2. Example Applications visible / NIR / MIR - day only, no cloud cover vegetation presence geological mapping (structure, mineral / petroleum exploration) urban and land use phytoplankton blooms meteorology (clouds, atmospheric scattering) DEM generation (stereo imagery)

3. Thermal infrared - day / night, rate of heating / cooling heat loss (urban) thermal plumes (pollution) mapping temperature geology forest fires meteorology (cloud temp, height) Example Applications

4. Active microwave - little affected by atmospheric conditions, day / night surface roughness (erosion) water content (hydrology) - top few cms vegetation - structure (leaf, branch, trunk properties) DEM production (SAR interferometry) Example Applications

5. Faculty of Geoinformation Science and Engineering Universiti Teknologi Malaysia 81310 UTM Skudai. Johor Bahru http://www.fksg.utm.my Optical Mechanisms

6. Completed Researches at CRSUTM

7. App 1: Pemetaan Kedalaman Objective : To extract depth information from satellite data, and to devise a fast and cost-effective alternative for acquiring depth information Study Area : Pulau Tioman Satellite remote sensing data Landsat Thematic Mapper - band 1 Determination of depth information Elimination of atmospheric & geometric errors Computation of depth Depth information in digital file Production of Hydrographic Chart

8. Depth information in digital file Production of Hydrographic Chart Digital File of Depth InformationAutomatic Generation of Hydrographic Chart

9. Objective : To extract sea bottom information from satellite data and to devise a fast and cost-effective alternative for acquiring sea bottom information Study Area : Langkawi Determination of sea bottom features Elimination of atmospheric & geometric errors Formation of “depth invariant index” for sea bottom features Classification of sea bottom features based on depth invariant App 2 : Pemetaan Dasar Laut

10. Product from Sea bottom feature mapping Production of “Sea bottom features” Plan Sea bottom features information is vital for : navigational hazards monitoring dredging operation exploration offshore engineering fisheries application

11. App 3 : Water Quality Objective : To map water quality and determine suspended sediment from satellite data Study Area : Straits of Klang Satellite remote sensing data Landsat Thematic Mapper - band 1 Automatic Production of SSC Maps

12. Objectives : To develop a suitable methodology for mapping coastal features and land cover using multi-temporal ERS-1 SAR satellite data Study Area : Kuala Terengganu & Baram, Sarawak Wave Spectra Analysis Detection of Oil Slicks Mapping of Natural & Artificial Features Modelling for Vegetation Backscattering Modelling Shallow Water Bathymetry Radar Remote Sensing for Land and Coastal Applications

13. Objective : Identifying & analysing biomass for vegetation mapping Study Area : Raub, Pahang Data from Red and Infrared Bands of Landsat-5 TM and NOAA AVHRR Satellites Computation of Vegetation Indices Correlation of index to ground biomass Research 7 : Vegetation Index Mapping

14. Objective : To determine sea surface temperature (SST) from satellite data at regional and sub-regional levels Study Area : Straits of Malacca & South China Sea surrounding Peninsular Malaysia AVHRR Data of NOAA Satellite were used to derive regional SST coverage of 1000 km 2. Landsat-5 TM band 6 was used for sub-regional SST coverage of 185 km 2. Determination of SST Elimination of “noises” and “errors” Customizing thermal algorithms Classification of SST Automatic generation of SST Map Research 8 : Sea Surface Temperature Mapping

15. Automatic Generation of Sea Surface Temperature off coastal waters surrounding Peninsular Malaysia SST is one of the prime input into analysis of fisheries / marine research. SST can be associated with pelagic fish species, hence, offers a “powerful” forecasting tool in deep sea fishing industries of Japan and Nordic countries. Research 8 output :

16. Biomass Estimation Map over study area JERS-1 SAR data over Sg. Pulai, Johore Mangrove forest segmented from SAR data. Field verification of calculated biomass Retrieval of tree parameters for model generation Figure 1 : Measurement of in-situ data for biomass obsevation. Figure 2 : Determination of mangrove patches using specific segmentation algorithm. Figure 3 : Corrected image of JERS-1 SAR (Synthetic Aperture Radar ) of study area. Figure 4 : Biomass estimation map over study area. Figure 5 : Survey of the study area carried out jointly with Johore Forestry Department. Global Rainforest Mapping Activities in Malaysia: Radar Remote Sensing For Forest Survey and Biomass Indicator

17. Phytoplankton sampling at the time of satellite pass in the study area.

18. Ocean colour mapping (NOAA satellite) Phytoplankton distribution of Kedah waters (Landsat image ) Seagrass distribution in Kedah waters ( Landsat image ) Derived sea-grass (a)and ocean colour (b) covering Langkawi island Ocean colour and seagrass mapping from satellite remotely sensed data for fisheries application

19. Spectral Signature : Surface Surfaces don’t reflect all wavelengths equally. They tend to absorb certain wavelengths, while reflecting others. The percentage of reflectance across the Electromagnetic Spectrum that a surface reflects is called its spectral signature. Spectral signatures can be affected by the time of year, weather, and environmental factors.

20. Spectral Signature: Vegetation For example, vegetation tends to reflect green light at a higher reflectivity than blue or red light, thus plants appear green to our eyes. Vegetation also has a high spectral response in the Near Infrared (NIR) and if our eyes could see this wavelength, then plants would appear very bright to us. Blue – 0.4um-0.5um Green – 0.5um-0.6um Red – 0.6um-0.7um Near Infrared (NIR) – 0.7um- 1.2um

21. Spectral Signature: Water The spectral signature for water exhibits moderate reflectance in the visible portion of the Electromagnetic Spectrum, but plunges to almost nothing in the NIR. In images displaying NIR, water appears black because of its low reflectivity in the Near Infrared. Blue – 0.4um-0.5um Green – 0.5um-0.6um Red – 0.6um-0.7um Near Infrared (NIR) – 0.7um- 1.2um