Water Resources Satellite

Flood / Drought

  • Status
    Using an ultra-small satellite constellation to monitor unauthorized discharges in the upper reaches of the Imjingang and Bukhangang Rivers. During the flood season, hydrological conditions are analyzed and shared up to twice a day (based on the Hwanggang Dam)..
  • Materials
    SAR satellite imagery (ICEYE, Capella; 1 m resolution) and optical satellite imagery (PlanetScope; 4 m resolution)
  • Method
    Using SAR data to assess reservoir water levels, downstream river widths, and whether gates were opened at eight dams, including the Hwanggang and Imnam Dams. Optical imagery is also used to identify changes around dams and analyze changes in water surface area across North Korea.
  • Satellite imagery direct-reception facilities Satellite imagery direct-reception facilities
  • Top)High-precision DEM /(Bottom)High-resolution Satellite Imagery (Top)High-precision DEM /(Bottom)High-resolution Satellite Imagery
  • Border Monitoring Information System
  • Status
    Analyzing detailed specifications (length, height, storage capacity, spillway facilities, etc.) of major dams in border areas (Imjingang and Bukhangang Rivers) using satellite data.
  • Materials
    Digital Surface Model (DSM, 50 cm), WorldView optical satellite imagery, etc.
  • Method
    3D stereo photogrammetric analysis and GIS terrain analysis, etc.
  • High-resolution Terrain Data Analysis: Analyzing 50 cm resolution terrain data to update information on dams and reservoirs. High-resolution Terrain Data Analysis: Analyzing 50 cm resolution terrain data to update information on dams and reservoirs.
  • 저수지 용량 분석: (저수지분석) 수위별 수체면적/저수량 분석 Reservoir Capacity Analysis: Analyzing water surface area and storage volume by water level.
  • Status
    Providing information on flood-affected areas, extent (area), and inundation depth using SAR satellite data.
  • Materials
    Utilizing Sentinel-1 data or activating a coordination mechanism to request emergency imaging from domestic and international providers (e.g., the International Charter: Space and Major Disasters).
  • Method
    Applying gamma-distribution thresholds using backscatter coefficients and DEM masking. For ungauged areas, GIS analysis data on global land cover and global population density are used.
  • Flood damage in Korea and border areas (mid-July 2024) Flood damage in Korea and border areas (mid-July 2024)
  • Amnok (Yalu) River flood damage (late July 2024) Amnok (Yalu) River flood damage (late July 2024)

Jeddah, Saudi Arabia Analysis of flood damage caused by record-breaking heavy rainfall (179 mm in 6 hours) in Jeddah, Saudi Arabia, in 2022.

  • Jeddah, Saudi Arabia
  • Jeddah, Saudi Arabia

Southern Brazil Spatiotemporal analysis of inundated areas, affected populations, and related impacts resulting from flooding that lasted two weeks in southern Brazil in 2024.

  • Southern Brazil
  • Southern Brazil

Ukraine Kakhovka Dam Collapse Analysis of inundation damage and facility displacement caused by the collapse of the Kakhovka Dam in Ukraine in 2023.

  • Post-collapse inundation damage analysis of the Kakhovka Dam Post-collapse inundation damage analysis of the Kakhovka Dam
  • Time-series displacement analysis of the Kakhovka Dam and surrounding areas Time-series displacement analysis of the Kakhovka Dam and surrounding areas
  • Color imagery and analysis products of affected areas Color imagery and analysis products of affected areas
  • Status
    Enhancing data products to provide wide-area information on changes in water resources and dam operations across the Korean Peninsula.
  • Materials
    Sentinel-1 (SAR, C-band, 10 m; free data every 12 days), observed precipitation (KMA, etc.), and soil and land-cover information.
  • Method
    Estimating soil moisture and developing drought indices using AI techniques.
  • Plan
    The water resources satellite will enable observations every three days for the same area, providing high-quality information applicable to operational work, such as water-cycle and flood-volume prediction.
  1. Sentinel-1 SLC data
  2. Apply orbit file
  3. Thermal/Border noise removal
  4. Radiometric calibration
  5. Speckle filtering
  6. Terrain correction
  7. VV, VH, LIA
Image Preprocessing
AI Input Data Configuration
Soil Moisture Estimation
Drought Index (SWDI) Estimation

Environment

  • Status
    Monitoring algal blooms (chlorophyll-a) across the Korean Peninsula using satellite imagery (distribution mapping and quantitative monitoring) and supporting operational work.
  • Materials
    ESA Sentinel-2 optical satellite imagery. The two satellites (Sentinel-2B and Sentinel-2C) collect imagery at 10-day intervals, enabling data acquisition for the same area every five days.
  • Method
    Estimating chlorophyll-a concentrations using per-channel spectral reflectance and spectral characteristics.
  • Plan
    Automate algal monitoring using Sentinel-2 data and develop optimization technologies for multi-satellite-based monitoring, including K-waterSAT.
  • Algorithm Verification Algorithm Verification
  • Andongho Lake Andongho Lake
  • Jinyangho Lake Jinyangho Lake
  • Nakdonggang River Basin Nakdonggang River Basin
  • Status
    Developing satellite-based wide-area monitoring technologies to assess turbidity levels in freshwater bodies.
  • Materials
    Global Water Quality-Spectral Dataset (GLORIA) and ESA Sentinel-2 optical satellite imagery.
  • Method
    Quantitatively estimating turbidity (NTU) values using channel-by-channel spectral reflectance and spectral characteristics.
  • Plan
    Acquire and validate paired spectral–turbidity datasets for domestic freshwater, then apply them to operational support.
  • Optical Satellite Imagery Optical Satellite Imagery
  • NTU Value Estimation정 NTU Value Estimation
  • Status
    Conducting satellite-based analysis of major forest-fire damage in Gyeongbuk and Gyeongnam in late March 2025; damage was observed near Imha Dam.
  • Materials
    ESA Sentinel-2 and Planet PlanetScope optical satellite data.
  • Materials
    Detecting changes between pre- and post-fire conditions using wavelength bands strongly correlated with vegetation.
  • Plan
    Provide continuous analysis on forest-fire recovery status.
  • Status
    Reviewing the use of satellite data to assess floating-debris inflow after rainfall in July 2024.
  • Materials
    European Sentinel-1 and Sentinel-2
  • Method
    Applying SAR-based change detection within water bodies and optical spectral analysis to compare conditions before and after debris occurrence.
  • July 12 Floating Debris Detection Results July 12 Floating Debris Detection Results
  • July 19 Floating Debris Detection Results July 19 Floating Debris Detection Results
  • Daecheong Lake area
    Review of Satellite Data Application for Monitoring Floating Debris Inflow After July 2024 Rainfall
    *Consists of vegetation (approximately 90%), styrofoam, and household waste.

