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Title
Abstract
Introduction
Study Area, Spectral, and Ancillary Data
Methodology
Change Detection in Databases
Results and Discussion
Conclusions
References
All Topics
Computer Science
Machine Learning

Historical Land Use as a Feature for Image Classification

Profile image of Jorge RecioJorge Recio

2011, Photogrammetric Engineering & Remote Sensing

https://doi.org/10.14358/PERS.77.4.377
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11 pages

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Abstract

This paper analyzes the effect of the addition of historical land-use as a descriptive feature in plot-based image classification when updating land-use/land-cover geospatial databases. Several historical databases have been simulated to assess the influence and significance of this feature in the classification. The causes, nature, and evolution of classification errors as the database currency varies are analyzed; and the impact of these errors on change detection during the updating process is evaluated. The results show that the addition of historical land-use information increases the overall accuracy of image classifications. During a database updating process, changes are detected by comparing the historical land-use with the classification results. The main drawback of employing historical land-use as a descriptive feature in image classification for change detection is that the percentage of undetectable errors significantly increases as more accurate is the database information.

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