- -

Estimación de parámetros biofísicos de la vegetación en praderas y cultivos en Chile mediante fotografía digital hemisférica obtenidas por una cámara GoPro

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Estimación de parámetros biofísicos de la vegetación en praderas y cultivos en Chile mediante fotografía digital hemisférica obtenidas por una cámara GoPro

Mostrar el registro completo del ítem

Uribe, D.; Mattar, C.; Camacho, F. (2018). Estimación de parámetros biofísicos de la vegetación en praderas y cultivos en Chile mediante fotografía digital hemisférica obtenidas por una cámara GoPro. Revista de Teledetección. (52):1-15. https://doi.org/10.4995/raet.2018.9315

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/114889

Ficheros en el ítem

Metadatos del ítem

Título: Estimación de parámetros biofísicos de la vegetación en praderas y cultivos en Chile mediante fotografía digital hemisférica obtenidas por una cámara GoPro
Otro titulo: Estimation of vegetation biophysical parameters in grasslands and crops in Chile through hemispheric digital photography by a GoPro camera
Autor: Uribe, D. Mattar, C. Camacho, F.
Fecha difusión:
Resumen:
[EN] The estimation of the biophysical parameters of vegetation such as LAI (Leaf Area Index), FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) and FCOVER (Fraction of Green Vegetation) have many climatic, ...[+]


[ES] La estimación de los parámetros biofísicos de la vegetación como el LAI (Leaf Area Index, FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) y FCOVER (Fraction of Green Vegetation) tienen una gran cantidad ...[+]
Palabras clave: GoPro , Parámetros Biofísicos de la Vegetación , DHP , Vegetation Biophysical Parameters
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Revista de Teledetección. (issn: 1133-0953 ) (eissn: 1988-8740 )
DOI: 10.4995/raet.2018.9315
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/raet.2018.9315
Código del Proyecto:
info:eu-repo/grantAgreement/CONICYT//11130359/
Descripción: Revista oficial de la Asociación Española de Teledetección
Agradecimientos:
Los autores agradecen el financiamiento parcial del proyecto Conicyt – Fondecyt Iniciación 11130359 “Estimating the Surface soil moisture at regional scale by using a synergic optical-passive microwave approach and remote ...[+]
Tipo: Artículo

Localización


 

References

Baret, F., Camacho, F., Cernicharo, J., Lacaze, R., Weiss, M. 2013. GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment, 137, 310-329. https://doi.org/10.1016/j.rse.2012.12.027

Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Niño, F.,Weiss, M., Samain, O., Roujean, J.L., Leroy, M. 2007. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm. Remote Sensing of Environment, 110(3), 275-286. https://doi.org/10.1016/j.rse.2007.02.018

Baret, F., Weiss, M. 2018. Gio Global Land Component - Lot I "Operation of the Global Land Component" Algorithm Theoretical Basis Document, 1-41. [+]
Baret, F., Camacho, F., Cernicharo, J., Lacaze, R., Weiss, M. 2013. GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment, 137, 310-329. https://doi.org/10.1016/j.rse.2012.12.027

Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Niño, F.,Weiss, M., Samain, O., Roujean, J.L., Leroy, M. 2007. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm. Remote Sensing of Environment, 110(3), 275-286. https://doi.org/10.1016/j.rse.2007.02.018

Baret, F., Weiss, M. 2018. Gio Global Land Component - Lot I "Operation of the Global Land Component" Algorithm Theoretical Basis Document, 1-41.

Baret, F., Weiss, M., Allard, D., Garrigues, S., Leroy, M., Jeanjean, H., et al., 2005. VALERI: a network of sites and a methodology for the validation of medium spatial resolution land satellite products. Remote Sensing of Environment, 76(3), 36-39.

Baret, F., Weiss, M., Verger, A., Smets, B. 2016. Gio Global Land Component - ATBD. Bréda, N.J.J. 2003. Ground-based measurements of leaf area index: A review of methods, instruments and current controversies. Journal of Experimental Botany, 54(392), 2403-2417. https://doi.org/10.1093/jxb/erg263

Bréda, N.J.J. 2003. Ground-based measurements of leaf area index: A review of methods, instruments and current controversies. Journal of Experimental Botany, 54(392), 2403-2417. https://doi.org/10.1093/jxb/erg263

Casanova, M., Salazar, O., Seguel, O., Luzio, W. 2013. The Soils of Chile, Springer. https://doi.org/10.1007/978-94-007-5949-7

