Skip to main content
USGS - science for a changing world

Landsat 8 six spectral band data and MODIS NDVI data for assessing the optimal regression tree models

Dates

Publication Date
Start Date
2013-05-20
End Date
2013-08-28

Citation

Gu, Yingxin, Wylie, B.K., and Boyte, S.P., 2016, Landsat 8 six spectral band data and MODIS NDVI data for assessing the optimal regression tree models: U.S. Geological Survey data release, https://dx.doi.org/10.5066/F7319T1P.

Summary

In this study, we developed a method that identifies an optimal sample data usage strategy and rule numbers that minimize over- and underfitting effects in regression tree mapping models. A LANDFIRE tile (r04c03, located mainly in northeastern Nevada), which is a composite of multiple Landsat 8 scenes for a target date, was selected for the study. To minimize any cloud and bad detection effects in the original Landsat 8 data, the compositing approach used cosine-similarity-combined pixels from multiple observations based on data quality and temporal proximity to a target date. Julian date 212, which yielded relatively low "no data and/or cloudy” pixels, was used as the target date with Landsat 8 observations from days 140–240 in 2013. [...]

Contacts

Attached Files

Click on title to download individual files attached to this item.

RSD.csv 506.29 KB
RSD_meta_FGDC_f3.xml
Original FGDC Metadata

View
12.67 KB

Purpose

The data was used as an example to build the data-driven regression tree models and demonstrate the optimal data usage strategy that minimizes possible over- and underfitting effects in the regression tree models.

Map

Communities

  • USGS Data Release Products

Tags

Provenance

Data source
Input directly

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/F7319T1P

Item Actions

View Item as ...

Save Item as ...

View Item...