[HTML][HTML] Remote sensing of soil degradation: Progress and perspective
Soils constitute one of the most critical natural resources and maintaining their health is vital
for agricultural development and ecological sustainability, providing many essential …
for agricultural development and ecological sustainability, providing many essential …
Satellite imagery to map topsoil organic carbon content over cultivated areas: an overview
There is a need to update soil maps and monitor soil organic carbon (SOC) in the upper
horizons or plough layer for enabling decision support and land management, while …
horizons or plough layer for enabling decision support and land management, while …
Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing
Soil organic carbon (SOC) is a key variable to determine soil functioning, ecosystem
services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral …
services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral …
Evaluating the potential impacts of land use changes on ecosystem service value under multiple scenarios in support of SDG reporting: A case study of the Wuhan …
Terrestrial ecosystem services can offer various kinds of benefits for human life and
production and play a critical role in the attainment of the Sustainable Development Goals …
production and play a critical role in the attainment of the Sustainable Development Goals …
An advanced soil organic carbon content prediction model via fused temporal-spatial-spectral (TSS) information based on machine learning and deep learning …
X Meng, Y Bao, Y Wang, X Zhang, H Liu - Remote Sensing of Environment, 2022 - Elsevier
Abstract Knowledge of the soil organic carbon (SOC) content is critical for environmental
sustainability and carbon neutrality. With the development of remote sensing data and …
sustainability and carbon neutrality. With the development of remote sensing data and …
Towards delivering on the sustainable development goals using earth observations
A Kavvada, G Metternicht, F Kerblat, N Mudau… - Remote Sensing of …, 2020 - Elsevier
With less than a decade left to attain the Sustainable Development Goals (SDGs), this
communication aims to improve understanding of the enabling environment that is essential …
communication aims to improve understanding of the enabling environment that is essential …
Soil properties: Their prediction and feature extraction from the LUCAS spectral library using deep convolutional neural networks
L Zhong, X Guo, Z Xu, M Ding - Geoderma, 2021 - Elsevier
Soil, as a non-renewable resource, should be monitored continuously to prevent its
degradation and promote sustainable agriculture. Soil spectroscopy in the visible-near …
degradation and promote sustainable agriculture. Soil spectroscopy in the visible-near …
[HTML][HTML] Soil Science-Informed Machine Learning
Abstract Machine learning (ML) applications in soil science have significantly increased over
the past two decades, reflecting a growing trend towards data-driven research addressing …
the past two decades, reflecting a growing trend towards data-driven research addressing …
Earth observation data-driven cropland soil monitoring: A review
We conducted a systematic review and inventory of recent research achievements related to
spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil …
spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil …
Towards spatially continuous mapping of soil organic carbon in croplands using multitemporal Sentinel-2 remote sensing
Intensified human activities can augment soil organic carbon (SOC) losses from the world's
croplands, making SOC a highly dynamic parameter both in space and time. Sentinel-2 …
croplands, making SOC a highly dynamic parameter both in space and time. Sentinel-2 …