Name
Abstract | ||
|---|---|---|
It is necessary to detect and monitor the distribution of mircophytobenthos (or algal mat) in tidal flats. KOMPSAT-2 will provide multi-spectral images with a spatial resolution of 4 m comparable with IKONOS. Using IKONOS and Landsat data, algal mat detection was tested in the Saemangeum area. Micro-benthic diatoms are abundant and a major primary product in the tidal flats. Fine grained upper tidal flats is considered to be the best conditions for microphythobenthos. A different type of microphytobenthos was found in coarse grained lower tidal flats. The newly reported microphytobenthos are algae and they began to exist after dike construction. A linear spectral unmixing (LSU) method was applied to the test data. The end-members were obtained by both spectral libraries built from field surveys and a remotely sensed image itself. End-members from spectral library were slightly more effective than those from image itself. A high resolution multi-spectral sensor in KOMPSAT-2 will provide useful data for long-term monitoring of microphytobenthos in tidal flats. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/IGARSS.2005.1526204 | IGARSS |
Keywords | Field | DocType |
mircophytobenthos distribution,remote sensing,benthic algae,ikonos data,oceanography,algal mat detection,microbenthic diatoms,kompsat-2,tides,multispectral images,spectral library,landsat data,saemangeum area,geophysical signal processing,linear spectral unmixing method,object detection,oceanographic techniques,microphytobenthos detection,remotely sensing,tidal flats,levee,multispectral imaging,primary production,algae,indexing terms,testing,remote monitoring,satellites,high resolution,spatial resolution | Satellite,Algal mat,Computer science,Hydrology,Remote sensing,Multispectral image,Image resolution,Geophysical signal processing | Conference |
Volume | ISSN | ISBN |
1 | 2153-6996 | 0-7803-9050-4 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joong-Sun Won | 1 | 80 | 16.84 |
| Yun-Kyung Lee | 2 | 22 | 5.59 |
| Jaewon Choi | 3 | 92 | 11.74 |