Cescatti, A. 2007. Indirect estimates of canopy gap fraction based on the linear conversion of hemispherical photographs. Methodology and comparison with standard thresholding techniques. Agricultural and Forest Meteorology, 143(1-2), 1-12. https://doi.org/10.1016/j.agrformet.2006.04.009

Chen, J.M., Black, T.A. 1992. Defining leaf area index for non-flat leaves. Plant, Cell & Environment, 15(4), 421-429. https://doi.org/10.1111/j.1365-3040.1992.tb00992.x

Confalonieri, R., Foi, M., Casa, R., Aquaro, S., Tona, E., Peterle, M., et al. 2013. Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods. Computers and Electronics in Agriculture, 96, 67- 74. https://doi.org/10.1016/j.compag.2013.04.019

De Bei, R., Fuentes, S., Gilliham, M., Tyerman, S., Edwards, E., Bianchini, N., Smith, J., Collins, C. 2016. Viticanopy: A free computer app to estimate canopy vigor and porosity for grapevine. Sensors, 16(4). https://doi.org/10.3390/s16040585

Demarez, V., Duthoit, S., Baret, F., Weiss, M., Dedieu, G. 2008. Estimation of leaf area and clumping indexes of crops with hemispherical photographs. Agricultural and Forest Meteorology, 148(4), 644-655. https://doi.org/10.1016/j.agrformet.2007.11.015

Fang, H., Liang, S., Hoogenboom, G. 2011. Integration of MODIS LAI and vegetation index products with the CSM-CERES-Maize model for corn yield estimation. International Journal of Remote Sensing, 32(4), 1039-1065. https://doi.org/10.1080/01431160903505310

Fournier, R.A., Landry, R., August, N.M., Fedosejevs, G., Gauthier, R.P. 1996. Modelling light obstruction in three conifer forests using hemispherical photography and fine tree architecture. Agricultural and Forest Meteorology, 82(1-4), 47-72. https://doi.org/10.1016/0168-1923(96)02345-3

Garrigues, S., Shabanov, N. V, Swanson, K., Morisette, J.T., Baret, F., Myneni, R.B. 2008. Intercomparison and sensitivity analysis of Leaf Area Index retrievals from LAI-2000, AccuPAR, and digital hemispherical photography over croplands. Agricultural and Forest Meteorology, 148(8-9), 1193-1209. https://doi.org/10.1016/j.agrformet.2008.02.014

Gower, S.T., Kucharik, C.J., Norman, J.M. 1999. Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems. Remote Sensing of Environment, 70(1), 29-51. https://doi.org/10.1016/S0034-4257(99)00056-5

Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., Baret, F. 2004. Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 121(1-2), 19- 35. https://doi.org/10.1016/j.agrformet.2003.08.027

Kross, A., McNairn, H., Lapen, D., Sunohara, M., Champagne, C. 2015. Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops. International Journal of Applied Earth Observation and Geoinformation, 34(1), 235-248. https://doi.org/10.1016/j.jag.2014.08.002

Lang, M., Kuusk, A., Mõttus, M., Rautiainen, M., Nilson, T. 2010. Canopy gap fraction estimation from digital hemispherical images using sky radiance models and a linear conversion method. Agricultural and Forest Meteorology, 150(1), 20-29. https://doi.org/10.1016/j.agrformet.2009.08.001

Latorre, C., Camacho, F., Mattar, C., Santamaría-Artigas, A., Leiva-Büchi, N., Lacaze, R. 2016. Obtención de mapas verdad-terreno de LAI, FAPAR y cobertura vegetal a partir de imágenes del satélite chileno FASat-C y medidas in-situ en la zona agrícola de Chimbarongo, Chile, para la validación de productos de satélite. Revista de Teledeteccion, 2016(47), 51- 64. https://doi.org/10.4995/raet.2016.5691

Li, W., Weiss, M., Waldner, F., Defourny, P., Demarez, V., Morin, D., Hagolle, O., Baret, F. 2015. A generic algorithm to estimate LAI, FAPAR and FCOVER variables from SPOT4_HRVIR and landsat sensors: Evaluation of the consistency and comparison with ground measurements. Remote Sensing, 7(11), 15494- 15516. https://doi.org/10.3390/rs71115494

López-Lozano, R., Baret, F., García de Cortázar-Atauri, I., Bertrand, N., Casterad, M.A. 2009. Optimal geometric configuration and algorithms for LAI indirect estimates under row canopies: The case of vineyards. Agricultural and Forest Meteorology, 149(8), 1307- 1316. https://doi.org/10.1016/j.agrformet.2009.03.001

Martínez, B., Camacho-de Coca, F., García-Haro, F. 2005a. Estimación de parámetros biofísicos de la cubierta vegetal a alta resolución a partir de medidas in-situ obtenidas en SPARC'03. XI Congreso Nacional de Teledetección, 21-23.

