Novel approaches in tropical forests mapping and monitoring-time for operationalization

For more than three decades, the remote sensing scientific community has successfully generated predictive models of tropical forest attributes and ecological processes at the leaf, canopy, patch and landscape scale by linking field-measured data to remotely sensed spectral values, as well as other variables derived from remotely sensed data. The main interest of these applications is to help describe ecological and functional patterns occurring at larger geographic scales with sufficient accuracy and precision and enable scientists to better understand ecological processes, such as the relationship between atmospheric fluxes, plant structural and ecophysiological traits, soil attributes, anthropogenic use, species occurrence and animal movement. However, as the earth’s environment suffers from ever-increasing human use and abuse, detecting spatiotemporal changes in these variables has become a necessary decision-making tool in conservation action and natural resources’ management. Moving from modeling into the study of soil, plants, wildlife and socioecological processes using remotely sensed data requires the extrapolation of single time-step models to its application on a time series of data with the same expected accuracy. The challenges in this matter are not trivial, since changes in soil moisture conditions, cloud contamination, canopy and leaf-level geometry and physiology can affect the strength of the proposed models. In this context, the term ‘Operationalization’ refers to migration from single time-step models to time series but also refers to the design and implementation of user-friendly tools to increase the efficacy of communicating spatiotemporal trends to the users.

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Main Authors: Carlos Portillo-Quintero, JOSE LUIS HERNANDEZ STEFANONI, Gabriela Reyes Palomeque, Mukti Ram Subedi
Format: info:eu-repo/semantics/article biblioteca
Language:eng
Subjects:info:eu-repo/classification/Autores/TROPICAL FORESTS, info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY, info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY, info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS, info:eu-repo/classification/Autores/DATA FUSION, info:eu-repo/classification/Autores/INTEGRATION, info:eu-repo/classification/Autores/MONITORING, info:eu-repo/classification/cti/2, info:eu-repo/classification/cti/24, info:eu-repo/classification/cti/2417, info:eu-repo/classification/cti/241713,
Online Access:http://cicy.repositorioinstitucional.mx/jspui/handle/1003/2829
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spelling dig-cicy-1003-28292023-10-30T17:21:19Z Novel approaches in tropical forests mapping and monitoring-time for operationalization Carlos Portillo-Quintero JOSE LUIS HERNANDEZ STEFANONI Gabriela Reyes Palomeque Mukti Ram Subedi 2022 info:eu-repo/semantics/article For more than three decades, the remote sensing scientific community has successfully generated predictive models of tropical forest attributes and ecological processes at the leaf, canopy, patch and landscape scale by linking field-measured data to remotely sensed spectral values, as well as other variables derived from remotely sensed data. The main interest of these applications is to help describe ecological and functional patterns occurring at larger geographic scales with sufficient accuracy and precision and enable scientists to better understand ecological processes, such as the relationship between atmospheric fluxes, plant structural and ecophysiological traits, soil attributes, anthropogenic use, species occurrence and animal movement. However, as the earth’s environment suffers from ever-increasing human use and abuse, detecting spatiotemporal changes in these variables has become a necessary decision-making tool in conservation action and natural resources’ management. Moving from modeling into the study of soil, plants, wildlife and socioecological processes using remotely sensed data requires the extrapolation of single time-step models to its application on a time series of data with the same expected accuracy. The challenges in this matter are not trivial, since changes in soil moisture conditions, cloud contamination, canopy and leaf-level geometry and physiology can affect the strength of the proposed models. In this context, the term ‘Operationalization’ refers to migration from single time-step models to time series but also refers to the design and implementation of user-friendly tools to increase the efficacy of communicating spatiotemporal trends to the users. info:eu-repo/classification/Autores/TROPICAL FORESTS info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS info:eu-repo/classification/Autores/DATA FUSION info:eu-repo/classification/Autores/INTEGRATION info:eu-repo/classification/Autores/MONITORING info:eu-repo/classification/cti/2 info:eu-repo/classification/cti/24 info:eu-repo/classification/cti/2417 info:eu-repo/classification/cti/241713 info:eu-repo/classification/cti/241713 Remote Sensing, 14(20), 5068, 2022. http://cicy.repositorioinstitucional.mx/jspui/handle/1003/2829 info:eu-repo/semantics/datasetDOI/https://doi.org/10.3390/rs14205068 info:eu-repo/semantics/openAccess eng citation:Portillo-Quintero, C.; Hernández-Stefanoni, J.L.; Reyes-Palomeque, G.; Subedi, M.R. Novel approaches in tropical forests mapping and monitoring-time for operationalization. Remote Sens. 2022, 14, 5068. https://doi.org/10.3390/rs14205068 http://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/publishedVersion application/pdf
institution CICY
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country México
countrycode MX
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region America del Norte
libraryname Biblioteca del CICY
language eng
topic info:eu-repo/classification/Autores/TROPICAL FORESTS
info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY
info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY
info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS
info:eu-repo/classification/Autores/DATA FUSION
info:eu-repo/classification/Autores/INTEGRATION
info:eu-repo/classification/Autores/MONITORING
info:eu-repo/classification/cti/2
info:eu-repo/classification/cti/24
info:eu-repo/classification/cti/2417
info:eu-repo/classification/cti/241713
info:eu-repo/classification/cti/241713
info:eu-repo/classification/Autores/TROPICAL FORESTS
info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY
info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY
info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS
info:eu-repo/classification/Autores/DATA FUSION
info:eu-repo/classification/Autores/INTEGRATION
info:eu-repo/classification/Autores/MONITORING
info:eu-repo/classification/cti/2
info:eu-repo/classification/cti/24
info:eu-repo/classification/cti/2417
info:eu-repo/classification/cti/241713
info:eu-repo/classification/cti/241713
spellingShingle info:eu-repo/classification/Autores/TROPICAL FORESTS
info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY
info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY
info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS
info:eu-repo/classification/Autores/DATA FUSION
info:eu-repo/classification/Autores/INTEGRATION
info:eu-repo/classification/Autores/MONITORING
info:eu-repo/classification/cti/2
info:eu-repo/classification/cti/24
info:eu-repo/classification/cti/2417
info:eu-repo/classification/cti/241713
info:eu-repo/classification/cti/241713
info:eu-repo/classification/Autores/TROPICAL FORESTS
info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY
info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY
info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS
info:eu-repo/classification/Autores/DATA FUSION
info:eu-repo/classification/Autores/INTEGRATION
info:eu-repo/classification/Autores/MONITORING
info:eu-repo/classification/cti/2
info:eu-repo/classification/cti/24
info:eu-repo/classification/cti/2417
info:eu-repo/classification/cti/241713
info:eu-repo/classification/cti/241713
Carlos Portillo-Quintero
JOSE LUIS HERNANDEZ STEFANONI
Gabriela Reyes Palomeque
Mukti Ram Subedi
Novel approaches in tropical forests mapping and monitoring-time for operationalization
description For more than three decades, the remote sensing scientific community has successfully generated predictive models of tropical forest attributes and ecological processes at the leaf, canopy, patch and landscape scale by linking field-measured data to remotely sensed spectral values, as well as other variables derived from remotely sensed data. The main interest of these applications is to help describe ecological and functional patterns occurring at larger geographic scales with sufficient accuracy and precision and enable scientists to better understand ecological processes, such as the relationship between atmospheric fluxes, plant structural and ecophysiological traits, soil attributes, anthropogenic use, species occurrence and animal movement. However, as the earth’s environment suffers from ever-increasing human use and abuse, detecting spatiotemporal changes in these variables has become a necessary decision-making tool in conservation action and natural resources’ management. Moving from modeling into the study of soil, plants, wildlife and socioecological processes using remotely sensed data requires the extrapolation of single time-step models to its application on a time series of data with the same expected accuracy. The challenges in this matter are not trivial, since changes in soil moisture conditions, cloud contamination, canopy and leaf-level geometry and physiology can affect the strength of the proposed models. In this context, the term ‘Operationalization’ refers to migration from single time-step models to time series but also refers to the design and implementation of user-friendly tools to increase the efficacy of communicating spatiotemporal trends to the users.
format info:eu-repo/semantics/article
topic_facet info:eu-repo/classification/Autores/TROPICAL FORESTS
info:eu-repo/classification/Autores/FUNCTIONAL DIVERSITY
info:eu-repo/classification/Autores/STRUCTURAL DIVERSITY
info:eu-repo/classification/Autores/VEGETATION STRUCTURE AND BIOMASS
info:eu-repo/classification/Autores/DATA FUSION
info:eu-repo/classification/Autores/INTEGRATION
info:eu-repo/classification/Autores/MONITORING
info:eu-repo/classification/cti/2
info:eu-repo/classification/cti/24
info:eu-repo/classification/cti/2417
info:eu-repo/classification/cti/241713
info:eu-repo/classification/cti/241713
author Carlos Portillo-Quintero
JOSE LUIS HERNANDEZ STEFANONI
Gabriela Reyes Palomeque
Mukti Ram Subedi
author_facet Carlos Portillo-Quintero
JOSE LUIS HERNANDEZ STEFANONI
Gabriela Reyes Palomeque
Mukti Ram Subedi
author_sort Carlos Portillo-Quintero
title Novel approaches in tropical forests mapping and monitoring-time for operationalization
title_short Novel approaches in tropical forests mapping and monitoring-time for operationalization
title_full Novel approaches in tropical forests mapping and monitoring-time for operationalization
title_fullStr Novel approaches in tropical forests mapping and monitoring-time for operationalization
title_full_unstemmed Novel approaches in tropical forests mapping and monitoring-time for operationalization
title_sort novel approaches in tropical forests mapping and monitoring-time for operationalization
url http://cicy.repositorioinstitucional.mx/jspui/handle/1003/2829
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AT joseluishernandezstefanoni novelapproachesintropicalforestsmappingandmonitoringtimeforoperationalization
AT gabrielareyespalomeque novelapproachesintropicalforestsmappingandmonitoringtimeforoperationalization
AT muktiramsubedi novelapproachesintropicalforestsmappingandmonitoringtimeforoperationalization
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