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Comparative Study of Methods for Automatic Identification a Comparative Study of Methods for Automatic Identification a

Comparative Study of Methods for Automatic Identification a - PowerPoint Presentation

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Comparative Study of Methods for Automatic Identification a - PPT Presentation

Wang Xiaojing 1 Zhang Yi 2 Zhao Xin 1 Luo Zhidong 3 1 Beijing Datum Technology Development COLTD 2 Beijing Forestry University 3 Monitoring  Centre of Soil and Water Conservation Ministry of Water ID: 563161

terraces identification extraction automatic identification terraces automatic extraction algorithm satellite characteristics method template resolution high based terrace ridge statistics

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Slide1

Comparative Study of Methods for Automatic Identification and Extraction of Terraces from High Resolution Satellite Data (China-GF-1)

Wang Xiaojing1,Zhang Yi2,Zhao Xin1 ,Luo Zhidong3

1Beijing Datum Technology Development CO.,LTD.2Beijing Forestry University3Monitoring Centre of Soil and Water Conservation, Ministry of Water Resources

August 2016

wangxiaojing@dtgis.comSlide2

Contents

1

2

3

4

Introduction

Terraces Interpretation

Characteristics

Automatic Identification and

Extraction Method

Results Comparison and Discussion

5

ConclusionsSlide3

1.Introduction

Importance of TerracesEffective measures / Long history / Large area / Heavy investmentApplication of Remote Sensing Technology in Terraces

Lack of new technology-computer automatic identification and extraction of terraces.Issues to be studiedUrgent business needs Research area:Hengshan County 4000km2

Data: China GF-1

satelliteSlide4

2.Terraces Interpretation Characteristics

typegeometryspectrumtexture

boundaryTypical terracefield: certain widthfield ridge: narrow, line features- straight line, arc or closed curvefield: higher reflectivityfield ridge: low reflectivity with dark color

smoothrepeatedly and alternatively

Complicated

near ridge: clear

near hill foot: confused

Atypical terrace

field: narrow

field ridge: cannot be seen

field: higher reflectivity

field ridge: cannot be seen

fuzzy

Same as Typical terrace

Table 2 Terraces Interpretation Characteristics on GF-1 SatelliteSlide5

3.Automatic Identification and Extraction Method of Terraces based on High Resolution SatelliteSlide6

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.1Edge Characteristics Statistics AlgorithmTechnical Route of Edge Characteristics Statistics for Terrace IdentificationSlide7

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.1Edge Characteristics Statistics AlgorithmImage Edge DetectionGF-1 2m/8m Fused Image

Canny Edge Detection ResultFrame ResultSlide8

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.1Edge Characteristics Statistics AlgorithmTerrace Identification and Shape Optimization

Judgement result of sample attribute

Overlapping RS image

Shape OptimizationSlide9

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.2 Template Matching AlgorithmTechnical Route of Template Matching for Terrace IdentificationSlide10

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.2 Template Matching Algorithm

Panchromatic image

Variance Picture of Search Image

Template Selection Picture

Template Scanning Pixel by Pixel Picture

Automatic Identification Effect Picture with Variance Threshold

0.45Slide11

3.Automatic Identification and Extraction Method of Terraces based on High Resolution Satellite

3.3 Fourier Transformation AlgorithmTechnical Route of Terrace Identification by Fourier Transformation AlgorithmSlide12

4.Results Comparison and Discussion

Three Algorithms

AlgorithmOverall Identification AccuracyTypical Terraces Identification AccuracyAtypical Terraces

Identification Accuracy

Edge Characteristics Statistics

55.19%

80.85%

51.34%

Template Matching

95.54%

97.18%

95.38%

Fourier Transformation

91.02%98.59%

90.25%Table 4 Comparison Table of Algorithm AccuracySlide13

4.Results Comparison and Discussion

Edge Characteristics Statistics

Template MatchingFourier Transformation

In accuracy

Completeness

and boundary

OthersSlide14

5.ConclusionsPropose two kinds of new algorithms for automatic identification and extraction of

terraces. Verify one algorithm on large extent area.It has laid basis for temporal and spatial extension of algorithm, to provide technical support for rapid terrace extraction in a large scale.DeficiencyFor further study, more features and vectors, self-adaptive template can be tried.Slide15

Thank You !