Influence of Spatial Aggregation on Prediction Accuracy of Green Vegetation Using Boosted Regression Trees
Data aggregation is a necessity when working with big data. Data reduction steps without loss of information are a scientific and computational challenge but are critical to enable effective data processing and information delineation in data-rich studies. We investigated the effect of four spatial...
Main Authors: | Brigitte Colin, Michael Schmidt, Samuel Clifford, Alan Woodley, Kerrie Mengersen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-08-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/10/8/1260 |
Similar Items
-
Estimating Spatial and Temporal Trends in Environmental Indices Based on Satellite Data: A Two-Step Approach
by: Brigitte Colin, et al.
Published: (2019-01-01) -
Prediction of home energy consumption based on gradient boosting regression tree
by: Peng Nie, et al.
Published: (2021-11-01) -
Monitoring of Urban Black-Odor Water Based on Nemerow Index and Gradient Boosting Decision Tree Regression Using UAV-Borne Hyperspectral Imagery
by: Lifei Wei, et al.
Published: (2019-10-01) -
Delta Boosting Implementation of Negative Binomial Regression in Actuarial Pricing
by: Simon CK Lee
Published: (2020-02-01) -
Ecological Risk Assessment and Impact Factor Analysis of Alpine Wetland Ecosystem Based on LUCC and Boosted Regression Tree on the Zoige Plateau, China
by: Mengjing Hou, et al.
Published: (2020-01-01)