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Simon Kraatz
Department of Electrical and Computer Engineering, 113 Knowles Engineering Building, 151 Holdsworth Way, University of Massachusetts, Amherst, MA 01003, USA

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Journal article
Published: 27 April 2021 in Remote Sensing of Environment
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Accurate knowledge of the distribution, breadth and change in agricultural activity is important to food security and the related trade and policy mechanisms. Routine observations afforded by spaceborne Synthetic Aperture Radar (SAR) allows for high-fidelity monitoring of agricultural parameters at the field scale. Here we evaluate the approach to be used for generating NASA's upcoming NASA ISRO SAR (NISAR) mission's L-band cropland product using Sentinel-1C-band data. This study uses all ascending Sentinel-1A/B data collected over the conterminous United States in 2017 to compute the coefficient of variation (CV) at 150 m × 150 m resolution and evaluates the overall accuracy (OA) of CV-based crop/non-crop classifications at 100 one-by-one degree tiles. We calculate accuracies using two approaches: (a) using a literature-recommended constant CV threshold of 0.5 (CVthr_0.5) and (b) determining optimal CV thresholds for every tile using Youden's J statistic (YJS), CVthr_YJS. These accuracy comparisons are important for determining (1) the viability of using a computationally inexpensive and straightforward approach for cropland classification over large spatial scales/diverse land covers (i.e., can accuracies ≥80% be routinely achieved?), (2) how closely OA0.5 compares to the performance ceiling (OAYJS). This information will help determine whether approach (a) is appropriate and how much potential room of improvement there could be in modifying it. Results for OA0.5 and OAYJS are 81.5% and 86.8%, respectively. A breakdown by census geographic region, showed that OA0.5 (OAYJS) exceeded 80% (90%) in the South and Midwest, but was only 76.1% (73.5%) in the West. The improvement in OAYJS mainly stems from tiles with >40% crop prevalence having about 10% greater OA values. To better examine the potential of the approach for land cover classification, results of approach (b) were also stratified by crop. Approach (b) accurately detected most non-crop classes as non-crop (>80%), but with low OAYJS values for grasslands/pasture, especially in the West. CV values for crop were distinct from non-crop indicating that the approach is suitable for crop/non-crop classifications. Because results CV values have substantial overlap within crop/non-crop classes, indicating the approach is poorly suited for land cover classifications. We also detected a strong geographic dependence of CVthr_YJS: values ranged from about 0.2 at the coasts and gradually increase to about 0.6 in the Central United States, most often falling close to 0.3 and 0.5.

ACS Style

Shannon Rose; Simon Kraatz; Josef Kellndorfer; Michael H. Cosh; Nathan Torbick; Xiaodong Huang; Paul Siqueira. Evaluating NISAR's cropland mapping algorithm over the conterminous United States using Sentinel-1 data. Remote Sensing of Environment 2021, 260, 112472 .

AMA Style

Shannon Rose, Simon Kraatz, Josef Kellndorfer, Michael H. Cosh, Nathan Torbick, Xiaodong Huang, Paul Siqueira. Evaluating NISAR's cropland mapping algorithm over the conterminous United States using Sentinel-1 data. Remote Sensing of Environment. 2021; 260 ():112472.

Chicago/Turabian Style

Shannon Rose; Simon Kraatz; Josef Kellndorfer; Michael H. Cosh; Nathan Torbick; Xiaodong Huang; Paul Siqueira. 2021. "Evaluating NISAR's cropland mapping algorithm over the conterminous United States using Sentinel-1 data." Remote Sensing of Environment 260, no. : 112472.

Preprint content
Published: 04 March 2021
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Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation. In addition to depending on overall biomass, the total amount of water in vegetation varies with relative water content, which is monotonically related to plant water potential, a quantity that drives plant hydraulic behavior. Thus there is a possible relationship between VOD and plant water potential. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in the northeastern United States. We retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and in-situ soil moisture data. We also measured water potentials of stem xylem and leaves on trees within the stand.

VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 5 AM. Over the whole growing season, VOD was also positively correlated with both the water potential of stem xylem and the xylem's dielectric constant (a proxy for water content). The presence of moisture on the leaves did not affect the observed relationship between VOD and xylem dielectric constant. We used our observed VOD-water potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.

ACS Style

Nataniel Holtzman; Leander Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. 2021, 1 .

AMA Style

Nataniel Holtzman, Leander Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, Alexandra Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. . 2021; ():1.

Chicago/Turabian Style

Nataniel Holtzman; Leander Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra Konings. 2021. "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand." , no. : 1.

