An assessment of landscape diversity using large scale field-based forest inventory

Abstract

Landscape diversity is considered as the variety of land cover classes in a landscape and it is usually calculated on land cover maps of entire landscape. However, in this study it is aimed to present a new procedure, that is, the use of field-based national forest inventories (NFIs) to estimate two diversity indices: Shannon's diversity and inverse Simpson. Specifically, it is also intended to investigate how well a combination estimator can improve the precision of the estimates. The permanent square cluster plots produced more precise (smaller variance) estimate of the indices than temporary ones. In addition, estimated variance of the indices using combination estimator was smaller than both permanent and temporary square cluster plots. The applied procedure in this study is very simple where classes of land cover are usually determined and recorded by field surveyor. The main advantages of using field-based inventories are that there is no need for land cover/ use maps or images of the landscape. In addition, quality of the landscape diversity assessment through remotely-sensed data is still highly dependent on the availability and quality of field data. As long as historical datasets from forest inventories is available in many countries it is thus possible to do trend analysis in landscape diversity over time.