0000000000213306
AUTHOR
Eric Vermote
Evaluation of the MODIS Albedo product over a heterogeneous agricultural area
In this article, the Moderate Resolution Imaging Spectroradiometer MODIS Bidirectional Reflectance Distribution Function BRDF/Albedo product MCD43 is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction EODIX project campaign, which was developed in Barrax Spain in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal RTLSR which corresponds to the MODIS BRDF algorithm and the RossThick-Maignan-LiSparse-Reciprocal RTLSR-HS, were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner AHS sensor. During the campaign, airborne im…
Analysis of directional effects on atmospheric correction
Abstract Atmospheric correction in the Visible and Near Infrared (VNIR) spectral range of remotely sensed data is significantly simplified if we assume a Lambertian target. However, natural surfaces are anisotropic. Therefore, this assumption will introduce an error in surface directional reflectance estimates and consequently in the estimation of vegetation indexes such as the Normalized Difference Vegetation Index (NDVI) and the surface albedo retrieval. In this paper we evaluate the influence of directional effects on the atmospheric correction and its impact in the NDVI and albedo estimation. First, we derived the NDVI and surface albedo from data corrected assuming a Lambertian surface…
The ARYA crop yield forecasting algorithm: Application to the main wheat exporting countries
Abstract Wheat is the most important commodity traded in the international food market. Thus, accurate and timely information on wheat production can help mitigate food price fluctuations. Within the existing operational regional and global scale agricultural monitoring systems that provide information on global crop yield and area forecasts, there are still fundamental gaps: #1. Lack of quantitative Earth Observation (EO) derived crop information, #2. Lack of global but detailed (national or subnational level) and timely crop production forecasts and #3. Lack of information on forecast uncertainties. In this study we present the Agriculture Remotely-sensed Yield Algorithm (ARYA) an EO-base…
Forecasting Wheat Yield Using Remote Sensing: The ARYA Forecasting System
In this study we present a model to forecast wheat yield based on the evolution of the Difference Vegetation Index (DVI) and the Growing Degree Days (GDD), presented in Franch et al. (2015), but adapted to Franch et al. (2019) model. Additionally, we explore how the Land Surface Temperature (LST) can be included into the model and if this parameter adds any value to the model when combined with the optical information. This study is applied to MODIS data at 1km resolution to monitor the national and state level yield of winter wheat in the United States and Ukraine from 2001 to 2019.
Improving the timeliness of winter wheat production forecast in the United States of America, Ukraine and China using MODIS data and NCAR Growing Degree Day information
Abstract Wheat is the most important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop type masks. It is based on the relationship between the Nor…
Correction for aerosol effects on satellite sea surface temperature measurements
Estimation of Sea Surface Temperature (SST) from split- window algorithms for NOAA-AVHRR data can be determined with rms values of 0.7 K on a global basis. However, this figure is not compatible with the stringent accuracy of 0.3 K required by climate studies. Among the different sources of errors, the presence of tropospheric aerosols in the satellite field of view prevents the retrieval of accurate satellite SSTs. Still, the effect of aerosols on temperature measurements derived from remote sensing techniques has been traditionally overlooked. Very few studies have addressed the problem of giving split-window algorithms which incorporate aerosol correction, although retrieving algorithms …
Evaluation of the AVHRR surface reflectance long term data record between 1984 and 2011
Abstract The long-term data record (LTDR) from the Advanced Very High-Resolution Radiometer (AVHRR) provides daily surface reflectance with global coverage from the 1980s to present day, making it a unique source of information for the study of land surface properties and their long-term dynamics. Surface reflectance is a critical input for the generation of products such as vegetation indices, albedo, and land cover. Therefore, it is of utmost importance to quantify its uncertainties to better understand how they might propagate into downstream products. Due to the prolonged length of the surface reflectance LTDR and previous unavailability of a well calibrated reference, no comprehensive …
Quantification of LAI interannual anomalies by adjusting climatological patterns
International audience; Scaling variations and shifts in the timing of seasonal phenology are central features of global change research. In this study, we propose a novel climatology fitting approach to quantify inter-annual anomalies in LAI seasonality. A consistent archive of daily LAI estimates was first derived from historical AVHRR satellite data for the 1981-2000 period over a globally representative sample of sites. The climatology values were then computed by averaging multi-year LAI profiles, gap filling and smoothing to eliminate possible high temporal frequency residual artifacts. The inter-annual variations in LAI were finally quantified by scaling and shifting the seasonal cli…