Journal article
Published: 01 February 2021 in Agronomy
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Crop area mapping is important for tracking agricultural production and supporting food security. Spaceborne approaches using synthetic aperture radar (SAR) now allow for mapping crop area at moderate spatial and temporal resolutions. Multi-frequency SAR data is highly useful for crop monitoring because backscatter response from vegetation canopies is wavelength dependent. This study evaluates the utility of C-band Sentinel-1B (Sentinel-1) and L-band ALOS-2 (PALSAR) data, collected during the 2019 growing season, for generating accurate active crop extent (crop vs. non-crop) classifications over an agricultural region in western Canada. Evaluations were performed against the Agriculture and Agri-Food Canada satellite-based Annual Cropland Inventory (ACI), an open data product that maps land cover across the extent of Canada’s agricultural land. Classifications were performed using the temporal coefficient of variation (CV) approach, where an optimal crop/non-crop delineating CV threshold (CVthr) is selected according to Youden’s J-statistic. Results show that crop area mapping agreed better with the ACI when using Sentinel-1 data (83.5%) compared to PALSAR (73.2%). Analysis of performance by crop reveals that PALSAR’s poorer performance can be attributed to soybean, urban, grassland, and pasture ACI classes. This study also compared CV values to in situ wet biomass data for canola and soybeans, showing that crops with lower biomass (soybean) had correspondingly lower CV values.

ACS Style

Simon Kraatz; Nathan Torbick; Xianfeng Jiao; Xiaodong Huang; Laura Robertson; Andrew Davidson; Heather McNairn; Michael Cosh; Paul Siqueira. Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site. Agronomy 2021, 11, 273 .

AMA Style

Simon Kraatz, Nathan Torbick, Xianfeng Jiao, Xiaodong Huang, Laura Robertson, Andrew Davidson, Heather McNairn, Michael Cosh, Paul Siqueira. Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site. Agronomy. 2021; 11 (2):273.

Chicago/Turabian Style

Simon Kraatz; Nathan Torbick; Xianfeng Jiao; Xiaodong Huang; Laura Robertson; Andrew Davidson; Heather McNairn; Michael Cosh; Paul Siqueira. 2021. "Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site." Agronomy 11, no. 2: 273.

Journal article
Published: 01 February 2021 in Biogeosciences
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Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation, based on theoretical and empirical evidence. Because the total amount of water in vegetation varies with relative water content (as well as with biomass), this correlation further suggests a possible relationship between VOD and plant water potential, a quantity that drives plant hydraulic behavior. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in central Massachusetts, United States. We measured stem xylem and leaf water potentials of trees within the stand and retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and measured soil moisture. VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 05:00 eastern daylight time (UTC−4). VOD was also positively correlated with both the measured dielectric constant and water potentials of stem xylem over the growing season. The presence of moisture on the leaves did not affect the observed relationship between VOD and stem water potential. We used our observed VOD–water-potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.

ACS Style

Nataniel M. Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. Biogeosciences 2021, 18, 739 -753.

AMA Style

Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, Alexandra G. Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. Biogeosciences. 2021; 18 (2):739-753.

Chicago/Turabian Style

Nataniel M. Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. 2021. "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand." Biogeosciences 18, no. 2: 739-753.

Informatics
Published: 23 January 2021 in Earth and Space Science
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Synthetic Aperture Radar (SAR) data are well‐suited for change detection over agricultural fields, owing to high spatiotemporal resolution and sensitivity to soil and vegetation. The goal of this work is to evaluate the science algorithm for the NASA ISRO SAR (NISAR) Cropland Area product using data collected by NASA's airborne UAVSAR platform and the simulated NISAR data derived from it. This study uses mode 129, which is to be used for global‐scale mapping. The mode consists of an upper (129A) and lower band (129B), respectively having bandwidths of 20 and 5 MHz. This work uses 129A data because it has a four times finer range resolution compared to 129B. The NISAR algorithm uses the coefficient of variation (CV) to perform crop/non‐crop classification at 100 m. We evaluate classifications using three accuracy metrics (overall accuracy, J‐statistic, Cohen's Kappa) and spatial resolutions (10, 30 and 100 m) for crop/non‐crop delineating CV thresholds (CVthr) ranging from 0 to 1 in 0.01 increments. All but the 10 m 129A product exceeded NISAR's mission accuracy requirement of 80%. The UAVSAR 10 m data performed best, achieving maximum overall accuracy, J‐statistic, and Kappa values of 85%, 0.62 and 0.60. The same metrics for the 129A product respectively are: 77%, 0.40, 0.36 at 10 m; 81%, 0.55, 0.49 at 30 m; 80%, 0.58, 0.50 at 100 m. We found that using a literature recommended CVthr value of 0.5 yielded suboptimal accuracy (65%) and that optimal CVthr values monotonically decreased with decreasing spatial resolution.This article is protected by copyright. All rights reserved.

