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Chen J.,Beijing Normal University | Zhu X.,Beijing Normal University | Zhu X.,Ohio State University | Vogelmann J.E.,Eros | And 3 more authors.
Remote Sensing of Environment | Year: 2011

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in 2003, resulting in about 22% of the pixels per scene not being scanned. The SLC failure has seriously limited the scientific applications of ETM+ data. While there have been a number of methods developed to fill in the data gaps, each method has shortcomings, especially for heterogeneous landscapes. Based on the assumption that the same-class neighboring pixels around the un-scanned pixels have similar spectral characteristics, and that these neighboring and un-scanned pixels exhibit similar patterns of spectral differences between dates, we developed a simple and effective method to interpolate the values of the pixels within the gaps. We refer to this method as the Neighborhood Similar Pixel Interpolator (NSPI). Simulated and actual SLC-off ETM+ images were used to assess the performance of the NSPI. Results indicate that NSPI can restore the value of un-scanned pixels very accurately, and that it works especially well in heterogeneous regions. In addition, it can work well even if there is a relatively long time interval or significant spectral changes between the input and target image. The filled images appear reasonably spatially continuous without obvious striping patterns. Supervised classification using the maximum likelihood algorithm was done on both gap-filled simulated SLC-off data and the original "gap free" data set, and it was found that classification results, including accuracies, were very comparable. This indicates that gap-filled products generated by NSPI will have relevance to the user community for various land cover applications. In addition, the simple principle and high computational efficiency of NSPI will enable processing large volumes of SLC-off ETM+ data. © 2011.


Friedl M.A.,Boston University | Sulla-Menashe D.,Boston University | Tan B.,Earth Resources Technology Inc. | Schneider A.,University of Wisconsin - Madison | And 3 more authors.
Remote Sensing of Environment | Year: 2010

Information related to land cover is immensely important to global change science. In the past decade, data sources and methodologies for creating global land cover maps from remote sensing have evolved rapidly. Here we describe the datasets and algorithms used to create the Collection 5 MODIS Global Land Cover Type product, which is substantially changed relative to Collection 4. In addition to using updated input data, the algorithm and ancillary datasets used to produce the product have been refined. Most importantly, the Collection 5 product is generated at 500-m spatial resolution, providing a four-fold increase in spatial resolution relative to the previous version. In addition, many components of the classification algorithm have been changed. The training site database has been revised, land surface temperature is now included as an input feature, and ancillary datasets used in post-processing of ensemble decision tree results have been updated. Further, methods used to correct classifier results for bias imposed by training data properties have been refined, techniques used to fuse ancillary data based on spatially varying prior probabilities have been revised, and a variety of methods have been developed to address limitations of the algorithm for the urban, wetland, and deciduous needleleaf classes. Finally, techniques used to stabilize classification results across years have been developed and implemented to reduce year-to-year variation in land cover labels not associated with land cover change. Results from a cross-validation analysis indicate that the overall accuracy of the product is about 75% correctly classified, but that the range in class-specific accuracies is large. Comparison of Collection 5 maps with Collection 4 results show substantial differences arising from increased spatial resolution and changes in the input data and classification algorithm. © 2009 Elsevier Inc.


Skarke A.,Mississippi State University | Ruppel C.,U.S. Geological Survey | Kodis M.,Brown University | Brothers D.,U.S. Geological Survey | Lobecker E.,Earth Resources Technology Inc.
Nature Geoscience | Year: 2014

