Abstract

Abstract. Accuracy assessment of forest type maps is essential to evaluate the classification of forest ecosystems quantitatively. However, map users do not understand in which regions those forest types are well classified from conventional static accuracy measures. Hence, the objective of this study is to unveil spatial heterogeneities of accuracies of forest type classification in a map. Four forest types (deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF)) found in the JAXA’s land use / cover map of Japan were assessed by a volunteered Site-based dataset for Assessment of Changing LAnd cover by JAXA (SACLAJ). A geographically weighted (GW) correspondence matrix was applied to them to calculate the degree of overall agreements of forest type classes (forest overall accuracy), and the degree of accuracy for each forest class (forest user’s and producer’s accuracies) in a spatially varying way. This study compared spatial surfaces of these measures with static ones of them. The results show that the forest overall accuracy of the forest map tends to be relatively more accurate in the central Japan, while less in the Kansai and Chubu regions and the northern edge of Hokkaido. Static forest user’s accuracy measures for DBF, DNF, and ENF are better than forest producer’s accuracy ones, while the GW approach tells us such characteristics vary spatially and some areas have opposite trends. This kind of spatial accuracy assessment provides a more informative description of the accuracy than the simple use of conventional accuracy measures.

Highlights

  • Land cover (LC) maps describe the Earth’s terrestrial surface, encompassing all attributes of the biosphere (International Panel on Climate Change, 2000)

  • We extend the concept of overall, user’s and producer’s accuracy measures to focus only on forest related classes

  • Accurate forest type classification maps are required for these applications, such map has not yet been achieved

Read more

Summary

Introduction

Land cover (LC) maps describe the Earth’s terrestrial surface, encompassing all attributes of the biosphere (International Panel on Climate Change, 2000). It is important to make an accurate LC classification map for high-quality quantification of these properties. The classification of plant functional types (PFTs) is one of the main and most challenging tasks toward accurate LC mapping. PFT mapping can be considered as a land cover classification in which plants are grouped with regard to their physiology and physiognomy (Moncrieff et al, 2016). In Japan, the forest type classification (i.e. deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), evergreen needleleaf forest (ENF), and

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call