Challenges and Opportunities in Lidar Remote Sensing

Wang, Zhien; Menenti, Massimo

doi:10.3389/frsen.2021.641723

Cited by 66 publications

(25 citation statements)

References 96 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some emerging technologies contain geographic information systems (GIS), city information modelling (CIM), digital twin, Internet of Things (IoT), etc. The latest research advances are: (1) data-driven intelligent environmental inversion; 8,24 (2) remote sensing monitoring and active identification of the whole process of ecological and environmental problems with space-ground integration; 24 (3) lightweight multi-source heterogeneous data resolution model for urban planning (e.g. urban climate map); 25 (4) big data based on ecological information for human behaviour simulation and intelligent O&M of cities.…”

Section: Society and Ecology: Environmental Equality And Urban Green ...mentioning

confidence: 99%

Planning for sustainable and ecological urban environment: Current trends and future developments

Wang

Yu²,

Cao

2022

Indoor and Built Environment

View full text Add to dashboard Cite

Section: Society and Ecology: Environmental Equality And Urban Green ...mentioning

confidence: 99%

Planning for sustainable and ecological urban environment: Current trends and future developments

Wang

Yu²,

Cao

2022

Indoor and Built Environment

View full text Add to dashboard Cite

“…Ground-based lidars have been widely used by the atmospheric science community for the measurement and retrieval of atmospheric properties [5]. For example, various types of lidars are routinely operated by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility, as well as other ground-based networks and observatories, e.g., [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Time-Gated, Time-Correlated Single-Photon-Counting Lidar to Observe Atmospheric Clouds at Submeter Resolution

Yang

Sua

Louridas³

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Most lidars used for cloud observations have the range resolution of about 10 m, so they are incapable of resolving submeter-scale processes that are crucial to cloud evolution. This article describes a prototype of a ground-based, vertically pointing, time-gated, time-correlated single-photon-counting lidar (referred to as the T2 lidar) developed to explore atmospheric clouds at range resolution two orders of magnitude finer than traditional atmospheric lidars. The T2 lidar emits green-light pulses (532 nm) at a repetition rate of 20.6 kHz and a pulse width of ∼650 ps, which enables the observation of aerosol and cloud layers at heights from a few hundred meters to 7.28 km above the ground level at range resolution down to 10 cm. In addition, a digital delay pulse generator controls the detector to only receive photons for a short period after each laser pulse. This time-gated technique blocks photons arriving from regions outside the target zone, thus significantly reducing the noise level and allowing observation even inside clouds. Initial observations show that the T2 lidar can detect sharp cloud boundaries and fine structures near the cloud base. Such refined measurements of cloud structure could lead to an improved understanding of microphysical processes such as droplet activation, entrainment and mixing, and precipitation.

show abstract

“…In the fields of remote sensing (16) and 3D scanning (17), Screened Poisson Reconstruction (SPR) (18) is often used to extract surfaces from point clouds. SPR reconstruction is designed to follow point locations exactly, giving it high fidelity to collected positions.…”

Section: Introductionmentioning

confidence: 99%

Extracting nanoscale membrane morphology from single-molecule localizations

Marin

Fuentes

Bewersdorf

et al. 2023

Preprint

View full text Add to dashboard Cite

Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that is manually cleaned and curated. Here we present a new method for extracting surfaces from generalized single-molecule localization microscopy (SMLM) data. This makes it possible to study the shape of specifically-labelled continuous structures inside of cells. We validate our method using simulations and demonstrate its reconstruction capabilities on SMLM data of the endoplasmic reticulum and mitochondria. Our method is implemented in the open-source Python Microscopy Environment.

show abstract

Challenges and Opportunities in Lidar Remote Sensing

Abstract: To support operational lidar applications, transferring research lidars into turnkey systems and reduce their costs are necessary steps. During the last 20 years, advances in industrial lasers improved

Cited by 66 publications

References 96 publications

Planning for sustainable and ecological urban environment: Current trends and future developments

Planning for sustainable and ecological urban environment: Current trends and future developments

A Time-Gated, Time-Correlated Single-Photon-Counting Lidar to Observe Atmospheric Clouds at Submeter Resolution

Extracting nanoscale membrane morphology from single-molecule localizations

Contact Info

Product

Resources

About