IGARSS’11, Vancouver

Water Body Detection from TanDEM-X Data: concept & first evaluation of an accurate water indication mask

A. Wendleder1), M. Breunig1), K. Martin2), B. Wessel1), A. Roth1) 1) German Aerospace Center DLR | 2) Company for Remote Sensing and Environmental Research SLU IGARSS 2011 / Vancouver / 2011-07-28

Slide 2

Outline

Introduction

Definition of the TanDEM-X water indication mask

Challenges for TanDEM-X water body detection

Concept & methodology of water body detection

Test site demonstration

Evaluation of classification results

Outlook

Slide 3

Definition of the TanDEM-X water indication maskGlobal mission – global DEM – global

water body mask

Water body mask primarily extracted for post-processing DEM editing

ongoing work in flattening of outpoking water bodies

correct orthorectification of remote sensing data

No production of a complete global water body inventory

Kurnool Kadapa Channel / India

frozen Lake Taimyr / Russia

Slide 4

Challenges for TanDEM-X water body detection TanDEM-X mission with 2 global acquisition data sets in 2011 & 2012

The water body detection runs completely data-driven

Processing at Raw DEM level (30*50 km ≈ 8.000*10.000 pixels)

400 up to 800 Raw DEM per day to be processed

Therefore maximum computing time of 3 minutes per product

Applicable for different appearances of water bodies worldwide (coastline, inland lake, river, tropical, arctic, arid or humide climates etc.)

tropical river & coastline in Indonesia small inland water bodies in Minnesota / USA

Slide 5

Concept & Methodology (I)

Input images are amplitude & coherence image

Exclusion of desert & polar regions

SRTM WAM

MODIS/Terra Land Cover Types

Exclusion of steep terrain

SRTM DEM

Potential Water bodies

available

Dataset:AmplitudeCoherence

SRTM Water Mask

yes

RawDEM

MODIS/TerraLand Cover Types

SRTM DEM

Calculation of slope

Slide 6

Median filter separately applied both to amplitude & coherence image

Threshold method with fix threshold values

Two different thresholds to handle complexity of water appearance

1. threshold: reliable classification

2. threshold: potential classification

Calculation of water body areas via Chain Code and elimination of water bodies < 1 hectare

Fusion of three intermediate water body layers

Concept & Methodology (II)

1. Threshold Analysis

on Amplitude

Water Mask

Fusion

Threshold Analysis

on Coherence

Medianfilter on Amplitude

Chain Code

Medianfilter on Coherence

Chain Code

2. Threshold Analysis

on Amplitude

Chain Code

Slide 7

Test site demonstration

River Elbe, Hamburg, Germany

acquired on January 27, 2011

Incidence angle 43.4° to 45.7°

Slide 8

Evaluation of classification results (I)

reference of area

reference within extraction of areasscompletene

extraction of area

reference within extraction of areascorrectnes

Calculation of completeness and correctness

reference vector layer data of digital landscape models from the Authoritative Topographic Cartographic Information System (ATKIS)

Slide 9

Evaluation of classification results (II)

Reference Completeness Correctness

Amplitude

ATKIS 86.9% 92.6%

ATKIS water bodies > 1hectare

88.1% 92.5%

Coherence

ATKIS 79.8% 98.7%

ATKIS water bodies > 1hectare

80.9% 98.7%

ATKIS: Authoritative Topographic Cartographic Information System

Slide 10

Evaluation of classification results (III)

Water body mask derived of amplitude image

rich in detail

susceptible to misclassifications

Water body mask derived of coherence image

significant and robust results

loss of details of small scale water bodies

Maximum of a correct & complete water mask with combination of both

Slide 11

Outlook

Accuracy assessment of the water body detection for different climate zones

robustness & global transferability of our approach

Mosaicking of different water bodies (neighboring acquisitions resp. first & second year acquisition) to an intermediate & final TanDEM-X water body mask product

TanDEM-X DEM editing using TanDEM-X water body mask

flattening of outpoking water bodies

Slide 12

River Elbe, Hamburg, Germany

SAR image

Water indication mask

DEM

edited DEM

Slide 14

Thank you for your attention!

Anna Wendleder | Markus Breunig

German Remote Sensing Data CenterTeam SAR Topography

Phone: +49 8153 28 3439Email: Anna.Wendleder@dlr.de | Markus.Breunig@dlr.de