Remote Sens. 2014, 6(3), 1973-1990; doi:10.3390/rs6031973
Article

Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa

1,†,* email, 1email, 2email, 3email, 4email, 5email and 4,†email
Received: 31 October 2013; in revised form: 24 February 2014 / Accepted: 25 February 2014 / Published: 4 March 2014
(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The recent Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g product provides a 30-year global times-series of remotely sensed leaf area index (LAI), an essential variable in models of ecosystem process and productivity. In this study, we use a new dataset of field-based LAITrue to indirectly validate the GIMMS LAI3g product, LAIavhrr, in East Africa, comparing the distribution properties of LAIavhrr across biomes and environmental gradients with those properties derived for LAITrue. We show that the increase in LAI with vegetation height in natural biomes is captured by both LAIavhrr and LAITrue, but that LAIavhrr overestimates LAI for all biomes except shrubland and cropland. Non-linear responses of LAI to precipitation and moisture indices, whereby leaf area peaks at intermediate values and declines thereafter, are apparent in both LAITrue and LAIavhrr, although LAITrue reaches its maximum at lower values of the respective environmental driver. Socio-economic variables such as governance (protected areas) and population affect both LAI responses, although cause and effect are not always obvious: a positive relationship with human population pressure was detected, but shown to be an artefact of both LAI and human settlement covarying with precipitation. Despite these complexities, targeted field measurements, stratified according to both environmental and socio-economic gradients, could provide crucial data for improving satellite-derived LAI estimates, especially in the human-modified landscapes of tropical Africa.
Keywords: hemispherical images; tropical landscapes; field assessments; Kenya; Ethiopia; Tanzania; East Africa; essential climate variables
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MDPI and ACS Style

Pfeifer, M.; Lefebvre, V.; Gonsamo, A.; Pellikka, P.K.E.; Marchant, R.; Denu, D.; Platts, P.J. Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa. Remote Sens. 2014, 6, 1973-1990.

AMA Style

Pfeifer M, Lefebvre V, Gonsamo A, Pellikka PKE, Marchant R, Denu D, Platts PJ. Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa. Remote Sensing. 2014; 6(3):1973-1990.

Chicago/Turabian Style

Pfeifer, Marion; Lefebvre, Veronique; Gonsamo, Alemu; Pellikka, Petri K.E.; Marchant, Rob; Denu, Dereje; Platts, Philip J. 2014. "Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa." Remote Sens. 6, no. 3: 1973-1990.

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