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BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca Department of Geography Universidade Federal do Rio Grande do Sul [email protected] Geotecnolog ias Aplicadas Laboratório de

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Page 1: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

BIOMASS MONITORINGAboveground biomass quantification for the natural grasslands

in the Pampa biome using remotely-sensed images

Eliana Lima da FonsecaDepartment of Geography

Universidade Federal do Rio Grande do Sul

[email protected]

Geotecnologias Aplicadas

Laboratório de

Page 2: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Pampa biome

Page 3: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Satellite images(NDVI – Spot Vegetation)

Image DevCoCast file

Field data(aboveground biomass)

Excel file

Field data(samples location)

Shapefile

NDVI values collected over samples

Regression modelBiomass (kg.ha-1) = a + b*NDVI

ABOVEGROUND BIOMASS QUANTIFICATION FOR THE NATURAL GRASSLANDS IN THE PAMPA BIOME USING REMOTELY-SENSED IMAGES

Study area: “Environment Protect Area of Ibirapuitã” , which is a region with 320,000 hectares.

Satellite images(NDVI – Spot Vegetation)

Image DevCoCast file

Biomass map

Page 4: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Study area: “Environment Protect Area of Ibirapuitã” , which is a region with 320,000 hectares.

Page 5: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

J F M A

M J J A

S O N D

NDVI time series over the Environment Protect Area of

Ibirapuitã for the year 2002.

Page 6: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Graph with the NDVI values collected over the sample area where measurements in situ were made

Page 7: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Mathematical relationship between NDVI and aboveground biomass for year 2002 and the ILWIS command to calculate the set of biomass map over the Ibirapuita_2002” map list

Page 8: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

J F M A

M J J A

S O N D

Aboveground biomass maps over the

Environment Protect Area of Ibirapuitã

for the year 2002.

Page 9: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Comparison between calculate and measure aboveground biomass

Residual analysis

Verification of the results

How to improve these results?The results of this model can be improved with a bigger dataset of “in situ” measurements in different plots and a longer time series for analysis.

Considerations about the resultsFor this kind of vegetation (natural grasslands) is not expected great values for the coefficient of determination, because these is non-homogeneous area, since the Pampa biome support very high levels of biodiversity.

Page 10: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Conclusions

• The Spot-Vegetation sensor allows to make good estimates for the grassland aboveground biomass using the NDVI images, since have an equation (mathematic model) to convert the satellite images in biomass.

• This kind of information is useful to monitoring the Pampa biome, and it is necessary in order to preserve the natural vegetation in association with economic exploration done by the traditional people.

Page 11: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Conclusions

• A model calibration for each kind of vegetation cover, also considering the local weather, allows making more realistic models, which are more useful at local conditions and at regional scale, when it is compared with global scale models.

• To develop a global model to estimate the aboveground biomass some generalizations are made, like consider the Brazilian Cerrado as an African Savanna.

• These generalizations are necessary for built a global scale model, but it can be an obstacle to apply the results in order to local planning.

Page 12: BIOMASS MONITORING Aboveground biomass quantification for the natural grasslands in the Pampa biome using remotely-sensed images Eliana Lima da Fonseca

Acknowledgments for Brazilian Staff

Charles Tebaldi2; Adriana Ferreira da Costa Vargas3; Vicente Celestino Pires Silveira4

2 Student at Bachelor in Geography Course - Universidade Federal do Rio Grande do Sul (UFRGS) – Brazil

3 Agronomist at Fundacao Maronna - Brazil4 Professor at Centre of Rural Science - Universidade Federal de Santa Maria (UFSM) - Brazil

Special thanks for ITC Staff !!

Geotecnologias Aplicadas

Laboratório de