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Geographies
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Feature Papers of Geographies in 2024
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Feature Papers of Geographies in 2024

A special issue of Geographies (ISSN 2673-7086).

Deadline for manuscript submissions: 30 December 2024 | Viewed by 2457

Special Issue Editor

Dr. Xu Chen

E-Mail Website
Guest Editor
Department of Geography, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: physical geography; environmental change; lake ecosystem; paleoecology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue, entitled “Feature Papers of Geographies in 2024”. This Special Issue will serve as a collection of articles from Editorial Board Members, Guest Editors, and Leading Researchers discussing new knowledge or new cutting-edge developments in centered around the different aspects of geography in 2024. Potential topics include, but are not limited to, the following:

  • Climatology;
  • Geomorphology;
  • Glaciology;
  • Biogeography;
  • Hydrology and hydrography;
  • Landscape ecology;
  • Soil geography;
  • Quaternary environmental change;
  • Environmental geography;
  • Geomatics;
  • Spatial analysis;
  • Cartography and mapping;
  • Geographical information systems.

Dr. Xu Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geographies is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climatology
  • geomorphology
  • glaciology
  • biogeography
  • hydrology and hydrography
  • landscape ecology
  • soil geography
  • global change
  • environmental management
  • geomatics
  • spatial analysis
  • cartography and mapping
  • geographical information systems

