160 research outputs found
Satellite evidence for significant biophysical consequences of the âGrain for Greenâ Program on the Loess Plateau in China
Afforestation has been implemented worldwide as regional and national policies to address environmental problems and to improve ecosystem services. China\u27s central government launched the âGrain for Greenâ Program (GGP) in 1999 to increase forest cover and to control soil erosion by converting agricultural lands on steep slopes to forests and grasslands. Here a variety of satellite data products from the Moderate Resolution Imaging Spectroradiometer were used to assess the biophysical consequences of the GGP for the Loess Plateau, the pilot region of the program. The average tree cover of the plateau substantially increased because of the GGP, with a relative increase of 41.0%. The GGP led to significant increases in enhanced vegetation index (EVI), leaf area index, and the fraction of photosynthetically active radiation absorbed by canopies. The increase in forest productivity as approximated by EVI was not driven by elevated air temperature, changing precipitation, or rising atmospheric carbon dioxide concentrations. Moreover, the afforestation significantly reduced surface albedo, leading to a positive radiative forcing and a warming effect on the climate. The GGP also led to a significant decline in daytime land surface temperature and exerted a cooling effect on the climate. The GGP therefore has significant biophysical consequences by altering carbon cycling, hydrologic processes, and surface energy exchange and has significant feedbacks to the regional climate. The net radiative forcing on the climate depends on the offsetting of the negative forcing from carbon sequestration and higher evapotranspiration and the positive forcing from lower albedo
How does the global Moderate Resolution Imaging Spectroradiometer (MODIS) Fraction of Photosynthetically Active Radiation (FPAR) product relate to regionally developed land cover and vegetation products in a semi-arid Australian savanna?
Spatio-temporally variable information on total vegetation cover is highly relevant to water quality and land management in river catchments adjacent to the Great Barrier Reef, Australia. A time series of the global Moderate Resolution Imaging Spectroradiometer (MODIS) Fraction of Photosynthetically Active Radiation (FPAR; 2000-2006) and its underlying biome classification (MOD12Q1) were compared to national land cover and regional, remotely sensed products in the dry-tropical Burdekin River. The MOD12Q1 showed reasonable agreement with a classification of major vegetation groups for 94% of the study area. We then compared dry-seasonal, quality controlled MODIS FPAR observations to (i) Landsat-based woody foliage projective cover (wFPC) (2004) and (ii) MODIS bare ground index (BGI) observations (2001-2003). Statistical analysis of the MODIS FPAR revealed a significant sensitivity to Landsat wFPC-based Vegetation Structural Categories (VSC) and VSC-specific temporal variability over the 2004 dry season. The MODIS FPAR relation to 20 coinciding MODIS BGI dry-seasonal observations was significant (Ï < 0.001) for homogeneous areas of low wFPC. Our results show that the global MODIS FPAR can be used to identify VSC, represent VSC-specific variability of PAR absorption, and indicate that the amount, structure, and optical properties of green and non-green vegetation components contribute to the MODIS FPAR signal
On the use of MODIS EVI to assess gross primary productivity of North American ecosystems
[1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remoteâsensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remoteâsensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remoteâsensing data
Development and Extrapolation of a General Light Use Efficiency Model for the Gross Primary Production
The global carbon cycle is one of the large biogeochemical cycles spanning all living and non-living compartments of the Earth system. Against the background of accelerating global change, the scientific community is highly interested in analyzing and understanding the dynamics of the global carbon cycle and its complex feedback mechanism with the terrestrial biosphere. The international network FLUXNET was established to serve this aim with measurement towers around the globe.
The overarching objective of this thesis is to exploit the powerful combination of carbon flux measurements and satellite remote sensing in order to develop a simple but robust model for the gross primary production (GPP) of vegetation stands. Measurement data from FLUXNET sites as well as remote sensing data from the NASA sensor MODIS are exploited in a data-based model development approach. The well-established concept of light use efficiency is chosen as modeling framework. As a result, a novel gross primary production model is established to quantify the carbon uptake of forests and grasslands across a broad range of climate zones. Furthermore, an extrapolation scheme is derived, with which the model parameters calibrated at FLUXNET sites can be regionalized to pave the way for spatially continuous model applications
ESA - RESGROW: Epansion of the Market for EO Based Information Services in Renewable Energy - Biomass Energy sector
Biomass energy is of growing importance as it is widely recognised, both scientifically and politically, that the increase of atmospheric CO2 has led to an enhanced efficiency of the greenhouse effect and, as such, warrants concern for climate change. It is accepted (IPCC 2011 and just recently in the draft version of the IPCC 2013 report) that climate change is partly induced by humans notably by using fossil fuels. For reducing the use of oil or coal, biomass energy is receiving more and more attention as an additional energy source available regionally in large parts of the world. Effective management of renewable energy resources is critical for the European and the global energy supply system.
The future contribution of bioenergy to the energy supply strongly depends on its availability, in other words the biomass potential. Biomass potentials are currently mainly assessed on a national to regional or on a global level, with the bulk biomass potential allocated to the whole country. With certain biomass fractions being of low energy density, transport distances and thus their spatial distribution are crucial economic and ecological factors. For other biomass fractions a super-regional or global market is envisaged. Thus spatial information on biomass potentials is vital for the further expansion of bioenergy use.
