Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices

Alfredo R. Huete, Dana Kerola, Kamel Didan, Willem van Leeuwen, Laerte Ferreira

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validate sites representing a wide range of vegetation conditions. The data successfully mapped the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. These results lead to the conclusion that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region, 250 m pixel sizes.

Original languageEnglish (US)
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
Editors Anon
PublisherIEEE
Pages785-787
Number of pages3
Volume2
StatePublished - 1998
EventProceedings of the 1998 IEEE International Geoscience and Remote Sensing Symposium, IGARSS. Part 1 (of 5) - Seattle, WA, USA
Duration: Jul 6 1998Jul 10 1998

Other

OtherProceedings of the 1998 IEEE International Geoscience and Remote Sensing Symposium, IGARSS. Part 1 (of 5)
CitySeattle, WA, USA
Period7/6/987/10/98

Fingerprint

SeaWiFS
vegetation index
biosphere
MODIS
Sensors
vegetation
vegetation cover
pixel
temporal variation
Land use
land use
Pixels
analysis

ASJC Scopus subject areas

  • Software
  • Geology

Cite this

Huete, A. R., Kerola, D., Didan, K., van Leeuwen, W., & Ferreira, L. (1998). Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. In Anon (Ed.), International Geoscience and Remote Sensing Symposium (IGARSS) (Vol. 2, pp. 785-787). IEEE.

Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. / Huete, Alfredo R.; Kerola, Dana; Didan, Kamel; van Leeuwen, Willem; Ferreira, Laerte.

International Geoscience and Remote Sensing Symposium (IGARSS). ed. / Anon. Vol. 2 IEEE, 1998. p. 785-787.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Huete, AR, Kerola, D, Didan, K, van Leeuwen, W & Ferreira, L 1998, Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. in Anon (ed.), International Geoscience and Remote Sensing Symposium (IGARSS). vol. 2, IEEE, pp. 785-787, Proceedings of the 1998 IEEE International Geoscience and Remote Sensing Symposium, IGARSS. Part 1 (of 5), Seattle, WA, USA, 7/6/98.
Huete AR, Kerola D, Didan K, van Leeuwen W, Ferreira L. Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. In Anon, editor, International Geoscience and Remote Sensing Symposium (IGARSS). Vol. 2. IEEE. 1998. p. 785-787
Huete, Alfredo R. ; Kerola, Dana ; Didan, Kamel ; van Leeuwen, Willem ; Ferreira, Laerte. / Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. International Geoscience and Remote Sensing Symposium (IGARSS). editor / Anon. Vol. 2 IEEE, 1998. pp. 785-787
@inproceedings{5477ee18cd054a5e96a38edff4cf7608,
title = "Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices",
abstract = "A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validate sites representing a wide range of vegetation conditions. The data successfully mapped the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. These results lead to the conclusion that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region, 250 m pixel sizes.",
author = "Huete, {Alfredo R.} and Dana Kerola and Kamel Didan and {van Leeuwen}, Willem and Laerte Ferreira",
year = "1998",
language = "English (US)",
volume = "2",
pages = "785--787",
editor = "Anon",
booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "IEEE",

}

TY - GEN

T1 - Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices

AU - Huete, Alfredo R.

AU - Kerola, Dana

AU - Didan, Kamel

AU - van Leeuwen, Willem

AU - Ferreira, Laerte

PY - 1998

Y1 - 1998

N2 - A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validate sites representing a wide range of vegetation conditions. The data successfully mapped the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. These results lead to the conclusion that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region, 250 m pixel sizes.

AB - A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validate sites representing a wide range of vegetation conditions. The data successfully mapped the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. These results lead to the conclusion that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region, 250 m pixel sizes.

UR - http://www.scopus.com/inward/record.url?scp=0031636735&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031636735&partnerID=8YFLogxK

M3 - Conference contribution

VL - 2

SP - 785

EP - 787

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

A2 - Anon, null

PB - IEEE

ER -