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Ecohydrological Sensing and Modeling with Geographic Information Systems
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Ecohydrological Sensing and Modeling with Geographic Information Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Environmental Sensing".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 6137

Special Issue Editors

Prof. Dr. Takashi Asaeda

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Guest Editor
Institute for Studies of the Global Environment, 7-1 Sophia University, Kioicho, Chiyoda, Tokyo 102-0094, Japan
Interests: aquatic plants; vegetation in floodplains; wetlands
Special Issues, Collections and Topics in MDPI journals
Dr. Dongdong Shao

E-Mail Website
Guest Editor
School of Environment, Beijing Normal University, Beijing 100875, China
Interests: eco- and environmental-hydraulics; estuarine hydrodynamics; morphodynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Petre Brețcan

E-Mail Website
Guest Editor
Department of Geography, Faculty of Humanities, Valahia University of Târgoviste, 130105 Dambovita, Romania
Interests: limnology; wetlands; water quality; geospatial analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Shuxin Luo

E-Mail Website
Guest Editor
1. Department of Geography, Humboldt-Universitaet zu Berlin, 12587 Berlin, Germany
2. Department 1 “Ecohydrology & Biogeochemistry” IGB Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany
Interests: ecohydrology; climate impacts; wetlands; groundwater hydrology; modelling

Special Issue Information

Dear Colleagues,

Recent advances in remote sensing technology, especially those based on unmanned aerial vehicle (UAV), have revolutionized ecological and environmental monitoring. The applicability of UAV as a flexible cost-effective tool for frequent high-resolution mapping and monitoring, particularly for small-scale systems when used in combination with multispectral cameras and the Structure from Motion (SfM) algorithm, has been well established. For large-scale environmental monitoring and mapping, the fusion of multi-source remote sensing data (e.g., satellite imagery, LiDAR, and SAR) and state-of-the-art (e.g., decision trees, machine learning) classification approaches can be used to achieve a high accuracy and high resolution in both time and space. At the same time, process-based models have been at the forefront of ecohydrological research in recent decades, and significant progress has been made in simplified generic model development as well as applications in real systems. However, the logistically demanding acquisition of basic data with high resolution, such as DEM and vegetation distribution, required for initial model construction, plus the additional measurements of the water level, velocity, etc., that are needed for model calibration and validation in a complex terrain such as wetlands still remain key technical challenges to which rapidly developing remote sensing technologies may provide a promising solution. Furthermore, high-performance computing, such as cluster-based parallel computing, is increasingly being employed to process and classify large remote sensing datasets in a timely fashion using machine learning algorithms and run model simulations. The integration of remote sensing data and numerical models in GIS can help us understand and predict ecohydrological changes induced by natural or anthropogenic disturbances. It can also be used to inform landscape design, ecological restoration through hydrological regulation, and other ecological conservation and restoration activities.

For this Special Issue, papers reporting theories, methodologies, and applications relating to the above topic are welcome. This Special Issue aims to cover, but is not limited to, the following areas:

  • Monitoring ecohydrological variations using various sensing technologies;
  • Modeling the ecological and hydrological processes in GIS;
  • Methods and approaches using GIS to assess ecohydrological changes;
  • Policies for regulating ecosystems in terms of ecohydrology.

Prof. Dr. Takashi Asaeda
Dr. Dongdong Shao
Dr. Petre Brețcan
Dr. Shuxin Luo
Guest Editors

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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • remote sensing
  • UAV
  • GIS
  • ecohydrology
  • ecological and hydrological modeling
  • landscape design
  • ecological conservation and restoration
  • basin management

Published Papers (2 papers)

