooked, leading to great uncertainties in ground spectral sampling of vegetation. It was found that the ground sampling points in the sensor view follow a Cauchy distribution, which is further modulated by the sensor directional response function. We proposed in situ light sensor calibration methods and showed that the user in situ calibration is more reliable than manufacturer’s lab calibration when our proposed calibration procedures are followed.<br/><br>
By taking the full advantages of more reliable and standardized reflectance, we proposed a plant phenology vegetation index (PPI), which is derived from a radiative transfer equation and uses red and near infrared reflectance. PPI shows good linearity with canopy green leaf area index, and is correlated with gross primary productivity, better than other vegetation indices in our test. With suppressed snow influences, PPI shows great potentials for retrieving phenology over coniferous-dominated boreal forests.<br/><br>
PPI was used to retrieve plant phenology from MODIS nadir BRDF-adjusted reflectance at European northern latitudes for the period 2000-2014. We estimated the trend of start of growing season (SOS), end of growing season (EOS), length of growing season (LOS), and the PPI integral for the time span, and found significant changes in most part of the region, with an average rate of -0.39 days·year-1 in SOS, 0.48 days·year-1 in EOS, 0.87 days·year-1 in LOS, and 0.79%·year-1 in the PPI integral over the past 15 years. We found that the plant phenology was significantly affected by climate in most part of the region, with an average sensitivity to temperature: SOS at -3.43 days·°C-1, EOS at 1.27 days·°C-1, LOS at 3.16 days·°C-1, and PPI integral at 2.29 %·°C-1, and to precipitation: SOS at 0.28 days∙cm-1, EOS at 0.05 days∙cm-1, LOS at 0.04 days∙cm-1, and PPI integral at -0.07%∙cm-1. These phenology variations were significantly related to decadal variations of atmospheric circulations, including the North Atlantic Oscillation and the Arctic Oscillation.<br/><br>
The methods developed in this thesis can help to improve the reliability of long-term field spectral measurements and to reduce uncertainties in remote sensing phenology retrieval and climate sensitivity estimation.},
  author       = {Jin, Hongxiao},
  isbn         = {978-91-85793-49-5},
  keyword      = {Remote sensing,climate sensitivity.,calibration,ground spectral tower,Plant phenology index (PPI),northern latitude},
  language     = {eng},
  pages        = {174},
  publisher    = {Department of Physical Geography and Ecosystem Science, Lund University},
  school       = {Lund University},
  title        = {Remote sensing phenology at European northern latitudes - From ground spectral towers to satellites},
  year         = {2015},
}