AI and ML for Wetlands: Remote Sensing-Driven Solutions for Climate-Resilient Ecosystem Management
Deadline 2026-10-31Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
Wetlands are among the most complex and productive ecosystems on Earth, shaped by strong interactions between water, vegetation, soil, and climate. They provide essential ecosystem services such as biodiversity support, flood attenuation, groundwater recharge, water quality improvement, and long-term carbon storage. Yet wetlands are also highly dynamic, often fragmented, and increasingly threatened by climate change…
HY-4A: Pioneering Global Ocean Salinity Mapping from Space
Deadline 2026-11-30Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
The successful November 14, 2024 launch of HY-4A, the inaugural satellite of the Chinese Ocean Salinity Mission (COSM), marks a significant advancement in space-based oceanography. As a key component of China's civil space infrastructure, HY-4A carries a sophisticated payload suite including the L-band Aperture Synthesis Microwave Radiometer (LASMR) and the Microwave Imager Combined Active and Passive (MICAP), which…
Scientific Advances in Surface Water and Hydrological Cycle Observations from the SWOT Mission
Deadline 2026-11-30Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
The Surface Water and Ocean Topography (SWOT) satellite mission marks a transformative advancement in Earth system observation, delivering the first global, high-resolution measurements of surface water elevation and extent. Utilizing a Ka-band radar interferometer, SWOT captures two-dimensional water surface elevation fields, enabling comprehensive quantification of river discharge, lake storage, floodplain dynamic…
Remote Sensing in Cloudy and Rainy Environments: Challenges, Advances, and Applications
Deadline 2026-12-31Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
Cloudy and rainy environments are common in tropical, subtropical, and other regions frequently affected by cloud cover and rainfall. These challenging conditions pose significant obstacles to remote sensing data acquisition, processing, and applications, while also motivating innovation in methodologies and technologies. Effective remote sensing methods and applications in these regions are crucial for supporting e…
Geospatial Intelligence and Earth Observation for Climate Extremes Resilience in the Global South
Deadline 2027-04-30Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
The Global South is disproportionately exposed to intensifying climate extremes, including tropical cyclones, flash floods, severe drought, and heatwaves. Understanding the dynamics, patterns, and evolution of these extreme events is of the utmost necessity as they directly jeopardize the food and water security of billions of people living in these regions. We therefore require a deeper understanding of these extre…
Geospatial Intelligence for Agricultural Monitoring: Integrating Remote Sensing, UAVs, and Artificial Intelligence
Deadline 2027-05-31Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
Agriculture is facing growing challenges associated with climate variability, water scarcity, land degradation, increasing food demand, and pressure on natural resources. Addressing these challenges requires accurate and timely information to support effective management and improve resource use efficiency. Integrating information from multiple data sources allows agricultural conditions to be monitored more consist…
Multimodal Remote Sensing Data Fusion for Geospatial Intelligence
Deadline 2027-05-31Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
Contemporary Earth observation and GIScience bring together satellite, airborne, nighttime light, in situ, mobile, social, and model-generated geospatial data. However, heterogeneities in scale, geometry, resolution, uncertainty and timeliness complicate joint analysis and pose critical open challenges, while data limitations such as cloud contamination, mismatched spatial and temporal sampling, missing observations…
VLM Driven Intelligent Interpretation of Remote Sensing Imagery
Deadline 2027-05-31Taylor & FrancisIndexed (Active)
Journal: GIScience & Remote Sensing
The rapid progress of vision-language models (VLMs) empowers intelligent remote sensing image interpretation, transforming traditional label-guided recognition into knowledge-driven scene understanding and reasoning to fuel industrial technical upgrades. Conventional remote sensing approaches constrained by limited semantic tags lack robust semantic expression, cross-region generalization, complex-scene reasoning ab…
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