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Ranson, K. Jon

Publications and source records attributed to Ranson, K. Jon.

At least 19 records

Digital Beamforming Synthetic Aperture Radar Developments at NASA Goddard Space Flight Center

Advanced Digital Beamforming (DBF) Synthetic Aperture Radar (SAR) technology is an area of research and development pursued at the NASA Goddard Space Flight Center (GSFC). Advanced SAR architectures enhances radar performance and opens a new set of capabilities in radar remote sensing. DBSAR-2 and EcoSAR are two state-of-the-art radar systems recently developed and tested. These new instruments employ multiple input-multiple output (MIMO) architectures characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instruments have been developed to support several disciplines in Earth and Planetary sciences. This paper describes the radars advanced features and report on the latest SAR processing and calibration efforts.

Wide band

Digital Beamforming Synthetic Aperture Radar (DBSAR): Performance Analysis During the Eco-3D 2011 and Summer 2012 Flight Campaigns

The Digital Beamforming Synthetic Aperture radar (DBSAR) is a state-of-the-art airborne radar developed at NASA/Goddard for the implementation, and testing of digital beamforming techniques applicable to Earth and planetary sciences. The DBSAR measurements have been employed to study: The estimation of vegetation biomass and structure - critical parameters in the study of the carbon cycle; The measurement of geological features - to explore its applicability to planetary science by measuring planetary analogue targets. The instrument flew two test campaigns over the East coast of the United States in 2011, and 2012. During the campaigns the instrument operated in full polarimetric mode collecting data from vegetation and topography features.

SAR

Development of NASA's Next Generation L-Band Digital Beamforming Synthetic Aperture Radar (DBSAR-2)

NASA's Next generation Digital Beamforming SAR (DBSAR-2) is a state-of-the-art airborne L-band radar developed at the NASA Goddard Space Flight Center (GSFC). The instrument builds upon the advanced architectures in NASA's DBSAR-1 and EcoSAR instruments. The new instrument employs a 16-channel radar architecture characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instrument has been design to support several disciplines in Earth and Planetary sciences. The instrument was recently completed, and tested and calibrated in a anechoic chamber.

SAR

The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

EcoSAR is a new synthetic aperture radar (SAR) instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. The instrument uses a phased-array beamforming architecture and supports full polarimetric measurements and single pass interferometry. This Instrument development is part of NASA's Earth Science Technology Office Instrument Incubator Program (ESTO IIP).

SAR

Taking Stock of Circumboreal Forest Carbon With Ground Measurements, Airborne and Spaceborne LiDAR

The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55degN in eastern Canada and from 55 to 60degN in eastern Eurasia. Both of these regions are expected to warm >3 C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content.

Biomass

Forest Biomass Mapping From Lidar and Radar Synergies

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper.

Sun, Guoqing

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.

Ranson, K. Jon

Simulation Studies of Forest Structure using 3D Lidar and Radar Models

The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.

Sun, Guoqing

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Ranson, K. Jon

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Ranson, K. Jon

Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature

The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.

Sun, Guoqing

Landsat-based Analysis of Mountain Forest-tundra Ecotone Response to Climate Trends in Sayan Mountains

observations of temperatures Siberia has shown a several degree warming over the past 30 years. It is expected that forest will respond to warming at high latitudes through increased tree growth and northward or upward slope migration. migration. Tree response to climate trends is most likely observable in the forest-tundra ecotone, where temperature mainly limits tree growth. Making repeated satellite observations over several decades provides an opportunity to track vegetation response to climate change. Based on Landsat data of the Sayan Mountains, Siberia, there was an increase in forest stand crown closure and an upward tree-line shift in the of the forest-tundra ecotone during the last quarter of the 2oth century,. On-ground observations, supporting these results, also showed regeneration of Siberian pine in the alpine tundra, and the transformation of prostrate Siberian pine and fir into arboreal (upright) forms. During this time period sparse stands transformed into closed stands, with existing closed stands increasing in area at a rate of approx. 1 %/yr, and advancing their upper border at a vertical rate of approx. 1.0 m/yr. In addition, the vertical rate of regeneration propagation is approx. 5 m/yr. It was also found that these changes correlated positively with temperature trends

Kharuk, Viatcheslav I.

SPOT-VEG Based Analysis of Siberian Silkmoth Outbreak

The spatial and temporal dynamics of an outbreak of the Siberian silkmoth were correlated with topographic features of the affected area using SPOT-VEG data and a high resolution digital elevation model (DEM). In 2002-2003 an outbreak affected approximately 20,000 ha in the South Siberian mountains of Russia. The outbreak began between the elevations of approximately 430- 480 m and on southwest slopes with steepness < 5 degrees. As the pest searched for food it moved up and down slope, resulting in an elevation distribution split within a range of approximately 390-540 m and slope steepness up to 15 degrees. In the final phase the azimuth distribution of damaged stands became even. The correlation between the initial phase and topographic features can be used to prioritize monitoring forest areas most vulnerable to destruction by pests.

Kharuk, Viatcheslav I.

