A novel approach for retrieving GPP of evergreen forest regions of India using random forest regression-Reference-Cited by-同舟云学术

A novel approach for retrieving GPP of evergreen forest regions of India using random forest regression

Published:2024-01 Issue: Volume:33 Page:101116
ISSN:2352-9385
Container-title:Remote Sensing Applications: Society and Environment
language:en
Short-container-title:Remote Sensing Applications: Society and Environment

Author:

Sarkar Deep Prakash,Uma Shankar B.^ORCID,Ranjan Parida Bikash^ORCID

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference78 articles.

1. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015;Abatzoglou;Sci. Data,2018

2. Estimating gross primary production of a forest plantation area using eddy covariance data and satellite imagery;Ahongshangbam;J. Indian Soc. Remote Sens.,2016

3. A suite of global, cross-scale topographic variables for environmental and biodiversity modeling;Amatulli;Sci. Data,2018

4. Spatiotemporal patterns of terrestrial gross primary production: A review: GPP spatiotemporal patterns;Anav;Rev. Geophys.,2015

5. Estimating global gross primary production from sun-induced chlorophyll fluorescence data and auxiliary information using machine learning methods;Bai;Remote Sens.,2021

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment;Remote Sensing;2024-05-31

2. Mapping urban heat: Unveiling nature-based solutions in Sari City, Iran.;Urban Climate;2024-05

3. Modeling GPP with Machine Learning using Multisource Features based on Fluxnet Data;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05