ACS Style

S. Kraatz; S. Rose; M.H. Cosh; N. Torbick; X. Huang; P. Siqueira. Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Noncrop Classification Over Stoneville, MS. Earth and Space Science 2021, 8, 1 .

AMA Style

S. Kraatz, S. Rose, M.H. Cosh, N. Torbick, X. Huang, P. Siqueira. Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Noncrop Classification Over Stoneville, MS. Earth and Space Science. 2021; 8 (1):1.

Chicago/Turabian Style

S. Kraatz; S. Rose; M.H. Cosh; N. Torbick; X. Huang; P. Siqueira. 2021. "Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Noncrop Classification Over Stoneville, MS." Earth and Space Science 8, no. 1: 1.

Preprint content
Published: 16 October 2020
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ACS Style

Nataniel Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. Supplementary material to "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand". 2020, 1 .

AMA Style

Nataniel Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, Alexandra G. Konings. Supplementary material to "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand". . 2020; ():1.

Chicago/Turabian Style

Nataniel Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. 2020. "Supplementary material to "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand"." , no. : 1.

Preprint content
Published: 16 October 2020
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Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation, based on theoretical and empirical evidence. Because the total amount of water in vegetation varies with relative water content (as well as with biomass), this correlation further suggests a possible relationship between VOD and plant water potential, a quantity that drives plant hydraulic behavior. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in central Massachusetts, United States. We measured stem xylem and leaf water potentials of trees within the stand, and retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and measured soil moisture. VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 5 AM. VOD was also positively correlated with both the measured dielectric constant and water potentials of stem xylem over the growing season. The presence of moisture on the leaves did not affect the observed relationship between VOD and stem water potential. We used our observed VOD-water potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.

ACS Style

Nataniel Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. 2020, 2020, 1 -26.

AMA Style

Nataniel Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, Alexandra G. Konings. L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. . 2020; 2020 ():1-26.

Chicago/Turabian Style

Nataniel Holtzman; Leander D. L. Anderegg; Simon Kraatz; Alex Mavrovic; Oliver Sonnentag; Christoforos Pappas; Michael H. Cosh; Alexandre Langlois; Tarendra Lakhankar; Derek Tesser; Nicholas Steiner; Andreas Colliander; Alexandre Roy; Alexandra G. Konings. 2020. "L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand." 2020, no. : 1-26.

Preprint content
Published: 02 September 2020
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ACS Style

Simon Kraatz; Shannon Rose; Michael Cosh; Nathan Torbick; Xiaodong Huang; Paul Siqueira. Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Non- crop Classification over Stoneville, MS. 2020, 1 .

AMA Style

Simon Kraatz, Shannon Rose, Michael Cosh, Nathan Torbick, Xiaodong Huang, Paul Siqueira. Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Non- crop Classification over Stoneville, MS. . 2020; ():1.

Chicago/Turabian Style

Simon Kraatz; Shannon Rose; Michael Cosh; Nathan Torbick; Xiaodong Huang; Paul Siqueira. 2020. "Performance Evaluation of UAVSAR and Simulated NISAR Data for Crop/Non- crop Classification over Stoneville, MS." , no. : 1.

