Google Earth Engine: a global analysis and future trends

A Velastegui-Montoya, N Montalván-Burbano… - Remote Sensing, 2023 - mdpi.com
The continuous increase in the volume of geospatial data has led to the creation of storage
tools and the cloud to process data. Google Earth Engine (GEE) is a cloud-based platform …

A survey of computer vision techniques for forest characterization and carbon monitoring tasks

S Illarionova, D Shadrin, P Tregubova, V Ignatiev… - Remote Sensing, 2022 - mdpi.com
Estimation of terrestrial carbon balance is one of the key tasks in the understanding and
prognosis of climate change impacts and the development of tools and policies according to …

UAV and machine learning based refinement of a satellite-driven vegetation index for precision agriculture

V Mazzia, L Comba, A Khaliq, M Chiaberge, P Gay - Sensors, 2020 - mdpi.com
Precision agriculture is considered to be a fundamental approach in pursuing a low-input,
high-efficiency, and sustainable kind of agriculture when performing site-specific …

Estimating the aboveground biomass of coniferous forest in Northeast China using spectral variables, land surface temperature and soil moisture

F Jiang, M Kutia, K Ma, S Chen, J Long… - Science of the Total …, 2021 - Elsevier
As a crucial indicator of forest growth and quality, estimating aboveground biomass (AGB)
plays a key role in monitoring the global carbon cycle and forest health assessments. Novel …

Estimating forest aboveground biomass using Gaofen-1 images, Sentinel-1 images, and machine learning algorithms: A case study of the Dabie Mountain Region …

H Han, R Wan, B Li - Remote Sensing, 2021 - mdpi.com
Quantitatively map** forest aboveground biomass (AGB) is of great significance for the
study of terrestrial carbon storage and global carbon cycles, and remote sensing-based data …

Forest height map** using feature selection and machine learning by integrating multi-source satellite data in Baoding City, North China

N Zhang, M Chen, F Yang, C Yang, P Yang, Y Gao… - Remote Sensing, 2022 - mdpi.com
Accurate estimation of forest height is crucial for the estimation of forest aboveground
biomass and monitoring of forest resources. Remote sensing technology makes it …

Assessment of the soil fertility status in Benin (West Africa)–Digital soil map** using machine learning

KOL Hounkpatin, AY Bossa, Y Yira, MA Igue… - Geoderma …, 2022 - Elsevier
A soil fertility index map (SFIm) can provide key information to decision-makers in regard to
spatial planning in the context of sustainable land management. The establishment of such …

Map** the forest canopy height in Northern China by synergizing ICESat-2 with Sentinel-2 using a stacking algorithm

F Jiang, F Zhao, K Ma, D Li, H Sun - Remote Sensing, 2021 - mdpi.com
The forest canopy height (FCH) plays a critical role in forest quality evaluation and resource
management. The accurate and rapid estimation and map** of the regional forest canopy …

Integrating spaceborne LiDAR and Sentinel-2 images to estimate forest aboveground biomass in Northern China

F Jiang, M Deng, J Tang, L Fu, H Sun - Carbon Balance and Management, 2022 - Springer
Background Fast and accurate forest aboveground biomass (AGB) estimation and map**
is the basic work of forest management and ecosystem dynamic investigation, which is of …

[HTML][HTML] Improving aboveground biomass estimation of natural forests on the Tibetan Plateau using spaceborne LiDAR and machine learning algorithms

F Jiang, H Sun, K Ma, L Fu, J Tang - Ecological Indicators, 2022 - Elsevier
Natural forests have the most complex structure and richest biodiversity among terrestrial
ecosystems and are essential for maintaining the carbon balance and stability of the …