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)

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

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

Faculty of Geoinformation Science and EngineeringUniversiti Teknologi Malaysia81310 UTM Skudai. Johor Bahruhttp://www.fksg.utm.my

Optical Mechanisms

Completed Researches at CRSUTM

App 1: Pemetaan KedalamanObjective : 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 dataLandsat Thematic Mapper - band 1

Determination of depth informationElimination of atmospheric & geometric errors Computation of depth

Depth information in digital fileProduction of Hydrographic Chart

Depth information in digital file Production of Hydrographic Chart

Digital File of Depth Information Automatic Generation of Hydrographic Chart

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 featuresElimination 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

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

App 3 : Water Quality Objective : To map water quality and determine suspended sediment

from satellite dataStudy Area : Straits of Klang

Satellite remote sensing dataLandsat Thematic Mapper - band 1

Automatic Production of SSC Maps

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

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 IndicesCorrelation of index to ground biomass

Research 7 : Vegetation Index Mapping

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 toderive regional SST coverage of 1000 km2.Landsat-5 TM band 6 was used for sub-regional SST coverage of 185 km2.

Determination of SSTElimination of “noises” and “errors”Customizing thermal algorithms

Classification of SST Automatic generation of SST Map

Research 8 : Sea Surface Temperature Mapping

Automatic Generation of Sea Surface Temperatureoff 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 :

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

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

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

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.

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

Spectral Signature: WaterThe 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