Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region-Reference-Cited by-同舟云学术

Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region

Published:2024-09 Issue: Volume:82 Page:102732
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Anees Shoaib Ahmad,Mehmood Kaleem,Khan Waseem Razzaq,Sajjad Muhammad,Alahmadi Tahani Awad,Alharbi Sulaiman Ali,Luo Mi

Publisher

Elsevier BV

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1. Assessment of climatic influences on net primary productivity along elevation gradients in temperate ecoregions;Trees, Forests and People;2024-12

2. Aboveground biomass inversion of forestland in a Jinsha River dry-hot valley by integrating high and medium spatial resolution optical images: A case study on Yuanmou County of Southwest China;Ecological Informatics;2024-11

3. Support Vector Machine Algorithm for Mapping Land Cover Dynamics in Senegal, West Africa, Using Earth Observation Data;Earth;2024-09-06