A multi-source data approach to carbon stock prediction using Bayesian hierarchical geostatistical models in plantation forest ecosystems

IF 6 2区地球科学 Q1 GEOGRAPHY, PHYSICAL

GIScience & Remote Sensing Pub Date : 2024-01-16 DOI:10.1080/15481603.2024.2303868

Tsikai S. Chinembiri, Onisimo Mutanga, Timothy Dube

引用次数: 0

Abstract

Modeling of environmental phenomena is usually confounded by the influence of multiple factors existing at different time and spatial scales. Bayesian modeling is presumed to be the best approach f...

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利用贝叶斯分层地质统计模型预测人工林生态系统碳储量的多源数据方法

环境现象的建模通常受到存在于不同时间和空间尺度的多种因素的影响。贝叶斯建模被认为是解决这些问题的最佳方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

GIScience & Remote Sensing 地学-遥感

CiteScore

11.20

自引率

9.00%

发文量

审稿时长

6 months

期刊介绍： GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.