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Related Experiment Video

Updated: Jul 1, 2025

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

[Distribution Prediction of Soil Heavy Metals Based on Remote Sensing Temporal-Spatial-Spectral Features and Random

Ze-Qiang Wang¹, Dong-You Zhang¹, Xi-Bo Xu^2,3

¹College of Geographical Sciences, Harbin Normal University, Harbin 150025, China.

Huan Jing Ke Xue= Huanjing Kexue

|March 12, 2024

Summary

This summary is machine-generated.

Soil arsenic levels in Changqing district show slight pollution, exceeding background values but not risk thresholds. Remote sensing data combined with a random forest model accurately predicted arsenic distribution, aiding pollution control efforts.

Area of Science:

Environmental Science
Geochemistry
Remote Sensing

Keywords:

arsenic(As)random forest(RF)soil spatial distribution prediction temporal-spatial-spectral features of remote sensing

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