There is recent indication that the boreal forests may be providing a significant Carbon sink whose quantification could be key in balancing the global Carbon budget. This project uses the recently acquired JERS-1 synthetic aperture radar (SAR) data over the North American boreal zone, which was collected as part of the Global Boreal Forest Mapping (GBFM) project, and ERS-1/2 SAR data, to quantify components of the Carbon cycle not reasonably obtained by other means. There are two distinct, but closely related, objectives in this project:
We are developing these maps on a 1-Km resolution scale, compatible with existing land-cover maps of the region derived from AVHRR. We have already developed the basic algorithms needed for both objectives during previous projects, in particular, BOREAS. These algorithms were developed for local scales, using multifrequency and multipolarization radar data from AIRSAR and SIR-C. Here, we extend these algorithms to the larger north-American boreal region and modify them for the two frequency-polarization combinations provided by JERS-1 and ERS-1/2. We will study the effects of the limited frequency and polarization parameters on derived products. JERS-1 data are available for nearly the entire region over two seasons. ERS-1/2 data are available to us for the area within the Alaska SAR Facility (ASF) receiving station mask for frequent coverages since 1991. These algorithms will provide the necessary ground work for the upcoming ALOS/PALSAR, Envisat, and Radarsat-2 missions, which will enable more accurate (due to their multipolarization capability) multitemporal generation of the same data products.
It is generally understood that the terrestrial carbon sink required to balance the global carbon budget could be located in the forested land of the Northern Hemisphere. The uncertainties of the magnitude and distribution of the sink, however, vary greatly and is the subject of several national and global scientific research programs, such as the Planned North American Carbon Program (NACP), Carbo-Europe, etc. The main goal of the NACP is to quantify and assess the role of various components of the carbon sink over North America. Among these components, the amount of carbon stock in forests and its spatial distribution play a major role in achieving this goal. Credible information on the woody biomass of forests is of significant economic value for the global multi-billion dollar timber industry and for the future market for carbon trade. Therefore, the overall objective of this investigation is to derive the spatial distribution of the forest biomass carbon stock of North America (US and Canada) for the beginning of this century by using a combination of forest inventory data and satellite remote sensing. This product will provide strong constraints on both the magnitude and the distribution of the net carbon uptake of the forests of this region.
We propose to use statistical regression and physically based models in conjunction with forest inventory data to estimate the woody biomass carbon content at a high resolution from the synergism of optical (MODIS, MISR) and radar (JERS-1and ALOS) remote sensing data. The results will be validated using detailed site-specific data in North America from various sources (US & Canadian Forest Service, LTER, BOREAS, etc.) and the information enhancement from the synergistic use of Terra and radar data will be quantified. The constraints on the magnitude of net carbon uptake by forests will be assessed by performing a series of comparative studies such as: 1) testing the spatial consistency of the derived biomass with forest inventory data for the US and Canada, and 2) evaluating the uncertainties of our method with respect to forest inventory data.
This proposal is directed to the EOS science Data Analysis and Modeling Research part of the NRA-03-OES-02, which calls for "research that will answer key ESE science questions defined in the ESE Research Strategy." By combining Terra (MODIS and MISR) and radar (JERS-1) data, the proposed research addresses key ESE research questions on Response (How do ecosystems respond to and affect global environmental change and the carbon cycle?), Forcing (What changes are occurring in global land cover and land use, and what are their causes?), and Variability (How are the global ecosystems changing?).
One of the greatest challenges facing humankind is the preservation of biodiversity. Accelerating rates of deforestation, along with landscape fragmentation and changes in climate patterns, are altering the characteristics of habitats and are predicted to result in unprecedented losses of species over the next few decades. Currently, considerable effort and resources are directed toward identifying and conserving regions of high species diversity. While defining "biodiversity hotspots" represents an important step toward prioritizing areas for conservation, adhering strictly to the current definition of "hotspot" will result in the loss of regions that are important in generating and maintaining adaptive diversity.
A series of recent studies have shown that the processes that generate and sustain biodiversity are highly structured spatially and depend critically on the distribution of both biotic and abiotic environmental variables. While the general spatial patterns of these processes can potentially be understood, their dynamic nature and their response to rapid changes of environment are yet to be understood and quantified. Predictive models of species distribution and diversity that combine biological, spatial, and temporally dynamic environmental data are important in quantifying patterns and processes of diversity.
The objective of this investigation is to develop a model that can integrate biological point locality and process data (e.g. genetic and morphological information and estimates of connectivity among populations) with remotely sensed environmental parameters to quantify patterns of species range and diversity in tropical regions. We propose to test and perform comparative analysis of this model using plants (tree species) and a wide taxonomic representation of vertebrate species (including species of birds, primates, and frogs) over two distinct tropical regions with pronounced environmental gradients: the western Amazonian region of South America (including the eastern slopes of the Andes), and the forest-savanna ecotones of Central Africa. The model will complement the existing GIS-based distribution models by: 1) introducing statistical and estimation approaches suitable for incorporating climate data and remote sensing detected (e.g. NDVI, spectral metrics) and derived environmental parameters (e.g. LAI, heterogeneity) at various spatial scales, 2) including biological and ecological process data in quantifying spatial patterns of diversity, and 3) allowing dynamic simulations to quantify the impacts of current and future anthropogenic and climate changes.
The key deliverables of the project are: 1) a dynamic spatial model for species distribution with embedded process based rules, 2) distribution patterns of target taxa and associated processes over Pan-Amazonian and Central African ecotonal gradients, and 3) demonstration of climate and human impacts on patterns and processes associated with species range and diversity. The remotely sensed data layers, the process of integration with biological data, and the model itself will be released from NASA and/or UCLA web-based systems.
The proposed research is directed to the cross-disciplinary scientific problems outlined under the NRA-03-OES-03 announcement and focuses on two main ESE Research Strategy questions on Variability (How are the global ecosystems changing?) and Response (How does the Earth system respond to natural and human-induced changes?).
The aerodynamic roughness length (Z0) is an important parameter to determine the vertical gradients of mean wind speed and the conditions for momentum transfer over a vegetated or bare rough surface. Over vegetated surfaces, the aerodynamic roughness length has a simple one-to-one relationship with the rms height of the vegetation at the top of the canopy. Once this roughness length is determined for a surface, it does not change with wind speed, stability or stress. During the LBA experiment the Regional Atmospheric Modeling System (RAMS) with flexible horizontal and vertical resolution will be used in conjunction with other models to simulate the atmospheric circulation and trace gas concentration and transport at various scales. This model is suitable to determine the effect of surface roughness parameter at trace gas transport both at local level for LBA study areas and on at the regional level for the entire Amazon basin. In this work we use two radar remote sensing data sets to estimate the vegetation roughness, independently and synergistically. The following steps outlines the LBA research project.
The effects of deforestation on health are diverse, and are becoming increasingly apparent with the highly publicized recent outbreaks of several zoonoses. In this proposal, researchers at UCLA, San Francisco State University, JPL/NASA, UC Davis, and the Institute of Ecology at Vilnius University, Lithuania, will form a multidisciplinary team to study the ecology of infectious blood-borne pathogens in African rainforest birds. We propose to determine how long-term anthropogenic changes in habitats affect the prevalence of infectious diseases in natural populations. Over the past 13 years, we have collected a unique set of more than 3500 individual blood samples from over 200 rainforest bird species in a variety of habitats across Cameroon, Equatorial Guinea, the Ivory Coast and Uganda. Sampling sites have included locations in the ecotone (the transitional region between the contiguous rainforest and savanna), in primary and secondary rainforests, and in sites experiencing intensive logging. Significantly, our samples include sites both before and after degradation, permitting a unique examination into the direct effects of human induced habitat alterations. Using complementary techniques of blood smear analysis, established PCR-based detection methods, and molecular phylogenetics, samples will be assayed for the pathogens that cause avian malaria, trypanosomiasis, filiariasis and tuberculosis. These diseases in birds, which have been correlated with fitness, have very similar pathologies to their human counterparts, making the study of birds an excellent model system. To assess the ecological correlates of the disease prevalence we will employ satellite imagery data with appropriate ground-truthing. These data will provide information about changes in temperature, rainfall, forest fragmentation and greenness over a longitudinal time frame, as well as data for cross-sectional comparisons between habitat types. We will address these three specific objectives:
The proposed research is significant because it will provide data on how human ecological change affects the prevalence of avian diseases and will subsequently use these data to build models that could predict how these changes may influence future epizootics. The proposed work leverages a unique collection of samples and makes use of our established resources and expertise in tropical field ecology, parasitology, molecular genetics, and remote sensing to address important interactions between diseases, their hosts, and their changing environments.
Our research will involve the training of students and researchers at a minority serving institution (SFSU), and abroad, in Lithuania and Africa. These collaborations will inevitably aid in the development of young scientists. In addition, once we ascertain basic ecological factors that contribute to the spread of disease, we shall be able to predict how future land use changes may affect disease outbreaks; and thus make informed suggestions that may influence policy decisions.
This instrument incubator program (IIP) proposal is directed towards development of a system that delivers science data and products to directly address the current NASA Research Announcement (NRA) science priority of measuring soil moisture "under a substantial vegetation canopy and reaching a useful depth within the uppermost soil layer" under the Global Water and Energy Cycle science topic. It enables measurement and derivation of data products not obtained from any other current, planned, or proposed instrument, with a solution that offers high science value through a low-mass and, in the long-term, low-cost approach. The proposed system is a synthetic aperture radar (SAR) operating at the two low frequencies of 420 MHz (UHF, P-band) and 118 MHz (VHF) to enable the vegetation and deep soil penetration. The future mission scenario is achieved from a sun-synchronous orbit of 1313 Km altitude, with a swath width of 430Km, incidence angle ranges of 17-30 degrees, resolution of 1 Km, and a 7-day exact repeat consistent with the temporal scale of variations of the subcanopy and subsurface soil moisture. Complimentary to proposed soil moisture missions at L-band, which aim at retrieving the top surface soil moisture for low- or no-vegetation areas at 3-day sampling intervals, this proposal optimizes the system design for under-vegetation and deep soil moisture, in addition to simultaneous measurement of the soil moisture at the top few centimeters. This is to be achieved by a light-weight 30-m mesh reflector antenna, fed by a dual-frequency single-structure feed array, which is the key technology item in this proposal.