open access

https://hdl.handle.net/2115/78799

Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover

英語

spectral indices

2019-07-03

Taylor & Francis

Geocarto International

34(8)

839-855

Developing techniques are required to generate agricultural land cover maps to monitor agricultural fields. Landsat 8 Operational Land Imager (OLI) offers reflectance data over the visible to shortwave-infrared range. OLI offers several advantages, such as adequate spatial and spectral resolution, and 16 day repeat coverage, furthermore, spectral indices derived from Landsat 8 OLI possess great potential for evaluating the status of vegetation. Additionally, classification algorithms are essential for generating accurate maps. Recently, multi-Grained Cascade Forest, which is also called deep forest, was proposed, and it was shown to give highly competitive performance for classification. However, the ability of this algorithm to generate crop maps with satellite data had not yet been evaluated. In this study, the reflectance at 7 bands and 57 spectral indices calculated from Landsat 8 OLI data were evaluated for its potential for crop type identification.

学術雑誌論文

Accepted Manuscript

This is an Accepted Manuscript of an article published by Taylor & Francis in Geocarto International on 3 Jul. 2019, available online: http://www.tandfonline.com/doi/abs/10.1080/10106049.2018.1425739.

1010-6049

1752-0762

AA10729367