Advances in Multi-Scale Geographic Environmental Monitoring: Ecosystem Differences and Multi-Scale Comparisons

Abstract submission deadline

31 May 2026

Manuscript submission deadline

31 August 2026

Viewed by

1000

Topic Information

Dear Colleagues,

The second volume of Advances in Multi-Scale Geographic Environmental Monitoring is dedicated to exploring the intricate dynamics of ecosystems and their responses to environmental changes through a multi-scale lens. This journal issue seeks to bridge the gap between ecosystem-specific studies and the broader understanding of ecological processes by emphasizing two central themes: ecosystem differences and multi-scale comparisons.

At its core, multi-scale geographic environmental monitoring involves the systematic observation and analysis of Earth's surface processes and human activities across varying spatial and temporal scales. By integrating data from global to local scales, this approach provides a comprehensive framework for understanding the complex interactions between natural systems and anthropogenic influences. The second volume builds on this foundation by focusing on the unique characteristics of different ecosystems—such as forests, wetlands, and urban areas—and how these ecosystems respond to environmental perturbations. Despite significant advancements in multi-scale monitoring, several critical gaps remain in the existing body of research. A notable limitation is the lack of comparative studies that span multiple ecosystems and scales, which hinders the ability to draw generalizable conclusions. Furthermore, current research often treats scales as isolated entities, failing to fully integrate them into a cohesive framework that captures the complexity of ecosystem processes. Another challenge lies in the limited application of advanced technologies, such as AI-driven remote sensing and IoT-enabled sensors, which, while promising, remain underutilized in multi-scale ecosystem studies. Future research directions aim to address these gaps while leveraging emerging technologies. A key priority is the development of cross-ecosystem frameworks that standardize methodologies for comparing ecosystems across scales. Enhancing scale integration is another critical focus, with efforts directed toward building models that explicitly account for scale dependencies and feedback mechanisms. Interdisciplinary collaboration will play a pivotal role in achieving these goals, fostering partnerships between ecologists, geographers, computer scientists, and policymakers to tackle complex environmental challenges. In light of the above, this topic aims to collect innovative original manuscripts on the theoretical, methodological, and applied aspects of multi-scale geographic environmental monitoring, especially concerning ecosystem differences and multi-scale comparisons. Review articles and meta-analysis papers on these topics are additionally welcome. Topics of interest include the following:

• Multi-scale driving mechanisms of spatial heterogeneity in geographic environmental elements;
• Coupled spatiotemporal modeling and validation of geographical environmental dynamics;
• Reconstruction of holistic monitoring technology systems in the era of intelligent perception;
• Multi-scale transmission and trade-off assessment of ecosystem service flows;
• Simulation of multi-level interactive feedback in key land surface processes;
• Identification of scale sensitivity thresholds in geographic environment research;
• Assessment paradigms of environmental carrying capacity under human–land system coupling;
• Cross-dimensional fusion and downscaling of multi-source heterogeneous geospatial big data;
• Scale-based source analysis and error propagation models for uncertainties in geographic element monitoring.

Dr. Jingzhe Wang
Dr. Xiangyu Ge
Dr. Zipeng Zhang
Dr. Ivan Lizaga
Dr. Yinghui Zhang
Dr. Yangyi Wu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agronomy agronomy	3.4	6.7	2011	17.2 Days	CHF 2600	Submit
Drones drones	4.8	7.4	2017	20.1 Days	CHF 2600	Submit
Geomatics geomatics	2.8	5.1	2021	20 Days	CHF 1000	Submit
ISPRS International Journal of Geo-Information ijgi	2.8	7.2	2012	34.2 Days	CHF 1900	Submit
Land land	3.2	5.9	2012	16 Days	CHF 2600	Submit
Remote Sensing remotesensing	4.1	8.6	2009	24.9 Days	CHF 2700	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.

Related Topic

Published Papers (2 papers)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Agronomy Drones Geomatics IJGI Land Remote Sensing

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

27 pages, 31400 KiB  

Open AccessArticle

Multi-Scale Analysis of Land Use Transition and Its Impact on Ecological Environment Quality: A Case Study of Zhejiang, China

by Zhiyuan Xu, Fuyan Ke, Jiajie Yu and Haotian Zhang

Land 2025, 14(8), 1569; https://doi.org/10.3390/land14081569 - 31 Jul 2025

Viewed by 190

Abstract

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and [...] Read more.

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

(This article belongs to the Topic Advances in Multi-Scale Geographic Environmental Monitoring: Ecosystem Differences and Multi-Scale Comparisons)

►▼ Show Figures

Figure 1

21 pages, 5313 KiB  

Open AccessArticle

MixtureRS: A Mixture of Expert Network Based Remote Sensing Land Classification

by Yimei Liu, Changyuan Wu, Minglei Guan and Jingzhe Wang

Remote Sens. 2025, 17(14), 2494; https://doi.org/10.3390/rs17142494 - 17 Jul 2025

Viewed by 331

Abstract

Accurate land-use classification is critical for urban planning and environmental monitoring, yet effectively integrating heterogeneous data sources such as hyperspectral imagery and laser radar (LiDAR) remains challenging. To address this, we propose MixtureRS, a compact multimodal network that effectively integrates hyperspectral imagery and [...] Read more.

Accurate land-use classification is critical for urban planning and environmental monitoring, yet effectively integrating heterogeneous data sources such as hyperspectral imagery and laser radar (LiDAR) remains challenging. To address this, we propose MixtureRS, a compact multimodal network that effectively integrates hyperspectral imagery and LiDAR data for land-use classification. Our approach employs a 3-D plus heterogeneous convolutional stack to extract rich spectral–spatial features, which are then tokenized and fused via a cross-modality transformer. To enhance model capacity without incurring significant computational overhead, we replace conventional dense feed-forward blocks with a sparse Mixture-of-Experts (MoE) layer that selectively activates the most relevant experts for each token. Evaluated on a 15-class urban benchmark, MixtureRS achieves an overall accuracy of 88.6%, an average accuracy of 90.2%, and a Kappa coefficient of 0.877, outperforming the best homogeneous transformer by over 12 percentage points. Notably, the largest improvements are observed in water, railway, and parking categories, highlighting the advantages of incorporating height information and conditional computation. These results demonstrate that conditional, expert-guided fusion is a promising and efficient strategy for advancing multimodal remote sensing models. Full article

(This article belongs to the Topic Advances in Multi-Scale Geographic Environmental Monitoring: Ecosystem Differences and Multi-Scale Comparisons)

►▼ Show Figures

Graphical abstract

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 1-2