Search results for "Leaf area index"
showing 10 items of 105 documents
Crop and irrigation water management using high resolution remote sensing and agrohydrological models
2006
A combined agrohydrological and remote sensing approach, called SIMODIS (Simulation and Management of On‐Demand Irrigation Systems) (D’Urso, 2001), has been used in a Sicilian test area to simulate the operation of on‐demand irrigation system. In SIMODIS the spatial distribution of crop factor, Kc, is directly calculated from canopy variables r (albedo), LAI (Leaf Area Index) and hc (crop height) derived from satellite‐based canopy spectral reflectance. Coupling these canopy variables with a specific data set of soil properties, the SIMODIS procedure was setup to simulate, in a distributed way, the water balance and, therefore, the irrigation deliveries for a set of 136 grape fields. For th…
Estimation of winter leaf area index and sky view fraction for snow modelling in boreal coniferous forests: consequences on snow mass and energy bala…
2012
Abstract in Undetermined Leaf area index (LAI) and canopy coverage are important parameters when modelling snow process in coniferous forests, controlling interception and transmitting radiation. Estimates of LAI and sky view factor show large variability depending on the estimation method used, and it is not clear how this is reflected in the calculated snow processes beneath the canopy. In this study, the winter LAI and sky view fraction were estimated using different optical and biomass-based approximations in several boreal coniferous forest stands in Fennoscandia with different stand density, age and site latitude. The biomass-based estimate of LAI derived from forest inventory data wa…
Multi-Season Phenology Mapping of Nile Delta Croplands Using Time Series of Sentinel-2 and Landsat 8 Green LAI
2022
Space-based cropland phenology monitoring substantially assists agricultural managing practices and plays an important role in crop yield predictions. Multitemporal satellite observations allow analyzing vegetation seasonal dynamics over large areas by using vegetation indices or by deriving biophysical variables. The Nile Delta represents about half of all agricultural lands of Egypt. In this region, intensifying farming systems are predominant and multi-cropping rotations schemes are increasing, requiring a high temporal and spatial resolution monitoring for capturing successive crop growth cycles. This study presents a workflow for cropland phenology characterization and mapping based on…
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery
2022
Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop’s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learni…
Assessment of workflow feature selection on forest LAI prediction with sentinel-2A MSI, landsat 7 ETM+ and Landsat 8 OLI
2020
The European Space Agency (ESA)’s Sentinel-2A (S2A) mission is providing time series that allow the characterisation of dynamic vegetation, especially when combined with the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions. Hybrid retrieval workflows combining non-parametric Machine Learning Regression Algorithms (MLRAs) and vegetation Radiative Transfer Models (RTMs) were proposed as fast and accurate methods to infer biophysical parameters such as Leaf Area Index (LAI) from these data streams. However, the exact design of optimal retrieval workflows is rarely discussed. In this study, the impact of…
FluorMODgui V3.0 : a graphic user interface for the spectral simulation of leaf and canopy chlorophyll fluorescence
2006
The FluorMODgui Graphic User Interface (GUI) software package developed within the frame of the FluorMOD project Development of a Vegetation Fluorescence Canopy Model is presented in this manuscript. The FluorMOD project was launched in 2002 by the European Space Agency (ESA) to advance the science of vegetation fluorescence simulation through the development and integration of leaf and canopy fluorescence models based on physical methods. The design of airborne or space missions dedicated to the measurement of solar-induced chlorophyll fluorescence using remote-sensing instruments require physical methods for quantitative feasibility analysis and sensor specification studies. The FluorMODg…
Use of Guided Regularized Random Forest for Biophysical Parameter Retrieval
2018
This paper introduces a feature selection method based on random forest -the Guided Regularized Random Forest (GRRF)- which can be used in classification and regression tasks. The method is based on the regularization of the information gain in the random forest nodes to obtain a subset of relevant and non-redundant features. The proposed method is used as a preliminary step In the process of retrieving biophysical parameters from a hyperspectral image. Preliminary experiments show that we can reduce the RMSE of the retrievals by around 7% for the Leaf Area Index and around 8% for the fraction of vegetation cover when compared to the results using random forest features.
Optimizing LUT-Based RTM Inversion for Semiautomatic Mapping of Crop Biophysical Parameters from Sentinel-2 and -3 Data: Role of Cost Functions
2014
Inversion of radiative transfer models (RTM) using a lookup-table (LUT) approach against satellite reflectance data can lead to concurrent retrievals of biophysical parameters such as leaf chlorophyll content (Chl) and leaf area index (LAI), but optimization strategies are not consolidated yet. ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity of old generation satellite sensors by providing superspectral images of high spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust, accurate, and operational retrieval methods. For three simulated Sentinel settings (S2-10 m: 4 bands, S2-20 m: 8 bands an…
Retrieving leaf area index from multi-angular airborne data
2009
This work is aimed to demonstrate the feasibility of a methodology for retrieving bio-geophysical variables whilst at the same time fully accounting for additional information on directional anisotropy. A model-based approach has been developed to deconvolve the angular reflectance into single landcovers reflectances, attempting to solve the inconsistencies of 1D models and linear mixture approaches. The model combines the geometric optics of large scale canopy structure with principles of radiative transfer for volume scattering within individual crowns. The reliability of the model approach to retrieve LAI has been demonstrated using data from DAISEX- 99 campaign at Barrax, Spain. Airborn…
Sensitivity analysis on the relationship between vegetation growth and multi-polarized radar data
2009
Spatially distributed soil moisture is required for watershed applications such as drought and flood prediction, crop irrigation scheduling, etc. In particular, an accurate assessment of the spatial and temporal variation of soil moisture is necessary to improve the predictive capability of runoff models, and for improving and validating hydrological processes forecasting. In recent years, several models have been developed in order to retrieve soil moisture using RADAR data. However, these models need precise prior knowledge about surface roughness. Within this framework, the present research aims to investigate the capabilities of multi polarimetric RADAR images to overcome the use of in …