Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Application of Remote Sensing in Environmental Monitoring
applsci-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Application of Remote Sensing in Environmental Monitoring

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: 20 July 2025 | Viewed by 1143

Special Issue Editor

Dr. Wei Chen

E-Mail Website
Guest Editor
College of Geosciences and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Interests: black carbon aerosol; aerosol radiative forcing; polarimetric remote sensing; atmospheric environment; environment ecology remote sensing; radiometric calibration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, with the rapid development of remote sensing technologies and sensors, remote sensing has become widely applied in environmental monitoring. For decades, with the help of remote sensing images, land phenology has been evaluated to investigate the impact of global warming. Furthermore, with high-resolution remote sensing images, changes in urban environments can be evaluated in detail. Hence, remote sensing plays an important role in environmental monitoring.

These recent advances have promoted research in the field of environmental monitoring. With the development of artificial intelligence, and other remote sensing technologies, applications of remote sensing in environmental monitoring have become increasingly pertinent.

This Special Issue on the “Application of Remote Sensing in Environmental Monitoring” welcomes original research articles and reviews with a focus on new algorithms and applications in environmental monitoring with remote sensing technologies. We invite researchers to submit their recent work to our journal.

Research areas may include (but are not limited to) the following:

  1. Algorithms in remote sensing environmental monitoring;
  2. Reviews on remote sensing environmental monitoring;
  3. Data analysis in remote sensing environmental monitoring;
  4. Dataset in remote sensing environmental monitoring.

Dr. Wei 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. Applied Sciences 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 2400 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
  • environmental monitoring
  • environment ecology

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

25 pages, 9849 KiB  
Article
Using Bi-Temporal Lidar to Evaluate Canopy Structure and Ecotone Influence on Landsat Vegetation Index Trends Within a Boreal Wetland Complex
by Farnoosh Aslami, Chris Hopkinson, Laura Chasmer, Craig Mahoney and Daniel L. Peters
Appl. Sci. 2025, 15(9), 4653; https://doi.org/10.3390/app15094653 - 23 Apr 2025
Viewed by 341
Abstract
Wetland ecosystems are sensitive to climate variation, yet tracking vegetation type and structure changes through time remains a challenge. This study examines how Landsat-derived vegetation indices (NDVI and EVI) correspond with lidar-derived canopy height model (CHM) changes from 2000 to 2018 across the [...] Read more.
Wetland ecosystems are sensitive to climate variation, yet tracking vegetation type and structure changes through time remains a challenge. This study examines how Landsat-derived vegetation indices (NDVI and EVI) correspond with lidar-derived canopy height model (CHM) changes from 2000 to 2018 across the wetland landscape of the Peace–Athabasca Delta (PAD), Canada. By comparing CHM change and NDVI and EVI trends across woody and herbaceous land covers, this study fills a gap in understanding long-term vegetation responses in northern wetlands. Findings show that ~35% of the study area experienced canopy growth, while 2% saw a reduction in height. CHM change revealed 11% ecotonal expansion, where shrub and treed swamps encroached on meadow and marsh areas. NDVI and EVI correlated significantly (p < 0.001) with CHM, particularly in shrub swamps (r2 = 0.40, 0.35) and upland forests (NDVI r2 = 0.37). However, EVI trends aligned more strongly with canopy expansion, while NDVI captured mature tree height growth and wetland drying, indicated by rising land surface temperatures (LST). These results highlight the contrasting responses of NDVI and EVI—NDVI being more sensitive to moisture-related changes such as wetland drying, and EVI aligning more closely with canopy structural changes—emphasizing the value of combining lidar and satellite indices to monitor wetland ecosystems in a warming climate. Full article
(This article belongs to the Special Issue Application of Remote Sensing in Environmental Monitoring)
►▼ Show Figures

Figure 1

26 pages, 6050 KiB  
Article
Multi-Scale Twin Networks for Coastal Zone Change Detection in Remote Sensing Imagery
by Peiqi Zhu, Xiaoyi Jiang, Qi He, Longfei Zhao, Yu Hong, Xue Guo and Hanrui Sun
Appl. Sci. 2025, 15(4), 1904; https://doi.org/10.3390/app15041904 - 12 Feb 2025
Viewed by 564
Abstract
Accurate coastal zone change detection is crucial for coastal urban planning and marine resource development. To address the specificity of coastal zone change detection and the category imbalance issue in the model, we propose a multi-scale coastal zone change detection method (AMMNet) based [...] Read more.
Accurate coastal zone change detection is crucial for coastal urban planning and marine resource development. To address the specificity of coastal zone change detection and the category imbalance issue in the model, we propose a multi-scale coastal zone change detection method (AMMNet) based on the attention mechanism. The method leverages multi-scale features extracted by the ResNet backbone, which are then optimized and integrated through high-frequency attention and spatio-temporal difference modules. These modules allow the model to focus on both global and local changes, enhancing its ability to detect variations in coastal zones. Additionally, the foreground attention module refines the model’s attention on relevant regions, ensuring improved performance. The experimental results show that our method achieves the highest scores in several evaluation metrics, demonstrating significant advantages in accuracy and generalization and effectively addressing the category imbalance problem. It provides a robust solution for coastal zone change detection. Full article
(This article belongs to the Special Issue Application of Remote Sensing in Environmental Monitoring)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop