The impact of seasonality on multi-scale feature extraction techniques. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Moore, Brian; McKee, Jacob J.
• Is Part Of: International journal of digital earth. Volume 13:Issue 1(2020)
• Page Start: 9
• Page End: 21
• Publication Date: 2020-01-02
• Subjects: Remote sensing -- high-resolution imagery -- image processing -- human settlement -- accuracy; Geographic information systems -- Periodicals; Sustainable development -- Information technology -- Periodicals; Social planning -- Information technology -- Periodicals; 910.285
• DOI: 10.1080/17538947.2018.1556354
• Languages: English
• ISSNs: 1753-8947

Abstract

ABSTRACT: A key component in constructing a broad-scale, gridded population dataset is fine resolution geospatial data accurately depicting the extent of human activity. Analogous datasets are often developed using a wide range of methods and classification techniques, including the use of spatial features, spectral features, or the coupling of both to identify the presence of man-made structures from high-resolution satellite imagery. By using spatial and textural-based descriptors to generate high-resolution settlement layers for two dissimilar regions at the peak of seasonal disparity, this study attempts to quantify the influence of seasonality on the accuracy of a supervised, multi-scale, feature extraction framework for automated delineation of human settlement. Results generated by numerous models are evaluated against a reference dataset allowing for assessment of seasonal and feature differences in the context of accuracy. Global or regional mapping of human settlement requires the assemblage of high-resolution satellite images with variegated acquisition characteristics (season, sun elevation, off-nadir, etc.) to produce a cloud-free composite image from which features are extracted. Results of this study suggest an emphasis on imagery criteria, in particular acquisition date, could improve classification accuracy when mapping human settlement at scale.