Seokho-ri, Daecheong Lake

  • 2023. 07. 18. 2023. 07. 18.
  • 2023. 07. 21. 2023. 07. 21.
  • 2023. 07. 24. 2023. 07. 24.

Change detection of floating-debris occurrence areas in Daecheong and Chungju Dams (SAR imagery)

  • July 18, Seokho-ri (Daecheong Lake) July 18, Seokho-ri (Daecheong Lake)
  • July 24, Seokho-ri (Daecheong Lake) July 24, Seokho-ri (Daecheong Lake)
  • July 18, Gyo-ri (Chungju Lake) July 18, Gyo-ri (Chungju Lake)
  • July 24, Gyo-ri (Chungju Lake) July 24, Gyo-ri (Chungju Lake)

Safety

  • Status
    Applying displacement-analysis techniques by facility type to verify and enhance the usefulness of satellite-based displacement monitoring.
  • Materials
    Monitoring on a 12-day cycle using Sentinel-1 data; cross-validation using an L-band unmanned helicopter is planned.
  • Method
    Conducting time-series displacement analysis with millimeter-level sensitivity for water facilities and surrounding ground using InSAR techniques.
  • Soyanggang Dam Soyanggang Dam
  • Gangjeong-Goryeong Weir Gangjeong-Goryeong Weir
  • Aracheon Stream (Levee) Aracheon Stream (Levee)
  • Status
    Deployment of an unmanned helicopter-based L-band SAR imaging radar observation system (nickname: Heliosa).
  • Materials
    L-band SAR observation system (capable of real-time observation)
  • Method
    Enhancing applicability to soil moisture, levee displacement, and leak detection by using it in a complementary manner with the C-band water resources satellite.
  • Plan
    Validating the accuracy of satellite-derived products through field observations using the Heliosa unmanned L-band SAR system.
  • Specifications and Dimensions Specifications and Dimensions
  • Flight Video
  • L-BAND SAR L-BAND SAR
  • Test Flight Results Test Flight Results

Miscellaneous

  • Status
    Assessing quantitative damage conditions by analyzing ground displacement and the extent and scale of damage in areas affected by major earthquakes using satellites.
  • Materials
    Sentinel-1, Sentinel-2, and high-resolution optical imagery such as WorldView and PlanetScope
  • Method
    Analyzing ground displacement using time-series InSAR techniques and detecting changes in damaged areas based on optical imagery.
  • Ground Displacement Analysis Ground Displacement Analysis
  • Affected Area Identification Affected Area Identification
  • Status
    Calculation of Zonal Impact Areas for Budget Allocation in Dam Vicinity Support Projects
  • Materials
    Remote-sensing-based high-resolution terrain data (DEM, 30 m to 5 m) provided by the National Geographic Information Institute.
  • Method
    Using GIS-based terrain analysis to estimate impact areas by local administrative unit (si-gun-gu, eup-myeon-dong, and ri), with outputs provided to the Water Resources Management Planning Department.
  • Han River System (Hantan River Dam) Han River System (Hantan River Dam)
  • Nakdonggang River System (Andong, Imha, Miryang, Nam River) Nakdonggang River System (Andong, Imha, Miryang, Nam River)
  • Status
    Identifying illegal facilities and cultivation on state-owned land using high-resolution optical satellite data.
  • Materials
    Purchase of paid optical imagery below 1 m resolution (potentially replaceable by K-waterSAT in the future, using 0.5 m National Land Satellite imagery).
  • Method
    Applying NDVI change detection over time and object detection using neural networks and deep learning.
  • 변화전
  • 변화 후
  • 변화 후
  • Topographical Feature Change Detection
    Applying NDVI change detection techniques over time
  • 탐지 전
  • 탐지 후
  • Feature Object Detection
    Object detection using neural networks and deep learning
  • Status
    Supporting the production of satellite-based water-resources factor data for strategic partner countries (Mekong region: Cambodia, Laos, Myanmar, Thailand, Vietnam).
  • Materials
    ESA Sentinel-1, Sentinel-2, Terra and Aqua, etc.
  • Method
    Using satellite band characteristics to estimate runoff change, agricultural and hydrological drought indices, soil indices, evapotranspiration, and vegetation indices for each region.
  • Runoff Analysis Based on Satellite Land Surface Models (LSM) Runoff Analysis Based on Satellite Land Surface Models (LSM)
  • Satellite-based Agricultural Drought Index Analysis Satellite-based Agricultural Drought Index Analysis
  • Satellite-based Hydrological Drought Index Analysis Satellite-based Hydrological Drought Index Analysis
맨 위로