Journal article
Published: 25 November 2019 in Remote Sensing of Environment
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Seasonal freeze-thaw (FT) affects over half the northern hemisphere and impacts many key processes of the Earth System such as energy exchange, hydrology and vegetation. Nearly all past studies using spaceborne FT retrievals have focused on characterizing FT specifically for natural environments. FT in the built environment is also routinely studied and a topic of great interest, especially with regards to transportation infrastructure. Whereas natural FT process are frequently investigated using spaceborne observations, FT studies of roads are often limited to local scales, using in situ or nearby weather station data only. Comparisons between FT retrievals obtained from NASA's Soil Moisture Active Passive (SMAP) satellite and roads in Alaska (AK) and the Contiguous United States (CONUS) showed that spaceborne FT retrievals had good agreement with road data. But those results also indicated that NASA FT retrievals in CONUS were relatively too warm compared to road data. If SMAP FT retrievals were to be used for identifying FT transition timing for applications by the transportation community, it is also important for frozen conditions to be identified more accurately. This work is primarily concerned with improving frozen retrievals made in CONUS by calculating new Normalized Polarization Ratio (NPR) thresholds as compared to those currently used in SMAP FT. We found that focusing on a temporal subset of October through May for comparisons greatly improved the correlation between NPR and effective soil temperature (Teff, one of SMAP's ancillary datasets), often from about zero to 0.6. We then applied linear regression between NPR and Teff to obtain new NPR thresholds resulting in the FT-Roads (FT-R) product. NASA FT and FT-R were evaluated against road data at about 1000 locations in CONUS and a battery of different tests indicated that FT-R performed better under nearly all conditions compared to NASA FT. Overall, NASA FT accuracies were 69% and 80% for 6 am and 6 pm SMAP retrievals, while FT-R achieved accuracies of 79% and 82%. We also investigated the potential for using Teff for road FT (6 am, only) and found that those comparisons were even more accurate (84%). We've also quantified inter- and intraregional differences of SMAP FT performance and found that accuracy metrics vary over twice as much between geographic subdivisions (9%) as compared to between the states within a subdivision (4%). Most importantly, the main goal of improving the detection of in situ frozen conditions in CONUS was realized, with FT-R accurately detecting frozen conditions >50% more frequently than NASA FT.

ACS Style

Simon Kraatz; Jennifer M. Jacobs; Ronny Schröder; Eunsang Cho; Heather J. Miller; Carrie M. Vuyovich. Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S. Remote Sensing of Environment 2019, 237, 111545 .

AMA Style

Simon Kraatz, Jennifer M. Jacobs, Ronny Schröder, Eunsang Cho, Heather J. Miller, Carrie M. Vuyovich. Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S. Remote Sensing of Environment. 2019; 237 ():111545.

Chicago/Turabian Style

Simon Kraatz; Jennifer M. Jacobs; Ronny Schröder; Eunsang Cho; Heather J. Miller; Carrie M. Vuyovich. 2019. "Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S." Remote Sensing of Environment 237, no. : 111545.

Journal article
Published: 15 October 2019 in Water Resources Research
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Human‐induced landscape changes affect hydrologic responses (e.g. floods) that can be detected from a suite of satellite and model datasets. Tapping these vast datasets using machine learning algorithms can produce critically important and accurate insights. In the Red River of the North Basin in the U.S., agricultural subsurface drainage (SD; so‐called tile drainage) systems have greatly increased since the late 1990s. Over this period, river flow in the Red River has markedly increased and six of 13 major floods during the past century have occurred in the past two decades. The impact of SD systems on river flow is elusive because there are surprisingly few SD records in the U.S. In this study, Random Forest machine learning (RFML) classification method running on Google Earth Engine's cloud computing platform was able to capture SD within a field (30 m) and its expansion over time for a large watershed (> 100,000 km2). The resulting RFML classifier drew from operational multiple satellites and model datasets (total 14 variables with 36 layers including vegetation, land cover, soil properties, climate variables). The classifier identified soil properties and land surface temperature to be the strongest predictors of SD. The maps agreed well with SD permit records (overall accuracies of 76.9 – 87.0%) and corresponded with subwatershed‐level statistics (r = 0.77 – 0.96). It is expected that the maps produced with this data‐intensive machine learning approach will help water resource managers to assess the hydrological impact from SD expansion and improve flood predictions in SD‐dominated regions.

ACS Style

Eunsang Cho; Jennifer M. Jacobs; Xinhua Jia; Simon Kraatz. Identifying Subsurface Drainage using Satellite Big Data and Machine Learning via Google Earth Engine. Water Resources Research 2019, 55, 8028 -8045.

AMA Style

Eunsang Cho, Jennifer M. Jacobs, Xinhua Jia, Simon Kraatz. Identifying Subsurface Drainage using Satellite Big Data and Machine Learning via Google Earth Engine. Water Resources Research. 2019; 55 (10):8028-8045.

Chicago/Turabian Style

Eunsang Cho; Jennifer M. Jacobs; Xinhua Jia; Simon Kraatz. 2019. "Identifying Subsurface Drainage using Satellite Big Data and Machine Learning via Google Earth Engine." Water Resources Research 55, no. 10: 8028-8045.

Journal article
Published: 29 January 2019 in Water
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Submarine pipelines have been extensively used for marine oil and gas extraction due to their high efficiency, safety, and low price. However, submarine pipelines are vulnerable to extreme waves (i.e., tsunami waves). Previous research has often used solitary waves as a basis for studying the impacts of tsunami waves on submarine pipelines, although the hydrodynamic characteristics and wave properties drastically differ from those of real-world tsunami waves. This paper numerically investigates the hydrodynamic characteristics of tsunami waves interacting with submarine pipelines, but instead uses an improved wave model to generate a tsunami-like wave that more closely resembles those encountered in the real-world. The tsunami-like wave generated based on a real-world tsunami wave profile recorded during a 2011 tsunami in Japan has been applied. Given the same wave height, simulation results show that peak hydrodynamic forces of the tsunami-like wave are greater than those of the solitary wave. Meanwhile, the duration of the acting force under the tsunami-like wave is much longer than that of the solitary wave. These findings underline the basic reasons for the destructive power of tsunamis. It is also noted that the hydrodynamic forces of the pipeline under the tsunami-like wave increase with wave height, but will decrease as water depth increases. In addition to the single pipeline, the complicated hydrodynamic characteristics of pipelines in tandem arrangement have been also numerically studied. It is believed that the findings drawn from this paper can enhance our understanding of the induced forces on submarine pipelines under extreme tsunami waves.

ACS Style

Enjin Zhao; Ke Qu; Lin Mu; Simon Kraatz; Bing Shi. Numerical Study on the Hydrodynamic Characteristics of Submarine Pipelines under the Impact of Real-World Tsunami-Like Waves. Water 2019, 11, 221 .

AMA Style

Enjin Zhao, Ke Qu, Lin Mu, Simon Kraatz, Bing Shi. Numerical Study on the Hydrodynamic Characteristics of Submarine Pipelines under the Impact of Real-World Tsunami-Like Waves. Water. 2019; 11 (2):221.

Chicago/Turabian Style

Enjin Zhao; Ke Qu; Lin Mu; Simon Kraatz; Bing Shi. 2019. "Numerical Study on the Hydrodynamic Characteristics of Submarine Pipelines under the Impact of Real-World Tsunami-Like Waves." Water 11, no. 2: 221.

Journal article
Published: 24 October 2018 in Cold Regions Science and Technology
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Seasonal freeze and thaw impact a road’s ability to bear loads. Temperature index models are one of the methods being used to manage seasonal weight restrictions on roads. Many of these methods are limited to specific regions in which they have been calibrated and more universally applicable models are sought. A multi-year study of Alaska Department of Transportation and Public Facilities (ADOT&PF) road subsurface temperature data probe observations at 25 stations was conducted to understand variations among stations as needed to support the development of generally applicable models. Time-stability analysis showed that stations located within 25 km had consistent temperatures with the consistency increasing with measurement depth. At greater separation distances, stations’ relative cold or warm biases were maintained across years. Up to 95% of temperature differences among stations was explained by latitude when linear regression was used. Temperature time series showed distinct isothermal conditions in spring at temperature below 0 oC. For stations located further south, thaw penetration rates were greater, and surface n-Factors varied more. A constant thawing index was also tested to determine thaw dates. Thaw depths corresponding to these dates were relatively consistent for northern stations but varied substantially for southern stations.

ACS Style

Simon Kraatz; Jennifer M. Jacobs; Heather J. Miller. Spatial and temporal freeze-thaw variations in Alaskan roads. Cold Regions Science and Technology 2018, 157, 149 -162.

AMA Style

Simon Kraatz, Jennifer M. Jacobs, Heather J. Miller. Spatial and temporal freeze-thaw variations in Alaskan roads. Cold Regions Science and Technology. 2018; 157 ():149-162.

Chicago/Turabian Style

Simon Kraatz; Jennifer M. Jacobs; Heather J. Miller. 2018. "Spatial and temporal freeze-thaw variations in Alaskan roads." Cold Regions Science and Technology 157, no. : 149-162.

Journal article
Published: 17 September 2018 in Remote Sensing
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Seasonal freeze-thaw (FT) impacts much of the northern hemisphere and is an important control on its water, energy, and carbon cycle. Although FT in natural environments extends south of 45°N, FT studies using the L-band have so far been restricted to boreal or greater latitudes. This study addresses this gap by applying a seasonal threshold algorithm to Soil Moisture Active Passive (SMAP) data (L3_SM_P) to obtain a FT product south of 45°N (‘SMAP FT’), which is then evaluated at SMAP core validation sites (CVS) located in the contiguous United States (CONUS). SMAP landscape FT retrievals are usually in good agreement with 0–5 cm soil temperature at SMAP grids containing CVS stations (>70%). The accuracy could be further improved by taking into account specific overpass time (PM), the grid-specific seasonal scaling factor, the data aggregation method, and the sampling error. Annual SMAP FT extent maps compared to modeled soil temperatures derived from the Goddard Earth Observing System Model Version 5 (GEOS-5) show that seasonal FT in CONUS extends to latitudes of about 35–40°N, and that FT varies substantially in space and by year. In general, spatial and temporal trends between SMAP and modeled FT were similar.

