Spectral saturation in the remote sensing of high-density vegetation traits: A systematic review of progress, challenges, and prospects

O Mutanga, A Masenyama, M Sibanda - ISPRS Journal of Photogrammetry …, 2023 - Elsevier
The saturation of spectral reflectance within densely vegetated regions is a renowned
challenge that has precluded the optimal use of broad-band remotely sensed data and its …

A systematic review of UAV applications for mapping neglected and underutilised crop species' spatial distribution and health

M Abrahams, M Sibanda, T Dube, VGP Chimonyo… - Remote Sensing, 2023 - mdpi.com
Timely, accurate spatial information on the health of neglected and underutilised crop
species (NUS) is critical for optimising their production and food and nutrition in developing …

Estimating the Aboveground Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data

T Huang, G Ou, Y Wu, X Zhang, Z Liu, H Xu, X Xu… - Remote Sensing, 2023 - mdpi.com
It is important to improve the accuracy of models estimating aboveground biomass (AGB) in
large areas with complex geography and high forest heterogeneity. In this study, k-nearest …

[HTML][HTML] A comparative analysis of machine learning techniques for aboveground biomass estimation: A case study of the Western Ghats, India

K Ayushi, KN Babu, N Ayyappan, JR Nair… - Ecological …, 2024 - Elsevier
Accurate assessment of aboveground biomass (AGB) in tropical forests, particularly within a
biodiversity hotspot, is vital for sustainable resource management and the preservation of …

Comparison of Weibull parameter estimation methods using LiDAR and mast wind data in an Indian offshore site: The Gulf of Khambhat

A Gautam, V Warudkar, JL Bhagoria - Ocean Engineering, 2022 - Elsevier
This paper gives a proper study of 11 types of Weibull parameters estimation methods and
their performance comparison for wind potential assessment on India's first offshore project …

Hydroclimatic adaptation critical to the resilience of tropical forests

C Singh, R van der Ent… - Global Change …, 2022 - Wiley Online Library
Forest and savanna ecosystems naturally exist as alternative stable states. The maximum
capacity of these ecosystems to absorb perturbations without transitioning to the other …

Modelling forest biomass dynamics in relation to climate change in Romania using complex data and machine learning algorithms

R Prăvălie, M Niculiţă, B Roşca, C Patriche… - … Research and Risk …, 2023 - Springer
Forest biomass controls climate stability, many ecological processes and various ecosystem
services. This study analyzes for the first time the recent changes (1987–2018) of forest …

Estimating above-ground biomass of the regional forest landscape of northern Western Ghats using machine learning algorithms and multi-sensor remote sensing …

FV Sainuddin, G Malek, A Rajwadi, PS Nagar… - Journal of the Indian …, 2024 - Springer
Estimating above-ground biomass (AGB) using machine learning (ML) algorithms and multi-
sensor satellite data is a promising approach for monitoring and managing forest resources …

A generic Self-Supervised Learning (SSL) framework for representation learning from spectral–spatial features of unlabeled remote sensing imagery

X Zhang, L Han - Remote Sensing, 2023 - mdpi.com
Remote sensing data has been widely used for various Earth Observation (EO) missions
such as land use and cover classification, weather forecasting, agricultural management …

Dominant expression of SAR backscatter in predicting aboveground biomass: Integrating multi-sensor data and machine learning in Sikkim Himalaya

AJ Prakash, S Mudi, S Paramanik, MD Behera… - Journal of the Indian …, 2024 - Springer
Accurate assessment of aboveground biomass (AGB) is crucial for understanding carbon
budgets, climate change impacts, and evaluating forest responses to environmental shifts. In …