chapter 9 application of remote sensing

8/11/2019 Chapter 9 Application of Remote Sensing

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APPLICATION OF

REMOTE SENSINGCG 505

Source: NASA


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Example Applications

visible / NIR / MIR - day only, no cloudcover

vegetation presence

geological mapping (structure, mineral /petroleum exploration)

urban and land use

phytoplankton blooms

meteorology (clouds, atmospheric

scattering)

DEM generation (stereo imagery)


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Thermal infrared - day / night, rate of heating /cooling

heat loss (urban)

thermal plumes (pollution)mapping temperature

geology

forest fires

meteorology (cloud temp, height)



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Active microwave - little affected byatmospheric conditions, day / night

surface roughness (erosion)

water content (hydrology) - top few cmsvegetation - structure (leaf, branch, trunk

properties)

DEM production (SAR interferometry)



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Pemetaan KedalamanObjective : To extract depth information from satellite data, and

to devise a fast and cost-effective alternative

for acquiring depth informationStudy 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


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Depth information in digital file Production of

Hydrographic Chart

Digital File of Depth Information Automatic Generation of Hydrographic Cha


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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

Pemetaan Dasar Laut


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Product from Sea bottom feature mapping

Production of Sea bottom features Plan

Sea bottom featuresinformation is vital for :

navigational hazards

monitoring

dredging operation

exploration

offshore engineering

fisheries application


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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


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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

Modeling for Vegetation Backscattering

Modeling Shallow Water Bathymetry

Radar Remote Sensing for Land and Coastal

Applications


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Objective : Identifying & analysing biomass for vegetation

mapping

Study Area : Raub, Pahang

Data from Red and Infrared Bands ofLandsat-5 TM and NOAA AVHRR Satellites

Computation of Vegetation Indices

Correlation of index to ground biomass

Vegetation Index Mapping


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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 indeep sea fishing

industries of Japan and

Nordic countries.


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Biomass

Estimation Mapover study area

JERS-1 SAR

data over Sg.Pulai, Johore

Mangrove

forestsegmented

from SAR data.

Field verification of

calculated biomass

Retrieval of

treeparameters 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


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Phytoplankton sampling at

the time of satellite pass in the study area.


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Ocean colour mapping

(NOAA satellite)

Phytoplanktondistribution 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


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Spectral Signature: Surface

Surfaces dont reflect allwavelengths equally. They tendto absorb certain wavelengths,while reflecting others.

The percentage of reflectanceacross the ElectromagneticSpectrum that a surface reflectsis called its spectral signature.

Spectral signatures can be

affected by the time of year,weather, and environmentalfactors.


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Spectral Signature: Water

The spectral signature for water

exhibits moderate reflectance inthe visible portion of theElectromagnetic Spectrum, butplunges to almost nothing in theNIR.

In images displaying NIR, waterappears black because of itslow reflectivity in the NearInfrared.

Blue0.4um-0.5um

Green0.5um-0.6um

Red0.6um-0.7um

Near Infrared (NIR)0.7um-1.2um

chapter 9 application of remote sensing

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