Review of remote sensing-based methods for forest aboveground biomass estimation: Progress, challenges, and prospects
Quantifying forest aboveground biomass (AGB) is essential for elucidating the global carbon
cycle and the response of forest ecosystems to climate change. Over the past five decades …
cycle and the response of forest ecosystems to climate change. Over the past five decades …
Development of forest aboveground biomass estimation, its problems and future solutions: A review
T Ma, C Zhang, L Ji, Z Zuo, M Beckline, Y Hu, X Li… - Ecological …, 2024 - Elsevier
Forest aboveground biomass (AGB) is crucial as it serves as a fundamental indicator of the
productivity, biodiversity, and carbon storage of forest ecosystems. This paper presents a …
productivity, biodiversity, and carbon storage of forest ecosystems. This paper presents a …
Species-level classification and mapping of a mangrove forest using random forest—utilisation of AVIRIS-NG and sentinel data
Although studies on species-level classification and mapping using multisource data and
machine learning approaches are plenty, the use of data with ideal placement of central …
machine learning approaches are plenty, the use of data with ideal placement of central …
Estimation of aboveground carbon density of forests using deep learning and multisource remote sensing
Forests are crucial in carbon sequestration and oxygen release. An accurate assessment of
forest carbon storage is meaningful for Chinese cities to achieve carbon peak and carbon …
forest carbon storage is meaningful for Chinese cities to achieve carbon peak and carbon …
Combining GEDI and sentinel data to estimate forest canopy mean height and aboveground biomass
Forest canopy mean height (CMH) and aboveground biomass (AGB) are key indicators for
evaluating forest ecosystem productivity. In this study, we proposed a new approach to …
evaluating forest ecosystem productivity. In this study, we proposed a new approach to …
A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest
Mangroves are well-recognized for their very high carbon sequestration potential. However,
studies on their role in global carbon cycling and climate change are hindered due to lack of …
studies on their role in global carbon cycling and climate change are hindered due to lack of …
Estimation of tropical forest aboveground biomass in Nepal using multiple remotely sensed data and deep learning
This study assessed the prediction accuracy of the forest aboveground biomass (AGB)
model using remotely sensed data sources (ie airborne laser scanning (ALS), RapidEye …
model using remotely sensed data sources (ie airborne laser scanning (ALS), RapidEye …
Deep semantic segmentation of mangroves in Brazil combining spatial, temporal, and polarization data from Sentinel-1 time series
GM de Souza Moreno, OA de Carvalho Júnior… - Ocean & Coastal …, 2023 - Elsevier
The automatic and accurate detection of mangroves from remote sensing data is essential to
assist in conservation strategies and decision-making that minimize possible environmental …
assist in conservation strategies and decision-making that minimize possible environmental …
Monitoring the tropical cyclone 'Yass' and 'Amphan' affected flood inundation using Sentinel-1/2 data and Google Earth Engine
B Halder, J Bandyopadhyay - Modeling Earth Systems and Environment, 2022 - Springer
The tropical cyclone is influenced the natural environmental conditions, biodiversity,
mangrove forest degradation; salinity increased, and flood inundation at the global …
mangrove forest degradation; salinity increased, and flood inundation at the global …
A near real-time mapping of tropical forest disturbance using sar and semantic segmentation in google earth engine
Satellite-based forest alert systems are an important tool for ecosystem monitoring, planning
conservation, and increasing public awareness of forest cover change. Continuous …
conservation, and increasing public awareness of forest cover change. Continuous …