Environmental remote sensing data used at VTT

Tuomas HämeTuomas.Hame@vtt.fi

+358 20 722-6282

VTT TECHNICAL RESEARCH CENTRE OF FINLAND

VTT Technical Research Centre of Finland

VTT ISthe biggest multi-technological applied research organisation in Northern Europe

VTT HASmultidisciplinary R&D from electronics to building technologyclients and partners: industrial and business enterprises, public sector, universities and research institutes

VTT CREATESnew technology and science-based innovations in co-operation with domestic and foreign partners

Turnover 232 M€Personnel 2,74076% with higher academic degree5,730 customersEstablished 1942 VTT has been granted ISO9001:2000 certificate.

Environmental remote sensing data use in the nutshell

Which data• All kind of imagery from Earth's surface• From ground-based cameras to AVHRR• Optical & radar

Use• Value adding chain development including• Preprocessing methods• Analysis methods• Software development• System development

For whom• Forest industry, consultants, European Space Agency,

Finnish and foreign governmental agencies and foreign private sector

Applications• Sustainable use of natural resources, mitigation of

environmental change impact and environmental disasters. Cost savings, more effective operation, timely information.

Environmentmonitoring

service

serviceEnvironmentMonitoring

Service

• Analysis• Processing• Product Tailoring

Satellite and airborne data

In situ measurements

Data providers

Models• Biomass• Weather• Ice• Smoke• Oil

GIS DBs ContextContent

Connecting people and data

Calibrated mosaic from Europein one-kilometer resolution using 63 weather satellite images

Location of forest types in red / NIR spectral domain

Figure 7. Target variable values in the spectral space in the Temperate and Borealstratum.

• Modis 1B-level data from summers 2000 and 2001

• 27 images• Ground

resolution 250 meters

• Size of the mosaic about 1400 km by 1900 km

• red channel = red reflectance

• green channel = near-infrared reflectance

• Landsat ETM+ image from 6th of July 2001 from Suonenjoki and stem volume values from Suonenjoki plot data

• Landsat ETM+ image from 10th

of June 2000 from Puumala and stem volume values from Puumala plot data

Stem volume models estimated from the Suonenjoki data sets

Coniferous trees Broad-leaved trees

Total stem volume in Finnish forestry districts

S-Both

Centra

Kainuu

SW FinLa

N-Kare

liaN-B

othN-S

Pirkan

maaCoa

stÅlan

EstimateStatistics

JERS radarimage mosaic (preliminary)from Eurasia

Effect of topographic normalization

SAR image without (left) and with (right) utilization of the DEM in radiometric and geometric correction

• Osa mosaiikista perspektiivikuvana

• Korkeutta liioiteltu 5-kertaisesti

• Perspektiivikuva tehty GRASS-GIS ohjelmistolla

• Lokan tekoaltaan itäpäästä kohti Sokostin seudun tuntureita

• Kuvat huhtikuulta 2007

• ALOS/Palsar data © JAXA, METI 2007

Esimerkki orto-oikaistusta Polarimetrisesta tutkakuvamosaiikista

Dual-Pol 12.6.2007/Heinavesi: Stem Volume Correlation/HV

• Whole dataset: r = 0.79

• 0…150 m3/ha: r = 0.93

• Saturation around 150 m3/ha

• One obvious clear-cut stand (harvested March 2007, ground March 2007)

Example of classification result

May: PolSARpro supervised ALOS/Palsar data © JAXA, METI 2007

ALOS/Palsar in the detection of clear cuts

R=20070612G=20070728B=20070912Yellow = cut

28.7.-12.9.Red = cut

12.6.-28.7.ALOS/Palsar

data © JAXA, METI 2007

Forest cover change in French Guiana1992-2003-2007using ESA radar

Natural disaster monitoring workstation

Web application infrastructure– Satellite imagery analysis– Other information– Multi-user tool with different user roles

Growing stock volume

287 m3/ha

0 m3/ha

Ikonos false color image of Suonenjoki test area estimate plotted on Ikonos PAN channel

Stem diameter

Stem number / ha

2941 stems/ha

0 stems/ha

Proportion of broadleaved trees from stem volume

Accuracy at plot level

0 100 200 300 400 5000

500Estimated stem vol vs. gnd data, FS1-BL-111203

stem volume [m3/ha]

R = 0.85

0 5 10 15 20 25 30 350

35Estimated stem diameter vs. gnd data, FS1-VOL-101203a

stem diameter [cm]

R = 0.90

Tree species study - tree detection

a) on aerial image b) on IKONOS PAN channel

Detected trees on Plot No: 2

Spruce (validation data)Pine (validation data)Birch (validation data)Trees located on Ikonos image

Forest Monitoring – Tree Species Map

Pine-%

Deciduous-%Spruce -%

Tree species proportions calculatedfor a 1 km x 1 km Ikonos-2 image

Average segment size 1 ha

Forest Monitoring - SegmentationHierarchical Pyramidas segmentation result

Ikonos-2 image , 1.4 km x 1.0 km

The mean size of the segments is in the three segmentations:

White borders: 1 ha

White and yellow borders: 0.5 ha

White, yellow and green borders: 0.3 ha

Image series from Enontekiö 28.8. - 28.9.2007Daily images recorded at high noon

Challenges

• Illumination intensity variation -especially sunny images

• Incident light colour balancevariations + trend

• Camera colour balance variations• Target movement (wind)

Web camera images

ForSe - Forest and Season MonitoringWeb Cameras In Automatic Autumn Colour Monitoring

A time series of web camera images and corresponding feature images from Enontekiöautumn 2007

SCI comparison with reference data/Oulanka site

Yellowing starts

Falling starts

Leaves yellowed (> 50%)

Leaves fallen (> 50%)

Phenology dates (Metla) marked with blue arrows

245 250 255 260 265 2700

Season colour development/Oulanka- Autumn 2007

greenlight greenyellowbrownfallen

The leaves' colour development forOulanka site

• 9 ROIs (1 ref + 9 for classification)• classifier training with Enontekiö sitedata (see slide 13)• no instances in class 'red' (not plotted)

The ROIs shown on Oulanka site imagetaken 16.9.2007

Lehdet täysikasvuisia

Kellastuminen alkaa

Variseminen alkaa

Lehdet kellastuneet

Lehdet varisseet

Kartan värien selitykset

Monitoring of seasonal changes

Autumn coloring in September-October 2005

Kioto+ (post-Kyoto) Satellite Mission in Brief

Proposed near-polar orbiting satellite monitoring system • Super high-resolution (0.5 m) optical images• Statistical sampling principle => conceptually comparable to field

measurements• Individual trees visible• Land cover class/class change can be defined without any

uncertainty

The images are permanent documents about the situation during image acquisition

Three major uses:1. Statistical data on global, regional and national forest and land

cover with confidence interval (target area 25 000 km2 and larger)2. Training and validation data for "wall-to-wall" satellite imagery3. Augmentation of field measurements

Sampling principle of Kioto+

15 km4 km

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