remotesensing-logo

Journal Browser

Journal Browser

Remote Sensing of Land Surfaces: Observation, Modeling, and Data Assimilation

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 595

Special Issue Editors


E-Mail Website
Guest Editor
School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: satellite remote sensing; data assimilation; weather forecasting
Special Issues, Collections and Topics in MDPI journals
Earth System Modeling and Prediction Center, China Meteorological Administration, Beijing 100081, China
Interests: satellite data assimilation; remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The land surface is a key component of the Earth system and it plays a critical role in various environmental processes. The accurate monitoring and analysis of land surface parameters, such as soil moisture, vegetation cover, land use, and surface temperature, are essential for numerous applications, including climate modeling, agricultural management, disaster response, and ecological conservation.

In recent years, the field of remote sensing has experienced significant advancements, profoundly enhancing the ability to observe, model, and understand the land surface. For example, satellite, airborne, and ground-based sensors, etc., can provide comprehensive, high-resolution, and continuous data across wide areas, as well as capture the dynamic and heterogeneous nature of land surfaces. At the same time, integrating remote sensing observations with modeling and data assimilation further enhances the ability to interpret and utilize land surface information. Combining observational data with numerical models provides accurate and coherent representations of land surface processes, which is also important for improving predictive models and resource management.

This Special Issue aims to showcase the latest research on the observation, modeling, and data assimilation of land surface process using remote sensing technologies, hopefully benefitting researchers, practitioners, and policymakers interested in this topic. All original research articles, review papers, technical notes, and case studies on this topic are welcomed.

Prof. Dr. Yansong Bao
Dr. Fu Wang
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. Remote Sensing 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 2700 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

  • land surface process
  • data assimilation
  • remote sensing 
  • land cover
  • soil moisture

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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 13935 KiB  
Article
A Diagnostic Analysis of the 2024 Beijing May 30 Gale Simulation Based on Satellite Observation Products
by Xiaoying Xu, Zhuoya Ni, Qifeng Lu, Ruixia Liu, Chunqiang Wu, Fu Wang and Jianglin Hu
Remote Sens. 2025, 17(8), 1378; https://doi.org/10.3390/rs17081378 - 12 Apr 2025
Viewed by 172
Abstract
A gale occurred in Beijing on 30 May 2024, which led to fallen trees and damaged infrastructure. This event was primarily driven by surface divergent winds induced by strong convective downdrafts. During the occurrence and development of this gale, solar shortwave radiation and [...] Read more.
A gale occurred in Beijing on 30 May 2024, which led to fallen trees and damaged infrastructure. This event was primarily driven by surface divergent winds induced by strong convective downdrafts. During the occurrence and development of this gale, solar shortwave radiation and cloud-related variables played a crucial role in triggering, sustaining, and organizing convection. This study proposes a new diagnostic analysis approach for this gale focusing on shortwave radiation and cloud-related variables involved in the physical processes of gale development, based on the FY-4B L2 products and simulations from the Mesoscale Weather Numerical Forecast System of the China Meteorological Administration (CMA-MESO). The diagnostic analysis results of this case show that before cloud formation, the CMA-MESO simulates stronger shortwave radiation heating in the initial stages, leading to an overestimation of surface temperature rise. Additionally, the simulated cloud formation occurs slightly later than observed, with reduced cloud coverage, shorter cloud duration, and lower cloud top heights, resulting in a weaker convective intensity compared to observations. Furthermore, the CMA-MESO underestimates the temperature gradient between the middle and lower troposphere and predicts lower convective instability, which leads to weaker forecasts of convection organization. Ultimately, this study provides a theoretical basis and technical support for enhancing the ability of the CMA-MESO to simulate this gale by using the FY-4B L2 data products for diagnostic analysis. Full article
Show Figures

Figure 1

Back to TopTop