ACS Style

Simon Kraatz; Jennifer M. Jacobs; Ronny Schröder; Eunsang Cho; Michael Cosh; Mark Seyfried; John Prueger; Stan Livingston. Evaluation of SMAP Freeze/Thaw Retrieval Accuracy at Core Validation Sites in the Contiguous United States. Remote Sensing 2018, 10, 1483 .

AMA Style

Simon Kraatz, Jennifer M. Jacobs, Ronny Schröder, Eunsang Cho, Michael Cosh, Mark Seyfried, John Prueger, Stan Livingston. Evaluation of SMAP Freeze/Thaw Retrieval Accuracy at Core Validation Sites in the Contiguous United States. Remote Sensing. 2018; 10 (9):1483.

Chicago/Turabian Style

Simon Kraatz; Jennifer M. Jacobs; Ronny Schröder; Eunsang Cho; Michael Cosh; Mark Seyfried; John Prueger; Stan Livingston. 2018. "Evaluation of SMAP Freeze/Thaw Retrieval Accuracy at Core Validation Sites in the Contiguous United States." Remote Sensing 10, no. 9: 1483.

Journal article
Published: 01 November 2017 in Ocean Engineering
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ACS Style

K. Qu; X.Y. Ren; S. Kraatz; E.J. Zhao. Numerical analysis of tsunami-like wave impact on horizontal cylinders. Ocean Engineering 2017, 145, 316 -333.

AMA Style

K. Qu, X.Y. Ren, S. Kraatz, E.J. Zhao. Numerical analysis of tsunami-like wave impact on horizontal cylinders. Ocean Engineering. 2017; 145 ():316-333.

Chicago/Turabian Style

K. Qu; X.Y. Ren; S. Kraatz; E.J. Zhao. 2017. "Numerical analysis of tsunami-like wave impact on horizontal cylinders." Ocean Engineering 145, no. : 316-333.

Journal article
Published: 03 March 2017 in Remote Sensing
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The capability of frequently and accurately monitoring ice on rivers is important, since it may be possible to timely identify ice accumulations corresponding to ice jams. Ice jams are dam-like structures formed from arrested ice floes, and may cause rapid flooding. To inform on this potential hazard, the CREST River Ice Observing System (CRIOS) produces ice cover maps based on MODIS and VIIRS overpass data at several locations, including the Susquehanna River. CRIOS uses the respective platform’s automatically produced cloud masks to discriminate ice/snow covered grid cells from clouds. However, since cloud masks are produced using each instrument’s data, and owing to differences in detector performance, it is quite possible that identical algorithms applied to even nearly identical instruments may produce substantially different cloud masks. Besides detector performance, cloud identification can be biased due to local (e.g., land cover), viewing geometry, and transient conditions (snow and ice). Snow/cloud confusions and large view angles can result in substantial overestimates of clouds and ice. This impacts algorithms, such as CRIOS, since false cloud cover precludes the determination of whether an otherwise reasonably cloud free grid consists of water or ice. Especially for applications aiming to frequently classify or monitor a location it is important to evaluate cloud masking, including false cloud detections. We present an assessment of three cloud masks via the parameter of effective revisit time. A 100 km stretch of up to 1.6 km wide river was examined with daily data sampled at 500 m resolution, examined over 317 days during winter. Results show that there are substantial differences between each of the cloud mask products, especially while the river bears ice. A contrast-based cloud screening approach was found to provide improved and consistent cloud and ice identification within the reach (95%–99% correlations, and 3%–7% mean absolute differences) between the independently observing platforms. River ice was also detected accurately (proportion correct 95%–100%) and more frequently. Owing to cross-platform compositing, it is possible to obtain an effective revisit time of 2.8 days and further error reductions.

ACS Style

Simon Kraatz; Reza Khanbilvardi; Peter Romanov. A Comparison of MODIS/VIIRS Cloud Masks over Ice-Bearing River: On Achieving Consistent Cloud Masking and Improved River Ice Mapping. Remote Sensing 2017, 9, 229 .