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Research

21 pages, 8847 KiB  
Article
Flash Flood Vulnerability Mapping Based on FFPI Using GIS Spatial Analysis Case Study: Valea Rea Catchment Area, Romania
by István Kocsis, Ștefan Bilașco, Ioan-Aurel Irimuș, Vasile Dohotar, Raularian Rusu and Sanda Roșca
Sensors 2022, 22(9), 3573; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093573 - 07 May 2022
Cited by 11 | Viewed by 2713
Abstract
The risk associated with extreme hydrological processes (flash floods, floods) is more present than ever, taking into account the global climatic changes, the expansion of inhabited areas and the changes emerging as a result of inadequate land management. Of all the hydrological risks, [...] Read more.
The risk associated with extreme hydrological processes (flash floods, floods) is more present than ever, taking into account the global climatic changes, the expansion of inhabited areas and the changes emerging as a result of inadequate land management. Of all the hydrological risks, slope flash floods represent the processes that have the highest impact because of the high speed of their development and their place of origin, which makes them difficult to predict. This study is performed in an area susceptible to the emergence of slope flash floods, the Valea Rea catchment area, spatially located in Northwest Romania, and exposed to western circulation, which favours the development of such processes. The entire research is based on a methodology involving the integration of spatial databases, which indicate the vulnerability of the territory in the form of a weighted average equation to highlight the major impact of the most relevant factor. A number of 15 factors have been used in raster spatial databases, obtained by conversion (land use, soil type, lithology, Hydrologic Soil Group, etc.), derived from the digital elevation model (slope, aspect, TWI, etc.) or by performing spatial analysis submodels (precipitation, slope length, etc). The integration of these databases by means of the spatial analysis equation based on the weighted average led to the vulnerability of the territory to FFPI, classified on five classes from very low to very high. The final result underlines the high and very high vulnerability (43%) of the analysed territory that may have a major impact on the human communities and the territorial infrastructure. The results obtained highlight the torrential nature of the analysed catchment area, identifying several hotspots of great risk, located mainly within the built-up areas of intensely inhabited regions; a fact which involves a major risk and significant potential material damage in the territory. The model was validated by directly comparing the results obtained with locations previously affected, where the flood effects have been identified, highlighting the fact that the model may be taken into account to be applied in practice, and also to be implemented in territories that share the same features. Full article
(This article belongs to the Special Issue Ecohydrological Sensing and Modeling with Geographic Information Systems)
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19 pages, 5744 KiB  
Article
Estimating Biomass and Carbon Sequestration Capacity of Phragmites australis Using Remote Sensing and Growth Dynamics Modeling: A Case Study in Beijing Hanshiqiao Wetland Nature Reserve, China
by Siyuan Wang, Sida Li, Shaoyan Zheng, Weilun Gao, Yong Zhang, Bo Cao, Baoshan Cui and Dongdong Shao
Sensors 2022, 22(9), 3141; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093141 - 20 Apr 2022
Cited by 5 | Viewed by 2337
Abstract
Estimating the biomass of Phragmites australis (Cav.) Trin. ex Steud., i.e., a common wetland macrophyte, and the associated carbon sequestration capacity has attracted increasing attention. Hanshiqiao Wetland Nature Reserve (HWNR) is a large P. australis wetland in Beijing, China, and provides an ideal [...] Read more.
Estimating the biomass of Phragmites australis (Cav.) Trin. ex Steud., i.e., a common wetland macrophyte, and the associated carbon sequestration capacity has attracted increasing attention. Hanshiqiao Wetland Nature Reserve (HWNR) is a large P. australis wetland in Beijing, China, and provides an ideal case study site for such purpose in an urban setting. In this study, an existing P. australis growth dynamics model was adapted to estimate the plant biomass, which was in turn converted to the associated carbon sequestration capacity in the HWNR throughout a typical year. To account for local differences, the modeling parameters were calibrated against the above-ground biomass (AGB) of P. australis retrieved from hyperspectral images of the study site. We also analyzed the sensitivity of the modeling parameters and the influence of environmental factors, particularly the nutrient availability, on the growth dynamics and carbon sequestration capacity of P. australis. Our results show that the maximum AGB and below-ground biomass (BGB) of P. australis in the HWNR are 2.93 × 103 and 2.49 × 103 g m−2, respectively, which are higher than the reported level from nearby sites with similar latitudes, presumably due to the relatively high nutrient availability and more suitable inundation conditions in the HWNR. The annual carbon sequestration capacity of P. australis in the HWNR was estimated to be 2040.73 gC m−2 yr−1, which was also found to be highly dependent on nutrient availability, with a 50% increase (decrease) in the constant of the nutrient availability KNP, resulting in a 12% increase (23% decrease) in the annual carbon sequestration capacity. This implies that a comprehensive management of urban wetlands that often encounter eutrophication problems to synergize the effects of nutrient control and carbon sequestration is worth considering in future practices. Full article
(This article belongs to the Special Issue Ecohydrological Sensing and Modeling with Geographic Information Systems)
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