Journal ArticleDOI
Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3
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TLDR
Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20 m and linear estimators of canopy chlorophyll and N content.About:
This article is published in International Journal of Applied Earth Observation and Geoinformation.The article was published on 2013-08-01. It has received 490 citations till now. The article focuses on the topics: Spectral bands & Red edge.read more
Citations
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Journal ArticleDOI
Estimating Pasture Biomass Using Sentinel-2 Imagery and Machine Learning
TL;DR: In this article, a sequential neural network model was developed by integrating Sentinel-2 time-series data, weekly field biomass observations and daily climate variables from 2017 to 2018 to estimate aboveground biomass at the paddock level in five dairy farms across northern Tasmania, Australia.
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Super-resolution enhancement of Sentinel-2 image for retrieving LAI and chlorophyll content of summer corn
Mingzheng Zhang,Wei Su,Yuting Fu,Dehai Zhu,Jing-Hao Xue,Jianxi Huang,Wei Wang,Jiayu Wu,Chan Yao +8 more
TL;DR: In this article, the spatial resolution of Sentinel-2 images was enhanced to 10m from original 20m, and the estimation accuracy was over 97% for pixels planted by summer corn, while the accuracy of summer corn canopy leaf area index (LAI), leaves chlorophyll content (LCC) and canopy chlorophyLL content (CCC) were retrieved by the linear and physical models for the corn growth monitoring purpose.
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Testing the capabilities of the new WorldView-3 space-borne sensor’s red-edge spectral band in discriminating and mapping complex grassland management treatments
TL;DR: In this article, the authors test the capabilities of the WorldView-3 satellite data derivatives in characterizing grasslands administered with different rangeland management treatments (i.e. mowing, grazing, burning, fertilizer application, and control: no-treatment), using discriminant analysis.
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Retrieval of Evapotranspiration from Sentinel-2: Comparison of Vegetation Indices, Semi-Empirical Models and SNAP Biophysical Processor Approach
Nieves Pasqualotto,Guido D'Urso,Salvatore Falanga Bolognesi,Oscar Rosario Belfiore,Shari Van Wittenberghe,Jesús Delegido,Alejandro Pezzola,Cristina Winschel,Jose Moreno +8 more
TL;DR: A comparative analysis of empirical (vegetation indices), semi-empirical (CLAIR model with fixed and calibrated extinction coefficient) and artificial neural network S2 products derived from the Sentinel Application Platform Software (SNAP) biophysical processor (ANN S2 Products) approaches indicates the good validation of ANN S2 LAI and CCC products and their further suitability for the implementation in evapotranspiration retrieval of agricultural areas.
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Unsupervised Sub-Pixel Water Body Mapping with Sentinel-3 OLCI Image
TL;DR: An unsupervised sub-pixel water body mapping (USWBM) method was proposed particularly for the Sentinel-3 OLCI image, and it aims to produce a finer spatial resolution water body map from the multispectral image.
References
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Journal ArticleDOI
Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
Daniel A. Sims,John A. Gamon +1 more
TL;DR: Developing spectral indices for prediction of leaf pigment content that are relatively insensitive to species and leaf structure variation and thus could be applied in larger scale remote-sensing studies without extensive calibration are developed.
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Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services
Matthias Drusch,U. Del Bello,S. Carlier,O. Colin,V. Fernandez,F. Gascon,Bianca Hoersch,Claudia Isola,P. Laberinti,P. Martimort,Aime Meygret,Francois Spoto,O. Sy,Franco Marchese,Pier Bargellini +14 more
TL;DR: An overview of the GMES Sentinel-2 mission including a technical system concept overview, image quality, Level 1 data processing and operational applications is provided.
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Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance
TL;DR: In this paper, a wide range of leaf chlorophyll levels were established in field-grown corn (Zea mays L.) with the application of 8 N levels: 0, 12.5%, 25, 50, 75, 100, 125, and 150% of the recommended rate.
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Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves
TL;DR: Spectral reflectance of maple, chestnut, wild vine and beech leaves in a wide range of pigment content and composition was investigated and it was shown that reciprocal reflectance (R lambda)-1 in the spectral range lambda related closely to the total chlorophyll content in leaves of all species.
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Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture
D. Haboudane,John R. Miller,John R. Miller,Nicolas Tremblay,Pablo J. Zarco-Tejada,Louise Dextraze +5 more
TL;DR: In this paper, a combined modeling and indices-based approach is presented to predict the crop chlorophyll content from remote sensing data while minimizing LAI (vegetation parameter) influence and underlying soil background effects.