Modeling Forest Productivity Using Envisat MERIS Data
Suha Berberoglu1, Fatih Evrendilek2, Coskun Ozkan3
1Department of Landscape Architecture, Faculty of Agriculture, Cukurova University, 01330 Adana, Turkey. suha@cu.edu.tr.
Sensors (Basel, Switzerland)
|September 15, 2017
Summary
This study quantifies conifer forest net primary productivity (NPP) in Turkey using Envisat MERIS data. The results show MERIS offers greater spatial detail for NPP estimation in complex terrains compared to global-scale data.
Area of Science:
- Earth Observation
- Forest Ecology
- Remote Sensing
Background:
- Accurate quantification of Net Primary Productivity (NPP) is crucial for understanding forest ecosystems and their response to environmental changes.
- Previous NPP estimations often lacked the spatial resolution required for complex terrains, limiting regional-scale ecological assessments.
- The Taurus Mountain range in Turkey presents a topographically complex region where detailed NPP data is needed.
Purpose of the Study:
- To derive 300-m pixel resolution land cover products from Envisat Medium Resolution Imaging Spectrometer (MERIS) data.
- To quantify the Net Primary Productivity (NPP) of conifer forests in the Taurus Mountain range, Turkey.
- To assess the capability of Envisat MERIS data for detailed regional-scale NPP estimation in complex landscapes.
Main Methods:
- Utilized the Carnegie-Ames-Stanford Approach (CASA) model to predict annual and monthly regional NPP.
- Estimated fractional tree cover using multi-temporal metrics from 47 Envisat MERIS images (March 2003–September 2005).
- Employed a regression tree algorithm to derive fractional tree cover from MERIS data, incorporating IKONOS and Landsat ETM imagery for calibration.
Main Results:
- Generated land cover products at a 300-m pixel resolution using Envisat MERIS data.
- Quantified regional NPP for conifer forests in the Taurus Mountain range, considering factors like temperature, precipitation, and vegetation index.
- Demonstrated that Envisat MERIS data provides superior spatial detail for NPP quantification in topographically complex terrain compared to coarser global-scale datasets like AVHRR.
Conclusions:
- Envisat MERIS data is effective for producing high-resolution land cover products suitable for regional NPP quantification.
- The study highlights the advantage of MERIS data over global-scale products for ecological studies in complex mountainous regions.
- This approach enhances our ability to monitor and understand forest productivity dynamics in challenging terrains.
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