Environmental Sciences Commons^™

Chlorophyll-Based Approach For Remote Estimation Of Crop Gross Primary Production: From In Situ Measurements To Satellite Imagery, Yi Peng

School of Natural Resources: Dissertations, Theses, and Student Research

The synoptic and accurate quantification of crop gross primary production (GPP) is essential for studying carbon budgets in croplands and monitoring crop status. The objective of this dissertation is to develop a quantitative technique to estimate crop GPP using remotely sensed data collected from close range to satellite altitudes. In this study, a model based on a recently developed paradigm, which relates crop GPP to a product of total crop chlorophyll content and incident radiation affecting vegetation photosynthesis, was justified for the remote estimation of GPP in crops. The model was tested with ground-observed incoming photosynthetically active radiation (PAR_{in …}

Arctic Cloud Macrophysical Characteristics From Cloudsat And Calipso, Yinghui Liu, Jeffrey R. Key, Steven A. Ackerman, Gerald G. Mace, Qiuqing Zhang

United States Department of Commerce: Staff Publications

The lidar and radar profiling capabilities of the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites provide opportunities to improve the characterization of cloud properties. An Arctic cloud climatology based on their observations may be fundamentally different from earlier Arctic cloud climatologies based on passive satellite observations, which have limited contrast between the cloud and underlying surface. Specifically, the Radar–Lidar Geometrical Profile product (RL-GEOPROF) provides cloud vertical profiles fromthe combination of active lidar and radar. Based on this data product for the period July 2006 to March 2011, this paper presents a new cloud macrophysical property characteristic analysis for …

State Of The Art Satellite And Airborne Marine Oil Spill Remote Sensing: Application To The Bp Deepwater Horizon Oil Spill, Ira Leifer, William J. Lehr, Debra Simecek-Beatty, Eliza Bradley, Roger Clark, Philip Dennison, Yongxiang Hu, Scott Matheson, Cathleen E. Jones, Benjamin Holt, Molly Reif, Dar A. Roberts, Jan Svejkovsky, Gregg Swayze, Jennifer Wozencraft

United States Department of Commerce: Staff Publications

The vast and persistent Deepwater Horizon (DWH) spill challenged response capabilities, which required accurate, quantitative oil assessment at synoptic and operational scales. Although experienced observers are a spill response's mainstay, few trained observers and confounding factors including weather, oil emulsification, and scene illumination geometry present challenges. DWH spill and impact monitoring was aided by extensive airborne and spaceborne passive and active remote sensing.

Oil slick thickness and oil-to-water emulsion ratios are key spill response parameters for containment/cleanup and were derived quantitatively for thick (>0.1 mm) slicks from AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data using a spectral library approach based …

View Angle Effects On Modis Snow Mapping In Forests, Qinchuan Xin, Curtis E. Woodcock, Jicheng Liu, Bin Tan, Rae A. Melloh, Robert E. Davis

United States Department of Commerce: Staff Publications

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical …

Monitoring Live Fuel Moisture Using Soil Moisture And Remote Sensing Proxies, Yi Qi, Philip E. Dennison, Jessica Spencer, David Riano

School of Natural Resources: Faculty Publications

Live fuel moisture (LFM) is an important fuel property controlling fuel ignition and fire propagation. LFM varies seasonally, and is controlled by precipitation, soil moisture, evapotranspiration, and plant physiology. LFM is typically sampled manually in the field, which leads to sparse measurements in space and time. Use of LFM proxies could reduce the need for field sampling while potentially improving spatial and temporal sampling density. This study compares soil moisture and remote sensing data to field-sampled LFM for Gambel oak (Quercus gambelii Nutt) and big sagebrush (Artemisia tridentata Nutt) in northern Utah. Bivariate linear regression models were constructed …

Estimation Of Chlorophyll-A Concentration In Turbid Productive Waters Using Airborne Hyperspectral Data, Wesley J. Moses, Anatoly Gitelson, Richard L. Perk, Daniela Gurlin, Donald C. Rundquist, Bryan C. Leavitt, Tadd M. Barrow, Paul Brakhage

