Sergio Marconi

Sergio Marconi
University of Florida | UF · School of Forest Resources and Conservation

Doctor of Philosophy

About

55
Publications
11,872
Reads
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592
Citations
Introduction
My curiosity covers different aspects of global change ecology and resource management. The common divisor is the use of modeling techniques to explore and predict ecological processes. I'm mainly engrossed in biogeochemical and vegetation modeling, from individual to regional scale. I'm interested in climate related alterations on tree auto-ecology and phenology; in LULUCF and pathogens related disturbances on landscape to regional scale. How will these trade-offs impact landscape patterns?
Additional affiliations
August 2015 - August 2020
University of Florida
Position
  • PhD Student
April 2015 - present
Centro Euro-Mediterraneo sui Cambiamenti Climatici
Position
  • Post Grad fixed term researcher
Description
  • meta-analysis of the biophysical impacts of specific land use change directions on regional to global Precipitations and Temperatures (LUC4C)
December 2014 - present
Tuscia University
Position
  • Project related fixed term collaborator
Description
  • Screening and determination of the best framework to develope an ecohydrological model and assess vertical water dynamics among different ecosystems

Publications

Publications (55)
Preprint
p>Automated individual tree crown (ITC) delineation plays an important role in forest remote sensing. Accurate ITC delineation benefits biomass estimation, allometry estimation, and species classification among other forest related tasks, all of which are used to monitor forest health and make important decisions in forest management. In this paper...
Preprint
p>Automated individual tree crown (ITC) delineation plays an important role in forest remote sensing. Accurate ITC delineation benefits biomass estimation, allometry estimation, and species classification among other forest related tasks, all of which are used to monitor forest health and make important decisions in forest management. In this paper...
Preprint
Functional traits are influenced by phylogenetic constraints and environmental conditions, but previous large-scale studies modeled traits either as species weighted averages or directly from the environment, precluding analyses of the relative contributions of inter- and intraspecific variation across regions. We developed a joint model integratin...
Preprint
Full-text available
Advances in remote sensing imagery and computer vision applications unlock the potential for developing algorithms to classify individual trees from remote sensing at unprecedented scales. However, most approaches to date focus on site-specific applications and a small number of taxonomic groups. This limitation makes it hard to evaluate whether th...
Article
Full-text available
It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operatio...
Article
Full-text available
A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30‐yr horizon of the network. In contrast to NEON’s extensive use of automated instruments to collect environmental data, NEON’s biodiversity surveys are almost entirely conducted using traditional human‐centric field methods. We belie...
Article
Full-text available
Supervised methods for object delineation in remote sensing require labeled ground-truth data. Gathering sufficient high quality ground-truth data is difficult, especially when targets are of irregular shape or difficult to distinguish from background or neighboring objects. Tree crown delineation provides key information from remote sensing images...
Preprint
Full-text available
Delineating and classifying individual trees in remote sensing data is challenging. Many tree crown delineation methods have difficulty in closed-canopy forests and do not leverage multiple datasets. Methods to classify individual species are often accurate for common species, but perform poorly for less common species and when applied to new sites...
Article
Full-text available
Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is to associate sensor data into individual crowns. While dozens of crown detection algorithms have been proposed, their performance is typically not compared based on standard data or evaluation metrics. There is a need for a ben...
Preprint
Full-text available
Supervised methods for object delineation in remote sensing require labeled ground-truth data. Gathering sufficient high quality ground-truth data is difficult, especially when the targets are of irregular shape or difficult to distinguish from the background or neighboring objects. Tree crown delineation provides key information from remote sensin...
Preprint
Full-text available
Functional traits are central to how organisms perform and influence ecosystem function. Although phylogenetic constraints and environmental conditions are both known to affect trait distributions, data limitations have resulted in large scale studies modeling traits either as species weighted averages (ignoring intraspecific variation) or as a fun...
Article
Full-text available
Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote sensing techniques allow surveys of individual trees at unprec...
Article
Functional ecology has increasingly focused on describing ecological communities based on their traits (measurable features affecting individuals fitness and performance). Analyzing trait distributions within and among forests could significantly improve understanding of community composition and ecosystem function. Historically, data on trait dist...
Preprint
Full-text available
Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is designing individual tree segmentation algorithms to associate pixels into delineated tree crowns. While dozens of tree delineation algorithms have been proposed, their performance is typically not compared based on standard da...
Preprint
Full-text available
Forests provide essential biodiversity, ecosystem and economic services. Information on individual trees is important for understanding the state of forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote sensing techniques allow surveys of indi...
Article
Remote sensing of forested landscapes can transform the speed, scale, and cost of forest research. The delineation of individual trees in remote sensing images is an essential task in forest analysis. Here we introduce a new Python package, DeepForest, that detects individual trees in high resolution RGB imagery using deep learning. While deep lear...
Preprint
Full-text available
Functional ecology has increasingly focused on describing ecological communities based on their traits (measurable features affecting individuals fitness and performance). Analyzing trait distributions within and among forests could significantly improve understanding of community composition and ecosystem function. Historically, data on trait dist...
Preprint
Full-text available
1. Remote sensing of forested landscapes can transform the speed, scale, and cost of forest research. The delineation of individual trees in remote sensing images is an essential task in forest analysis. Here we introduce a new Python package, DeepForest, that detects individual trees in high resolution RGB imagery using deep learning. 2. While dee...
Article
Full-text available
Key message Bastin et al. 2019 use two flawed assumptions: 1) that the area suitable for restoration does not contain any carbon currently, and 2) that soil organic carbon (SOC) from increased canopy cover will accumulate quickly enough to mitigate anthropogenic carbon emissions. We re-evaluated the potential carbon storage worldwide using empirica...
