Geography Commons^™

Family Tourism: Understanding The Concept And Improving The Parents - Children Relationship, Anukrati Sharma Anu, Shruti Arora Dr.

Journal of Sustainability and Resilience

Family tourism is driven by the increasing importance placed on promoting family togetherness, keeping family bonds alive and creating family memories. It not only builds life long memories, but also gives break away from the usual routine, opening the minds to new cultures, foods and experiences and even good for health. According to the researchers, positive relationships between parents and children are important for children’s overall development and builds trust. Various articles on family tourism from 2010 to 2023 were gathered from the Web of Sciences, UGC Journals, Scopus indexed journals, books, websites and was reviewed by the researchers.

Examining Crises Resilience In Tourism : A Systematic Review Of Literature, Kanyamwa Lunanga Félix

Journal of Sustainability and Resilience

This study is the systematic review of literature on the resilience of tourism businesses. Following the various crises and disasters that shook the World between 2000 and 2020, the interest of researchers in tourism resilience has increased significantly. Despite the interest felt by these scientists, the notion of resilience has remained fragmented in terms of its definition and dimensions. This review presents an overview of the literature on the resilience of tourism businesses from 2013 to June 2023. The study revealed that there is a lack of cohesion in the literature on resilience from the definition to its influencing factors. …

Toward Energy-Efficient Deep Neural Networks For Forest Fire Detection In An Image, Yali Wang, Chuulabat Purev, Hunter Barndt, Henry Toal, Jason Kim, Luke Underwood, Luis Avalo, Arghya Kusum Das

The Geographical Bulletin

Forest fires cause huge losses and are a serious problem facing many countries worldwide, including the USA, Canada, Brazil, Siberia, and Indonesia, to name a few. Automatic identification of forest fires in an image is thus an important field to research in order to minimize disasters while also helping in mitigation planning and designing rescue tactics. Artificial Intelligence technologies, especially deep neural networks, have emerged recently with promises to detect fires with better accuracy from an image. However, the massive energy consumption of deep neural networks thwarts their widespread adoption, especially when it comes to onsite detection of fire utilizing …

Gis-Based Spatial And Temporal Analyses Of Motor Vehicle Crashes In The Atlanta Metropolitan Region 2017-2021, Heyward Stober, Jeong C. Seong

The Geographical Bulletin

Motor vehicle crash analysis is among the most insightful metrics for public safety officials, researchers, and drivers. In this article, geographical information systems (GIS) tools were used to study the spatial and temporal trends of traffic crashes and fatal crashes. The methodology involves collecting spatial crash data over time and using computer-based analysis to overlay the road data against various spatial and temporal parameters in the Atlanta metropolitan region. Results show major crash hotspots in the region, such as the cites of Marietta, Kennesaw, and College Park. Hotspots tend to form on interstate highways, while smaller state highways have fewer …

Recovery Of Microtopography Following Prairie Restoration: Implications For Biodiversity Monitoring, Karli Cich, Scott Powell

The Geographical Bulletin

Tallgrass prairies are often restored from agricultural fields where the natural microtopography has long since been removed. Therefore, our study investigates the degree to which restored prairies recover microtopography. Differences in microtopography were measured using precise elevation data collected from LiDAR to compare differences in microtopography between crop fields, fallow fields, newer restored prairies, and older restored prairies. We also compared plant biodiversity indices between newer and older restored prairies using nested plot vegetation sampling. Our first research question is how microtopography differs between the sites. Our results show that older restored prairies had the most microtopographic variation, followed by …

Modeling The Impact Of Ocean Temperature Increases On The Distribution Of Seagrasses Around The Korean Peninsula Using A Machine Learning Technique, Jina Jang, Seohyeon Kim, Jeong Seong

The Geographical Bulletin

Seagrasses are important resources which form a vital part of the ocean ecosystem. They are also considered blue carbon because of their capability of sequestrating carbon. Seagrass distribution can be affected by many factors including ocean temperature. It is highly likely that recent climate change may increase ocean temperature significantly in East Asia and consequently alter seagrass distribution patterns. This study aims at predicting the impact of ocean temperature increases on seagrass habitats around the Korean Peninsula. Using the Maximum Entropy (MaxEnt) Model, seagrass habitat distributions were modeled when sea temperature rises by 1°C, 2°C, 3°C, and 4°C. Results show …

