File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Can MODIS EVI monitor ecosystem productivity in the Amazon rainforest?

TitleCan MODIS EVI monitor ecosystem productivity in the Amazon rainforest?
Authors
KeywordsAmazon
anomalies
EVI
MODIS
phenology
Issue Date2014
Citation
Geophysical Research Letters, 2014, v. 41, n. 20, p. 7176-7183 How to Cite?
AbstractThe enhanced vegetation index (EVI) obtained from satellite imagery has often been used as a proxy of vegetation functioning and productivity in the Amazon rainforest. However, recent studies indicate that EVI patterns are strongly affected by satellite data artifacts. Hence, it is unclear if EVI is sensitive to subtle seasonal variations in evergreen Amazon forest productivity. This study analyzes 12-years of Moderate Resolution Imaging Spectroradiometer (MODIS) EVI in order to evaluate its response to factors driving productivity in the Amazon. We show that, after removing cloud and aerosol contamination, and correcting bidirectional reflectance distribution function effects, radiation and rainfall extremes show no influence on EVI anomalies. However, EVI seasonal patterns are still evident after accounting for Sun-sensor geometry effects. This remaining pattern cannot be explained by solar radiation or rainfall, but it is significantly correlated to gross primary production (GPP). Nevertheless, we argue that the causality between GPP and EVI should be interpreted with caution. Key Points Monthly EVI anomalies are not sensitive to radiation or rainfall extremesEVI seasonality in the Amazon is still present after BRDF correctionAlthough EVI and GPP correlate, interpretations of causality require caution
Persistent Identifierhttp://hdl.handle.net/10722/309213
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 1.850
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorMaeda, Eduardo Eiji-
dc.contributor.authorHeiskanen, Janne-
dc.contributor.authorAragão, Luiz E.O.C.-
dc.contributor.authorRinne, Janne-
dc.date.accessioned2021-12-15T03:59:45Z-
dc.date.available2021-12-15T03:59:45Z-
dc.date.issued2014-
dc.identifier.citationGeophysical Research Letters, 2014, v. 41, n. 20, p. 7176-7183-
dc.identifier.issn0094-8276-
dc.identifier.urihttp://hdl.handle.net/10722/309213-
dc.description.abstractThe enhanced vegetation index (EVI) obtained from satellite imagery has often been used as a proxy of vegetation functioning and productivity in the Amazon rainforest. However, recent studies indicate that EVI patterns are strongly affected by satellite data artifacts. Hence, it is unclear if EVI is sensitive to subtle seasonal variations in evergreen Amazon forest productivity. This study analyzes 12-years of Moderate Resolution Imaging Spectroradiometer (MODIS) EVI in order to evaluate its response to factors driving productivity in the Amazon. We show that, after removing cloud and aerosol contamination, and correcting bidirectional reflectance distribution function effects, radiation and rainfall extremes show no influence on EVI anomalies. However, EVI seasonal patterns are still evident after accounting for Sun-sensor geometry effects. This remaining pattern cannot be explained by solar radiation or rainfall, but it is significantly correlated to gross primary production (GPP). Nevertheless, we argue that the causality between GPP and EVI should be interpreted with caution. Key Points Monthly EVI anomalies are not sensitive to radiation or rainfall extremesEVI seasonality in the Amazon is still present after BRDF correctionAlthough EVI and GPP correlate, interpretations of causality require caution-
dc.languageeng-
dc.relation.ispartofGeophysical Research Letters-
dc.subjectAmazon-
dc.subjectanomalies-
dc.subjectEVI-
dc.subjectMODIS-
dc.subjectphenology-
dc.titleCan MODIS EVI monitor ecosystem productivity in the Amazon rainforest?-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1002/2014GL061535-
dc.identifier.scopuseid_2-s2.0-84911453716-
dc.identifier.volume41-
dc.identifier.issue20-
dc.identifier.spage7176-
dc.identifier.epage7183-
dc.identifier.eissn1944-8007-
dc.identifier.isiWOS:000345343100025-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats