Advances in Earth Observation Technologies to Support Water-Related Sustainable Development Goals (SDGs)

Topic Information

Dear Colleagues,

In recent years, Earth Observation Technologies (EOTs) have made significant strides in water resource monitoring and management, providing critical support for achieving water-related Sustainable Development Goals (SDGs). This Special Issue focuses on exploring how EOTs can drive sustainable water development, covering SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 14 (Life Below Water). Emerging technologies such as satellite remote sensing, drone monitoring, and artificial intelligence show great potential and innovative applications in water quality monitoring, water resource accessibility and allocation, flood and drought early warning, and wetland and coastal ecosystem conservation.

This Topic aims to attract research from fields including remote sensing, hydrology, environmental science, and geographic information systems, showcasing advances in EOTs for monitoring water-related disaster events, assessing water resource availability, and exploring water-related ecosystems evolution. We also encourage researchers to share innovative methods in data collection, analysis, and decision-support systems for water-related SDGs. Through this Topic, we hope to promote interdisciplinary collaboration and technological advancements that provide scientific foundations for water-related sustainable management and conservation globally.

In this Topic, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

1. Flood and drought monitoring and assessment;
2. Satellite-based water quality monitoring;
3. Water-related ecosystem protection monitoring;
4. Water resources use efficiency and sustainable management;
5. Remote sensing for water availability and distribution;
6. Assessing impacts of climate change on water resources with EOT;
7. Integration of EOT with ground-based observations for water-related SDGs;
8. Policy and governance implications of EOT in water management.

We look forward to receiving your contributions.

Dr. Wei Jiang
Dr. Elhadi Adam
Dr. Qingke Wen
Dr. Teodosio Lacava
Dr. Yizhu Lu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Drones drones	4.4	5.6	2017	19.2 Days	CHF 2600	Submit
Forests forests	2.4	4.4	2010	16.2 Days	CHF 2600	Submit
Geomatics geomatics	-	-	2021	22.1 Days	CHF 1000	Submit
ISPRS International Journal of Geo-Information ijgi	2.8	6.9	2012	35.8 Days	CHF 1900	Submit
Land land	3.2	4.9	2012	16.9 Days	CHF 2600	Submit
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700	Submit
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600	Submit
Water water	3.0	5.8	2009	17.5 Days	CHF 2600	Submit

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (4 papers)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Drones Forests Geomatics IJGI Land Remote Sensing Sensors Water

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

Error

Oops... you haven't selected anything for export.

Ok

clear

attachment

Supplementary material:
Supplementary File 1 (ZIP, 27 KiB)

21 pages, 14978 KiB  

Open AccessArticle

Determining the Spectral Characteristics of Fynbos Wetland Vegetation Species Using Unmanned Aerial Vehichle Data

by Kevin Musungu, Moreblessings Shoko and Julian Smit

Geomatics 2025, 5(2), 17; https://doi.org/10.3390/geomatics5020017 - 29 Apr 2025

Viewed by 115

Abstract

The Cape Floristic Region (CFR) boasts rich biodiversity but faces threats from invasive species and land-use changes. Fynbos wetland vegetation within the CFR is under-mapped despite its crucial role in supporting biodiversity and maintaining hydrological cycles. This study assessed the potential of UAV [...] Read more.

The Cape Floristic Region (CFR) boasts rich biodiversity but faces threats from invasive species and land-use changes. Fynbos wetland vegetation within the CFR is under-mapped despite its crucial role in supporting biodiversity and maintaining hydrological cycles. This study assessed the potential of UAV VIS-NIR data, gathered during Spring and Summer, to identify the spectral characteristics of eleven Fynbos wetland species in a seep wetland. Spectral distances derived from reflectance data revealed distinct spectral clustering of plant species, highlighting which species could be distinguished from each other. UAV data also captured differences in reflectance across spectral bands for both dates. Spectral statistics indicated that certain species could be more accurately classified in Spring than in Summer, and vice versa. These findings underscore the efficacy of UAV multispectral data in analyzing the reflectance patterns of fynbos wetland species. Additionally, the sensitivity of UAV multispectral data to foliar pigment composition across different seasonal stages was confirmed. Lastly, species classification results demonstrated that a random forest classifier is well suited, with relative producer and user accuracies aligning with the derived spectral distances. The results highlight the potential of UAV imagery for monitoring these endemic species and creating opportunities for scalable mapping of Fynbos seep wetlands. Full article

(This article belongs to the Topic Advances in Earth Observation Technologies to Support Water-Related Sustainable Development Goals (SDGs))

►▼ Show Figures

Figure 1

26 pages, 9389 KiB  

Open AccessArticle

Unravelling the Characteristics of Microhabitat Alterations in Floodplain Inundated Areas Based on High-Resolution UAV Imagery and Remote Sensing: A Case Study in Jingjiang, Yangtze River

by Yichen Zheng, Dongshuo Lu, Zongrui Yang and Jianbo Chang

Drones 2025, 9(4), 315; https://doi.org/10.3390/drones9040315 - 18 Apr 2025

Viewed by 254

Abstract

The floodplain of a large river plays a crucial role in the river’s ecosystem and serves as an essential microhabitat for river fish to complete their life history events. Over the past four decades, the floodplain represented by the Jingjiang section in the [...] Read more.

The floodplain of a large river plays a crucial role in the river’s ecosystem and serves as an essential microhabitat for river fish to complete their life history events. Over the past four decades, the floodplain represented by the Jingjiang section in the middle reaches of the Yangtze River has experienced a significant reduction in area, complexity, and diversity of fish microhabitats. This study quantitatively analyzed the dynamic changes and geomorphological structure of the floodplain in the Jingjiang reach (JJR) of the Yangtze River using satellite remote sensing images and high-resolution unmanned aerial vehicle (UAV) optical images. We built an enhanced U-Net model incorporating both the CBAM and SE parallel attention mechanisms to classify these images and identify environmental structural units. The accuracy of the enhanced model was 16.39% higher compared to original U-Net model. At the same time, the improved normalized difference water index (mNDWI), enhanced vegetation index (EVI), and normalized difference vegetation index (NDVI) were utilized to extract the flood frequency of the floodplain and analyze the area changes of the floodplain in the JJR. The trend of the flood area in the JJR during the flood season was consistent with the overall trend of flood areas in the flood season, which generally exhibits a downward tendency. In 2022, the floodplain of the JJR underwent substantial anthropogenic disturbances, with 40% of its area comprising anthropogenic environmental units. Compared to historical periods, the impervious surface within the floodplain has increased annually, while ecological units such as riparian forests and trees have gradually diminished or even disappeared, leading to a simplification of structural complexity. These findings provide a critical background and robust data foundation for the protection and restoration of fish habitats and the formulation of strategies for fish population reconstruction in the Yangtze River. Full article

(This article belongs to the Topic Advances in Earth Observation Technologies to Support Water-Related Sustainable Development Goals (SDGs))

►▼ Show Figures

Figure 1

23 pages, 10852 KiB  

Open AccessArticle

Precise Drought Threshold Monitoring in Winter Wheat Different Growth Periods Using a Multispectral Unmanned Aerial Vehicle

by Wenlong Song, Hongjie Liu, Yizhu Lu, Juan Lv, Rognjie Gui, Long Chen, Mengyi Li and Xiuhua Chen

Drones 2025, 9(3), 157; https://doi.org/10.3390/drones9030157 - 20 Feb 2025

Viewed by 461

Abstract

Agricultural drought significantly affects crop growth and food production, making accurate drought thresholds essential for effective monitoring and discrimination. This study aims to monitor the threshold ranges for different drought levels of winter wheat during three growth periods using a multispectral Unmanned Aerial [...] Read more.

