Search results for "Geomatics"
showing 10 items of 495 documents
Land use classification from multitemporal Landsat imagery using the Yearly Land Cover Dynamics (YLCD) method
2011
Abstract Several previous studies have shown that the inclusion of the LST (Land Surface Temperature) parameter to a NDVI (Normalized Difference Vegetation Index) based classification procedure is beneficial to classification accuracy. In this work, the Yearly Land Cover Dynamics (YLCD) approach, which is based on annual behavior of LST and NDVI, has been used to classify an agricultural area into crop types. To this end, a time series of Landsat-5 images for year 2009 of the Barrax (Spain) area has been processed: georeferenciation, destriping and atmospheric correction have been carried out to estimate NDVI and LST time series for year 2009, from which YLCD parameters were estimated. Then…
Interpretability of Recurrent Neural Networks in Remote Sensing
2020
In this work we propose the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for multivariate time series of satellite data for crop yield estimation. Recurrent nets allow exploiting the temporal dimension efficiently, but interpretability is hampered by the typically overparameterized models. The focus of the study is to understand LSTM models by looking at the hidden units distribution, the impact of increasing network complexity, and the relative importance of the input covariates. We extracted time series of three variables describing the soil-vegetation status in agroe-cosystems -soil moisture, VOD and EVI- from optical and microwave satellites, as well as available in si…
Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression
2021
Monitoring cropland phenology from optical satellite data remains a challenging task due to the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to overcome these challenges and gain better knowledge of crop dynamics. The arrival of cloud computing platforms such as Google Earth Engine (GEE) has enabled us to propose a Sentinel-2 (S2) phenology end-to-end processing chain. To achieve this, the following pipeline was implemented: (1) the building of hybrid Gaussian Process Regression (GPR) retrieval models of crop traits optimized with active learning, (2) implementation of these models on GEE (3) generation of spatiotemporally continuous maps and time seri…
Processing of 3D Models for Networking of CH in Geomatics
2020
In recent times the possibility of reconstruction of complex 3D Cultural Heritage (CH) environments has opened new scenarios for touristic and scientific aims. The different needs for networking or conservation purposes of CH lead to study proper structuring of 3D models. In light of this, a scientific approach has been developed in order to test the networking capabilities, comparing different loading configurations of 3D environments with multiple combinations of 3D models inside them, considering different solutions. This experimentation has been based on WebGL-HTML5 technologies and allowed to discover the true balance between performances of proposed system, the quality of visualizatio…
Quantification of LAI interannual anomalies by adjusting climatological patterns
2011
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…
Comparison of in Situ Land Surface Temperatures Measured with Radiometers and Pyrgeometers: Consequences for Calibration and Validation of Thermal In…
2018
Land surface temperature (LST) is a key magnitude in many exchange processes between the surface and the atmosphere. LST measurement from satellites provides an efficient way to monitor its change across wide areas on Earth, an essential issue being LST validation using in situ measurements to assess its accuracy and precision. Presently, there are two widely used methodologies: temperature measurements made by wideband radiometers observing the land surface with a given viewing angle and a limited field of view, and measurements provided by total radiation pyrgeometers with a nearly hemispheric field of view. Although both measurements are correlated, they are not equivalent; thus, it is r…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Study of Temperature Heterogeneities at Sub-Kilometric Scales and Influence on Surface–Atmosphere Energy Interactions
2019
The retrieval of land surface temperature (LST) from remote sensing techniques has been studied and validated during the past 40 years, leading to important improvements. Accurate LST values are currently obtained through measurements using medium resolution thermal infrared (TIR) sensors. However, the most recent review reports demonstrated that the future TIR LST products need to obtain reliable temperature values at a high spatial resolution (100 m or higher) to study temperature variations between different elements in a heterogeneous kilometric area. The launch of high-resolution TIR sensors in the near future requires studies of the temporal evolution and spatial heterogeneities of th…
How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment
2016
This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spanning 4 continents and covering 15 crop types with corresponding Landsat satellite images. Best-fit functions for the LAI-VI relationships were generated and assessed in terms of crop type, vegetation index, level of radiometric/atmospheric processing, method of LAI measurement, as well as the time difference between LAI measurements and satellite overpass. These global LAI-VI relationships were evalu…
Levantamiento 3D para el estudio arqueológico y la reconstrucción virtual del Santuario de Isis en la antigua Lilybaeum (Italia)
2020
[EN] In recent years, the use of three-dimensional (3D) models in cultural and archaeological heritage for documentation and dissemination purposes has increased. New geomatics technologies have significantly reduced the time spent on fieldwork surveys and data processing. The archaeological remains can be documented and reconstructed in a digital 3D environment thanks to the new 3D survey technologies. Furthermore, the products generated by modern surveying technologies can be reconstructed in a virtual environment on effective archaeological bases and hypotheses coming from a detailed 3D data analysis. However, the choice of technologies that should be used to get the best results for dif…