Search results for "modis"
showing 10 items of 55 documents
Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud
2020
Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…
Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values
2016
Land Surface Temperature (LST) as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same obser…
A multisensor fusion approach to improve LAI time series
2011
International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …
Monitoring elevation variations in leaf phenology of deciduous broadleaf forests from SPOT/VEGETATION time-series
2011
International audience; In mountain forest ecosystems where elevation gradients are prominent, temperature gradient-based phonological variability can be high. However, there are few studies that assess the capability of remote sensing observations to monitor ecosystem phenology along elevation gradients, despite their relevance under climate change. We investigated the potential of medium resolution remotely sensed data to monitor the elevation variations in the seasonal dynamics of a temperate deciduous broadleaf forested ecosystem. Further, we explored the impact of elevation on the onset of spring leafing. This study was based on the analysis of multi-annual time-series of VEGETATION da…
The sedimentary and remote-sensing reflection of biomass burning in Europe
2018
Aim: We provide the first European-scale geospatial training set relating the charcoal signal in surface lake sediments to fire parameters (number, intensity and area) recorded by satellite moderate resolution imaging spectroradiometer (MODIS) sensors. Our calibration is intended for quantitative reconstructions of key fire-regime parameters by using sediment sequences of microscopic (MIC from pollen slides, particles 10-500 µm) and macroscopic charcoal (MAC from sieves, particles > 100 µm). Location: North-south and east-west transects across Europe, covering the mediterranean, temperate, alpine, boreal and steppe biomes. Time period: Lake sediments and MODIS active fire and burned area…
A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
2018
This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…
Climatología del Índice de Haines y aplicación a los incendios forestales en la Comunidad Valenciana
2015
Los incendios forestales, junto a las precipitaciones torrenciales, constituyen un grave problema en la cuenca del Mediterráneo Occidental, estando catalogados entre los riesgos meteorológicos de mayor importancia en estas regiones (Estrela, 2008). Por ello, resulta esencial analizar los procesos que generan estos riesgos y mejorar su pronóstico. La predicción de riesgo de incendio forestal es fundamental para evaluar la probabilidad de desarrollo, producción de daños y su posible extensión. Durante años, la inestabilidad y el aire seco se han asociado con el desarrollo de grandes incendios forestales en EUA, siendo Haines (Haines, 1988) el primer científico en desarrollar un índice de ries…
Simulación y validación de los algoritmos de la temperatura de la superficie terrestre para los datos de MODIS y AATSR
2007
Se ha construido una base de datos de perfiles de radiosondeos atmosféricos, de alcance global y para situaciones sin nubes, con la finalidad de simular medidas radiométricas desde sensores abordo de satélite en el infrarrojo térmico. El objetivo de la simulación era generar algoritmos de "split-window" (SW) y ángulo dual (DA) para obtener la temperatura de la superficie terrestre (LST) a partir del Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) y de los datos del Envisat/Advanced Along Track Scanning Radiometer (AATSR). La base de datos contiene 382 perfiles de radiosondeo obtenidos desde la superficie terrestre, con una distribución casi uniforme en contenido de agua precipit…
Are remote sensing evapotranspiration models reliable across South American ecoregions?
2021
Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM-MOD), and Penman–Monteith Nagler model (PME-VI).…
Effects of rainfall events on the evapotranspiration retrieved by an energy balance model
2009
An alternative way to map the actual evapotranspiration (ET) spatial distribution at daily scale is the application of residual surface energy balance models to satellite images that are characterised by high temporal frequency and moderate spatial resolution, like those acquired by the MODIS sensors on board of TERRA and AQUA platforms. Within this research the well-known SEBAL model has been applied on an area located in the southern part of Sicily (Imera Meridionale catchment) using four images acquired between the 27th of March and the 11th of April 2007. The catchment extends for about 2000 km2 and includes both mountains and hill areas: the first are located in the northern part (the …