536 research outputs found
PYSMM
No full textPYthon Sentinel-1 soil-Moisture Mapping Toolbox (PYSMM)
This package acts as an interface to Google Earth Engine for the estimation of surface soil moisture based on Copernicus Sentinel-1 intensity data. It is meant as a supplement to the following publication: Greifeneder, F., C. Notarnicola, W. Wagner. A machine learning based approach for global surface soil moisture estimations with Google Earth Engine. The estimation of soil moisture is based on a Gradient Boosting Trees Regression machine learning approach. The model training was performed based on in-situ data from the International Soil Moisture Network (ISMN). PYSMM all processing steps for spatial and temporal mapping of surface soil moisture are fully executed online on GEE - none of the input data-sets needs to be downloaded.
Acknowledgements: This work was partially funded by the Horizon 2020 project “Ecopotential – Improving Future Ecosystem Benefits through Earth Observation, which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement n° 641762) and the European Fund for Regional Development project “DPS4ESLAB”
Exploitation of C and X band SAR images for soil moisture change detection estimation in agricultural areas (Po valley-Italy)
No full textThis paper presents the analysis of C and X band images in the scope of soil moisture detection in agricultural fields. Archived data have been analyzed in order to understand the SAR signal behavior of vegetated fields in comparison to bare soils. The results indicate that the sensitivity to bare fields of C and X band signatures is very close, while it changes in presence of vegetation. In particular the effect is directly proportional to amount of vegetation that in this preliminary analysis has been evaluated through the NDVI variable.
After this analysis, a statistical approach has been applied to SAR images to infer the information on the soil moisture values. Several experiments have been carried out by considering only C band data, only X band data and a combination of C and X band data. For bare soils, C and X band data determine very similar results and in good agreement to ground measurements. For vegetated fields, C band data tend to underestimate soil moisture due to the vegetation attenuation, while X band data, mainly influenced by vegetation, determine very poor results. Encouraging results are obtained by the combination of C and X band data, thus indicating that X band data can be used in combination to C band data in order to compensate the effect of vegetation
A novel Multilevel Biodiversity Index (MBI) for combined field and satellite imagery surveys
No full textIn an epoch of fast and dramatic changes in ecosystems, a complete survey of biodiversity and an analysis of its spatial patterns from the field shall be associated with satellite imagery, which can provide a synoptic observation in space and time of the territory. This work presents the preliminary results of a new approach to monitor the biodiversity of a well-defined area, which takes into account species diversity and the landscape characteristics in terms of ecosystems diversity (land cover classes). We developed a Multilevel Biodiversity Index (MBI) and we tested it in a study site of 400 km2, belonging to the Central Mediterranean Ecoregion and consisting of forested areas, scrublands and steppes (Murge). With the aim to reach a global land cover classification system and a standardisation of the biodiversity surveys, the MBI can be easily adapted to study areas of different ecoregions on Earth. This index could certainly be useful for future studies and to address environmental policies in order to protect vulnerable ecosystems and assign a conservation priority rank that takes into account the presence of diversity both in terms of species and ecosystems
LCA of Italian and Spanish bovine leather production systems in an industrial ecology perspective
No full textIntegration of X-SAR observations with data of other remote sensing techniques: preliminary results achieved with Cosmo/SkyMed announcement of opportunity projects
No full textThe Italian Space Agency is funding 27 scientific projects in the framework of Cosmo/Skymed program (hereafter CSK) . A subset of them are focusing on the improvements of the quality and quantity of information which can be extracted from X-SAR data if integrated with other independent techniques like GPS or SAR imagery in L and C bands. The GPS observations, namely zenith total delays
estimated by means of GPS ground stations, could be helpful to estimate the troposphere bias to remove
from IN-SAR imagery. Another contribution of GPS could be the improvements of the orbits of Cosmo/SkyMed satellites. In particular the GPS navigation data of the CSK satellites could serve to improve the atmospheric drag models acting on them. The integration of SAR data in L and C bands on the other hand are helpful to investigate land hydrogeology parameters as well as to improve global precipitation observations. The combined use of L, C and X SAR data with different penetration depth could give profiles of land surface properties, especially in forest and snow/ice-packs. For what concern the use of X-SAR
imagery for rain precipitation monitoring, particular attention will be paid to its polarimetric properties that
we plan to determine aligning the CSK observations with those obtained with ground L and C radars.