Article
Full-text available
Tree crown detection is a fundamental task in remote sensing for forestry and ecosystem ecology. While many individual tree segmentation algorithms have been proposed, the development and testing of these algorithms is typically site specific, with few methods evaluated against data from multiple forest types simultaneously. This makes it difficult...
Preprint
Full-text available
One of the first beings affected by changes in the climate are trees, one of our most vital resources. In this study tree species interaction and the response to climate in different ecological environments is observed by applying a joint species distribution model to different ecological domains in the United States. Joint species distribution mod...
Preprint
Full-text available
Tree detection is a fundamental task in remote sensing for forestry and ecosystem ecology applications. While many individual tree segmentation algorithms have been proposed, the development and testing of these algorithms is typically site specific, with few methods evaluated against data from multiple forest types simultaneously. This makes it di...
Preprint
Full-text available
Key Message Bastin et al. 2019 used flawed assumptions in calculating the carbon storage of restored forests worldwide, resulting in a gross overestimate. Context Bastin et al. 2019 use two flawed assumptions: 1) that the area suitable for restoration does not contain any carbon currently, and 2) that soil organic carbon (SOC) from increased canop...
Article
Full-text available
Remote sensing can transform the speed, scale, and cost of biodiversity and forestry surveys. Data acquisition currently outpaces the ability to identify individual organisms in high resolution imagery. We outline an approach for identifying tree-crowns in RGB imagery while using a semi-supervised deep learning detection network. Individual crown d...
Article
Full-text available
Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to conve...
Preprint
Full-text available
Remote sensing can transform the speed, scale, and cost of biodiversity and forestry surveys. Data acquisition currently outpaces the ability to identify individual organisms in high resolution imagery. We outline an approach for identifying tree-crowns in true color, or red/green blue (RGB) imagery using a deep learning detection network. Individu...
Chapter
Full-text available
Understanding the dynamics of organic carbon mineralization is fundamental in forecasting biosphere to atmosphere net carbon ecosystem exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid process based model 3D-CMCC FEM where also heterotrophic respiration (R h ) is explicitly simulated. The aim was to quanti...
Preprint
Full-text available
Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to conve...
Preprint
Full-text available
Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification from remote sensing images. We ran a competition to help improve three tasks that are central to conve...
Article
Full-text available
Understanding the dynamics of organic carbon mineralization is fundamental in forecasting biosphere to atmosphere net carbon ecosystem exchange (NEE). With this perspective, we developed 3D‐CMCC‐PSM, a new version of the hybrid process based model 3D‐CMCC FEM where also heterotrophic respiration (R h ) is explicitly simulated. The aim was to qua...
Preprint
Full-text available
Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (Rh) is explicitly simulated. The aim was to quantify...
Preprint
Full-text available
Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (Rh) is explicitly simulated. The aim was to quantify...
Article
Full-text available
Anthropogenic land cover changes (LCC) affect regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. This change in surface energy budget may exacerbate or counteract biogeochemical greenhouse gas effects of LCC, with a large body of emerging assessments being p...
Preprint
Full-text available
Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (Rh) is explicitly simulated. The aim was to quantify...
Poster
It is widely accepted that tree phenology has an important role in driving the uncertainty of biogeochemical cycles models. Nevertheless, seasonality in phenology is driven by processes still obscure in some extent, and difficult to represent. The timing of periodic life cycle events, leaf development, and senescence is a good example. In this work...
Article
Full-text available
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary production (GPP), against eddy covariance GPP data for ten FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration schemes, was implemented in...
Article
Full-text available
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration schemes, was implemented i...
Article
Full-text available
Degradation, a reduction of the ecosystem’s capacity to supply goods and services, is widespread in tropical forests and mainly caused by human disturbance. To maintain the full range of forest ecosystem services and support the development of effective conservation policies, we must understand the overall impact of degradation on different forest...
Preprint
Full-text available
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary production (GPP), against eddy covariance GPP data for ten FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration 5 schemes, was implemented...
Poster
Full-text available
The two main processes involved in ecosystems carbon balance are gross primary production (GPP) and respiration. Ecosystem respiration (Reco) is determined by heterotrophic (RH) and autotrophic (RA) respira- tion, the former driven by microbial decomposition of soil organic matter (SOM), the latter by growth and maintenance of plant tissues. By the...
Thesis
Full-text available
The two main processes involved in forest ecosystems carbon balance are photosynthesis (GPP) and respiration. Ecosystem respiration (Reco) is determined by heterotrophic and autotrophic respiration, the former driven by microbial decomposition of soil organic matter (SOM), the latter by growth and maintenance of plant tissues. By differencing photo...
Poster
Full-text available
3D-CMCC-Forest Ecosystem Model is a process based model formerly developed for complex forest ecosystems to estimate growth, water and carbon cycles, phenology and competition processes on a daily/monthly time scale. The Model integrates some characteristics of the functional-structural tree models with the robustness of the light use efficiency ap...
Thesis
Full-text available
The two main processes involved in forest ecosystems carbon balance are photosynthesis (GPP) and respiration. Ecosystem respiration (Reco) is determined by heterotrophic and autotrophic respiration, the former driven by microbial decomposition of soil organic matter (SOM), the latter by growth and maintenance of plant tissues. By differencing photo...

Questions

Question (1)
Question
I would like to explore the potential of NEON sites hyper spectral data for classifying individual trees on a species level. The following step would be quantify intra-species variability in fundamental plant traits (i.e. leaves specific traits?)
Can you gently point me interesting books, chapters or papers concerning species recognition for North America plants using hyper spectral sensors?
Thanks!

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