@article{haedrich_petras_petrasova_blumentrath_mitasova_2023, title={Integrating GRASS GIS and Jupyter Notebooks to facilitate advanced geospatial modeling education}, volume={27}, url={https://doi.org/10.1111/tgis.13031}, DOI={10.1111/tgis.13031}, abstractNote={AbstractOpen education materials are critical for the advancement of open science and the development of open‐source software. These accessible and transparent materials provide an important pathway for sharing both standard geospatial analysis workflows and advanced research methods. Computational notebooks allow users to share live code with in‐line visualizations and narrative text, making them a powerful interactive teaching tool for geospatial analytics. Specifically, Jupyter Notebooks are quickly becoming a standard format in open education. In this article, we introduce a new GRASS GIS package, grass.jupyter, that enhances the existing GRASS Python API to allow Jupyter Notebook users to easily manage and visualize GRASS data including spatiotemporal datasets. While there are many Python‐based geospatial libraries available for use in Jupyter Notebooks, GRASS GIS has extensive geospatial functionality including support for multi‐temporal analysis and dynamic simulations, making it a powerful teaching tool for advanced geospatial analytics. We discuss the development of grass.jupyter and demonstrate how the package facilitates teaching open‐source geospatial modeling with a collection of Jupyter Notebooks designed for a graduate‐level geospatial modeling course. The open education notebooks feature spatiotemporal data visualizations, hydrologic modeling, and spread simulations such as the spread of invasive species and urban growth.}, number={3}, journal={Transactions in GIS}, publisher={Wiley}, author={Haedrich, Caitlin and Petras, Vaclav and Petrasova, Anna and Blumentrath, Stefan and Mitasova, Helena}, year={2023}, month={May}, pages={686–702} }
 @article{breton_haedrich_2021, title={Terrain-Scatter Augmented Vertical Plane Model for Radio Path Loss Estimation in Complex Terrain}, ISSN={["2155-7578"]}, DOI={10.1109/MILCOM52596.2021.9653008}, abstractNote={The fundamental challenge of complex (typically mountainous or urban) terrain for radio-frequency systems is that a direct line-of-sight is difficult or impossible to achieve between a radio transmitter and receiver. In the context of ground-based military operations, occupying line-of-sight positions to optimize communications or surveillance capabilities often exposes Soldiers and/or equipment to unacceptable risks from both conventional and electronic warfare. Propagation models for tactical use commonly analyze terrain only in the vertical plane containing both transmitter and receiver in order to simplify both the required data and computational burdens. However, these advantages come at the cost of ignoring reflections from topography within and outside the vertical plane path, which can have serious implications for radio-frequency direction finding, surveillance, and high-speed data transfer in complex terrain. This work summarizes our efforts to address these issues by developing a hybrid path loss model, one specifically designed for ground-to-ground radio links in complex rural terrain. The model uses an existing international-standard vertical plane diffraction model (VPM) to account for path losses associated with obstacles, and then augments those results with geospatially derived terrain reflection/scattering effects. Our prototype Terrain Scatter Augmented Vertical Plane Model (TSAVPM) provides physically credible path loss results in complex terrain at tactically relevant spatial scales (∼250 sq. km) and computational costs (under 40 seconds on a single 4.2 GHz central processing unit).}, journal={2021 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM 2021)}, author={Breton, Daniel J. and Haedrich, Caitlin E.}, year={2021} }
 @article{wilson_kamrath_haedrich_breton_hart_2021, title={Urban noise distributions and the influence of geometric spreading on skewness}, url={https://doi.org/10.1121/10.0005736}, DOI={10.1121/10.0005736}, abstractNote={Statistical distributions of urban noise levels are influenced by many complex phenomena, including spatial and temporal variations in the source level, multisource mixtures, propagation losses, and random fading from multipath reflections. This article provides a broad perspective on the varying impacts of these phenomena. Distributions incorporating random fading and averaging (e.g., gamma and noncentral Erlang) tend to be negatively skewed on logarithmic (decibel) axes but can be positively skewed if the fading process is strongly modulated