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- School of Natural Resources: Faculty Publications (3)
- United States Geological Survey: Staff Publications (3)
- Department of Earth and Atmospheric Sciences: Faculty Publications (1)
- Geography and the Environment: Graduate Student Capstones (1)
- Mathematics, Physics, and Computer Science Faculty Articles and Research (1)
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Articles 1 - 9 of 9
Full-Text Articles in Other Environmental Sciences
Impact Of Deadly Dust Storms (May 2018) On Air Quality, Meteorological, And Atmospheric Parameters Over The Northern Parts Of India, Sudipta Sarkar, Akshansa Chauhan, Rajesh Kumar, Ramesh P. Singh
Impact Of Deadly Dust Storms (May 2018) On Air Quality, Meteorological, And Atmospheric Parameters Over The Northern Parts Of India, Sudipta Sarkar, Akshansa Chauhan, Rajesh Kumar, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and …
Spectrally Based Bathymetric Mapping Of A Dynamic, Sandbedded Channel: Niobrara River, Nebraska, Usa, E. Dilbone, C.J. Legleiter, J.S. Alexander, B. Mcelroy
Spectrally Based Bathymetric Mapping Of A Dynamic, Sandbedded Channel: Niobrara River, Nebraska, Usa, E. Dilbone, C.J. Legleiter, J.S. Alexander, B. Mcelroy
United States Geological Survey: Staff Publications
Methods for spectrally based mapping of river bathymetry have been developed and tested in clear‐flowing, gravel‐bed channels, with limited application to turbid, sandbed rivers. This study used hyperspectral images and field surveys from the dynamic, sandy Niobrara River to evaluate three depth retrieval methods. The first regressionbased approach, optimal band ratio analysis (OBRA), paired in situ depth measurements with image pixel values to estimate depth. The second approach used ground‐based field spectra to calibrate an OBRA relationship. The third technique, image‐to‐depth quantile transformation (IDQT), estimated depth by linking the cumulative distribution function (CDF) of depth to the CDF of an …
A Model Of The Effects Of Deforestation On Local Climate In The North Cascades, Monica R. H. Jasper
A Model Of The Effects Of Deforestation On Local Climate In The North Cascades, Monica R. H. Jasper
Geography and the Environment: Graduate Student Capstones
Changes in areal extent of land cover types may lead to alterations in the surface energy budget that contribute to anthropogenic climate forcing. This study examines the effects of deforestation in the Cascade Range on local temperature. Temperature sensors were installed in 14 forest stands, taking measurements for one year. Estimated tree age, circumference, and species were recorded to calculate stand density index. Satellite imagery was used to calculate shade fraction from spectral mixture analysis, which is a proxy for canopy structure and density. These data were used to construct seasonal cycles of temperature to model variation with stand density …
Informative Spectral Bands For Remote Green Lai Estimation In C3 And C4 Crops, Oz Kira, Anthony L. Nguy-Robertson, Timothy J. Arkebauer, Raphael Linker, Anatoly A. Gitelson
Informative Spectral Bands For Remote Green Lai Estimation In C3 And C4 Crops, Oz Kira, Anthony L. Nguy-Robertson, Timothy J. Arkebauer, Raphael Linker, Anatoly A. Gitelson
School of Natural Resources: Faculty Publications
Green leaf area index (LAI) provides insight into the productivity, physiological and phenological status of vegetation. Measurement of spectral reflectance offers a fast and nondestructive estimation of green LAI. A number of methods have been used for the estimation of green LAI; however, the specific spectral bands employed varied widely among the methods and data used. Our objectives were (i) to find informative spectral bands retained in three types of methods, neural network (NN), partial least squares (PLS) regression and vegetation indices (VI), for estimating green LAI in maize (a C4 species) and soybean (a C3 species); (ii) to assess …
Productivity, Absorbed Photosynthetically Active Radiation, And Light Use Efficiency In Crops: Implications For Remote Sensing Of Crop Primary Production, Anatoly A. Gitelson, Yi Peng, Timothy J. Arkebauer, Andrew E. Suyker
Productivity, Absorbed Photosynthetically Active Radiation, And Light Use Efficiency In Crops: Implications For Remote Sensing Of Crop Primary Production, Anatoly A. Gitelson, Yi Peng, Timothy J. Arkebauer, Andrew E. Suyker