AMA Style

Simon Kraatz, Reza Khanbilvardi, Peter Romanov. A Comparison of MODIS/VIIRS Cloud Masks over Ice-Bearing River: On Achieving Consistent Cloud Masking and Improved River Ice Mapping. Remote Sensing. 2017; 9 (3):229.

Chicago/Turabian Style

Simon Kraatz; Reza Khanbilvardi; Peter Romanov. 2017. "A Comparison of MODIS/VIIRS Cloud Masks over Ice-Bearing River: On Achieving Consistent Cloud Masking and Improved River Ice Mapping." Remote Sensing 9, no. 3: 229.

Journal article
Published: 01 February 2017 in Applied Ocean Research
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ACS Style

K. Qu; X.Y. Ren; S. Kraatz. Numerical investigation of tsunami-like wave hydrodynamic characteristics and its comparison with solitary wave. Applied Ocean Research 2017, 63, 36 -48.

AMA Style

K. Qu, X.Y. Ren, S. Kraatz. Numerical investigation of tsunami-like wave hydrodynamic characteristics and its comparison with solitary wave. Applied Ocean Research. 2017; 63 ():36-48.

Chicago/Turabian Style

K. Qu; X.Y. Ren; S. Kraatz. 2017. "Numerical investigation of tsunami-like wave hydrodynamic characteristics and its comparison with solitary wave." Applied Ocean Research 63, no. : 36-48.

Journal article
Published: 01 November 2016 in Cold Regions Science and Technology
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ACS Style

Simon Kraatz; R. Khanbilvardi; P. Romanov. River ice monitoring with MODIS: Application over Lower Susquehanna River. Cold Regions Science and Technology 2016, 131, 116 -128.

AMA Style

Simon Kraatz, R. Khanbilvardi, P. Romanov. River ice monitoring with MODIS: Application over Lower Susquehanna River. Cold Regions Science and Technology. 2016; 131 ():116-128.

Chicago/Turabian Style

Simon Kraatz; R. Khanbilvardi; P. Romanov. 2016. "River ice monitoring with MODIS: Application over Lower Susquehanna River." Cold Regions Science and Technology 131, no. : 116-128.

Review article
Published: 01 August 2014 in Renewable and Sustainable Energy Reviews
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In order to facilitate development of tidal power, a high-resolution survey with unprecedentedly fine grids has been made for marine hydrokinetic (MHK) energy at the seashore of New Jersey (NJ) and its neighbor states (Tang, Kraatz, Qu, Chen, Aboobaker, Jiang. High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: a case study at coast of New Jersey, USA. Renewable and Sustainable Energy Reviews 32 (2014), 960–982). As a sequel as well as the finish to this survey, the current paper makes a thorough search for potential sites for actual tidal power generation along the entire shorelines of NJ and partial coast of New York, with special attention to locations near transportation infrastructures, and it evaluates their power density, surface area, water depth, distance to environmentally sensitive zones, etc. A list of 32 top sites are identified along the coastlines, and, among them, 21 sites with total surface area of 13 km2 are located in the nearshore regions of NJ, and many sites are found next to its bridges. Another 10 favorable sites are also picked up near ports, docks, and marinas in NJ. An estimate indicates that 3.95×105 kW of tidal power could be extracted from the 21 sites. Analysis shows that sea-level-rise could substantially change tidal energy at the identified sites, and it is a factor that has to be taken into account in site selection. On the basis of these results, the approaches for a high-resolution survey for MHK energy are summarized and their future development is discussed.

ACS Style

H.S. Tang; K. Qu; G.Q. Chen; S. Kraatz; N. Aboobaker; C.B. Jiang. Potential sites for tidal power generation: A thorough search at coast of New Jersey, USA. Renewable and Sustainable Energy Reviews 2014, 39, 412 -425.

AMA Style

H.S. Tang, K. Qu, G.Q. Chen, S. Kraatz, N. Aboobaker, C.B. Jiang. Potential sites for tidal power generation: A thorough search at coast of New Jersey, USA. Renewable and Sustainable Energy Reviews. 2014; 39 ():412-425.

Chicago/Turabian Style

H.S. Tang; K. Qu; G.Q. Chen; S. Kraatz; N. Aboobaker; C.B. Jiang. 2014. "Potential sites for tidal power generation: A thorough search at coast of New Jersey, USA." Renewable and Sustainable Energy Reviews 39, no. : 412-425.