This study, which is an updated version of a study carried out in 2007 in frame of the ENVISOLAR project, analyses the potential use of Earth Observation data as input for biomass models in order to assessment and manage of the biomass energy resources especially biomass potentials of agricultural and forest areas with high spatial resolution (typical 1km x 1km). In addition to a sorrow review of recent developments in data availability and approaches in comparison to its 2007â version, this study also includes a review on approaches to directly correlate remote sensing data with biomass estimations.
An overview of existing biomass models is given covering models using remote sensing data as input as well as models using only meteorological and/or management data as input. It covers the full life cycle from the planning stage to plant management and operations (Figure 1). Several groups of stakeholders were identified
New Methods for Measurements of Photosynthesis from Space
Our ability to close the Earth's carbon budget and predict feedbacks in a warming climate
depends critically on knowing where, when, and how carbon dioxide (CO2) is exchanged
between the land and atmosphere. In particular, determining the rate of carbon fixation by
the Earth's biosphere (commonly referred to as gross primary productivity, or GPP) and the
dependence of this productivity on climate is a central goal. Historically, GPP has been
inferred from spectral imagery of the land and ocean. Assessment of GPP from the color of
the land and ocean requires, however, additional knowledge of the types of plants in the
scene, their regulatory mechanisms, and climate variables such as soil moistureâjust the
independent variables of interest!
Sunlight absorbed by chlorophyll in photosynthetic organisms is mostly used to drive
photosynthesis, but some can also be dissipated as heat or reâradiated at longer wavelengths
(660â800 nm). This nearâinfrared light reâemitted from illuminated plants is termed solarinduced
fluorescence (SIF), and it has been found to strongly correlate with GPP. To advance
our understanding of SIF and its relation to GPP and environmental stress at the planetary
scale, the Keck Institute for Space Studies (KISS) convened a workshopâheld in Pasadena,
California, in August 2012âto focus on a newly developed capacity to monitor chlorophyll
fluorescence from terrestrial vegetation by satellite. This revolutionary approach for
retrieving global observations of SIF promises to provide direct and spatially resolved
information on GPP, an ideal bottomâup complement to the atmospheric net CO2 exchange
inversions.
Workshop participants leveraged our efforts on previous studies and workshops related to
the European Space Agencyâs FLuorescence EXplorer (FLEX) mission concept, which had
already targeted SIF for a possible satellite mission and had developed a vibrant research
community with many important publications. These studies, mostly focused on landscape,
canopy, and leafâlevel interpretation, provided the groundâwork for the workshop, which
focused on the global carbon cycle and synergies with atmospheric net flux inversions.
Workshop participants included key members of several communities: plant physiologists
with experience using active fluorescence methods to quantify photosynthesis; ecologists
and radiative transfer experts who are studying the challenge of scaling from the leaf to
regional scales; atmospheric scientists with experience retrieving photometric information
from spaceâborne spectrometers; and carbon cycle experts who are integrating new
observations into models that describe the exchange of carbon between the atmosphere,
land and ocean. Together, the participants examined the link between âpassiveâ fluorescence
observed from orbiting spacecraft and the underlying photochemistry, plant physiology and
biogeochemistry of the land and ocean.
This report details the opportunity for forging a deep connection between scientists doing
basic research in photosynthetic mechanisms and the more applied community doing
research on the Earth System. Too often these connections have gotten lost in empiricism
associated with the coarse scale of global models. Chlorophyll fluorescence has been a major
tool for basic research in photosynthesis for nearly a century. SIF observations from space,
although sensing a large footprint, probe molecular events occurring in the leaves below.
This offers an opportunity for direct mechanistic insight that is unparalleled for studies of
biology in the Earth System.
A major focus of the workshop was to review the basic mechanisms that underlie this
phenomenon, and to explore modeling tools that have been developed to link the biophysical
and biochemical knowledge of photosynthesis with the observableâin this case, the
radiance of SIFâseen by the satellite. Discussions led to the identification of areas where
knowledge is still lacking. For example, the inability to do controlled illumination
observations from space limits the ability to fully constrain the variables that link
fluorescence and photosynthesis.
Another focus of the workshop explored a âtopâdownâ view of the SIF signal from space.
Early studies clearly identified a strong correlation between the strength of this signal and
our best estimate of the rate of photosynthesis (GPP) over the globe. New studies show that
this observation provides improvements over conventional reflectanceâbased remote
sensing in detecting seasonal and environmental (particularly drought related) modulation
of photosynthesis. Apparently SIF responds much more quickly and with greater dynamic
range than typical greenness indices when GPP is perturbed. However, discussions at the
workshop also identified areas where topâdown analysis seemed to be âout in frontâ of
mechanistic studies. For example, changes in SIF based on changes in canopy light
interception and the light use efficiency of the canopy, both of which occur in response to
drought, are assumed equivalent in the topâdown analysis, but the mechanistic justification
for this is still lacking from the bottomâup side.