School of Natural Resources: Faculty Publications
Vegetation productivity metrics such as gross primary production (GPP) at the canopy scale are greatly affected by the efficiency of using absorbed radiation for photosynthesis, or light use efficiency (LUE). Thus, close investigation of the relationships between canopy GPP and photosynthetically active radiation absorbed by vegetation is the basis for quantification of LUE. We used multiyear observations over irrigated and rainfed contrasting C3 (soybean) and C4 (maize) crops having different physiology, leaf structure, and canopy architecture to establish the relationships between canopy GPP and radiation absorbed by vegetation and quantify LUE. Although multiple LUE definitions are reported in the literature, …
Multi-Scale Evaluation Of Light Use Efficiency In Modis Gross Primary Productivity For Croplands In The Midwestern United States, Qinchuan Xin, Mark Broich, Andrew E. Suyker, Le Yu, Peng Gong
Multi-Scale Evaluation Of Light Use Efficiency In Modis Gross Primary Productivity For Croplands In The Midwestern United States, Qinchuan Xin, Mark Broich, Andrew E. Suyker, Le Yu, Peng Gong
School of Natural Resources: Faculty Publications
Satellite remote sensing provides continuous observations of land surfaces, thereby offering opportunities for large-scale monitoring of terrestrial productivity. Production Efficiency Models (PEMs) have been widely used in satellite-based studies to simulate carbon exchanges between the atmosphere and ecosystems. However, model parameterization of the maximum light use efficiency (ε*GPP) varies considerably for croplands in agricultural studies at different scales. In this study, we evaluate cropland ε*GPP in the MODIS Gross Primary Productivity (GPP) model (MOD17) using in situ measurements and inventory datasets across the Midwestern US. The site-scale calibration using 28 site-years tower measurements derives ε*GPP values …
Merging Remote Sensing Data And National Agricultural Statistics To Model Change In Irrigated Agriculture, Jesslyn F. Brown, Md Shahriar Pervez
Merging Remote Sensing Data And National Agricultural Statistics To Model Change In Irrigated Agriculture, Jesslyn F. Brown, Md Shahriar Pervez
United States Geological Survey: Staff Publications
Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High …
Extending Airborne Electromagnetic Surveys For Regional Active Layer And Permafrost Mapping With Remote Sensing And Ancillary Data, Yukon Flats Ecoregion, Central Alaska, Neal J. Pastick, M. Torre Jorgenson, Bruce K. Wylie, Burke J. Minsley, Lei Ji, Michelle A. Walvoord, Bruce D. Smith, Jared D. Abraham, Joshua R. Rose
Extending Airborne Electromagnetic Surveys For Regional Active Layer And Permafrost Mapping With Remote Sensing And Ancillary Data, Yukon Flats Ecoregion, Central Alaska, Neal J. Pastick, M. Torre Jorgenson, Bruce K. Wylie, Burke J. Minsley, Lei Ji, Michelle A. Walvoord, Bruce D. Smith, Jared D. Abraham, Joshua R. Rose
United States Geological Survey: Staff Publications
Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
Effects Of Lightning And Other Meteorological Factors On Fire Activity In The North American Boreal Forest: Implications For Fire Weather Forecasting, David Peterson, Jun Wang, Charles Ichoku, Lorraine Remer
Effects Of Lightning And Other Meteorological Factors On Fire Activity In The North American Boreal Forest: Implications For Fire Weather Forecasting, David Peterson, Jun Wang, Charles Ichoku, Lorraine Remer
Department of Earth and Atmospheric Sciences: Faculty Publications
The effects of lightning and other meteorological factors on wildfire activity in the North American boreal forest are statistically analyzed during the fire seasons of 2000–2006 through an integration of the following data sets: the MODerate Resolution Imaging Spectroradiometer (MODIS) level 2 fire products, the 3-hourly 32-km gridded meteorological data from North American Regional Reanalysis (NARR), and the lightning data collected by the Canadian Lightning Detection Network (CLDN) and the Alaska Lightning Detection Network (ALDN). Positive anomalies of the 500 hPa geopotential height field, convective available potential energy (CAPE), number of cloud-to-ground lightning strikes, and the number of consecutive dry …