Search results for "Red edge"

Intraspecific Differences in Spectral Reflectance Curves as Indicators of Reduced Vitality in High-Arctic Plants

2017

Remote sensing is a suitable candidate for monitoring rapid changes in Polar regions, offering high-resolution spectral, spatial and radiometric data. This paper focuses on the spectral properties of dominant plant species acquired during the first week of August 2015. Twenty-eight plots were selected, which could easily be identified in the field as well as on RapidEye satellite imagery. Spectral measurements of individual species were acquired, and heavy metal contamination stress factors were measured contemporaneously. As a result, a unique spectral library of dominant plant species, heavy metal concentrations and damage ratios were achieved with an indication that species-specific chan…

Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content

2011

ESA’s upcoming satellite Sentinel-2 will provide Earth images of high spatial, spectral and temporal resolution and aims to ensure continuity for Landsat and SPOT observations. In comparison to the latter sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region, which are centered at 705, 740 and 783 nm. This study addresses the importance of these new bands for the retrieval and monitoring of two important biophysical parameters: green leaf area index (LAI) and chlorophyll content (Ch). With data from several ESA field campaigns over agricultural sites (SPARC, AgriSAR, CEFLES2) we have evaluated the efficacy of two empirical methods that specifically make use of the…

A red-edge spectral index for remote sensing estimation of green LAI over agroecosystems

2013

Abstract Leaf area index (LAI) is a key biophysical parameter for the monitoring of agroecosystems. Conventional two-band vegetation indices based on red and near-infrared relationships such as the normalized difference vegetation index (NDVI) are well known to suffer from saturation at moderate-to-high LAI values (3–5). To bypass this saturation effect, in this work a robust alternative has been proposed for the estimation of green LAI over a wide variety of crop types. By using data from European Space Agency (ESA) campaigns SPARC 2003 and 2004 (Barrax, Spain) experimental LAI values over 9 different crop types have been collected while at the same time spaceborne imagery have been acquir…

Prototyping Sentinel-2 green LAI and brown LAI products for cropland monitoring.

2022

Abstract For agricultural applications, identification of non-photosynthetic above-ground vegetation is of great interest as it contributes to assess harvest practices, detecting crop residues or drought events, as well as to better predict the carbon, water and nutrients uptake. While the mapping of green Leaf Area Index (LAI) is well established, current operational retrieval models are not calibrated for LAI estimation over senescent, brown vegetation. This not only leads to an underestimation of LAI when crops are ripening, but is also a missed monitoring opportunity. The high spatial and temporal resolution of Sentinel-2 (S2) satellites constellation offers the possibility to estimate …

Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques

2019

Sustainable management of orchard fields requires detailed information about the tree types, which is a main component of precision agriculture programs. To this end, hyperspectral imagery can play a major role in orchard tree species mapping. Efficient use of hyperspectral data in combination with field measurements requires the development of optimized band selection strategies to separate tree species. In this study, field spectroscopy (350 to 2500 nm) was performed through scanning 165 spectral leaf samples of dominant orchard tree species (almond, walnut, and grape) in Chaharmahal va Bakhtiyari province, Iran. Two multivariable methods were employed to identify the optimum wavelengths:…

Gaussian processes retrieval of leaf parameters from a multi-species reflectance, absorbance and fluorescence dataset.

2013

Abstract: Biochemical and structural leaf properties such as chlorophyll content (Chl), nitrogen content (N), leaf water content (LWC), and specific leaf area (SLA) have the benefit to be estimated through nondestructive spectral measurements. Current practices, however, mainly focus on a limited amount of wavelength bands while more information could be extracted from other wavelengths in the full range (400-2500 nm) spectrum. In this research, leaf characteristics were estimated from a field-based multi-species dataset, covering a wide range in leaf structures and Chl concentrations. The dataset contains leaves with extremely high Chl concentrations (>100 mu g cm(-2)), which are seldom es…

Estudio de bofedales en los Andes ecuatorianos a través de la comparación de imágenes Landsat-8 y Sentinel-2

2019

[EN] The objective of the present study was to compare the Landsat-8 and Sentinel-2 images to calculate the wetland´s extension, distribution and degree of conservation, in Reserva de Producción de Fauna Chinborazo (RPFCH) protected area located in the Andean region of Ecuador. This process was developed with in situ work in 16 wetlands, distributed in different conservation levels. The Landsat-8 and Sentinel-2 images were processed through a radiometric calibration (restoration of lost lines or píxels and correction of the stripe of the image) and an atmospheric correction (conversion of the digital levels to radiance values), to later calculate the Vegetation spectral indexes: NDVI, SAVI …

Feasibility of hyperspectral vegetation indices for the detection of chlorophyll concentration in three high Arctic plants: Salix polaris, Bistorta v…

2018

Remote sensing, which is based on a reflected electromagnetic spectrum, offers a wide range of research methods. It allows for the identification of plant properties, e.g., chlorophyll, but a registered signal not only comes from green parts but also from dry shoots, soil, and other objects located next to the plants. It is, thus, important to identify the most applicable remote-acquired indices for chlorophyll detection in polar regions, which play a primary role in global monitoring systems but consist of areas with high and low accessibility. This study focuses on an analysis of in situ-acquired hyperspectral properties, which was verified by simultaneously measuring the chlorophyll conc…

2021

Nitrogen (N) is one of the key nutrients supplied in agricultural production worldwide. Over-fertilization can have negative influences on the field and the regional level (e.g., agro-ecosystems). Remote sensing of the plant N of field crops presents a valuable tool for the monitoring of N flows in agro-ecosystems. Available data for validation of satellite-based remote sensing of N is scarce. Therefore, in this study, field spectrometer measurements were used to simulate data of the Sentinel-2 (S2) satellites developed for vegetation monitoring by the ESA. The prediction performance of normalized ratio indices (NRIs), random forest regression (RFR) and Gaussian processes regression (GPR) f…

Scenario-based discrimination of common grapevine varieties using in-field hyperspectral data in the western of Iran

2019

Abstract Field spectroscopy is an accurate, rapid and nondestructive technique for monitoring of agricultural plant characteristics. Among these, identification of grapevine varieties is one of the most important factors in viticulture and wine industry. This study evaluated the discriminatory ability of field hyperspectral data and statistical techniques in case of five common grapevine varieties in the western of Iran. A total of 3000 spectral samples were acquired at leaf and canopy levels. Then, in order to identify the best approach, two types of hyperspectral data (wavelengths from 350 to 2500 nm and 32 spectral indices), two data reduction methods (PLSR and ANOVA-PCA) and two classif…