1,720,965 research outputs found
Rappresentazioni Multiscala: generalizzazione di dati geografici in Ambiente GIS
No full textL’utilizzo di strumenti GIS per la gestione e l’analisi di informazioni territoriali, geografiche ed ambientali, ha spinto l’utente a dotarsi di una enorme quantità di dati a differente livello di dettaglio; nonostante la grande capacità di memorizzazione rappresentata dai moderni strumenti informatici, si pone comunque il problema della loro integrazione a causa della carenza di standardizzazione, in particolar modo nella generazione degli opportuni metadati. Una soluzione a questo problema è rappresentata dalle operazioni di generalizzazione cartografica effettuate in ambiente GIS.
Tuttavia, nonostante la prepotente diffusione dei sistemi informativi territoriali, non è stata ancora completamente recepita dalle aziende, dai professionisti e dagli Enti Pubblici, la necessità di modificare profondamente le metodologie di restituzione delle basi cartografiche deputate al loro utilizzo all’interno di GIS.
L’organizzazione dei dati cartografici ha impietosamente messo in luce come la cartografia numerica sino ad oggi prodotta mal si presta allo scopo, in quanto nasce dall’impiego di operazioni di restituzione numerica quasi integralmente mutuate da quelle analogiche.
E’ necessario allora definire quali caratteristiche debbano possedere i dati cartografici da trattare perché diventino sufficientemente idonei ad essere impiegati all’interno di un SIT. E’ importante notare che in una qualunque cartografia gli oggetti sono identificati da codici che presi singolarmente non costituiscono tematismi ma solo una base per la realizzazione delle coperture del SIT. Così come va sottolineato che le coperture non si possono ottenere dalla semplice unione di più codici. Perché ciò avvenga la restituzione cartografica andrebbe effettuata dopo aver progettato il sistema informativo. Ciononostante le carte attualmente prodotte trasportano informazioni che, accuratamente filtrate e controllate, possono costituire singole coperture.
Nella maggioranza dei casi, si rende allora necessario intervenire preventivamente sulla base dati cartografica al fine di generare i necessari tematismi attraverso l’analisi della codifica utilizzata, delle incongruenze geometriche e la loro successiva ristrutturazione
STRUCTURING AND VALIDATION OF PHOTOGRAMMETRIC TERRITORIAL DATA
No full textIn the loving memory of Mariasofia Paparo, this publication focuses on the validation procedures of photogrammetric geographic information and the production and interpretation of complex reports, which are essential for handling the vast amount of generated data. Furthermore, sources of error in the structuring of geographic data and the quality parameters and conformity criteria necessary for the utilization of such data within the national geodatabase have been investigated
Digital terrain model generalization for multiscale use
No full textGeomatics techniques and applications to process lidar data, large-scale map, stereo-pair airborne photos, and Very High Resolution satellite imagery allow building very detailed Digital Terrain Models. Indeed, in studies characterized by a smaller reference scale, lower resolution models are required to handle a smaller amount of data. Therefore, rather than producing more models with different resolutions, it is preferable to create only one of the multiscale types by using generalization techniques. Different approaches are described in literature in order to achieve this purpose and the results are different in relation to the technique used. This paper aims to compare different algorithms and procedures for Digital Terrain Model generalization. The area selected for this study presents a variegate zone with variable slopes, in order to examine the generalization process in different gradient ranges. Elevation data are extracted from 1:5,000 scale mapping and processed with Geostatistical Analyst to produce Digital Terrain Models with 4 m cell resolution. Five different approaches for generalization are adopted and compared: two based on filtering algorithms (respectively media and median), three on regeneration of Digital Terrain Model interpolating contours or elevation points extracted from the starting model. A new index is provided to evaluate each resulting model also in reference to its capacity to preserve the initial significant values. All the operations are carried out using the Geographic Information System software
Multiscale representation: a data generalization workflow and quality evaluation experience in GIS enviroment
No full textConcerning geographic data representation, what a user need is specific tools for the representation and evaluation of the data on which the decision process relies. In cartographic applications, users need to deal with maps of the same geographic region at different levels of abstractions. Usually it’s used to maintain one database per level detail; a multiscale representation GIS would allow storing all original geographical information in a single database, and enforce the consistency of the different representations through appropriate, automatic generalization processes.
In this paper we deal with the problem of geographic data generalization, beginning from a generalization workflow by improving specific routines.
To aim the goals of the generalization process, we used the ESRI ArcGIS 8.1 platform. Inside this enviroment it have been implemented some generalization functionalities by improving appropriate ruotines in Visual Basic language. After a presentation of the generalization workflow, all cartographic constraints, of geometric, topological and semantic nature, governing the generalization process, are specified. In the next step these constraints will be translated into tools for assessing the need and the quality of generalization solutions. These tools are associated with a particular data model. For that data model the constraints can be best translated to measures and generalization algorithms and parameterized. This framework is based on constraints that are used to control the process and represent the user requirements in a way the system can manage to reach a quality close to these requirements; it reflects the idea that more than one acceptable solution may exist to a given generalization problem. The goal was the production of a topographic map at scale 1:50000, 1:100000 and 1:250000 from the “Carta Tecnica Regionale”, CTR, (official regional cartography) of the “Regione Autonoma della Sardegna”, RAS, (Regional Administration of Sardinia), at scale 1:10000, in a GIS environment.
According with the official national and international standards, we provide the definition of the characteristics and associated quality evaluation tool to be used in order to validate the geographic data
Rappresentazione dei DBT IntesaGIS alle scale di sintesi: un percorso metodologico a partire dal DB10k
No full textLe specifiche tecniche dell’IntesaGIS non hanno ancora affrontato il problema della rappresentazione dei dati del DBT alle scale di dettaglio quali, per esempio, 100k o 250k, né la eventuale derivazione dei DBT a tali scale.
L’obiettivo di questa ricerca consiste nella redazione degli elementi essenziali di una proposta progettuale per la costruzione di un database a scale di sintesi, a partire dalla costruenda base dati della Regione Sardegna alla scala 1:10.000, DB10k. Questo obiettivo è perseguito nel rispetto della struttura del database originale e secondo le prescrizioni tecniche, “Specifiche di contenuto dei Database Topografici di interesse generale”, redatto dal gruppo di lavoro Intesa GIS WG01 che opera nell’ambito dell’Intesa Stato-Regioni.
Il documento propone, di fatto, una strutturazione originale di un modello logico a scale di sintesi nel rispetto dei dati territoriali contenuti nel DBT alla scala di partenza.
Durante questo passaggio, è mantenuta intatta l’architettura del database geografico: in particolare sono evidenziate le classi di oggetti, con i loro attributi; inoltre, le classi sono state raggruppate in temi e questi in strati. Per ogni classe è riportata una descrizione esplicativa, la lista degli attributi con i relativi domini, e viene indicata la primitiva geometrica.