Anyway the study goals, the approaches proposed, the test sites identified and the external data selected for
the development and validation will be described for each project. Particular attention will be paid to single
the advantages that the research activities can benefit from the added potentials of CSK system: the more
frequent revisiting time and the higher resolution capabilities
Satellite and airborne remote sensing data for monitoring degraded areas
No full textThis study introduces two applications of remotely sensed data to detect degraded areas and to evaluate the relative pollution produced in the neighborhood areas. The first one regards the possible methodology to extract spatial information for dumps monitoring based on the discrimination ability of texture analysis. The second one analyses the spectral behaviour of an area stressed by an industrial settlement in Southern Italy. Both cases have been studied with the aid of high and very high resolution images. The general purpose is the development of models and automated procedures to identify environmental parameters associated to pollution and degradation by using satellite images
Numerical investigation on the effect of the snowpack surface roughness on the radar echo
No full textSouthern Italy illegal dumps detection based on spectral analysis of remotely sensed data and land cover maps
No full textThis work intends to test the use of remotely sensed data, as a mean to identify degraded lands with a high environmental hazard. The approach uses data from the sensor Thematic Mapper on Landsat 5 in synergy with digital ortho-photos (1:10000) and land cover map Corine 1990 to create a methodology useful to identify areas with dumps. The analysed scene is relative to an area located in the Apulia Region in Southern Italy, where it is known the presence of a dump nearthe Margherita di Savoia "saline" (salt evaporation pool). As this dump is in its early phase, it is impossible to use thermal anomaly as a characteristic sign of its presence. So its identification proceeds through the extraction of the spectral signatures of the dump area and of the neighbourhood zones. The analysis is developed in three steps: 1. Monitoring the change in the zone nearby the pools, especially if abandoned; 2. Pointing out the dump presence by the spectral signature specificity; 3. Individuating areas characterized by the same spectral properties. A pre-processing analysis is carried out by the Principal Component Transformation in order to minimize spectral noise and redundancy. Subsequently, the images are classified by the unsupervised algorithm ISODATA aiming at automatically individuating radiometric classes. The regions of interest are identified by help of the land cover map and then characterised by their spectral signatures. The identification of the dump is a feasible objective because of the temporal stability of its spectral signature, with respect to those of the other areas
Titan dune heights retrieval by using Cassini Radar Altimeter
No full textThe Cassini Radar is a Ku band multimode instrument capable of providing topographic and mapping information. During several of the 93 Titan fly-bys performed by Cassini, the radar collected a large amount of data observing many dune fields in multiple modes such as SAR, Altimeter, Scatterometer and Radiometer. Understanding dune characteristics, such as shape and height, will reveal important clues on Titan's climatic and geological history providing a better understanding of aeolian processes on Earth. Dunes are believed to be sculpted by the action of the wind, weak at the surface but still able to activate the process of sand-sized particle transport. This work aims to estimate dunes height by modeling the shape of the real Cassini Radar Altimeter echoes. Joint processing of SAR/Altimeter data has been adopted to localize the altimeter footprints overlapping dune fields excluding non-dune features. The height of the dunes was estimated by applying Maximum Likelihood Estimation along with a non-coherent electromagnetic (EM) echo model, thus comparing the real averaged waveform with the theoretical curves. Such analysis has been performed over the Fensal dune field observed during the T30 flyby (May 2007). As a result we found that the estimated dunes' peak to trough heights difference was in the order of 60-120 m. Estimation accuracy and robustness of the MLE for different complex scenarios was assessed via radar simulations and Monte-Carlo approach. We simulated dunes-interdunes different composition and roughness for a large set of values verifying that, in the range of possible Titan environment conditions, these two surface parameters have weak effects on our estimates of standard dune heights deviation. Results presented here are the first part of a study that will cover all Titan's sand seas. (C) 2014 Published by Elsevier Inc
- …
