Ovidiu Csillik

Ovidiu Csillik
California Institute of Technology | CIT · Jet Propulsion Laboratory

Dr

About

18
Publications
14,482
Reads
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1,789
Citations
Citations since 2016
15 Research Items
1730 Citations
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20162017201820192020202120220100200300400
20162017201820192020202120220100200300400
20162017201820192020202120220100200300400
Additional affiliations
February 2020 - present
Wageningen University & Research
Position
  • PostDoc Position
January 2019 - December 2019
Arizona State University
Position
  • PostDoc Position
August 2018 - January 2019
Carnegie Institution for Science
Position
  • PostDoc Position
Education
October 2015 - July 2018
University of Salzburg
Field of study
  • Geoinformatics
October 2011 - July 2013
West University of Timisoara
Field of study
  • Remote Sensing & GIS

Publications

Publications (18)
Article
Full-text available
Remote sensing is important to precision agriculture and the spatial resolution provided by Unmanned Aerial Vehicles (UAVs) is revolutionizing precision agriculture workflows for measurement crop condition and yields over the growing season, for identifying and monitoring weeds and other applications. Monitoring of individual trees for growth, frui...
Article
Full-text available
Tropical forests are crucial for mitigating climate change, but many forests continue to be driven from carbon sinks to sources through human activities. To support more sustainable forest uses, we need to measure and monitor carbon stocks and emissions at high spatial and temporal resolution. We developed the first large-scale very high-resolution...
Article
Full-text available
In the Peruvian Amazon, high biodiversity tropical forest is underlain by gold-enriched subsurface alluvium deposited from the Andes, which has generated a clash between short-term earnings for miners and long-term environmental damage. Tropical forests sequester important amounts of carbon, but deforestation and forest degradation continue to spre...
Article
Full-text available
Monitoring aboveground carbon stocks and fluxes from tropical deforestation and forest degradation is important for mitigating climate change and improving forest management. However, high temporal and spatial resolution analyses are rare. This study presents the most detailed tracking of aboveground carbon over time, with yearly, quarterly and mon...
Article
Full-text available
Spatially explicit monitoring of tropical forest aboveground carbon is an important prerequisite for better targeting and assessing forest conservation efforts and more transparent reporting of carbon losses. Here, we combine near-real-time forest disturbance alerts based on all-weather radar data with aboveground carbon stocks to provide carbon lo...
Preprint
Full-text available
Background: Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties in land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific land covers. In this stu...
Article
Full-text available
Crop type mapping is relevant to a wide range of food security applications. Supervised classification methods commonly generate these data from satellite image time-series. Yet, their successful implementation is hindered by the lack of training samples. Solutions like transfer learning, development of temporal-spectral signatures of the target cl...
Article
Full-text available
Monitoring tropical forests using spaceborne and airborne remote sensing capabilities is important for informing environmental policies and conservation actions. Developing large-scale machine learning estimation models of forest structure is instrumental in bridging the gap between retrospective analysis and near-real-time monitoring. However, mos...
Article
Full-text available
The increasing volume of remote sensing data with improved spatial and temporal resolutions generates unique opportunities for monitoring and mapping of crops. We compared multiple single-band and multi-band object-based time-constrained Dynamic Time Warping (DTW) classifications for crop mapping based on Sentinel-2 time series of vegetation indice...
Conference Paper
Full-text available
Attempts towards a global geomorphometric atlas have been done in the past when computational power was less evolved than nowadays. In this study, we present a possible way to create a global geomorphometric atlas by taking advantage of the Google Earth Engine (GEE) computational capabilities. To exemplify how accessible, efficient and fast GEE wor...
Article
Full-text available
Accurate and timely detection of weeds between and within crop rows in the early growth stage is considered one of the main challenges in site-specific weed management (SSWM). In this context, a robust and innovative automatic object-based image analysis (OBIA) algorithm was developed on Unmanned Aerial Vehicle (UAV) images to design early post-eme...
Article
Efficient methodologies for mapping croplands are an essential condition for the implementation of sustainable agricultural practices and for monitoring crops periodically. The increasing spatial and temporal resolution of globally available satellite images, such as those provided by Sentinel-2, creates new possibilities for generating accurate da...
Conference Paper
Full-text available
The increasing spatial and temporal resolution of Sentinel-2 data creates new premises for cropland mapping and monitoring at local, regional and global scale. This paper reports the results of a study dedicated to cropland mapping from Sentinel-2 time-series data using objects as spatial analysis units. The Sentinel-2 time-series data stack was au...
Article
Full-text available
Speed and accuracy are important factors when dealing with time-constraint events for disaster, risk, and crisis-management support. Object-based image analysis can be a time consuming task in extracting information from large images because most of the segmentation algorithms use the pixel-grid for the initial object representation. It would be mo...
Article
The strength of a population resides in the resilience of its individuals and is closely related to the stability of its habitat. Stream macroinvertebrates are sensitive to environmental changes concerning habitat stability, thus they require shelter to prevent drift during severe floods. We propose a novel approach to estimate the impact of flash-...
Article
Automated procedures are developed to alleviate long tails in frequency distributions of morphometric variables. They minimize the skewness of slope gradient frequency distributions, and modify the kurtosis of profile and plan curvature distributions towards that of the Gaussian (normal) model. Box-Cox (for slope) and arctangent (for curvature) tra...
Article
Full-text available
We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and...
Conference Paper
Full-text available
In this paper, we introduce an algorithm to delineate elementary forms on Digital Elevation Models (DEMs). Elementary forms are defined by constant values of fundamental morphometric properties and limited by discontinuities of these properties. A multiresolution segmentation technique was customized to partition the layers of altitude derivatives...

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