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Remote Sensing
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Remote Sensing for Modeling and Understanding Land-Atmosphere Interaction Processes
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Remote Sensing for Modeling and Understanding Land-Atmosphere Interaction Processes

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

Deadline for manuscript submissions: 31 October 2026 | Viewed by 3483

Special Issue Editors

Dr. Ren Wang

E-Mail Website
Guest Editor
School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: land-atmosphere interactions; hydroclimatology; global change; extreme climate; drought; remote sensing; machine learning
Prof. Dr. Dagang Wang

E-Mail Website
Guest Editor
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
Interests: extreme climate change; land surface process simulation; climate effects of urbanization; hydrometeorological
Dr. Wenbin Zhu

E-Mail Website
Guest Editor
Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
Interests: remote sensing hydrology; evapotranspiration; water resources management

Special Issue Information

Dear Colleagues,

Land–atmosphere interactions play a crucial role in shaping hydroclimatic patterns and ecosystems through the exchange of energy, water, and carbon between land surface and the atmosphere. They also influence the occurrence and severity of extreme disasters. These interactions are complex and encompass a range of physical and biological processes, including soil moisture, evapotranspiration, runoff, snow cover, vegetation, etc. Understanding and accurately modeling them is key for climate prediction, natural resources management, and addressing environmental challenges. Remote sensing has become an invaluable tool to monitor these processes, offering insights across various spatial and temporal scales. With the advances in remote sensing techniques, modelling methods, and data analytics, there is an unprecedented opportunity to refine our models and deepen our understanding of land–atmosphere interactions.

This Special Issue aims to bring together the latest advances in remote sensing techniques and their application to the modeling of land–atmosphere interactions. It will provide a comprehensive overview of how remote sensing enhances our understanding of these interactions and improve predictive models for climate, hydrology, and environmental sciences. This topic is closely aligned with the journal's scope, which focuses on innovative remote sensing techniques and their integration into environmental and geospatial sciences. By presenting cutting-edge research in this area, this Special Issue will contribute to advancing both theoretical knowledge and practical applications related to land–atmosphere interactions.

We invite contributions from a variety of disciplines, including geography, climatology, hydrology, ecosystem, and disaster management, all related to remote sensing and land–atmosphere interactions. The suggested themes include, but are not limited to, the following:

  1. Land-atmosphere interactions;
  2. Soil moisture dynamics;
  3. Vegetation ecosystems;
  4. Evapotranspiration processes;
  5. Land use/land cover change;
  6. Land-atmosphere heat exchange;
  7. Carbon cycle and carbon emission monitoring;
  8. Climate change and weather prediction;
  9. Monitoring and early warning of extreme events;
  10. Improvement or validation of land surface model.

Dr. Ren Wang
Prof. Dr. Dagang Wang
Dr. Wenbin Zhu
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 250 words) can be sent to the Editorial Office for assessment.

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

  • remote sensing
  • land-atmosphere interaction
  • evapotranspiration
  • soil moisture
  • vegetation ecosystem
  • land use/land cover change
  • land surface model
  • hydrological modeling
  • machine learning

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

Published Papers (3 papers)