Merging IceSAT GLAS and Terra MODIS Data in Order to Derive Forest Type Specific Tree Heights in the Central Siberian Boreal Forest

Mapping of boreal forest's type, biomass, and other structural parameters are critical for understanding of the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. We believe the nature of the forest structure information available from MISR and GLAS can be used to help identify forest type, age class, and estimate above ground biomass levels beyond that now possible with MODIS alone. The ground measurements will be used to develop relationships between remote sensing observables and forest characteristics and provide new information for understanding forest changes with respect to environmental change. Lidar is a laser altimeter that determines the distance from the instrument to the physical surface by measuring the time elapsed between the pulse emission and the reflected return. Other studies have shown that the returned signal may identify multiple returns originating from trees, building and other objects and permits the calculation of their height. Studies using field data have shown that lidar data can provide estimates of structural parameters such as biomass, stand volume and leaf area index and allows remarkable differentiation between primary and secondary forest. NASA's IceSAT Geoscience Laser Altimeter System (GLAS) was launched in January 2003 and collected data during February and September of that year. This study used data acquired over our study sites in central Siberia to examine the GLAS signal as a source of forest height and other structural characteristics. The purpose of our Siberia project is to improve forest cover maps and produce above-ground biomass maps of the boreal forest in Northern Eurasia from MODIS by incorporating structural information inherent in the Terra MISR and ICESAT Geoscience Laser Altimeter System (GLAS) instruments. A number of forest cover classifications exist for the boreal forest. We believe the limiting factor in these products is the lack of structural information, particularly in the vertical dimension. The emphasis of this project is to improve upon satellite maps of boreal forest structure parameters (i.e. height and biomass) using temporal, multi-angle, and vertical profile information of GLAS data. The existing and near future lidar data is useful for demonstrating these techniques and pursuing current estimates. Future lidar missions may be several years in the future, so we will work other new data sets that may aide in biomass estimates such as ALOS PALSAR We will continue this work to produce an accurate map of current above ground forest phytomass/carbon storage possible for the study area. We plan to develop, test, and integrate remote sensing methods for extracting forest canopy structure measures. We are compiling our field measurements and will compare them with the remote sensing methods where possible. We also be able to produce a realistic error bound on the remotely sensed carbon estimates.

Ranson, K. Jon

MODIS NDVI Response Following Fires in Siberia

The Siberian boreal forest is considered a carbon sink but may become an important source of carbon dioxide if climatic warming predictions are correct. The forest is continually changing through various disturbance mechanisms such as insects, logging, mineral exploitation, and especially fires. Patterns of disturbance and forest recovery processes are important factors regulating carbon flux in this area. NASA's Terra MODIS provides useful information for assessing location of fires and post fire changes in forests. MODIS fire (MOD14), and NDVI (MOD13) products were used to examine fire occurrence and post fire variability in vegetation cover as indicated by NDVI. Results were interpreted for various post fire outcomes, such as decreased NDVI after fire, no change in NDVI after fire and positive NDVI change after fire. The fire frequency data were also evaluated in terms of proximity to population centers, and transportation networks.

Ranson, K. Jon

NASA's EOS Terra Mission Update

NASA launched the Terra spacecraft, first major platform for the Earth Observing System, in December 1999. The platform has five instruments that acquire global data for a wide variety of scientific studies of the Earth's land, oceans, and atmosphere. The Terra mission initiated a process of long-term measurements designed to assess and monitor the health of the Earth. This paper provides an overview of the Terra mission and the status of the spacecraft and instruments during the past year.

Ranson, K. Jon

Contribution of Chlorophyll Fluorescence to the Reflectance of Corn Foliage

To assess the contribution of chlorophyll fluorescence (ChlF) to apparent reflectance (Ra) in the red/far-red, spectra were collected on a C4 agricultural species (corn, Zea Mays L.) under conditions ranging from nitrogen deficiency to excess. A significant contribution of ChlF to Ra was observed, with on average 10-25% at 685nm and 2-6% at 740nm of Ra being due to ChlF. Higher ChlF was consistently measured from the abaxial leaf surface as compared to the adaxial. Using 350-665nm excitation, the study confirms the trends in three ChlF ratios established previously by active F technology, suggesting that the ChlF utility this technology has developed for monitoring vegetation physiological status is likely applicable also under natural solar illumination.

Campbell, Petya K. Entcheva

Combining Radar and Optical Data for Forest Disturbance Studies

Disturbance is an important factor in determining the carbon balance and succession of forests. Until the early 1990's researchers have focused on using optical or thermal sensors to detect and map forest disturbances from wild fires, logging or insect outbreaks. As part of a NASA Siberian mapping project, a study evaluated the capability of three different radar sensors (ERS, JERS and Radarsat) and an optical sensor (Landsat 7) to detect fire scars, logging and insect damage in the boreal forest. This paper describes the data sets and techniques used to evaluate the use of remote sensing to detect disturbance in central Siberian forests. Using images from each sensor individually and combined an assessment of the utility of using these sensors was developed. Transformed Divergence analysis and maximum likelihood classification revealed that Landsat data was the single best data type for this purpose. However, the combined use of the three radar and optical sensors did improve the results of discriminating these disturbances.

Ranson, K. Jon