Methane emissions from the sea floor affect methane inputs into the atmosphere, ocean acidification and de-oxygenation, the distribution of chemosynthetic communities and energy resources. Global methane flux from seabed cold seeps has only been estimated for continental shelves, at 8 to 65 Tg CH 4 yr -1, yet other parts of marine continental margins are also emitting methane. The US Atlantic margin has not been considered an area of widespread seepage, with only three methane seeps recognized seaward of the shelf break. However, massive upper-slope seepage related to gas hydrate degradation has been predicted for the southern part of this margin, even though this process has previously only been recognized in the Arctic. Here we use multibeam water-column backscatter data that cover 94,000 km 2 of sea floor to identify about 570 gas plumes at water depths between 50 and 1,700 m between Cape Hatteras and Georges Bank on the northern US Atlantic passive margin. About 440 seeps originate at water depths that bracket the updip limit for methane hydrate stability. Contemporary upper-slope seepage there may be triggered by ongoing warming of intermediate waters, but authigenic carbonates observed imply that emissions have continued for more than 1,000 years at some seeps. Extrapolating the upper-slope seep density on this margin to the global passive margin system, we suggest that tens of thousands of seeps could be discoverable. © 2014 Macmillan Publishers Limited. All rights reserved.


Wu X.,National Oceanic and Atmospheric Administration | Yu F.,Earth Resources Technology Inc.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013

A cold bias of ∼-2 K was found for Channel 6 (13.3 μm) of the Imager instrument on the 13th of Geostationary Operational Environmental Satellite (GOES-13) during its postlaunch tests. Similar bias was found previously for GOES-12 and for other instruments (the High Resolution Infrared Radiation Sounder, the Moderate Resolution Imaging Spectroradiometer, and the Spinning Enhanced Visible and Infrared Imager) in the similar spectral region. It was often suspected that the spectral response function (SRF) of these instruments may be in error; in some cases, it had been demonstrated that an altered SRF can eliminate most of the differences between the measured and the expected values. Using products recently developed for the Global Space-based Inter-Calibration System, this paper concluded that an SRF error is the root cause for the GOES Imager Channel 6 bias. Based on this theory, an algorithm was developed to correct for the bias. Application of this correction to GOES-13 Imager Channel 6 resulted in an SRF shift of -2.1cm-1. The remaining biases have mean of nearly zero and much reduced standard deviation and are independent of the thermal structure of the interlaying atmosphere. This correction has also been successfully applied of other channels and of other GOES, which was described in a companion paper. © 2012 IEEE.


Zhang X.,Earth Resources Technology Inc. | Goldberg M.D.,National Oceanic and Atmospheric Administration | Yu Y.,National Oceanic and Atmospheric Administration
Agricultural and Forest Meteorology | Year: 2012

While determining vegetation phenology from the time series of historical satellite data has been widely investigated throughout the last decade, little effort has been devoted to real-time monitoring and short-term forecasting. The latter is more important for numerical weather modeling, ecosystem forecasting, forest and crop management, and health risk warning. In this study we developed a prototype approach for the real-time monitoring and short-term forecasting of fall foliage status (including low coloration, moderate coloration, near-peak coloration, peak coloration, and post-peak coloration) using temporal satellite observations. The algorithm combined the climatology of vegetation phenology and temporally available satellite observations to establish a set of potential temporal trajectories of foliage development at a given time. These trajectories were used to identify foliage coloration phases in real time, to predict the occurrence of future phenological events, and, furthermore, to analyze the uncertainty of monitoring and forecasting. With an increase in satellite observations, monitoring and forecasting were continuously updated. The approach developed was tested using MODIS (Moderate Resolution Imaging Spectroradiometer) data at a spatial resolution of 500. m across northeastern North America and evaluated using field measurements at the Harvard Forests of the northeastern United States and standard MODIS foliage coloration phases. The results indicate that short-term forecasting can be well implemented in more than half a month before the occurrence of a foliage phase, and that the accuracy of the real-time monitoring of both near-peak-coloration and peak-coloration occurrence is less than 5 days in most mixed forests and deciduous forests. © 2012 Elsevier B.V..


