Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years

J **: A case study for Belgium
K Van Tricht, A Gobin, S Gilliams, I Piccard - Remote Sensing, 2018 - mdpi.com
A timely inventory of agricultural areas and crop types is an essential requirement for
ensuring global food security and allowing early crop monitoring practices. Satellite remote …

Improving land cover classification in an urbanized coastal area by random forests: The role of variable selection

F Zhang, X Yang - Remote Sensing of Environment, 2020 - Elsevier
Land cover map** in complex environments can be challenging due to their landscape
heterogeneity. With the increasing availability of various open-access remotely sensed …

[HTML][HTML] Monitoring rice agriculture across myanmar using time series Sentinel-1 assisted by Landsat-8 and PALSAR-2

N Torbick, D Chowdhury, W Salas, J Qi - Remote Sensing, 2017 - mdpi.com
Assessment and monitoring of rice agriculture over large areas has been limited by cloud
cover, optical sensor spatial and temporal resolutions, and lack of systematic or open access …

[Књига][B] Fundamentals of satellite remote sensing: An environmental approach

E Chuvieco - 2020 - taylorfrancis.com
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a
definitive guide to remote sensing systems that focuses on satellite-based remote sensing …

Estimating aboveground biomass using Sentinel-2 MSI data and ensemble algorithms for grassland in the Sheng** Lake Wetland, China

C Li, L Zhou, W Xu - Remote Sensing, 2021 - mdpi.com
Wetland vegetation aboveground biomass (AGB) directly indicates wetland ecosystem
health and is critical for water purification, carbon cycle, and biodiversity conservation …

Influence of variable selection and forest type on forest aboveground biomass estimation using machine learning algorithms

Y Li, C Li, M Li, Z Liu - Forests, 2019 - mdpi.com
Forest biomass is a major store of carbon and plays a crucial role in the regional and global
carbon cycle. Accurate forest biomass assessment is important for monitoring and map** …

[HTML][HTML] Using a U-net convolutional neural network to map woody vegetation extent from high resolution satellite imagery across Queensland, Australia

N Flood, F Watson, L Collett - … Journal of Applied Earth Observation and …, 2019 - Elsevier
Convolutional neural networks offer a new approach to classifying high resolution imagery.
We use the U-net neural network architecture to map the presence or absence of trees and …