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Sensors 2007, 7(10), 2115-2127;

Modeling Forest Productivity Using Envisat MERIS Data

Department of Landscape Architecture, Faculty of Agriculture, Cukurova University, 01330 Adana, Turkey
Department of Environmental Engineering, Faculty of Engineering and Architecture, Abant Izzet Baysal University, Golkoy Campus, 14280 Bolu, Turkey
Department of Geodesy and Photogrammetry, Faculty of Engineering, Erciyes University, 38039 Kayseri, Turkey
Author to whom correspondence should be addressed.
Received: 4 September 2007 / Accepted: 2 October 2007 / Published: 5 October 2007
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The aim of this study was to derive land cover products with a 300-m pixelresolution of Envisat MERIS (Medium Resolution Imaging Spectrometer) to quantify netprimary productivity (NPP) of conifer forests of Taurus Mountain range along the EasternMediterranean coast of Turkey. The Carnegie-Ames-Stanford approach (CASA) was usedto predict annual and monthly regional NPP as modified by temperature, precipitation,solar radiation, soil texture, fractional tree cover, land cover type, and normalizeddifference vegetation index (NDVI). Fractional tree cover was estimated using continuoustraining data and multi-temporal metrics of 47 Envisat MERIS images of March 2003 toSeptember 2005 and was derived by aggregating tree cover estimates made from high-resolution IKONOS imagery to coarser Landsat ETM imagery. A regression tree algorithmwas used to estimate response variables of fractional tree cover based on the multi-temporal metrics. This study showed that Envisat MERIS data yield a greater spatial detailin the quantification of NPP over a topographically complex terrain at the regional scalethan those used at the global scale such as AVHRR. View Full-Text
Keywords: NPP; Envisat MERIS; CASA; Mediterranean conifer forest. NPP; Envisat MERIS; CASA; Mediterranean conifer forest.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Berberoglu, S.; Evrendilek, F.; Ozkan, C.; Donmez, C. Modeling Forest Productivity Using Envisat MERIS Data. Sensors 2007, 7, 2115-2127.

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