Application of imaging spectroscopy to mapping canopy nitrogen in the forests of the central appalachian mountains using hyperion and aviris

Townsend, Philip A.; Foster, Jane R.; Chastain, Robert A.; Currie, William S.

doi:10.1109/tgrs.2003.813205

Cited by 152 publications

(127 citation statements)

References 32 publications

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“…Although patterns related to dominant forest functional groups are evident (e.g., higher values in the eastern deciduous biome and lower values in northern evergreens), there is considerable variability within vegetation types, with the highest overall estimates in forests of the midAppalachian region. This region has been identified as having high foliar N concentrations relative to other temperate deciduous forests (20,21), with some evidence that variation is linked to patterns of atmospheric N deposition (21). Additional field measurements can confirm or reject this hypothesis and determine whether or not similar trends can be applied over other regions and vegetation types.…”

Section: Resultsmentioning

confidence: 97%

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

Ollinger

Richardson

Martin

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

357

289

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The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth's climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO 2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO 2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle-climate models.nitrogen cycle ͉ climate change ͉ foliar nitrogen ͉ ecosystem-climate feedback ͉ remote sensing T errestrial ecosystems influence the Earth's climate through regulation of mass and energy exchange with the atmosphere. In recent years, much of the focus has been directed toward factors affecting the Ϸ1-to 2-Pg carbon (C) sink that is believed to exist in the terrestrial biosphere (1). Candidate mechanisms include forest regrowth after agricultural abandonment (2) and growth enhancement from nitrogen (N) deposition and/or elevated CO 2 (3, 4). In each case, interactions between C and N play a central role. Observations of N limitations to productivity are widespread (5), and responses to experimental CO 2 fertilization are often restricted by N availability (6-8). Although evidence of an N deposition effect on net C exchange has only recently been documented (4), the importance of N as a regulator of C assimilation is well established through the widely observed relationship between leaf-level photosynthetic capacity (A max ) and foliar N concentrations (9-11). Despite this understanding, few analyses have included continuous variation in plant N status as a driver of C cycle processes at regional to global scales. There are at least 2 reasons for this. First, because evidence for the photosynthesis-foliar N relationship comes predominantly from leaf-level observations, there is uncertainty about whether similar trends occur over whole-plant canopies or whether canopy-level factors such as leaf area index (LAI) become dominant at this scale. Second, although many ecosystem models simulate plant and soil N dynamics, there are no widely available methods for obtaining mapped foliar N estimates over ...

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Section: Resultsmentioning

confidence: 97%

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

Ollinger

Richardson

Martin

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

357

289

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“…Remote sensing of N in forest canopies by hyperspectral sensors is often coupled with intensive forest sampling 355 measurements. This method has been effective at detecting canopy N concentration locally in a vast range of environments (Serrano et al, 2002;Smith et al, 2002;Townsend et al, 2003;Ollinger et al, 2008;Wang et al, 2016). Applying this technique at larger scales has already been explored.…”

Section: Perspectives For Larger Scale Applicationsmentioning

confidence: 99%

Regional detection of canopy nitrogen in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index