Zhang X.,Earth Resources Technology Inc. | Goldberg M.D.,National Oceanic and Atmospheric Administration
Remote Sensing of Environment | Year: 2011

Fall foliage coloration is a phenomenon that occurs in many deciduous trees and shrubs worldwide. Measuring the phenology of fall foliage development is of great interest for climate change, the carbon cycle, ecology, and the tourist industry; but little effort has been devoted to monitoring the regional fall foliage status using remotely-sensed data. This study developed an innovative approach to monitoring fall foliage status by means of temporally-normalized brownness derived from MODIS (Moderate Resolution Imaging Spectroradiometer) data. Specifically, the time series of the MODIS Normalized Difference Vegetation Index (NDVI) was smoothed and functionalized using a sigmoidal model to depict the continuous dynamics of vegetation growth. The modeled temporal NDVI trajectory during the senescent phase was further combined with the mixture modeling to deduce the temporally-normalized brownness index which was independent of the surface background, vegetation abundance, and species composition. This brownness index was quantitatively linked with the fraction of colored and fallen leaves in order to model the fall foliage coloration status. This algorithm was tested by monitoring the fall foliage coloration phase using MODIS data in northeastern North America from 2001 to 2004. The MODIS-derived timing of foliage coloration phases was compared with in-situ measurements, which showed an overall absolute mean difference of less than 5. days for all foliage coloration phases and about 3. days for near peak coloration and peak coloration. This suggested that the fall foliage coloration phase retrieved from the temporally-normalized brownness index was qualitatively realistic and repeatable. © 2010 Elsevier Inc.


Ganguly S.,Bay Area Environmental Research Institute | Friedl M.A.,Boston University | Tan B.,Earth Resources Technology Inc. | Zhang X.,Earth Resources Technology Inc. | Verma M.,Boston University
Remote Sensing of Environment | Year: 2010

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatio-temporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of variance suggesting that the algorithm is reliable and robust, except in the tropics where some systematic differences are observed. Finally, comparisons with ground data suggest that the algorithm is performing well, but that end of season metrics associated with vegetation senescence and dormancy have higher uncertainties than start of season metrics. © 2010 Elsevier Inc.


In antenna design, based on application requirements various criteria such as bandwidth, directivity, radiation efficiency, construction, cost, and fabrication difficulty are used for product evaluation. Among these criteria, design of an antenna with ultra-wide bandwidth has increasingly been demanded for next generation wireless communication systems. Purpose of this research is to developing such a broad band antenna by using a hybrid structure consists of a monopole antenna (with variations) and multi-annular dielectric resonator antennas. From simulation via Ansys HFSSTM, one of our designs reaches a high bandwidth ratio beyond 5:1. Further, one variation of the design can obtain an even broader bandwidth ratio.


Blythe J.N.,Earth Resources Technology Inc. | Dadi U.,Earth Resources Technology Inc.
Environmental Science and Policy | Year: 2012

An approach to coastal management has been proposed that will better address important social-environmental problems, using a concept called knowledge integration. Knowledge integration involves bridging previously distinct technical subject areas to allow holistic, generally better, and more effective environmental policy. Science-management integration is a specific type of integration which may precede and enable other types of integration efforts for coastal management. Technical information may be contributed from many scientific disciplines in making decisions about coastal environment. Additional knowledge may be necessary so that technical information from the sciences is used in a manner consistent with scientific applications. This manuscript illustrates this point by focusing on two different areas of science relevant to coastal management, biodiversity informatics from ecological science and ocean currents modelling from physical oceanography. In addition, a use case is presented for the Coral Triangle Initiative, which illustrates general issues involved in developing capacity for science-management integration by coastal managers. The use of knowledge integration technology is discussed as a method of providing coastal managers access to expert knowledge for reliable use of technical information in coastal management applications. © 2012 Elsevier Ltd.


Shuai Y.,Earth Resources Technology Inc. | Shuai Y.,NASA | Masek J.G.,NASA | Gao F.,Earth Resources Technology Inc. | And 2 more authors.
Remote Sensing of Environment | Year: 2011

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos may be used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of ±0.02-0.05 for these validation sites during available clear days in 2003-2005, with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers. © 2011 Elsevier Inc.

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