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27 pages, 7254 KB  
Article
Shifts in the Decoupling and Driving Mechanisms of Grassland Greening and Water Availability in the Northern Hemisphere
by Gongxin Wang, Haiwei Zhang, Yuqing Shao and Changqing Jing
Remote Sens. 2026, 18(5), 829; https://doi.org/10.3390/rs18050829 - 7 Mar 2026
Cited by 1 | Viewed by 608
Abstract
Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly [...] Read more.
Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly understood. Here, we integrated multi-source satellite observations with CMIP6 model ensembles to systematically assess the spatiotemporal evolution and trend divergence of leaf area index (LAI) and WA across Northern Hemisphere grasslands from 2000 to 2100. Our results showed that grassland LAI exhibited sustained growth during 2000–2020, with 55.28% of regions showing significant increasing trends. However, 73.67% of grassland regions experienced declining WA during the historical period, revealing widespread decoupling between grassland greening and water deficit. Future scenario projections indicated a reversal to increasing WA trends, with 57.51% of regions showing significant increases under SSP5–8.5. Furthermore, 61.87% of grasslands exhibited greening-driven drying (GDD) characteristics during the historical period, while greening-driven wetting (GDW) regions were projected to expand to 72.44% in the future. Analysis along aridity gradients revealed that humid zones contributed most prominently to LAI and WA changes. Mechanistic decomposition demonstrated that grassland WA changes shifted from precipitation-dominated control (53.60%) in the historical period toward a regime jointly governed by precipitation dominance and coupled precipitation–evapotranspiration drivers in the future. Concurrently, the dominant factor controlling grassland greening transitioned from vapor-pressure deficit (VPD) to temperature (TEM) control. Additionally, driving factors exhibited pronounced differentiation patterns along aridity gradients during the historical phase: arid zones were dominated by soil moisture (SM) and semi-arid zones displayed dual control by SM and VPD, while humid zones were governed by coupled TEM-VPD regulation. This study reveals the divergent trends between grassland greening and WA and unravels their driving mechanisms, offering important scientific evidence for formulating regionally differentiated ecological water resource management strategies. Full article
(This article belongs to the Special Issue Remote Sensing for Modeling and Understanding Land-Atmosphere Interaction Processes)
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23 pages, 3707 KB  
Article
Spatiotemporal Patterns and Climate Attributions of Seasonal Stability of Vegetation Growth in Northern China
by Juanzhu Liang, Liping Fan, Yuke Zhou and Wenfang Li
Remote Sens. 2026, 18(5), 773; https://doi.org/10.3390/rs18050773 - 4 Mar 2026
Viewed by 457
Abstract
The earlier onset of vegetation phenology and longer growing seasons resulting from global warming are widely recognized as beneficial for enhancing the carbon sink function of terrestrial ecosystems. However, significant uncertainty remains regarding whether the increased growth during the early growing season can [...] Read more.
The earlier onset of vegetation phenology and longer growing seasons resulting from global warming are widely recognized as beneficial for enhancing the carbon sink function of terrestrial ecosystems. However, significant uncertainty remains regarding whether the increased growth during the early growing season can be sustained and converted into growth benefits during the later season or even throughout the entire year. This study focuses on vegetation in northern China. Based on solar-induced chlorophyll fluorescence (SIF) data from 2001 to 2020, it establishes an analytical framework for assessing the “seasonal stability” of vegetation growth. The framework quantifies the evolutionary characteristics of early growth enhancement signals during the late growing season. Furthermore, structural equation modeling (SEM) is employed to elucidate the underlying climate-driven mechanisms. The results indicate: (1) Vegetation growth season stability in northern China has long been dominated by the Strong stabilizing type (accounting for 87.4%), suggesting that early growth enhancement signals are mostly attenuated or suppressed during seasonal progression rather than continuously amplified. (2) This stable pattern exhibits a distinct spatial structure at the interannual scale. The expansive and Weak stabilizing types undergo event-driven expansions during specific climatic years, with different vegetation functional types adopting differentiated regulatory strategies during this process. Shallow-rooted grasslands demonstrate higher growth elasticity, while forest vegetation exhibits stronger ecological inertia. (3) Mechanistic analysis reveals that in water-limited zones, enhanced early growth accelerates transpiration processes, thereby disrupting seasonal soil moisture continuity and exacerbating water deficits during the late growing season. This inhibits late-season photosynthesis, constituting a core hydrological–physiological regulatory mechanism that maintains the dominance of Strong stabilizing in the region. Conversely, in energy-limited zones, late-season temperature emerges as the dominant factor constraining sustained growth. This study examines the transmission and modulation mechanisms of early growth signals to the later growing season from the perspective of intra-seasonal dynamics, providing a new analytical approach for incorporating interseasonal processes into assessments of vegetation growth and carbon sink stability in northern China. Full article
(This article belongs to the Special Issue Remote Sensing for Modeling and Understanding Land-Atmosphere Interaction Processes)
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Other

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14 pages, 3560 KB  
Technical Note
Global Asymmetric Changes in Land Evapotranspiration Components During Drought: Patterns and Variability
by Ren Wang and Hongyu Zhu
Remote Sens. 2025, 17(16), 2790; https://doi.org/10.3390/rs17162790 - 12 Aug 2025
Cited by 3 | Viewed by 1442
Abstract
Understanding and predicting changes in land evapotranspiration (ET) during droughts is crucial for elucidating land-atmosphere interactions. While previous studies have primarily focused on overall ET or individual components, they often overlook the mutual influences among different ET components. To address this gap, this [...] Read more.
Understanding and predicting changes in land evapotranspiration (ET) during droughts is crucial for elucidating land-atmosphere interactions. While previous studies have primarily focused on overall ET or individual components, they often overlook the mutual influences among different ET components. To address this gap, this study presents the first global analysis of concurrent changes in multiple ET components during meteorological droughts. Utilizing advanced satellite-based and reanalysis-based datasets, including the Global Land Evaporation Amsterdam Model (GLEAM) and the ECMWF reanalysis v5 (ERA5-Land) for the period 2000–2020, we find that the average probability of drought-driven increases in ET (P(ET+)) was approximately 0.5 during drought events. In contrast, the probabilities of an increase for the primary components—bare soil evaporation (Eb), canopy interception evaporation (Ei), and transpiration (Et)—were below 0.4, while the probability of drought-driven increases in snow sublimation (Es) exceeded 0.6. Globally, ET decreased by an average of 20.5 mm/month during a given drought period, though it increased in humid regions and snow-covered areas. Mild droughts resulted in an overall ET reduction, with increases in Eb and Es partially offsetting decreases in Et and Ei. However, as drought intensity increased, ET shifted toward an increase, which was constrained under extreme droughts. These findings highlight the asymmetric and interdependent responses of ET components to drought, underscoring the critical need to understand these interactions for accurately predicting ET dynamics under drought stress. Full article
(This article belongs to the Special Issue Remote Sensing for Modeling and Understanding Land-Atmosphere Interaction Processes)
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