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Articles 1 - 7 of 7

Full-Text Articles in Social and Behavioral Sciences

Land Surface Anomalies Preceding The 2010 Russian Heat Wave And A Link To The North Atlantic Oscillation, C. K. Wright, K. M. De Beurs, G. M. Henebry Dec 2014

Land Surface Anomalies Preceding The 2010 Russian Heat Wave And A Link To The North Atlantic Oscillation, C. K. Wright, K. M. De Beurs, G. M. Henebry

Natural Resource Management Faculty Publications

The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April–May–June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to …


Improved Time Series Land Cover Classification By Missing-Observation-Adaptive Nonlinear Dimensionality Reduction, David P. Roy, L. Yan Dec 2014

Improved Time Series Land Cover Classification By Missing-Observation-Adaptive Nonlinear Dimensionality Reduction, David P. Roy, L. Yan

GSCE Faculty Publications

Dimensionality reduction (DR) is a widely used technique to address the curse of dimensionality when high-dimensional remotely sensed data, such as multi-temporal or hyperspectral imagery, are analyzed. Nonlinear DR algorithms, also referred to as manifold learning algorithms, have been successfully applied to hyperspectral data and provide improved performance compared with linear DR algorithms. However, DR algorithms cannot handle missing data that are common in multi-temporal imagery. In this paper, the Laplacian Eigenmaps (LE) nonlinear DR algorithm was refined for application to multi-temporal satellite data with large proportions of missing data. Refined LE algorithms were applied to 52-week Landsat time series …


Sensitivity Of Mesoscale Modeling Of Smoke Direct Radiative Effect To The Emission Inventory: A Case Study In Northern Sub-Saharan African Region, Feng Zhang, Jun Wang, Charles Ichoku, Edward J. Hyer, Zhifeng Yang, Cui Ge, Shenjian Su, Xiaoyang Zhang, Shobha Kondragunta, Christine Wiedinmyer, Johannes W. Kaiser, Arlindo Da Silva Jul 2014

Sensitivity Of Mesoscale Modeling Of Smoke Direct Radiative Effect To The Emission Inventory: A Case Study In Northern Sub-Saharan African Region, Feng Zhang, Jun Wang, Charles Ichoku, Edward J. Hyer, Zhifeng Yang, Cui Ge, Shenjian Su, Xiaoyang Zhang, Shobha Kondragunta, Christine Wiedinmyer, Johannes W. Kaiser, Arlindo Da Silva

GSCE Faculty Publications

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of …


Interannual Variation In Biomass Burning And Fire Seasonality Derived From Geostationary Satellite Data Across The Contiguous United States From 1995 To 2011, Xiaoyang Zhang, Shobha Kondragunta, David Roy Jun 2014

Interannual Variation In Biomass Burning And Fire Seasonality Derived From Geostationary Satellite Data Across The Contiguous United States From 1995 To 2011, Xiaoyang Zhang, Shobha Kondragunta, David Roy

GSCE Faculty Publications

Wildfires exhibit a strong seasonality that is driven by climatic factors and human activities. Although the fire seasonality is commonly determined using burned area and fire frequency, it could also be quantified using biomass consumption estimates that directly represent biomass loss (a combination of the area burned and the fuel loading). Therefore, in this study a data set of long-term biomass consumed was derived from geostationary satellite data to explore the interannual variation in the fire seasonality and the possible impacts of climate change and land management practices across the Contiguous United States (CONUS). Specifically, daily biomass consumed data were …


Landsat-8: Science And Product Vision For Terrestrial Global Change Research, David P. Roy, M. A. Wulder, T. R. Loveland, C. E. Woodcock, R. G. Allen, M. C. Anderson, D. Helder, J. R. Irons, D. M. Johnson, R. Kennedy, T. A. Scambos, C. B. Schaaf, J. R. Schott, Y. Sheng, E. F. Vermote, A. S. Belward, R. Bindchadler, W. B. Cohen, F. Gao, J. D. Hipple, P. Hostert, J. Huntington, C. O. Justice, A. Kilic, V Kovalskyy, Z. P. Lee, L. Lymburner, J. G. Masek, J. Mccorkel, Y. Shuai, R. Trezza, J. Vogelmann, R. H. Wynne, Z. Zhu Mar 2014

Landsat-8: Science And Product Vision For Terrestrial Global Change Research, David P. Roy, M. A. Wulder, T. R. Loveland, C. E. Woodcock, R. G. Allen, M. C. Anderson, D. Helder, J. R. Irons, D. M. Johnson, R. Kennedy, T. A. Scambos, C. B. Schaaf, J. R. Schott, Y. Sheng, E. F. Vermote, A. S. Belward, R. Bindchadler, W. B. Cohen, F. Gao, J. D. Hipple, P. Hostert, J. Huntington, C. O. Justice, A. Kilic, V Kovalskyy, Z. P. Lee, L. Lymburner, J. G. Masek, J. Mccorkel, Y. Shuai, R. Trezza, J. Vogelmann, R. H. Wynne, Z. Zhu

GSCE Faculty Publications

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, twothermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat …


Fire Type Classification In The Brazilian Tropical Moist Forest Biome, Sanath Kumar Sathyachandran Jan 2014

Fire Type Classification In The Brazilian Tropical Moist Forest Biome, Sanath Kumar Sathyachandran

Electronic Theses and Dissertations

The Brazilian Tropical Moist Forest Biome (BTMFB) is “Earth’s greatest biological treasure and a major component of the earth system” and forest degradation and deforestation by fire is a serious issue in this region. Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably …


Evaluation And Application Of A New Shape-Sensitive Metric Useful For Characterizing Both Spectral Curves And Lidar Waveforms, Eric Ariel L. Salas Jan 2014

Evaluation And Application Of A New Shape-Sensitive Metric Useful For Characterizing Both Spectral Curves And Lidar Waveforms, Eric Ariel L. Salas

Electronic Theses and Dissertations

This dissertation seeks to investigate hyperspectral and waveform LiDAR datasets through a new analytical framework called Moment Distance method that uses a metric derived from the shape of the curve (spectral or waveform). In the case of hyperspectral data, the shape of the reflectance curve should unmask fine points of the spectra usually not considered by existing band-specific indices. To explore the advantages and shortcomings of this new approach, leaf and canopy hyperspectral reflectance samples were simulated using the physicallybased models PROSPECT (a leaf model) and SAIL (a canopy model). Sensitivity analysis was conducted with the goal of understanding the …