Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

International Journal of Digital Earth
By: , and 

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Abstract

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US
Series title International Journal of Digital Earth
DOI 10.1080/17538947.2016.1158876
Volume 9
Issue 10
Year Published 2016
Language English
Publisher Taylor and Francis
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 18 p.
First page 963
Last page 980
Online Only (Y/N) N
Additional Online Files (Y/N) N