@inproceedings{062acd7f74a24d29985e5dd74d0c14ad,
title = "Object-based algorithms and methods for quantifying urban growth pattern using sequential satellite images",
abstract = "Previously, urban growth pattern is described and measured by the pixel-by-pixel comparison of satellite images. The geographic extent, patterns and types of urban growth are derived from satellite images separated in time. However, the pixel-by-pixel comparison approach suffers from several drawbacks. Firstly, slight error in image geo-reference can cause false detection of changes. Secondly, it's difficult to recognize and correct artifact changes induced by data noise and data processing errors. Thirdly, only limited information can be derived. In this paper, we present a new objectbased method to describe and quantify urban growth patterns. The different types of land cover are classified from sequential satellite images as urban objects. The geometric and shape attributes of objects and the spatial relationship between them are employed to identify the different types of urban growth pattern. The algorithms involved in the object-based method are implemented by using C++ programming language and the software user interface is developed by using ArcObjects and VB.Net. A simulated example is given to demonstrate the utility and effectiveness of this new method.",
keywords = "Object-based method, Sequential images, Urban growth",
author = "Bailang Yu and Hongxing Liu and Yige Gao and Jianping Wu",
year = "2008",
doi = "10.1117/12.793369",
language = "英语",
isbn = "9780819473035",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Remote Sensing and Modeling of Ecosystems for Sustainability V",
note = "Remote Sensing and Modeling of Ecosystems for Sustainability V ; Conference date: 13-08-2008 Through 13-08-2008",
}