Mapping Forest Aboveground Biomass with MODIS and Fengyun-3C VIRR Imageries in Yunnan Province, Southwest China Using Linear Regression, K-Nearest …
The aboveground biomass (AGB) of a forest is an important indicator of the forest's terrestrial
carbon storage and its relation to climate change. Due to the advantage of extensive spatial …
carbon storage and its relation to climate change. Due to the advantage of extensive spatial …
Modelling Forest Ecosystems: A crossroad between scales, techniques and applications
JA Blanco, A Ameztegui, F Rodríguez - Ecological Modelling, 2020 - Elsevier
Forests are likely the most complex ecosystems on Earth, as they cross scales from the
largest and longest-lived organisms on the planet (trees) with a myriad of diminutive …
largest and longest-lived organisms on the planet (trees) with a myriad of diminutive …
[HTML][HTML] Combining sample plot stratification and machine learning algorithms to improve forest aboveground carbon density estimation in northeast China using …
M Chen, X Qiu, W Zeng, D Peng - Remote Sensing, 2022 - mdpi.com
Timely, accurate estimates of forest aboveground carbon density (AGC) are essential for
understanding the global carbon cycle and providing crucial reference information for …
understanding the global carbon cycle and providing crucial reference information for …
A systematic review of remote sensing and machine learning approaches for accurate carbon storage estimation in natural forests
C Matiza, O Mutanga, K Peerbhay… - Southern Forests: a …, 2023 - Taylor & Francis
The assessment of carbon storage in natural forests is paramount in the ongoing efforts
against climate change. While traditional field-based methods for quantifying carbon storage …
against climate change. While traditional field-based methods for quantifying carbon storage …
Estimating burn severity and carbon emissions from a historic megafire in boreal forests of China
Wildfires, especially those of large size, worsen air quality and alter the carbon cycle through
combustion of large quantities of biomass and release of carbon into the atmosphere. The …
combustion of large quantities of biomass and release of carbon into the atmosphere. The …
Spatial-temporal changes in soil organic carbon and pH in the Liaoning Province of China: A modeling analysis based on observational data
Quantification of soil organic carbon (SOC) and pH, and their spatial variations at regional
scales, is a foundation to adequately assess agriculture, pollution control, or environmental …
scales, is a foundation to adequately assess agriculture, pollution control, or environmental …
Evaluating k-Nearest Neighbor (kNN) Imputation Models for Species-Level Aboveground Forest Biomass Mapping in Northeast China
Quantifying spatially explicit or pixel-level aboveground forest biomass (AFB) across large
regions is critical for measuring forest carbon sequestration capacity, assessing forest …
regions is critical for measuring forest carbon sequestration capacity, assessing forest …
Spatially explicit reconstruction of post-megafire forest recovery through landscape modeling
Megafires are large wildfires that occur under extreme weather conditions and produce
mixed burn severities across diverse environmental gradients. Assessing megafire effects …
mixed burn severities across diverse environmental gradients. Assessing megafire effects …
基于随机森林模型的青藏高原森林地上生物量遥感估算
张鹏超, 梁宇, 刘波, 马天啸, 吴苗苗 - 生态学杂志, 2023 - cje.net.cn
遥感数据可以实时快速获取森林属性信息, 利用遥感技术数据估算的森林地上生物量(
aboveground biomass, AGB) 具有空间连续性且精度较高的优势. 与低纬度或低海拔的森林 …
aboveground biomass, AGB) 具有空间连续性且精度较高的优势. 与低纬度或低海拔的森林 …
A comprehensive evaluation model for forest fires based on MCDA and machine learning: A case study of Zhenjiang City, China
R Xing, W Ju, H Lu - Environment, Development and Sustainability, 2024 - Springer
In recent years, forest fire accidents around the world have caused many casualties and
property losses. Therefore, the development of a new risk model to assess the risk of forest …
property losses. Therefore, the development of a new risk model to assess the risk of forest …