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At least 37 records · Page 2

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↗

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↗

More Surprises from the Moon

Even with the naked eye, the dark, extensive plains of the lunar maria can be clearly seen on the surface of the Moon. The maria formed after meteorite impacts created large craters that later filled with lava flows. Mare volcanism is the dominant type of volcanic activity on the Moon and the lavas are made up of basaltic rocks. However, non-mare volcanic deposits, though rare, have been observed on the lunar nearside. The deposits are distinguished from the maria because they are compositionally more evolved rich in silica, potassium and thorium. The deposits are limited in surface extent and it was unknown whether similar non-mare volcanism occurred at all on the Moon s farside. Writing in Nature Geoscience, Jolliff et al. report using Lunar Reconnaissance Orbiter images and compositional data to identify the rare occurrence of more compositionally evolved volcanic deposits in an isolated area on the Moon s farside. In the 1960s and 1970s, rock and soil samples were collected by the Apollo and Luna missions, by the USA and USSR respectively. This material represents a geologic treasure trove that continues to provide a wealth of information about the Moon and its evolution, and it was a very small fraction of these samples that gave the first hint that non-mare volcanic activity might have occurred. The samples contained fragments of complex volcanic rocks that were unrelated to the maria basalts. Violent bombardment of the Moon by meteorite impacts has caused significant mixing of the rocks at its surface, so the fragments could have had a source hundreds or thousands of kilometres away. The origin of the fragments was unknown. Several decades later, the Lunar Prospector mission used a gamma-ray spectrometer to map the distribution and abundance of various elements, including thorium, on the Moon s surface. The maps identified a distinct and large area of high thorium concentration, as well as several smaller, but equally peculiar areas of high thorium concentration on the nearside of the Moon (Fig. 1). The rocks that contained high thorium contents also exhibited geomorphological and spectral features that were typical of volcanic deposits, and so the thorium hotspots were thought to represent non-mare volcanism on the nearside of the Moon. A relatively large region with extremely high thorium concentrations - the Compton-Belkovich thorium anomaly - was also identified on the Moon s farside. This thorium hotspot was particularly unusual because it was completely isolated, alone on the farside of the Moon, far from the nearest maria. No high-resolution image data were available for this region, so a definitive interpretation of the source of this isolated anomaly has been impossible.

Petro, Noah↗

Uncertainties in Ice-Sheet Altimetry from a Spaceborne 1064-nm Single-Channel Lidar Due to Undetected Thin Clouds

In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface-elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases the photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to as atmospheric path delay. This paper complements previous studies in the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus- cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and an analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an example, the average path delays for FOV = 167 microrad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica are illustrated.

Yang, Yuekui↗

SLAR image interpretation keys for geographic analysis

A means for side-looking airborne radar (SLAR) imagery to become a more widely used data source in geoscience and agriculture is suggested by providing interpretation keys as an easily implemented interpretation model. Interpretation problems faced by the researcher wishing to employ SLAR are specifically described, and the use of various types of image interpretation keys to overcome these problems is suggested. With examples drawn from agriculture and vegetation mapping, direct and associate dichotomous image interpretation keys are discussed and methods of constructing keys are outlined. Initial testing of the keys, key-based automated decision rules, and the role of the keys in an information system for agriculture are developed.

Coiner, J. C.↗

SAR in support of geological investigations of the Sudbury structure

Imaging radar is an important contributing source of information for a range of geological problems and environments. Airborne SAR and ERS-1 data integrated with other geoscience datasets are being used in an attempt to characterize the crustal fracturing associated with the Sudbury structure. This presentation highlights examples of integrated and composite images aimed at facilitating the interpretation of the Sudbury structure. This work is the result of an ongoing cooperative multidisciplinary SAR study of the basin carried out by the Canada Center for Remote Sensing, Ontario's provincial Remote Sensing Office, the Ontario Geological Survey, and the Geological Survey of Canada.

Singhroy, V.↗

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Cetin, Haluk↗

Efficient Kriging via Fast Matrix-Vector Products

Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrixvector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.

Memarsadeghi, Nargess↗

A Fast Implementation of the ISODATA Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to ISODATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Memarsadeghi, Nargess↗

A Fast Implementation of the Isodata Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to IsoDATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Memarsadeghi, Nargess↗

Scaling Estimates of Vegetation Structure in Amazonian Tropical Forests Using Multi-Angle MODIS Observations

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r(exp 2)= 0.54, RMSE= 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy(0.52 less than or equal to r(exp 2) less than or equal to 0.61; p less than 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (sigma(sup 0)) from SeaWinds/QuikSCAT presented an r(exp 2) of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.

MODIS↗

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Image Data over the Atmospheric Radiation Measurement Sites

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 (micro)m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-(micro)m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer (AVHRR)) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 degrees N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

Detection↗

Mars Observer: A global mapping mission

Mars Observer will be launched in September 1991, arrive at Mars in August 1993, and begin mapping in December 1993. Mapping will be conducted from a low-altitude (400 km) polar orbit over a period of one Martian year (687 days). Each of the seven instruments will be able to observe Mars continuously over this period. The scientific mission centers on global Geoscience and Climatology observations of the Mars atmosphere, surface, and interior. The seven experiments involve gamma-ray and neutron spectroscopy, magnetometry, surface and atmospheric imaging, atmospheric sounding, laser altimetry, gravity mapping, and thermal emission spectroscopy.

Palluconi, Frank K.↗

Characterization of spacecraft and environmental disturbances on a SmallSat

The objective of this study is to model the on-orbit vibration environment encountered by a SmallSat. Vibration control issues are common to the Earth observing, imaging, and microgravity communities. A spacecraft may contain dozens of support systems and instruments each a potential source of vibration. The quality of payload data depends on constraining vibration so that parasitic disturbances do not affect the payload's pointing or microgravity requirement. In practice, payloads are designed incorporating existing flight hardware in many cases with nonspecific vibration performance. Thus, for the development of a payload, designers require a thorough knowledge of existing mechanical devices and their associated disturbance levels. This study evaluates a SmallSat mission and seeks to answer basic questions concerning on-orbit vibration. Payloads were considered from the Earth observing, microgravity, and imaging communities. Candidate payload requirements were matched to spacecraft bus resources of present day SmallSats. From the set of candidate payloads, the representative payload GLAS (Geoscience Laser Altimeter System) was selected. The requirements of GLAS were considered very stringent for the 150 - 500 kg class of payloads. Once the payload was selected, a generic SmallSat was designed in order to accommodate the payload requirements (weight, size, power, etc.). This study seeks to characterize the on-orbit vibration environment of a SmallSat designed for this type of mission and to determine whether a SmallSat can provide the precision pointing and jitter control required for earth observing payloads.

Johnson, Thomas A.↗

Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 1: AVIRIS Workshop

This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D. C. October 25-29, 1993 The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, October 25-26 (the summaries for this workshop appear in this volume, Volume 1); The Thermal Infrared Multispectral Scanner (TMIS) workshop, on October 27 (the summaries for this workshop appear in Volume 2); and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, October 28-29 (the summaries for this workshop appear in Volume 3).

Green, Robert O.↗

Summaries of the 4th Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop

This is volume 2 of a three volume set of publications that contain the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on October 25-26. The summaries for this workshop appear in Volume 1. The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27. The summaries for this workshop appear in Volume 2. The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29. The summaries for this workshop appear in Volume 3.

Realmuto, Vincent J.↗