Selection of an appropriate classification technique for coastal biomass mapping

using high and low resolution dataset

Urooj Saeed, GIS CoordinatorWorld Wide Fund for Nature – Pakistan

saeed.urooj@gmail.com

Presented at 2nd International Conference on Advances in Space Technologies29-30 November, 2008; Islamabad, Pakistan

2nd International Conference on Advances in Space Technologies

Presentation Outlines

Research Questions Study Area Methodology Analysis and Results Conclusions and recommendations

2nd International Conference on Advances in Space Technologies

Research Questions

Maximum Likelihood Classification (MLC) or Sub Pixel Classification (SPC)- which is time and cost efficient technique for coastal biomass mapping?

Can medium resolution satellite data be used as an alternate of better-resolution satellite data?

2nd International Conference on Advances in Space Technologies

Sandspit is located at the west of Liyari river, near Hawks Bay along the Karachi coast line.

Area = 1618 ha

Major vegetation types : Mangrove Saltbush Algae

Study Area

2nd International Conference on Advances in Space Technologies

Satellite Data Used Landsat image of 30 m resolution

Spatial resolution 30m Acquisition date 6th October, 2001 Tide Height Value2m

Quickbird image Spatial resolution 2.4m Acquisition date 27th April, 2003 Tide Height Value2m

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Data acquisition & preprocessing Field Survey Image Classification

Maximum Likelihood – Landsat and QuickBird

Sub Pixel – Landsat Comparison and Analysis

Methodology

2nd International Conference on Advances in Space Technologies

Field Visit Avicennia marina – dominant mangrove

species, height varies from 5 to 20 ft. More the distance from the creeks less is the

density/height of the mangroves Floating algae was also observed GPS coordinates of different forest density

classes were recorded

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Maximum Likelihood Classification (MLC) MLC calculates different statistical

parameters from the inputs known as training areas and on the basis of these parameters it assigns a specific class to certain pixel

In this study MLC technique was used to develop output maps of both the datasets i.e Quick Bird and Landsat

2nd International Conference on Advances in Space Technologies

2nd International Conference on Advances in Space Technologies

MLC results – Landsat MLC results – QuickBird

2nd International Conference on Advances in Space Technologies

Land cover Classes QuickBird (ha) Landsat (ha)

Tall Mangroves 57.45 87.83

Medium Mangroves 125.9 216.41

Small Mangroves 180.89 113.68

Regeneration 5.35 Nil

Sub-Total for Mangroves 370 417.92

Salt Bushes 38.57 Nil

Floating Algae 131.03 Nil

Algae on mud 42.82 Nil

Sludge/wet soil 11.18 66.11

Water 364.04 378.91

Settlements 45.86 119.35

Salt pans 25.61 116.56

Mudflats 149.52 155.39

Land soil 444.66 398.04

Tabular comparison of MLC results

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Sub Pixel Classification (SPC)

SPC is used to map the landcover classes which are smaller than the pixel size

Five major modules were used to run this algorithm

In this study SPC was applied only on Landsat satellite image

2nd International Conference on Advances in Space Technologies

2nd International Conference on Advances in Space Technologies

SPC results for MangrovesSPC results for SaltbushSPC results for Algae

2nd International Conference on Advances in Space Technologies

M

A

S

Association map of Mangroves, Saltbush and Algae

2nd International Conference on Advances in Space Technologies

LandcoverClasses

QuickBird(ha)

Landsat(ha)

Difference(ha)

MLC MLC SPC Landsat (MLC) – QuickBird (MLC)

Landsat (SPC) – QuickBird (MLC)

Mangroves 376.65 417.92 375.56 41.27 - 1.09

Saltbush 26.05 Nil 26.33 - 0.28

Algae 42.82 Nil 67.65 - 24.83

Tabular comparison of SPC and MLC

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Conclusions and Recommendations

MLC when applied on Landsat failed to separate a very important vegetationcomponent into a different landcover classes.

By using SPC, mixed pixel problem was satisfactorily overcome by classifying high spatialfrequency vegetation classes i.e. saltbush and algae

SPC proved to be a time effective technique as less training areasfor Material of Interest (MOI) were required

Due to the time and cost effectiveness, it is highly recommended to use SPC on medium resolution data for coastal biomass mapping at large area.

It is also suggested to use selective patches of high resolution satellite image forthe ground truthing and MOI definition.

2nd International Conference on Advances in Space Technologies

2nd International Conference on Advances in Space Technologies

Thank Thank youyou