Martínez, B., García-haro, F., Camacho-de Coca, F. 2005b. Estimación de parámetros biofísicos de vegetación utilizando el método de la cámara hemisférica. Revista de Teledetección, 23, 13-26.

Mattar, C., Hernández, J., Santamaría-Artigas, A., Durán-Alarcón, C., Olivera-Guerra, L., Inzunza, M., Tapia, D., Escobar-lavín, E. 2014. A first in-flight absolute calibration of the Chilean Earth Observation Satellite. ISPRS Journal of Photogrammetry and Remote Sensing, 92, 16-25. https://doi.org/10.1016/j.isprsjprs.2014.02.017

Mougin, E., Demarez, V., Diawara, M., Hiernaux, P., Soumaguel, N., Berg, A. 2014. Estimation of LAI, fAPAR and fCover of Sahel rangelands (Gourma, Mali). Agricultural and Forest Meteorology, 198, 155- 167. https://doi.org/10.1016/j.agrformet.2014.08.006

Nestola, E., Sánchez-Zapero, J., Latorre, C., Mazzenga, F., Matteucci, G., Calfapietra, C., Camacho, F. 2017. Validation of PROBA-V GEOV1 and MODIS C5 & C6 fAPAR Products in a Deciduous Beech Forest Site in Italy. Remote Sensing, 9(2), 126. https://doi.org/10.3390/rs9020126

Olivera-Guerra, L., Mattar, C., Galleguillos, M. 2014. Estimation of real evapotranspiration and its variation in Mediterranean landscapes of central-southern Chile. International Journal of Applied Earth Observation and Geoinformation, 28(1), 160-169. https://doi.org/10.1016/j.jag.2013.11.012

Olivera-Guerra, L., Merlin, O., Mattar, C., Duran-Alarcon, C., Santamaria-Artigas, A., Stefan, V. 2015. Combining meteorological and lysimeter data to evaluate energy and water fluxes over a row crop for remote sensing applications. International Geoscience and Remote Sensing Symposium (IGARSS), 2015-Novem, 4649- 4651. https://doi.org/10.1109/IGARSS.2015.7326865

Paul M. Rich, 1990. Characterizing Plant Canopies with Hemispherical Photograph s. Remote Sensing Reviews, 5(November 2012), 37-41. https://doi.org/10.1080/02757259009532119

Rigon, J.P.G., Capuani, S., Fernandes, D.M., Guimarães, T.M. 2016. A novel method for the estimation of soybean chlorophyll content using a smartphone and image analysis. Photosynthetica, 54(4), 559-566. https://doi.org/10.1007/s11099-016-0214-x

Sarricolea, P., Herrera-Ossandon, M., MeseguerRuiz, Ó. 2017. Climatic regionalisation of continental Chile. Journal of Maps, 13(2), 66-73. https://doi.org/10.1080/17445647.2016.1259592

Sellers, P.J., Dickinson, R.E., Randall, D.A., Betts, A.K., Hall, F.G., Berry, J.A., et al. 1997. Modeling the Exchanges of Energy, Water, and Carbon between Continents and the Atmosphere. Science , 275(5299), 502-509. https://doi.org/10.1126/science.275.5299.502

Tarnavsky, E., Garrigues, S., Brown, M.E. 2008. Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products. Remote Sensing of Environment, 112(2), 535-549. https://doi.org/10.1016/j.rse.2007.05.008

Verger, A., Baret, F., Camacho, F. 2011. Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with CHRIS/PROBA observations. Remote Sensing of Environment, 115(2), 415-426. https://doi.org/10.1016/j.rse.2010.09.012

Weiss, M., Baret, F. 2016. Can Eye User Manual.

Weiss, M., Baret, F., Smith, G.J., Jonckheere, I., Coppin, P. 2004. Review of methods for in situ leaf area index (LAI) determination Part II. Estimation of LAI, errors and sampling. Agricultural and Forest Meteorology, 121(1-2), 37-53. https://doi.org/10.1016/j.agrformet.2003.08.001

Zheng, G., Moskal, L.MX009. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors. Sensors, 9(4), 2719-2745. https://doi.org/10.3390/s90402719

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem