Search results for " Google Earth"
showing 9 items of 9 documents
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…
Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform
2021
Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…
Confronto di due approcci statistici non parametrici per la valutazione della suscettibilità da frana nella catena appenninica settentrionale sicilia…
2012
Oggigiorno, la valutazione della diversa importanza delle variabili geoambientali nel determinare le condizioni di suscettibilità da frana di un’area è uno dei problemi più attuali della geologia. L’uso ed il confronto di due differenti approcci statistici, ha consentito di stimare le condizioni di predisposizione all’instabilità gravitativa dei versanti, per un esteso settore settentrionale della catena appenninica siciliana, ricadente all’interno delle tavolette I.G.M.I. nn. 259 I SE “Scillato” e 259 II NE “Caltavuturo”. L’area oggetto della sperimentazione, estesa circa 200 Km2, è stata suddivisa in maniera semi-automatica in 1827 unità idro-morfologiche o unità di versante. Per ciascun’…
Exporting a Google Earth™ aided earthflow susceptibility model: a test in central Sicily
2012
Abstract In the framework of a regional landslide susceptibility study in southern Sicily, a test has been carried out in the Tumarrano river basin (about 80 km2) aimed at characterizing its landslide susceptibility conditions by exporting a ‘‘source model’’, defined and trained inside a limited (about 20 km2) representative sector (the ‘‘source area’’). Also, the possibility of exploiting Google Earth TM software and photo-images databank to produce the landslide archives has been checked. The susceptibility model was defined, according to a multivariate geostatistic approach based on the conditional analysis, using unique condition units (UCUs), which were obtained by combining four selec…
Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy
2016
Abstract A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004–2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km 2 , respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Mul…
On the Accuracy of Cadastral Marks: Statistical Analyses to Assess the Congruence among GNSS-Based Positioning and Official Maps
2022
Cadastral marks constitute a dense source of information for topographical surveys required to update cadastral maps. Historically, in Italy, cadastral marks have been the cartographic network for the implementation of mapping updates. Different sources of cadastral marks can be used by cadastral surveyors. In recent years, the cadastre is moving toward a digital world, and with the advancement of surveying technology, GNSS CORS technology has emerged in the positioning of cadastral marks. An analysis of congruence among cadastral marks using GNSS CORS and official maps is missing. Thus, this work aims to analyze the positional accuracy of some cadastral marks, located in Palermo, Italy, wi…
Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine
2022
Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyll content (LCC), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and fractional vegetation cover (FVC), being fundamental for assessing photosynthetic activity on Earth. The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SC…
INTEGRATED SFM TECHNIQUES USING DATA SET FROM GOOGLE EARTH 3D MODEL AND FROM STREET LEVEL
2017
Abstract. Structure from motion (SfM) represents a widespread photogrammetric method that uses the photogrammetric rules to carry out a 3D model from a photo data set collection. Some complex ancient buildings, such as Cathedrals, or Theatres, or Castles, etc. need to implement the data set (realized from street level) with the UAV one in order to have the 3D roof reconstruction. Nevertheless, the use of UAV is strong limited from the government rules. In these last years, Google Earth (GE) has been enriched with the 3D models of the earth sites. For this reason, it seemed convenient to start to test the potentiality offered by GE in order to extract from it a data set that replace the UAV …
Factor selection procedures in a Google Earthtm aided landslide susceptibility model: application to the Beiro river basin (Spain)
2011
A procedure to select the controlling factors connected to the slope instability has been defined. It allowed to assess the landslide susceptibility in the Rio Beiro basin (about 10 km2) over the north-eastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed to generate a landslide inventory consisting in 127 phenomena. Univariate tests, using both association coefficients and validation results of single parameter susceptibility models, allowed to select among 15 controlling factors the ones that resulted as good predictor variables; these have been combined for unique conditions analysis and susceptibility maps were finally prepared. In…