YESAT

🐚 Tidalflat - Nature's true source of life 🐚

This incredible ecosystem is submerged half the day, constantly shifting as tides ebb and flow. South Korea's mudflats span 2,443.3 km² (about 4x Seoul's size!), requiring advanced monitoring approaches beyond traditional drone and vessel surveys.

Our research leverages 🛰️SAR satellite imagery🛰️ to observe mudflats consistently regardless of weather conditions. By analyzing pixel brightness, exposure timing, and capture dates across images, we can map tidalflat topography and exposure frequencies of these dynamic environments. This research will be crucial for developing monitoring strategies as we face global sea level rise challenges and enviornment pollution caused by coastal developments.

radar remote sensing geospatial information tidal flat

💧💧 Hydrological research with LIS!💧💧

Our lab is developing high-resolution hydrological models of the Korean Peninsula using the Land Information System (LIS) — a software framework that integrates satellite data, in-situ observations, and advanced data assimilation techniques. LIS allows us to simulate complex hydrological processes and quantify key components of the water cycle, contributing to a better understanding of regional water budgets.

The applications are far-reaching: 🌊 forecasting floods and droughts 💧 optimizing water resource management 🌱 supporting data-driven environmental policy and decision-making

We're excited about the potential of LIS to enhance our understanding of South Korea’s unique hydrological systems and challenges! 🔥🔥

land information system water resources

🛰️🛰️ SAR satellite imagery for change detection 🛰️🛰️

Once mostly used by engineering and military applications, satellite data is now helping us analyze national economies and predict global crop yields - a true human-focused evolution. This research explores this emerging technologies by using time-series satellite imagery to monitor reclamation projects and facilities in public waters. We're creating effective monitoring algorithm that support policy decisions and implementation around these shared resources for coastal mapping, policy development, and to utilize execution processes.

This research combines remote sensing technology with public policy to provide data-driven insights that help improve the management of our shared water resources.

geosciences remote sensing

🌏🌏 Measuring Earth's water storage with satellite? 🌏🌏

Fascinating GRACE project in action🔥🔥 These satellites fly in formation, precisely measuring distance changes between them caused by Earth's gravitational variations. This research focuses on overcoming GRACE's biggest limitation - coarse spatial resolution (about 330km). While perfect for large-scale hydrological research like monitoring climate change impacts on water resources, this resolution is too broad for local studies☹️☹️. Therefore, We're developing statistical downscaling techniques that combine GRACE data with various numerical models to enhance spatial resolution.

This work has exciting applications for drought/flood prediction, groundwater depletion monitoring, and sea level variation analysis. The GRACE mission allowed us how to track water movement across our planet - now we're taking that revolutionary data to the next level! 😎😎

GRACE water resources

🤖🤖 Remote Sensing x AI research from our lab ! 🤖🤖

Why should AI be used for detecting nearshore aquaculture facilities?

The complex coastal environment creates non-linear relationships between aquaculture facilities and their spectral reflectivity, making traditional detection methods (like threshold-based approaches) insufficient. Also, various types of aquaculture structures are densely positioned throughout Korea's southern coastal waters. Therefore, conventional methodologies struggle to accurately identify these facilities.

We're addressing these challenges by combining multi-satellite imagery with AI techniques to detect nearshore aquaculture facilities along the Korean peninsula's southern coast. This fusion approach allows us to extract complementary information from different satellite sources, compensating for the limitations of individual sensors while enhancing detection capabilities. By analyzing complex spatiotemporal patterns in coastal satellite big data, we're building foundational datasets for comprehensive environmental monitoring. Our research evaluates detection accuracy across different facility types, contributing to more effective coastal management strategies.

Please keep watching our cutting-edge Remote Sensing × AI research 🔥🔥

AI aquaculture facility coastal environment management

🌊🐳 Advancing Coastal Altimetry: Overcoming Challenges in Sea Level Measurement 🐳🌊

We focuses on developing specialized altimetry data processing methods for coastal regions. Satellite altimeters are used to observe sea surface height, and it is determined by measuring the round-trip time of the radar pulse from the satellite. The waveform represents the signal reflected from the surface over time, and provides surface information depending on the waveform shape. In general, the waveform shape in the ocean reaches its peak when the radar pulse reaches the surface, after which the slope becomes gradual. Sea level measurements are challenging to use when near land because the signal is contaminated by the terrain around it and takes on a different waveform shape.

To overcome these limitations, enhanced technologies like SAR mode altimeters (utilizing the Doppler effect) and FF-SAR mode altimeters are being developed to produce high-resolution sea surface height data. We're working with these various altimeter modes to create processing techniques specifically optimized for coastal environments.

Remote Sensing Altimeter Waveform Sea Level

⛰️⛰️ Subsidence Monitoring : Time-series SAR Interferometry Method Applied to Monitor Ground Deformation ⛰️⛰️

We applie Persistent Scatterer Interferometric SAR (PSI) to monitor ongoing ground subsidence. Synthetic Aperture Radar (SAR) is revolutionizing how we track ground movement - it works regardless of weather conditions or time of day, making it ideal for continuous monitoring. By analyzing multiple SAR images of the same location over time, we can create precise time-series measurements of ground subsidence.

This approach allows us to detect subtle changes that would be impossible to observe through traditional field methods, providing critical data for infrastructure safety and urban planning. The time-series analysis will reveal patterns and progression rates that help predict and mitigate potential hazards.

PSInSAR Interferometry SAR