Predicting Cloud Fraction With Instantaneous Direct And Diffuse Shortwave Solar Irradiance, Jamison Lerma, Emily K. Blackaby, Maosi Chen, Sasha Madronich, Wei Gao

The Geographical Bulletin

The purpose of this study is to compare the different performances of three commonly used models (i.e., linear regression, random forest regression, and deep neural network (DNN)) to predict cloud fraction (CF) using ground-based shortwave solar radiation measurements and analyze the importance of the input features. The CF data are obtained from the Surface Radiation Budget (SURFRAD) and the Atmospheric Radiation Measurement (ARM) and the irradiance data from the USDA UV-B Monitoring and Research Program. The study finds that CF of opaque and total clouds can be best predicted using both Random Forest Regression and DNN with the validation R2 …

Prediction Of Traffic Congestion Using A Time-Series Model And Spatiotemporal Data: A Case Study Of The Atlanta Downtown Connector, Yunsik Kim

The Geographical Bulletin

Traffic congestion poses significant socio-economic challenges, and many urban commuters experience time and cost burdens due to traffic jams. Effectively managing and predicting traffic congestion is crucial for contemporary urban planning and operations. This study aims to predict congestion using time-series deep learning models, focusing on a chronically congested road section. The research area is the Atlanta Downtown Connector, a heavily trafficked route passing through the heart of the city of Atlanta. To address issues often associated with sensor and GPS-based data collection, traffic data was obtained from an open-source online map service, Google Maps. A multivariate time-lagged LSTM model …

A Remote Sensing Investigation Of The 2022 Invasion Of Eastern Ukraine On Agricultural Landcover, Michael S. Agbozo, Luke J. Marzen, Chandana Mitra

The Geographical Bulletin

Ukraine-Russian political relations over the years have alternatively experienced periods of tranquility and turmoil with violent conflicts since 1917, including the events of the 2014 annexation of Crimea and the 2022 Russian invasion of the entirety of Ukraine. These conflicts remain developmental threats and their assessment requires multi-perspective analysis. Understanding the spatial dimensions of such conflicts and their consequences on physical and social spaces at varying scales could provide credible scientific impetuses on which targeted post-conflict remediations could be built. This preliminary study therefore takes advantage of the capabilities of satellite remote sensing, to provide quick and effective spatiotemporal analysis …

Open-Source Based Change Pattern Analysis Of Urban Green Spaces Using Landscape Metrics, Mohammad Anwar Alattar

The Geographical Bulletin

A growing number of studies have been conducted on urban green spaces (UGSs), given their essential role in mitigating urbanization externalities. The current available methods for acquiring and analyzing UGSs data suffer from several limitations. For example, free satellite imagery exhibits pixel distortion and fails to account for fine-grained structure such as accurate geometry or size. Moreover, official UGSs datasets are typically updated periodically, not continuously. This work provides a Python-derived open-source based analysis for acquiring, modeling and analyzing UGSs change patterns using landscape metrics. To demonstrate the feasibility of the proposed approach, it is applied on the New York …

Evaluating The Use Of Unpiloted Aerial Systems To Detect And Monitor Beech Bark Disease In New England Forests, Isabelle Lopez, Benjamin T. Fraser, Russell G. Congalton

The Geographical Bulletin

The American beech (Fagus grandifolia) plays a key role throughout eastern North American forests. However, beech bark disease (BBD) causes widespread mortality of beech trees. We investigated whether imagery collected using an unpiloted aerial system (UAS) could differentiate beech tree health. Reference data were collected from 140 beech trees in New Hampshire and were visually classified as having “no/trace damage,” “moderate damage,” or “heavy damage.” Multispectral imagery was collected from a UAS, and 44 image features were derived for each beech crown. We used machine learning to identify the importance of each feature in distinguishing between the three health classes …

High-Mountain Hazards In The Indian Himalaya: An Assessment Of The Causes And Effects Of The Chamoli Flood In 2021, Christina M. Salzmann, Sarah J. Halvorson, Anna E. Klene

The Geographical Bulletin

On 7 February 2021, a devastating flood severely impacted the Ronti Gad, Rishiganga, and Dhauliganga River Valleys in the northwestern District of Chamoli, India. The flood washed away two hydropower projects and caused more than 200 fatalities. This study assessed some of the causes and effects of this catastrophic flood event and aims to provide further documentation that the event was not caused by a glacial lake outburst flood, as many reports initially indicated. Analysis of high-resolution satellite imagery, digital elevation model (DEM) differencing, and precipitation and temperature data showed that an ice-rock avalanche was released as a result of …

Editors' Note, Jc Seong

The Geographical Bulletin

Editors' Note

Front Matters, Nancy Hoalst Pullen

The Geographical Bulletin

Front Matter

Volume 64-2 Complete Issue, Nancy Hoalst Pullen

The Geographical Bulletin

Complete Issue

The Usage Of Band Ratios To Predict Lake Water Quality Parameters Using Sentinel-2 L1c Imagery, Austin Spoor, Ho-Seop Cha

International Journal of Geospatial and Environmental Research

Band ratios using remote imagery can be useful for monitoring large bodies of water when high quality imagery is available. Sentinel-2 satellite imagery provides frequent, high-resolution coverage of the globe. This study set out to test the usefulness of existing band ratios for estimating chlorophyll a (CHL-a), dissolved organic carbon (DOC), and turbidity with Sentinel-2 imagery. USGS in-situ data was matched to Sentinel-2 imagery of Beaver Lake, Arkansas taken August 2015 to July 2019 and the dark spectrum fitting (DSF) atmospheric correction method in ACOLITE was applied to generate surface reflectance values. CHL-a was estimated using two …

The Status Of Urban System In Bethlehem Governorate: Study On Urban Geography, Yacoub Jeries Al-Qasasfeh

An-Najah University Journal for Research - B (Humanities)

The aim of the study is to analyse the status of urban system in Bethlehem governorate, through setting the hierarchical ratings for different urban populations in it. And showing the adequacy of this rating by applying certain quantitive measurements including the grade and volume of these populations, their urban density, the law of primate city by Jefferson, and the volumetric grade according to Zipf's rule of grade and volume. Also showing the volumetric urban contrast between them, and the volume of the urban domination for the main city in the governorate according to the laws and the followed modules in …

Staying Power: The Struggle For Space And Place In Crown Heights, Brooklyn, Erin E. Lilli

Dissertations, Theses, and Capstone Projects

This dissertation looks at how gentrification touches down, at the neighborhood and individual scale, in Crown Heights and reproduces experiences of racial inequality in home and place. Taking an historical materialist approach and drawing on residential oral histories, this study frames these reproductions of racial inequality as always-in-tension with ongoing acts of resistance from Black homeowners, renters, and long-term residents. Specifically, the research explores the conditions under which Black residents of a predominantly Afro-Caribbean neighborhood acquire and maintain—and in some cases lose—their housing and sense of place and belonging. These residents resist the varied tactics of anti-Blackness such as landlord …

College Of Natural Sciences 2023 Year-End Publication, College Of Natural Sciences

College of Natural Sciences Newsletters and Reports

Page 1 Dean's Message
Page 3 Department Highlights
Page 4 One Day for State
Page 5 Noble Prize Winner Speaks on Campus
Page 6-7 Faculty Excellence
Page 8-9 Student Excellence
Page 10 Outreach Program
Page 10 Events and Traditions
Page 11 Connections Abroad
Page 12 Student Spotlight
Page 13 Alumni Spotlight
Page 14 First Ever Drone Day
Page 15 Grand Opening of POET Bioproducts Center
Page 16 Work Anniversaries

Increasing Mine Waste Will Induce Land Cover Change That Results In Ecological Degradation And Human Displacement, John R. Owen, Deanna Kemp, Alex M. Lechner, Michelle Ang Li Ern, Éléonore Lèbre, Gavin M. Mudd, Mark G. Macklin, Muhamad Risqi U. Saputra, Tahjudil Witra, Anthony J. Bebbington

Geography

Highlights

• Mining-induced displacement is a severely under researched social policy problem.
• Through global data sources and historic remote sensing we analyze this problem.
• The main output of most mining activity is hazardous waste.
• We confirm waste as the principal source of human displacement globally in mining.
• Resources to fuel urbanisation and energy transition targets will drive increases in waste.