Workshop participants considered implications of these mechanistic and empirical insights
for largeâscale models of the carbon cycle and biogeochemistry, and also made progress
toward incorporating SIF as a simulated output in land surface models used in global and
regionalâscale analysis of the carbon cycle. Comparison of remotely sensed SIF with modelsimulated
SIF may open new possibilities for model evaluation and data assimilation,
perhaps leading to better modeling tools for analysis of the other retrieval from GOSAT
satellite, atmospheric CO2 concentration. Participants also identified another application for
SIF: a linkage to the physical climate system arising from the ability to better identify
regional development of plant water stress. Decreases in transpiration over large areas of a
continent are implicated in the development and âlockingâinâ of drought conditions. These
discussions also identified areas where current land surface models need to be improved in
order to enable this research. Specifically, the radiation transport treatments need dramatic
overhauls to correctly simulate SIF.
Finally, workshop participants explored approaches for retrieval of SIF from satellite and
groundâbased sensors. The difficulty of resolving SIF from the overwhelming flux of reflected
sunlight in the spectral region where fluorescence occurs was once a major impediment to
making this measurement. Placement of very high spectral resolution spectrometers on
GOSAT (and other greenhouse gasâsensing satellites) has enabled retrievals based on infilling
of solar Fraunhofer lines, enabling accurate fluorescence measurements even in the
presence of moderately thick clouds. Perhaps the most interesting challenge here is that
there is no readily portable groundâbased instrumentation that even approaches the
capability of GOSAT and other planned greenhouse gas satellites. This strongly limits scientistsâ ability to conduct groundâbased studies to characterize the footprint of the GOSAT
measurement and to conduct studies of radiation transport needed to interpret SIF
measurement.
The workshop results represent a snapshot of the state of knowledge in this area. New
research activities have sprung from the deliberations during the workshop, with
publications to follow. The introduction of this new measurement technology to a wide slice
of the community of Earth System Scientists will help them understand how this new
technology could help solve problems in their research, address concerns about the
interpretation, identify future research needs, and elicit support of the wider community for
research needed to support this observation.
Somewhat analogous to the original discovery that vegetation indices could be derived from
satellite measurements originally intended to detect clouds, the GOSAT observations are a
rare case in which a (fortuitous) global satellite dataset becomes available before the
research community had a consolidated understanding on how (beyond an empirical
correlation) it could be applied to understanding the underlying processes. Vegetation
indices have since changed the way we see the global biosphere, and the workshop
participants envision that fluorescence can perform the next indispensable step by
complementing these measurements with independent estimates that are more indicative of
actual (as opposed to potential) photosynthesis. Apart from the potential FLEX mission, no
dedicated satellite missions are currently planned. OCOâ2 and â3 will provide much more
data than GOSAT, but will still not allow for regional studies due to the lack of mapping
capabilities. Geostationary observations may even prove most useful, as they could track
fluorescence over the course of the day and clearly identify stressârelated downâregulation of
photosynthesis. Retrieval of fluorescence on the global scale should be recognized as a
valuable tool; it can bring the same quantum leap in our understanding of the global carbon
cycle as vegetation indices once did
ENHANCING CONSERVATION WITH HIGH RESOLUTION PRODUCTIVITY DATASETS FOR THE CONTERMINOUS UNITED STATES
Human driven alteration of the earthâs terrestrial surface is accelerating through land use changes, intensification of human activity, climate change, and other anthropogenic pressures. These changes occur at broad spatio-temporal scales, challenging our ability to effectively monitor and assess the impacts and subsequent conservation strategies. While satellite remote sensing (SRS) products enable monitoring of the earthâs terrestrial surface continuously across space and time, the practical applications for conservation and management of these products are limited. Often the processes driving ecological change occur at fine spatial resolutions and are undetectable given the resolution of available datasets. Additionally, the links between SRS data and ecologically meaningful metrics are weak. Recent advances in cloud computing technology along with the growing record of high resolution SRS data enable the development of SRS products that quantify ecologically meaningful variables at relevant scales applicable for conservation and management. The focus of my dissertation is to improve the applicability of terrestrial gross and net primary productivity (GPP/NPP) datasets for the conterminous United States (CONUS).
In chapter one, I develop a framework for creating high resolution datasets of vegetation dynamics. I use the entire archive of Landsat 5, 7, and 8 surface reflectance data and a novel gap filling approach to create spatially continuous 30 m, 16-day composites of the normalized difference vegetation index (NDVI) from 1986 to 2016. In chapter two, I integrate this with other high resolution datasets and the MOD17 algorithm to create the first high resolution GPP and NPP datasets for CONUS. I demonstrate the applicability of these products for conservation and management, showing the improvements beyond currently available products. In chapter three, I utilize this dataset to evaluate the relationships between land ownership and terrestrial production across the CONUS domain.
The main results of this work are three publically available datasets: 1) 30 m Landsat NDVI; 2) 250 m MODIS based GPP and NPP; and 3) 30 m Landsat based GPP and NPP. My goal is that these products prove useful for the wider scientific, conservation, and land management communities as we continue to strive for better conservation and management practices
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