Developing multi-temporal methods for monitoring urban growth

Authors: Heng Wan*, Virginia Polytechnic Institute & State University, Yang Shao, Virginia Polytechnic Institute & State University
Topics: Land Use and Land Cover Change, Geographic Information Science and Systems
Keywords: NLCD, urban
Session Type: Paper
Day: 4/4/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Buchanan, Marriott, Mezzanine Level
Presentation File: No File Uploaded

In the US, National Land-cover database (NLCD) has been widely used as the baseline land-cover data for a variety of research and applications. Currently, there is a 5-year time lag between the image-capture date and the product-release date. During this time lag, some areas may have experienced substantial land cover changes, especially in urban/suburban settings. There are also land change modelling applications that require higher temporal frequency (e.g., annual) input data. This study aims at finding an effective method to update the NLCD to an annual resolution. Analysis ready Landsat data from 1988 to 2017 for the study area was downloaded to generate NDVI time series data for all the changing pixels identified by the percent developed impervious change layer. Then three methods, including threshold-value method, break-point method, and minimum-value method were applied to the NDVI time series of each changing pixel to identify its corresponding urbanization year. An accuracy assessment based on Google Earth historical image data was processed to draw the final conclusion. The study area was the path-027/row-009 scene of the Landsat World Reference System2 (WRS-2) encompassing Washington D.C. metropolitan areas in the northeast and a large portion of the Northern Virginia.

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