A5063630204- Remote Sensing and LiDAR Applications
- Remote Sensing in Agriculture
- Species Distribution and Climate Change
- Land Use and Ecosystem Services
- Forest Ecology and Biodiversity Studies
- Forest ecology and management
- Scientific Computing and Data Management
- 3D Surveying and Cultural Heritage
- Hydrology and Watershed Management Studies
- Peatlands and Wetlands Ecology
- Atmospheric and Environmental Gas Dynamics
- Research Data Management Practices
- Advanced Optical Sensing Technologies
- Distributed and Parallel Computing Systems
- Advanced Neural Network Applications
- Wildlife-Road Interactions and Conservation
- Cloud Computing and Resource Management
- Robotics and Sensor-Based Localization
- Radiomics and Machine Learning in Medical Imaging
University of Amsterdam
2022-2023
LifeWatch (Israel)
2021-2023
University of Twente
2017-2021
Institute for Biodiversity
2021
Leaf area index (LAI) has frequently been measured in the field using traditional optical methods such as digital hemispherical photography (DHP). However, DHP retrieved LAI, there is always contribution of woody components due to difficulty distinguishing and foliar materials. In addition, leaf angle distribution which strongly affects estimation LAI either ignored while convergent 57.5°, or inversed simultaneously with multiple directions. Terrestrial laser scanning (TLS) provides a...
Abstract Virtual research environments (VREs) provide user‐centric support in the lifecycle of activities, for example, discovering and accessing assets or composing executing application workflows. A typical VRE is often implemented as an integrated environment, including a catalog assets, workflow management system, data framework, tools enabling user collaboration. In contrast, notebook like Jupyter allow researchers to rapidly prototype scientific code share their experiments online...
Digital colour-infrared (CIR) aerial photographs, which have been collected routinely in many parts of the world, are an invaluable data source for monitoring and assessment forest resources. Yet, potential these automated individual tree species mapping remains largely unexplored. One way to maximize usefulness digital CIR photographs is integrate them with modern complementary remote sensing technologies such as light detection ranging (LiDAR) system 3D segmentation algorithms. In this...
Quantifying ecosystem structure is of key importance for ecology, conservation, restoration, and biodiversity monitoring because the diversity, geographic distribution abundance animals, plants other organisms tightly linked to physical vegetation associated microclimates. Light Detection And Ranging (LiDAR) — an active remote sensing technique can provide detailed high resolution information on laser pulse emitted from sensor its subsequent return signal (leaves, branches, stems) delivers...
Mapping a specific tree species at individual level across landscapes using remote sensing is challenging, especially in forests where co-occurring exhibit similar characteristics. In Central European mixed forests, silver fir and Norway spruce have been identified as pair of coniferous with spectral structural characteristics, typically leading to major misclassification error mapping studies. Here, we aimed accurately map trees spruce-dominated natural forest the Bavarian Forest National...
Abstract In a recent perspective (Diversity and Distributions, 29, 39–50), ‘10 variables’ were proposed to measure vegetation structure from airborne laser scanning (ALS) for assessing species distributions habitat suitability. We worry about this list because the variables predominantly represent variation in height, vertical variability of biomass is insufficiently captured, cover are ill‐defined or not ecosystem agnostic. urge better defined, more comprehensive balanced list, which...
The third Dutch national airborne laser scanning flight campaign (AHN3, Actueel Hoogtebestand Nederland) conducted between 2014 and 2019 during the leaf-off season (October-April) across whole Netherlands provides a free open-access, country-wide dataset with ∼700 billion points point density of ∼10(-20) points/m2. AHN3 cloud was obtained Light Detection And Ranging (LiDAR) technology contains for each x, y, z coordinates additional characteristics (e.g. return number, intensity value, scan...
Abstract Literate computing environments, such as the Jupyter (i.e., Notebooks, JupyterLab, and JupyterHub), have been widely used in scientific studies; they allow users to interactively develop code, test algorithms, describe narratives of experiments an integrated document. To scale up analyses, many implemented environment architectures encapsulate whole notebooks reproducible units autoscale them on dedicated remote infrastructures (e.g., highperformance cloud environments). The...
National and regional data products of the ecosystem structure derived from airborne laser scanning (ALS) surveys with Light Detection And Ranging (LiDAR) technology are essential for ecology, biodiversity, monitoring. However, noises like powerlines often remain, hindering accurate measurement 3D structures LiDAR. Currently, there is a lack studies assessing powerline noise removal in context generating ALS point clouds. Here, we assessed (1) performance accuracy, (2) effectiveness, (3)...
Abstract. Recent years have seen a rapid surge in the use of Light Detection and Ranging (LiDAR) technology for characterizing structure ecosystems. Even though repeated airborne laser scanning (ALS) surveys are increasingly available across several European countries, only few studies so far derived data products ecosystem at national scale, possibly due to lack free open source tools computational challenges involved handling large volumes data. Nevertheless, high-resolution generated from...
Quantifying ecosystem structure is of great importance for forest management, ecology, biodiversity monitoring, and climate change modeling. Advances in remote sensing — specifically Light Detection And Ranging (LiDAR) have enabled the mapping vegetation with unprecedented detail. However, considerable effort advanced technical skills are required researchers to process massive amounts LiDAR data, giving challenges handling big data high computational costs. Different requirements...
The cover image is based on the Research Article Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment by Zhiming Zhao et al., https://doi.org/10.1002/spe.3098.