School of Natural Resources: Faculty Publications

Algorithms based on red and near infra-red (NIR) reflectances measured using field spectrometers have been previously shown to yield accurate estimates of chlorophylla concentration in turbid productive waters, irrespective of variations in the bio-optical characteristics of water. The objective of this study was to investigate the performance of NIR-red models when applied to multi-temporal airborne reflectance data acquired by the hyperspectral sensor, Airborne Imaging Spectrometer for Applications (AISA), with non-uniform atmospheric effects across the dates of data acquisition. The results demonstrated the capability of the NIR-red models to capture the spatial distribution of chlorophyll-a in surface waters without the need …

Operational Meris-Based Nir-Red Algorithms For Estimating Chlorophyll-A Concentrations In Coastal Waters — The Azov Sea Case Study, Wesley J. Moses, Anatoly A. Gitelson, Sergey Berdnikov, Vladislav Saprygin, Vasily Povazhnyi

School of Natural Resources: Faculty Publications

We present here results that strongly support the use of MERIS-based NIR-red algorithms as standard tools for estimating chlorophyll-a (chl-a) concentration in turbid productive waters. The study was carried out as one of the steps in testing the potential of the universal applicability of previously developed NIR-red algorithms, which were earlier calibrated using a limited set of MERIS imagery and in situ data from the Azov Sea and the Taganrog Bay, Russia, and data that were synthetically generated using a radiative transfer model. We used an extensive set of MERIS imagery and in situ data collected over …

Arctic Cloud Macrophysical Characteristics From Cloudsat And Calipso, Yinghui Liu, Jeffrey R. Key, Steven A. Ackerman, Gerald G. Mace, Qiuqing Zhang

United States Department of Commerce: Staff Publications

The lidar and radar profiling capabilities of the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites provide opportunities to improve the characterization of cloud properties. An Arctic cloud climatology based on their observations may be fundamentally different from earlier Arctic cloud climatologies based on passive satellite observations, which have limited contrast between the cloud and underlying surface. Specifically, the Radar–Lidar Geometrical Profile product (RL-GEOPROF) provides cloud vertical profiles from the combination of active lidar and radar. Based on this data product for the period July 2006 to March 2011, this paper presents a new cloud macrophysical property characteristic analysis …

The Development Of A New Optical Total Suspended Matter Algorithm For The Chesapeake Bay, Michael Ondrusek, Eric Stengel, Christopher Kinkade, Ronald Vogel, Phillip Keegstra, Craig Hunter, Chunai Kim

United States Department of Commerce: Staff Publications

Sediment loading is one of the primary threats to the health of the Chesapeake Bay.We have developed a high resolution (250 m) ocean color satellite tool to monitor sediment concentrations in the Bay. In situ optical and sediment sampling is used to develop a total suspended matter (TSM) algorithm for the Chesapeake Bay. The Coastal Optical Characterization Experiment (COCE) is part of an ongoing effort to optically characterize processes and to develop regional remote sensing ocean color algorithms in the coastalwaters. The goal is to characterize sediment concentrations and to develop a tool to track plumes cascading down the Bay …

Characterization Of Turbidity In Florida’S Lake Okeechobee And Caloosahatchee And St. Lucie Estuaries Using Modis-Aqua Measurements, Menghua Wang, Carl J. Nim, Seunghyun Son, Wei Shi

United States Department of Commerce: Staff Publications

This paper describes the use of ocean color remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to characterize turbidity in Lake Okeechobee and its primary drainage basins, the Caloosahatchee and St. Lucie estuaries from 2002 to 2010. Drainage modification and agricultural development in southern Florida transport sediments and nutrients from watershed agricultural areas to Lake Okeechobee. As a result of development around Lake Okeechobee and the estuaries that are connected to Lake Okeechobee, estuarine conditions have also been adversely impacted, resulting in salinity and nutrient fluctuations. The measurement of water turbidity in lacustrine and …