Indigenous forest wood volume estimation in a dry savanna, Zimbabwe: exploring the performance of high-and-medium spatial resolution multispectral sensors

Abstract

Continuous, accurate estimation and mapping of forest dendrometric characteristics such as wood volume using remote sensing is fundamental for better understanding the role of forests in the carbon cycle and for informed management strategies for forests and woodlands. In this study, we tested whether and to what extent spectral vegetation indices derived from new generation high-spatial resolution multispectral sensors (WorldView-2 and GeoEye-1) estimate indigenous forest wood volume when compared to medium-spatial resolution broadband sensors (Landsat 5 Thematic Mapper) based on two savanna woodland types in Zimbabwe. Subsequently, the best regression model relating wood volume and vegetation indices was applied to map the indigenous forest wood volume of two study sites. Our results showed that spectral vegetation indices derived from new generation multispectral sensors of high resolution yielded plausible indigenous forest wood volume estimates when compared to spectral vegetation indices derived from medium resolution broadband Landsat 5 TM. The findings of our study demonstrated that accurate estimates of indigenous forest wood volume can be derived using vegetation indices derived from high spatial resolution images. Furthermore, these findings emphasise the importance of vegetation indices derived from high resolution satellite images for estimating forest structural attributes, such as wood volume, among others.

Keywords:

• dry savanna woodlands
• high spatial resolution
• new generation sensors
• regression function
• WorldView-2

ACKNOWLEDGEMENTS

This work was conducted within the framework of the Research Platform ‘Production and Conservation in Partnership’ ‘RP-PCP’. We thank the Ministère Français des Affaires Etrangères et Européennes for supporting the project through the French Embassy in Zimbabwe (RP-PCP grant/CC#5). We would like to thank the Director General of Zimbabwe Parks and Wildlife Management Authority and the Estate Manager of Mukuvisi Woodland Nature Reserve and Environment Centre for granting us permission to access their respective study sites. We are also grateful to the GeoEye Foundation for the GeoEye-1 satellite imagery grant. We also want to thank Fadzai Zengeya for granting us permission to use her WorldView-2 satellite imagery.