Estimation of Stand Type Parameters and Land Cover Using Landsat-7 ETM Image: A Case Study from Turkey
Alkan Günlü1, Fatih Sivrikaya2, Emin Zeki Baskent3
1Karadeniz Technical University, Faculty of Forestry 61080, Trabzon-Turkey. alkan61@ktu.edu.tr.
Sensors (Basel, Switzerland)
|November 24, 2016
Summary
Remote sensing with Landsat 7 ETM images effectively estimates forest development stages and land cover. However, low spatial resolution limits detailed mapping of stand types and minor vegetation communities.
Area of Science:
- Forestry
- Remote Sensing
- Geographic Information Systems (GIS)
Background:
- Remote sensing offers a cost-effective method for large-area forest information crucial for inventory.
- Assessing forest stand parameters like crown closure, development stage, and land cover is vital for forest management.
Purpose of the Study:
- To determine forest stand parameters using Landsat 7 ETM imagery and GIS.
- To classify and map stand parameters and compare remote sensing results with existing forest cover maps.
Main Methods:
- Utilized Landsat 7 ETM imagery and a forest cover type map.
- Employed supervised classification for estimating stand parameters.
- Applied GIS spatial analysis functions for mapping.
- Conducted accuracy assessments including kappa statistic and overall accuracy.
Main Results:
- Development stages were estimated with 92% overall accuracy and a 0.89 kappa statistic.
- Development stages achieved the highest spatial accuracy at 72.2%, though classification accuracy was higher.
- Stand type classification accuracy was notably lower at 32.8%.
Conclusions:
- Landsat 7 ETM imagery can adequately determine forest development stages, crown closure, and land cover.
- The low spatial resolution of Landsat 7 ETM restricts the mapping and monitoring of minor vegetation communities and individual stand types.
- High-resolution satellite imagery, potentially combined with field data, is recommended for detailed stand-level analysis.
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