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

24 pages, 43880 KiB  
Article
Assessing the Efficiency of Fully Two-Dimensional Hydraulic HEC-RAS Models in Rivers of Cyprus
by Georgia Siakara, Nikolaos Gourgouletis and Evangelos Baltas
Geographies 2024, 4(3), 513-536; https://doi.org/10.3390/geographies4030028 - 5 Aug 2024
Viewed by 321
Abstract
Floods are among the most widespread and recurrent natural disasters globally. In the European region, climate change leads to an increase in the incidence and intensity of flooding. For effective management of the phenomenon, the European Union instituted Directive 2007/60/EC for the assessment [...] Read more.
Floods are among the most widespread and recurrent natural disasters globally. In the European region, climate change leads to an increase in the incidence and intensity of flooding. For effective management of the phenomenon, the European Union instituted Directive 2007/60/EC for the assessment and management of flood risks in order to reduce the negative consequences of flooding on human health, economic activities, the environment, and cultural heritage. Cyprus, as a member of the European Union, had to comply with the provisions of the directive. Within the second implementation of the directive, combined 1D/2D hydraulic models were conducted. These data served as a benchmark for the present research, in which the differences in the inundated area, depths, and simulation time are investigated using a full 2D hydraulic simulation. The present research examines two Areas of Potentially Significant Flood Risk, one in an urban and one in a rural area. Overall, the proposed 2D methodology was found to represent inundated areas to a good extent with almost zero deviation in comparison to the 1D/2D method. This study demonstrated the adequacy of the 2D hydraulic simulation method, which offers greater flexibility in modeling a variety of hydraulic scenarios, enabling planning and flood risk management that is vital for protecting communities, infrastructure and the environment from the devastating impacts of floods. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2024)
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13 pages, 19454 KiB  
Article
Understanding the Basis of Schmitt’s Map of South Germany: Georeferencing the Sketches of Staržinsky and Sarret (Late 1790’s)
by Eszter Kiss and Gábor Timár
Geographies 2024, 4(3), 500-512; https://doi.org/10.3390/geographies4030027 - 2 Aug 2024
Viewed by 498
Abstract
Schmitt’s map was one of the outstanding survey products of the late 18th century, produced through Habsburg military mapping in the shadow of the Napoleonic Wars in the area of today’s southern Germany and some neighboring regions. The main geodetic basis for the [...] Read more.
Schmitt’s map was one of the outstanding survey products of the late 18th century, produced through Habsburg military mapping in the shadow of the Napoleonic Wars in the area of today’s southern Germany and some neighboring regions. The main geodetic basis for the map work was the series of surveys in Germany conducted by C.-F. Cassini de Thury in the 1760s. However, this was only a horizontal control for part of Schmitt’s map. The Cassini survey chains were linked in the 1790s by a complementary survey in the northern part of the map work: the Staržinsky-Sarret survey, which is the subject of this study. The authors have searched through the archive summary drafts of this survey. The georeferencing of the photographed sketches in the Cassini projection was feasible with surprisingly low error. By using the global SRTM elevation database, it was possible to identify the points/summits of the Staržinsky-Sarret survey between which visibility is possible. Thus, despite the fact that only one of the seven map sketches examined explicitly presents a triangulation structure, we present a possible triangulation pattern that could have been used to provide geodetic control in the northern part of the Schmitt map. The authors consider this survey as the basis for the assumption that georeferencing the Schmitt map in its own projection is possible in this area with relatively small residual errors. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2024)
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19 pages, 14515 KiB  
Article
Neighborhood-Scale Wildfire Evacuation Vulnerability in Hays County, TX
by Chad Ramos and Yihong Yuan
Geographies 2024, 4(3), 481-499; https://doi.org/10.3390/geographies4030026 - 31 Jul 2024
Viewed by 371
Abstract
Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is [...] Read more.
Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is prone to fire, and rapid population growth has created a substantial WUI. Despite this, there is not sufficient research addressing neighborhood-level evacuation risks. The goal of this research, then, is to search Hays County for neighborhoods that face the highest combined risk of wildfire and potential evacuation difficulty. This research provides a limited use case wherein local decision-makers can quantify the combined risk of wildfire and constrained evacuation at the neighborhood scale by making use of standard spatial analysis techniques and publicly available datasets. The results show an alarming trend of low-egress neighborhoods in fire-prone areas within Hays County which carry the risk of a very difficult evacuation in cases when wildfire warning time is short. By using publicly available datasets and standard techniques, this research provides methods for local decision-makers across the state to identify these at-risk neighborhoods within their own jurisdictions which may aid in emergency planning and mitigation. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2024)
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15 pages, 2524 KiB  
Article
Application of Machine Learning Models for Improving Discharge Prediction in Ungauged Watershed: A Case Study in East DuPage, Illinois
by Amin Asadollahi, Binod Ale Magar, Bishal Poudel, Asyeh Sohrabifar and Ajay Kalra
Geographies 2024, 4(2), 363-377; https://doi.org/10.3390/geographies4020021 - 6 Jun 2024
Viewed by 858
Abstract
Accurate flood prediction models and effective flood preparedness rely on thoroughly understanding rainfall–runoff dynamics. Similarly, effective rainfall–runoff models account for multiple interrelated parameters for robust runoff prediction. Process-based physical models offer valuable insights into hydrological processes, but their effectiveness can be hindered by [...] Read more.
Accurate flood prediction models and effective flood preparedness rely on thoroughly understanding rainfall–runoff dynamics. Similarly, effective rainfall–runoff models account for multiple interrelated parameters for robust runoff prediction. Process-based physical models offer valuable insights into hydrological processes, but their effectiveness can be hindered by data limitations or difficulties in acquiring specific data. Motivated by the frequent flooding events and limited data availability in the East Branch DuPage watershed, Illinois, this study addresses a critical gap in research by investigating effective discharge prediction methods. In this study, two significant machine learning (ML) models, artificial neural network (ANN) and support vector machine (SVM), were employed for discharge prediction. Historical data spanning from 2006 to 2021 were utilized to assess the performance of the models. Hyperparameter tuning was performed on the models to optimize their performance, and root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and the normalized root mean squared error (NRMSE) were used as evaluation metrics. Although both machine learning models demonstrated strong performance, the analysis revealed that the ANN model emerged as the more reliable option for predicting discharge in the watershed. Crucially, the ANN model surpassed the SVM model’s performance, achieving superior accuracy in predicting peak discharge events within the study area. Our findings have the potential to assist decision-makers and communities in implementing more dependable flood mitigation strategies, particularly in regions where hydrology data are limited. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2024)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Title: Assessing the Efficiency of Fully 2-Dimensional Hydraulic Hec-Ras Models in Rivers of Cyprus

Authors: Georgia Siakara, Nikolaos Gourgouletis, Evangelos Baltas

2. Title: A Balloon Mapping Approach to Forecast Increases in PM10 from the Shrinking Shoreline at the Salton Sea

Authors: Ryan G. Sinclair, Joseliede Gaio, Seth Wiafe, Isabella Arzeno-Soltero and William C. Porter

3. Title: Neighborhood-Scale Wildfire Evacuation Vulnerability in Hays County, TX

Authors: Yihong Yuan and Chad Ramos

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