The Impact of Mapping Error on the Performance of Upscaling Agricultural Maps

The Impact of Mapping Error on the Performance of Upscaling Agricultural Maps

Aggregation methods are the most common way of upscaling land cover maps. To analyze the impact of land cover mapping error on upscaling agricultural maps, we utilized the Cropland Data Layer (CDL) data with corresponding confidence level data and simulated eight levels of error using a Monte Carlo...

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Bibliographic Details
Main Authors: Peijun Sun, Russell G. Congalton, Heather Grybas, Yaozhong Pan
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Remote Sensing
Subjects:
upscaling
land cover map
proportional error
landscape pattern
Monte Carlo simulation
Online Access:https://www.mdpi.com/2072-4292/9/9/901

Internet

https://www.mdpi.com/2072-4292/9/9/901

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