Agricultural drought significantly affects crop growth and food production, making accurate drought thresholds essential for effective monitoring and discrimination. This study aims to monitor the threshold ranges for different drought levels of winter wheat during three growth periods using a multispectral Unmanned Aerial Vehicle (UAV). Firstly, based on controlled field experiments, six vegetation indices were used to develop UAV optimal inversion models for the Leaf Area Index (LAI) and Soil–Plant Analysis Development (SPAD) during the jointing–heading period, heading–filling period, and filling–maturity period of winter wheat. The results show that during the three growth periods, the DVI-LAI, NDVI-LAI, and RVI-LAI models, along with the DVI-SPAD, RVI-SPAD, and TCARI-SPAD models, achieved the highest inversion accuracy. Based on the UAV-inversed LAI and SPAD indices, threshold ranges for different drought levels were determined for each period. The accuracy of LAI threshold monitoring during three periods was 92.8%, 93.6%, and 90.5%, respectively, with an overall accuracy of 92.4%. For the SPAD index, the threshold monitoring accuracy during three periods was 93.1%, 93.0%, and 92%, respectively, with an overall accuracy of 92.7%. Finally, combined with yield data, this study explores UAV-based drought disaster monitoring for winter wheat. This research enriches and expands the crop drought monitoring system using a multispectral UAV. The proposed drought threshold ranges can enhance the scientific and precise monitoring of crop drought, which is highly significant for agricultural management. Full article

(This article belongs to the Topic Advances in Earth Observation Technologies to Support Water-Related Sustainable Development Goals (SDGs))

►▼ Show Figures

Figure 1

22 pages, 4714 KiB  

Open AccessArticle

Spatiotemporal Evolution and Driving Mechanisms of Ecological Risk in the Yuncheng Salt Lake Wetland, China

by Qicheng He, Zhihao Zhang, Yuan Zhang, Tianyue Sun, Weipeng Wang and Zhifeng Zhang

Water 2025, 17(4), 524; https://doi.org/10.3390/w17040524 - 12 Feb 2025

Viewed by 577

Abstract

As the only large sulfate-type salt lake in the global warm temperate deciduous forest zone, Yuncheng Salt Lake plays a crucial role in maintaining ecosystem stability and establishing a regional ecological barrier due to its unique ecological characteristics. Currently, there is a lack [...] Read more.

As the only large sulfate-type salt lake in the global warm temperate deciduous forest zone, Yuncheng Salt Lake plays a crucial role in maintaining ecosystem stability and establishing a regional ecological barrier due to its unique ecological characteristics. Currently, there is a lack of research on the spatial and temporal differentiation of ecological risks in inland lakes, particularly salt lake wetland ecosystems, under current and future scenarios. Moreover, studies using optimal parameter-based geographical detectors to identify the influencing factors of landscape ecological risks—while avoiding subjective bias—remain limited. This study utilizes land use/land cover data of Yuncheng Salt Lake from 1990 to 2022 to construct a landscape ecological risk assessment model. By employing spatial autocorrelation analysis, the optimal geographical detector, and the Patch-level Land Use Simulation (PLUS) model, the study explores the dynamic evolution of ecological risks in Yuncheng Salt Lake wetlands under different current and future scenarios. Furthermore, it analyzes the influence of various natural and socio-economic factors on ecological risk, aiming to provide valuable insights for targeted ecological risk warning and management measures in inland salt lake regions. The results indicate that: (1) Between 1990 and 2022, the area of built-up land in Yuncheng Salt Lake wetlands increased significantly, primarily due to the continuous decline in farmland area, while the water area initially decreased and then increased. (2) The landscape ecological risk index declined over the study period, indicating an improvement in the ecological risk status of Yuncheng Salt Lake wetlands in recent years, with the overall ecosystem security trending positively. (3) Topographical conditions are the primary factors influencing landscape ecological risk in Yuncheng Salt Lake wetlands, followed by mean annual temperature and population density. The synergistic effect of elevation with annual precipitation and NDVI (Normalized Difference Vegetation Index) exhibits the strongest explanatory power for the landscape ecological risk in the region. (4) Under different future scenarios, the proportion of high ecological risk areas in Yuncheng Salt Lake wetlands is projected to decrease to varying extents, with the ecological protection scenario contributing more effectively to the sustainable development of the salt lake wetland ecosystem. Full article

(This article belongs to the Topic Advances in Earth Observation Technologies to Support Water-Related Sustainable Development Goals (SDGs))

►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

 

Error

Oops... you haven't selected anything for export.

Ok

clear

Displaying articles 1-4