by source power variations (e.g., compound gamma). In contrast, distributions incorporating randomly positioned sources and explicit geometric spreading [e.g., exponentially modified Gaussian (EMG)] tend to be positively skewed with exponential tails on logarithmic axes. To evaluate the suitability of the various distributions, one-third octave band sound-level data were measured at 37 locations in the North End of Boston, MA. Based on the Kullback-Leibler divergence as calculated across all of the locations and frequencies, the EMG provides the most consistently good agreement with the data, which were generally positively skewed. The compound gamma also fits the data well and even outperforms the EMG for the small minority of cases exhibiting negative skew. The lognormal provides a suitable fit in cases in which particular non-traffic noise sources dominate.}, journal={The Journal of the Acoustical Society of America}, author={Wilson, D. Keith and Kamrath, Matthew J. and Haedrich, Caitlin E. and Breton, Daniel J. and Hart, Carl R.}, year={2021}, month={Aug} }
 @book{haedrich_breton_2019, title={Measuring very high frequency and ultrahigh frequency radio noise in urban environments : a mobile measurement system for radio-frequency noise}, DOI={10.21079/11681/33290}, abstractNote={Radio-frequency (RF) background noise is an important parameter in designing and predicting performance of RF communication and sensor systems.Modern man-made RF noise consists of unintentional emissions from sources such as electronic devices, power transmission lines, and internal combustion engine ignitions.Governments and academia have previously measured RF noise at fixed, representative locations within the urban environment.Considering the heterogeneous mix of office buildings, retail and residential buildings, transportation hubs, and parks that compromise modern cities, we hypothesize that RF-noise power varies significantly throughout the urban environment.To characterize this variability, we present a mobile, tunable RF-noise measurement system designed to record frequencies from 63 MHz to 1 GHz in a 1 MHz to 10 MHz bandwidth.This report describes the system design, including the choice of preselection filters, preamplifiers, and RF shielding necessary to measure low RF-noise levels while avoiding intermodulation distortion problems that arise in an environment with many strong emitters.Additionally, we describe techniques developed to reliably geolocate RF data in urban environments.GPS (global positioning system) reception is often poor in dense urban environments.We mitigate this issue by using a 1 m surveying wheel for geolocation.}, institution={Engineer Research and Development Center (U.S.)}, author={Haedrich, Caitlin and Breton, Daniel}, year={2019}, month={Jul} }
 @article{breton_haedrich_kamrath_wilson_2019, title={Street‐Scale Mapping of Urban Radio Frequency Noise at Very High Frequency and Ultra High Frequency}, volume={11}, url={https://doi.org/10.1029/2019RS006893}, DOI={10.1029/2019RS006893}, abstractNote={Abstract Modern measurement campaigns of man‐made radio frequency (RF) noise have reported results from fixed locations that are assumed to be representative of the surroundings. Models derived from these measurements include parameters to express the variability in time and in space over very large distances (i.e., differences between cities). Despite the rapidly evolving mixture of noise sources, especially in modern urban environments, spatial variation of RF noise power at the scale of streets and blocks is essentially unknown in the very high frequency and ultra high frequency bands. Using a portable calibrated noise measurement system of our design, RF noise was recorded over a 1‐MHz bandwidth for frequencies of 142.0, 246.5, and 972 MHz. Noise surveys were conducted during daytime working hours in two different neighborhoods within Boston, Massachusetts, USA, with each survey transiting a fixed, several kilometer long route, repeated twice to enable separation of temporal from spatial variability. Significant and spatially repeatable variations in median power, peak power, and voltage deviation were observed over distances of tens to hundreds of meters, dependent upon the measurement frequency. The observed spatial patterns of median and peak power appear to be repeatable on timescales of hours to weeks, and likely beyond, suggesting that these noise patterns are persistent features of the urban environment.}, journal={Radio Science}, publisher={American Geophysical Union (AGU)}, author={Breton, Daniel J. and Haedrich, Caitlin E. and Kamrath, Matthew J. and Wilson, D. Keith}, year={2019}, month={Nov} }