Review article
Published: 11 February 2014 in Renewable and Sustainable Energy Reviews
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The first and a crucial step in development of tidal power, which is now attracting more and more attention worldwide, is a reliable survey of temporal and spatial distribution of tidal energy along coastlines. This paper first reviews the advance in assessment of tidal energy, in particular marine hydrokinetic (MHK) energy, and discusses involved challenges and necessary approaches, and then it makes a thorough survey as an illustrative case study on distributions and top sites of MHK energy within the Might-Atlantic-Bight (MAB) with emphasis on the New Jersey (NJ) coastlines. In view of the needs in actual development of tidal power generation and sensitivity of tidal power to flow speed, the former being proportional to the third power of the latter, a high-resolution and detailed modeling is desired. Data with best available accuracy for coastlines, bathymetry, tributaries, etc. are used, meshes as fine as 20 m and less for the whole NJ coast are generated, and the unstructured grid finite volume coastal ocean model (FVCOM) and high performance computing (HPC) facilities are employed. Besides comparison with observation data, a series of numerical tests have been made to ensure reliability of the modeling results. A detailed tidal energy distribution and a list of top sites for tidal power are presented. It is shown that indeed sea-level-rise (SLR) affects the tidal energy distribution significantly. With SLR of 0.5 m and 1 m, tidal energy in NJ coastal waters increases by 21% and 43%, respectively, and the number of the top sties tends to decrease along the barrier islands facing the Atlantic Ocean and increase in the Delaware Bay and the Delaware River. On the basis of these results, further discussions are made on future development for accurate assessment of tidal energy.

ACS Style

H.S. Tang; S. Kraatz; K. Qu; G.Q. Chen; N. Aboobaker; C.B. Jiang. High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: A case study at coast of New Jersey, USA. Renewable and Sustainable Energy Reviews 2014, 32, 960 -982.

AMA Style

H.S. Tang, S. Kraatz, K. Qu, G.Q. Chen, N. Aboobaker, C.B. Jiang. High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: A case study at coast of New Jersey, USA. Renewable and Sustainable Energy Reviews. 2014; 32 ():960-982.

Chicago/Turabian Style

H.S. Tang; S. Kraatz; K. Qu; G.Q. Chen; N. Aboobaker; C.B. Jiang. 2014. "High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: A case study at coast of New Jersey, USA." Renewable and Sustainable Energy Reviews 32, no. : 960-982.

Journal article
Published: 30 April 2013 in Natural Hazards
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Catastrophic flooding associated with sea-level rise and change of hurricane patterns has put the northeastern coastal regions of the United States at a greater risk. In this paper, we predict coastal flooding at the east bank of Delaware Bay and analyze the resulting impact on residents and transportation infrastructure. The three-dimensional coastal ocean model FVCOM coupled with a two-dimensional shallow water model is used to simulate hydrodynamic flooding from coastal ocean water with fine-resolution meshes, and a topography-based hydrologic method is applied to estimate inland flooding due to precipitation. The entire flooded areas with a range of storm intensity (i.e., no storm, 10-, and 50-year storm) and sea-level rise (i.e., current, 10-, and 50-year sea level) are thus determined. The populations in the study region in 10 and 50 years are predicted using an economic-demographic model. With the aid of ArcGIS, detailed analysis of affected population and transportation systems including highway networks, railroads, and bridges is presented for all of the flood scenarios. It is concluded that sea-level rise will lead to a substantial increase in vulnerability of residents and transportation infrastructure to storm floods, and such a flood tends to affect more population in Cape May County but more transportation facilities in Cumberland County, New Jersey.

ACS Style

Han Song Tang; Steven I-Jy Chien; Marouane Temimi; Cheryl Ann Blain; Qu Ke; Liuhui Zhao; Simon Kraatz. Vulnerability of population and transportation infrastructure at the east bank of Delaware Bay due to coastal flooding in sea-level rise conditions. Natural Hazards 2013, 69, 141 -163.

AMA Style

Han Song Tang, Steven I-Jy Chien, Marouane Temimi, Cheryl Ann Blain, Qu Ke, Liuhui Zhao, Simon Kraatz. Vulnerability of population and transportation infrastructure at the east bank of Delaware Bay due to coastal flooding in sea-level rise conditions. Natural Hazards. 2013; 69 (1):141-163.

Chicago/Turabian Style

Han Song Tang; Steven I-Jy Chien; Marouane Temimi; Cheryl Ann Blain; Qu Ke; Liuhui Zhao; Simon Kraatz. 2013. "Vulnerability of population and transportation infrastructure at the east bank of Delaware Bay due to coastal flooding in sea-level rise conditions." Natural Hazards 69, no. 1: 141-163.