Algorithms for estimating green leaf area index in C3 and C4 crops for MODIS, Landsat TM/ETM+, MERIS, Sentinel MSI/OLCI, and Venμs sensors
نویسندگان
چکیده
Algorithms for estimating green leaf area index in C3 and C4 crops for MODIS, Landsat TM/ETM+, MERIS, Sentinel MSI/OLCI, and Venμs sensors Anthony L. Nguy-Robertson & Anatoly A. Gitelson a Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska–Lincoln, Lincoln, Nebraska, USA b Faculty of Civil and Environmental Engineering, Israel Institute of Technology (Technion), Haifa, Israel Published online: 28 Apr 2015.
منابع مشابه
Toward Generic Models for Green LAI Estimation in Maize and Soybean: Satellite Observations
Informative spectral bands for green leaf area index (LAI) estimation in two crops were identified and generic models for soybean and maize were developed and validated using spectral data taken at close range. The objective of this paper was to test developed models using Aqua and Terra MODIS, Landsat TM and ETM+, ENVISAT MERIS surface reflectance products, and simulated data of the recently-l...
متن کاملComparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations
We analyzed 27 established and new simple and therefore perhaps portable satellite phycocyanin pigment reflectance algorithms for estimating cyanobacterial values in a temperate 8.9 km2 reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense coincident water surface observations collected from 44 sites within 1 h of image acquisition. The algorithms were adapted to...
متن کاملHyperspectral versus multispectral data for estimating leaf area index in four different biomes
Motivated by the increasing importance of hyperspectral remote sensing data, this study sought to determine whether current-generation narrow-band hyperspectral remote sensing data could better track vegetation leaf area index (LAI) than traditional broad-band multispectral data. The study takes advantage of a unique dataset, wherein field measurements of LAI were acquired at the same general t...
متن کاملRadiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacy
The use of Pseudoinvariant Areas (PIA) makes it possible to carry out a reasonably robust and automatic radiometric correction for long time series of remote sensing imagery, as shown in previous studies for large data sets of Landsat MSS, TM, and ETM+ imagery. In addition, they can be employed to obtain more coherence among remote sensing data from different sensors. The present work validates...
متن کاملClassification of C3 and C4 Vegetation Types Using MODIS and ETM+ Blended High Spatio-Temporal Resolution Data
The distribution of C3 and C4 vegetation plays an important role in the global carbon cycle and climate change. Knowledge of the distribution of C3 and C4 vegetation at a high spatial resolution over local or regional scales helps us to understand their ecological functions and climate dependencies. In this study, we classified C3 and C4 vegetation at a high resolution for spatially heterogeneo...
متن کامل