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Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sensing of Environment
, 2005
"... Abstract MODIS primary production products (MOD17) are the first regular, near-real-time data sets for repeated monitoring of vegetation primary production on vegetated land at 1-km resolution at an 8-day interval. But both the inconsistent spatial resolution between the gridded meteorological data ..."
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Cited by 76 (8 self)
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Abstract MODIS primary production products (MOD17) are the first regular, near-real-time data sets for repeated monitoring of vegetation primary production on vegetated land at 1-km resolution at an 8-day interval. But both the inconsistent spatial resolution between the gridded meteorological data and MODIS pixels, and the cloud-contaminated MODIS FPAR/LAI (MOD15A2) retrievals can introduce considerable errors to Collection4 primary production (denoted as C4 MOD17) results. Here, we aim to rectify these problems through reprocessing key inputs to MODIS primary vegetation productivity algorithm, resulting in improved Collection5 MOD17 (here denoted as C5 MOD17) estimates. This was accomplished by spatial interpolation of the coarse resolution meteorological data input and with temporal filling of cloud-contaminated MOD15A2 data. Furthermore, we modified the Biome Parameter Look-Up
C.: Assessing the carbon balance of circumpolar Arctic tundra using remote sensing and process modelling, Ecol
- Appl
, 2007
"... Abstract. This paper reviews the current status of using remote sensing and process-based modeling approaches to assess the contemporary and future circumpolar carbon balance of Arctic tundra, including the exchange of both carbon dioxide and methane with the atmosphere. Analyses based on remote se ..."
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Cited by 25 (1 self)
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Abstract. This paper reviews the current status of using remote sensing and process-based modeling approaches to assess the contemporary and future circumpolar carbon balance of Arctic tundra, including the exchange of both carbon dioxide and methane with the atmosphere. Analyses based on remote sensing approaches that use a 20-year data record of satellite data indicate that tundra is greening in the Arctic, suggesting an increase in photosynthetic activity and net primary production. Modeling studies generally simulate a small net carbon sink for the distribution of Arctic tundra, a result that is within the uncertainty range of field-based estimates of net carbon exchange. Applications of processbased approaches for scenarios of future climate change generally indicate net carbon sequestration in Arctic tundra as enhanced vegetation production exceeds simulated increases in decomposition. However, methane emissions are likely to increase dramatically, in response to rising soil temperatures, over the next century. Key uncertainties in the response of Arctic ecosystems to climate change include uncertainties in future fire regimes and uncertainties relating to changes in the soil environment. These include the response of soil decomposition and respiration to warming and deepening of the soil active layer, uncertainties in precipitation and potential soil drying, and distribution of wetlands. While there are numerous uncertainties in the projections of process-based models, they generally indicate that Arctic tundra will be a small sink for carbon over the next century and that methane emissions will increase considerably, which implies that exchange of greenhouse gases between the atmosphere and Arctic tundra ecosystems is likely to contribute to climate warming.
Net primary production and canopy nitrogen in a temperate forest landscape: An analysis using imaging spectroscopy, modeling, and field data
- Ecosystems
, 2005
"... Understanding spatial patterns of net primary pro-duction (NPP) is central to the study of terrestrial ecosystems, but efforts are frequently hampered by a lack of spatial information regarding factors such as nitrogen availability and site history. Here, we examined the degree to which canopy nitro ..."
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Cited by 23 (5 self)
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Understanding spatial patterns of net primary pro-duction (NPP) is central to the study of terrestrial ecosystems, but efforts are frequently hampered by a lack of spatial information regarding factors such as nitrogen availability and site history. Here, we examined the degree to which canopy nitrogen can serve as an indicator of patterns of NPP at the Bartlett Experimental Forest in New Hampshire by linking canopy nitrogen estimates from two high spectral resolution remote sensing instruments with field measurements and an ecosystem model. Predicted NPP across the study area ranged from less than 700 g m)2 year)1 to greater than 1300 g m)2 year)1 with a mean of 951 g m)2 year)1. Spatial patterns
Potential of MODIS ocean bands for estimating CO2 flux from terrestrial vegetation: A novel approach.
- Geophysical Research Letters,
, 2004
"... [1] A physiologically-driven spectral index using two ocean-color bands of MODIS satellite sensor showed great potential to track seasonally changing photosynthetic light use efficiency (LUE) and stress-induced reduction in net primary productivity (NPP) of terrestrial vegetation. Based on these fi ..."
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Cited by 9 (0 self)
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[1] A physiologically-driven spectral index using two ocean-color bands of MODIS satellite sensor showed great potential to track seasonally changing photosynthetic light use efficiency (LUE) and stress-induced reduction in net primary productivity (NPP) of terrestrial vegetation. Based on these findings, we developed a simple ''continuous field'' model solely based on remotely sensed spectral data that could explain 88% of variability in flux-tower based daily NPP. For the first time, such a procedure is successfully tested at landscape level using satellite imagery. These findings highlight the unexplored potential of narrow-band satellite sensors to improve estimates of spatial and temporal distribution in terrestrial carbon flux.
Estimating vegetation cover in an urban environment based on Landsat ETM + imagery: A case study in Phoenix, USA
"... Studies of urban ecological systems can be greatly enhanced by combining ecosystem modelling and remote sensing which often requires establishing statistical relationships between field and remote sensing data. At the Central Arizona–Phoenix Long-Term Ecological Research (CAPLTER) site in the southw ..."
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Cited by 9 (0 self)
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Studies of urban ecological systems can be greatly enhanced by combining ecosystem modelling and remote sensing which often requires establishing statistical relationships between field and remote sensing data. At the Central Arizona–Phoenix Long-Term Ecological Research (CAPLTER) site in the southwestern USA, we estimated vegetation abundance from Landsat ETM + acquired at three dates by computing vegetation indices (NDVI and SAVI) and conducting linear spectral mixture analysis (SMA). Our analyses were stratified by three major land use/land covers—urban, agricultural, and desert. SMA, which provides direct measures of vegetation end member fraction for each pixel, was directly compared with field data and with the independent accuracy assessment dataset constructed from air photos. Vegetation index images with highest correlation with field data were used to construct regression models whose predictions were validated with the accuracy assessment dataset. We also investigated alternative regression methods, recognizing the inadequacy of traditional Ordinary Least Squares (OLS) in biophysical remote sensing. Symmetrical regressions—reduced major axis (RMA) and bisector ordinary least squares (OLSbisector)—were evaluated and compared with OLS. Our results indicated that SMA was a more accurate approach to vegetation quantification in urban and agricultural land uses, but had a poor accuracy when applied to desert vegetation. Potential sources of errors and some improvement recommendations are discussed.
A working framework for quantifying carbon sequestration in disturbed land mosaics. Environ
- Manage
, 2004
"... ABSTRACT / We propose a working framework for future studies of net carbon exchange (NCE) in disturbed land-scapes at broad spatial scales based on the central idea that landscape-level NCE is determined by the land mosaic, in-cluding its age structure. Within this framework, we argue that the area- ..."
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Cited by 5 (0 self)
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ABSTRACT / We propose a working framework for future studies of net carbon exchange (NCE) in disturbed land-scapes at broad spatial scales based on the central idea that landscape-level NCE is determined by the land mosaic, in-cluding its age structure. Within this framework, we argue that the area-of-edge-influence (AEI), which is prevalent in many disturbed, fragmented landscapes, should constitute a distinct ecosystem type since numerous studies have indicated unique ecological properties within these areas. We present and justify four working hypotheses currently being tested in northern Wisconsin, based on this framework: (1) the area of an ecosystem that is influenced by structural edges (e.g., AEI) has NCE that is significantly different from the ecosystem inte-rior; (2) age structure and composition of an ecosystem play critical roles in determining the ecosystem’s contribution to
Phenology and gross primary production of two dominant savanna woodland ecosystems in Southern Africa. Remote Sens. Environ
"... Accurate estimation of gross primary production (GPP) of savanna woodlands is needed for evaluating the terrestrial carbon cycle at various spatial and temporal scales. The eddy covariance (EC) technique provides continuous measurements of net CO 2 exchange (NEE) between terrestrial ecosystems and ..."