Loozen

Rebel

Karssenberg

et al. 2017

Preprint

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) from a Mediterranean forests inventory in the region of Catalonia, NE of Spain. The relationships between the datasets were studied after resampling both datasets to lower spatial resolutions (20 km, 15 km, 10 km and 5 km) and at the initial higher spatial resolution of 1 km. The results at the higher spatial resolution yielded significant relationships between MTCI and both canopy N concentration and content, r 2 = 0.32 and r 2 = 0.17, respectively.We also investigated these relationships per plant functional type. While the relationship between MTCI and canopy N 20 concentration was strongest for deciduous broadleaf and mixed plots (r 2 = 0.25 and r 2 = 0.47, respectively), the relationship between MTCI and canopy N content was strongest for evergreen needleleaf trees (r 2 = 0.20). At the species level, canopy N concentration was strongly related to MTCI for European Beech plots (r 2 = 0.71). These results present a new perspective on the application of MTCI time series for canopy N detection, ultimately leading towards the generation of canopy N maps that can be used to constrain global vegetation models. capacity (Evans, 1989;Reich et al., 1995;Reich et al., 1997;Reich et al., 1999;Wright et al., 2004), specific leaf area, leaf life span (Reich et al., 1999;Wright et al., 2004) and light use efficiency (Kergoat et al., 2008). Leaf N concentration expressed on a leaf area basis, also called leaf N content (N g m -2 ) has also been linked with chlorophyll content, Rubisco content (Evans, 35 1989) and photosynthetic capacity (Evans, 1989;Reich et al., 1995). At stand scale, canopy nitrogen concentration, which represents the leaf N concentration averaged over the stand canopy, has also been found to correlate with above ground Net Primary Productivity (NPP) (Reich, 2012), while canopy N content has been linked with the canopy light use efficiency (Green et al., 2003).Given their links to many vegetation processes, leaf and canopy N variables could be used to constrain N cycle modules in 40 global vegetation models. At the global scale, ample data is available to constrain models for the C cycle; however, data to constrain the N cycle are limited. Currently, canopy N data is not widely available and canopy N sampling campaigns are timeconsuming and thus expensive tasks. Moreover, upscaling from local sampling campaign measurements represents an additional limitation. In this perspective, local, regional or even global remotely sensed canopy N estimates will be a valuable addition, enabling us to collect information in a less time intensive and expensive manner than traditional on-field sampling 45 campaigns. Such near global canopy N estimates will be beneficial as input in global vegetation models or to calibrate and validate these models.Currently, different remote sensing techniques have been applied to detect canopy N in terrestrial vegetation. Imaging spectrometry from either airborne or spaceborne sensors coupled with different analysis methods, including partial least squares regression (PLS), continuu...

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“…For each nutrient, the PLSR model with the minimum root mean PRESS was selected. For flush model comparison, the model with the least number of latent factors with a van der Voet T 2 significance level greater than 0.10 was selected (Townsend et al 2003). The van der Voet T 2 is a test statistic that indicates whether model residuals are significantly greater than residuals in the model with the lowest error (Tobias 1995).…”

Section: Indexmentioning

confidence: 99%

Predicting macronutrient concentrations from loblolly pine leaf reflectance across local and regional scales

Stein

Thomas

Lorentz

et al. 2014

GIScience & Remote Sensing

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Given the economic importance of loblolly pine (Pinus taeda) in the southeastern US, there is a need to establish efficient methods of detecting potential nutrient deficiencies that may limit productivity. This study evaluated the use of remote sensing for macronutrient assessment in loblolly pine. Reflectance-based models were developed at two spatial scales: (1) a natural nutrient gradient across the species' range, and (2) localized fertilization and genotype treatments in North Carolina and Virginia. Fascicles were collected regionally from 237 samples of 3 flushes at 18 sites, and locally from 72 trees with 2 fertilization treatments and 6 genotypes. Sample spectral reflectance was calculated using a spectroradiometer, and nutrient concentrations were measured with dry combustion and wet chemical digestion. Results were analyzed statistically using nutrient correlations with reflectance and common vegetation indices, and partial least squares regression (PLSR). PLSR performed well at the regional scale, with R 2 values for nitrogen, phosphorus, potassium, calcium, and magnesium of 0. 81, 0.70, 0.68, 0.42, and 0.51, respectively. No model successfully predicted nutrients at local sites for any treatment or canopy stratum. This discrepancy implies that a large nutrient range and/or spatial scale may be necessary to model loblolly pine nutrients with spectral reflectance.

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Application of imaging spectroscopy to mapping canopy nitrogen in the forests of the central appalachian mountains using hyperion and aviris

Cited by 152 publications

References 32 publications

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

Regional detection of canopy nitrogen in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index

Predicting macronutrient concentrations from loblolly pine leaf reflectance across local and regional scales

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