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Cited by 2 (0 self)
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Accurate estimation of gross primary production (GPP) of savanna woodlands is needed for evaluating the terrestrial carbon cycle at various spatial and temporal scales. The eddy covariance (EC) technique provides continuous measurements of net CO 2 exchange (NEE) between terrestrial ecosystems and the atmosphere. Only a few flux tower sites were run in Africa and very limited observational data of savanna woodlands in Africa are available. Although several publications have reported on the seasonal dynamics and interannual variation of GPP of savanna vegetation through partitioning the measured NEE data, current knowledge about GPP and phenology of savanna ecosystems is still limited. This study focused on two savanna woodland flux tower sites in Botswana and Zambia, representing two dominant savanna woodlands (mopane and miombo) and climate patterns (semi-arid and semi-humid) in Southern Africa. Phenology of these savanna woodlands was delineated from three vegetation indices derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and GPP estimated from eddy covariance measurements at flux tower sites (GPP EC ). The Vegetation Photosynthesis Model (VPM), which is driven by satellite images and meteorological data, was also evaluated, and the results showed that the VPM-based GPP estimates (GPP VPM ) were able to track the seasonal dynamics of GPP EC . The total GPP VPM and GPP EC within the plant growing season defined by a water-related vegetation index differed within the range of ± 6%. This study suggests that the VPM is a valuable tool for estimating GPP of semi-arid and semi-humid savanna woodland ecosystems in Southern Africa.
FOREST ECOSYSTEM DYNAMICS USING SPOT AND MODIS SATELLITE IMAGES
"... A 9-year time series of the SPOT NDVI for two deciduous (Fagus sylvatica, Quercus cerris/Quercus frainetto) and one evergreen conifer (Pinus nigra) forest was constructed in order to perform a dynamics analysis. The deciduous species show similar response to precipitation and temperature. Their prod ..."
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A 9-year time series of the SPOT NDVI for two deciduous (Fagus sylvatica, Quercus cerris/Quercus frainetto) and one evergreen conifer (Pinus nigra) forest was constructed in order to perform a dynamics analysis. The deciduous species show similar response to precipitation and temperature. Their productivity depends on winter precipitation and spring temperature. The conifer seems to be unaffected by precipitation variations and is dependent on winter temperature. Additionally, 2-year NDVI, EVI and NDWI time series extracted by MODIS images were used to investigate temporal dynamics of the deciduous ecosystems. NDVI and EVI are strongly correlated with LAI and NDWI with leaf water potential. An empirical model for the estimation of Gross Primary Productivity (GPP) – based on field measured data – was constructed and used as a reference in order to evaluate the MODIS GPP product. It seems that MODIS underestimates GPP and does not closely follow its seasonal fluctuations. A more accurate Light Use Efficiency (LUE) model – based mostly on satellite data – is presented. 1.
The limits to models in ecology
- Eds.), Models in Ecosystem Science
, 2003
"... Models are convenient tools to summarize, organize and synthesize knowl-edge or data in forms allowing the formulation of quantitative, probabilistic, or Bayesian statements about possible or future states of the modeled entity. Mod-eling has a long tradition in Earth sciences, where the capacity to ..."
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Cited by 1 (0 self)
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Models are convenient tools to summarize, organize and synthesize knowl-edge or data in forms allowing the formulation of quantitative, probabilistic, or Bayesian statements about possible or future states of the modeled entity. Mod-eling has a long tradition in Earth sciences, where the capacity to predict ecol-ogically relevant phenomena is ancient (e.g. motion of planets and stars). Since then, models have been developed to examine phenomena at many levels of complexity, from physiological systems and individual organisms to whole ecosystems and the globe. The demand for reliable predictions, and therefore, models is rapidly rising, as environmental issues become a prominent concern of society. In addition, the enormous technological capacity to generate and share data creates a consider-able pressure to assimilate these data into coherent syntheses, typically pro-vided by models. Yet, modeling still encompasses a very modest fraction of the ecological literature, and modeling skills are remarkably sparse among ecolo-gists (Chapter 3). The growing demand for models is in contrast with their lim-