Sono, inoltre, indicate le principali relazioni tra le diverse classi, (appartenenti allo stesso tema o a temi diversi), che sono implementate nel database nel modo più opportuno. Questa fase, lontana da essere esaustiva, sarà sicuramente oggetto, nel corso di ulteriori sviluppi, di successivi interventi per raggiungere un contesto dotato di specifiche più precise o con aggiunta di ulteriori elementi
GIS Based Analysis and Accuracy Estimation of Sea Surface Temperature from MODIS Thermal Images
No full textCapturing the thermal emission from the Earth, satellite sensors permit to derive sea surface temperature (SST). The infrared radiance intercepted by the sensor also depends on other variables, such as the surface emissivity, viewing geometry and the atmospheric contribution. All variables that affect atmospheric absorption and emission must be carefully considered. The brightness temperature of the surface measured by satellite sensor needs transformation to obtain SST. To remove the noise generated by the atmosphere, an equation can be used to derive a set of SST algorithm coefficients that can be applied to the brightness temperature image. Temperature data from specific points are necessary for the scope. This article aims to demonstrate that, in absence of an adequate temperature dataset, SST can be derived by MODIS thermal images (pixel dimensions: 1 km x 1 km) using Copernicus data even if it has a lower spatial resolution (0.0625° x 0.0625°). The study area includes an extended part of the Mediterranean Sea which contains the Strait of Sicily, the Adriatic, Ionian, and Tyrrhenian Seas. The Pathfinder algorithm developed by NOAA based on an equation with pre-established coefficients is also applied for comparison. Temperatures recorded by buoys are used to test the result accuracy. The experiments testify the good performance of the adopted approach
Using GIS tools to enhance the shape of coastline extracted from Sentinel-2 satellite images
No full textSentinel-2 images are widely used for coastline extraction. One of the most widespread methods is the Normalized Difference Water Index (NDWI), which permits distinguishing between water and non-water pixels. The result obtained, since it derives from satellite images, preserves the shape of the pixels, which is often labeled as unrealistic. For this reason, Geographic Information Systems (GIS) tools are often used in the literature to simplify and/or smooth the coastline obtained from satellite images in order to make it as similar to reality as possible. However, these operations are not always optimal. In this work, we analyze the coastline extracted from Sentinel-2 images concerning the island of Giglio (Italy), in particular four coastlines are compared: the standard coastline, i.e. the one obtained directly from the NDWI; the coastline resulting from the smoothing application; the coastline resulting from the simplification application; and finally, the coastline resulting from both simplification and smoothing application. The results show a higher efficiency of smoothing compared to simplification
Accuracy evaluation for coastline extraction from Pléiades imagery based on NDWI and IHS pan-sharpening application
No full textAccurate coastline position is of fundamental importance for many applications concerning coastal zone monitoring, management, and planning. For example, coastal erosion phenomena require a careful and continuous monitoring due to the dynamic nature of the coastline which can undergo sudden and significant changes in position and shape over time. Various techniques allow acquiring the coastline, among these the use of multispectral optical sensors operating from satellites is one of the most widespread. With the advent of high and very high geometric resolution (VHR) satellites, it is possible to obtain images with a pixel size of less than 1 m that allow extracting accurate coastlines. The purpose of this article is to define a fast approach to investigate the degree of accuracy of one of the most popular techniques for the automatic extraction of the coastline, based on the Normalized Difference Water Index (NDWI) use. In this study, the coastline is achieved from VHR Pléiades imagery (2 m for multispectral and 0.5 m for panchromatic). Therefore, NDWI is obtained and processed both from initial images and pan-sharpened images. The resulting coastlines are submitted to smoothing and their accuracy is therefore evaluated. For this purpose, a reference coastline is manually achieved from panchromatic image. Two different methods are proposed for coastline accuracy evaluation, both based on the geometrical analysis of the polygons generated by the intersection between the extracted coastline and the reference one. This study demonstrates that the proposed methods permit to easily evaluate the accuracy of the extracted coastline; in addition, the results confirm the effectiveness of NDWI and highlight the limited benefits of pan-sharpened images for this index application
Coastline Extraction from Optical Satellite Imagery and Accuracy Evaluation
No full textDifferent techniques can be applied for shoreline acquisition. Direct survey, based on GNSS (Global Navigation Satellite System) or total station, permits to obtain 3D information that is useful for the correct definition of the coastline also in consideration of the tidal effects. However, the acquisition of long stretches of coast using in-situ survey may be too expensive and time consuming. Additionally, many studies require to reconstruct temporal shoreline dynamics, and, in absence of survey carried out in the past, remotely sensed data may be a valuable source of information. For those reasons, there is a widespread usage of aerial and satellite imagery in many studies needing coastline detection. This research aims to analyze methodological aspects of coastline extraction from optical satellite imagery at medium and high resolution: the evaluation of the results accuracy permits to compare two different approaches based on the multispectral band use. The attention is focused on Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI), both applied to medium resolution imagery (Landsat 8 OLI) and to high resolution imagery (GeoEye-1). Maximum Likelihood Classification (MLC), one of the most common classification methods in remote sensing based on Bayes’ Theorem, is applied to determine a threshold to separate seawater from land. An index based on the direct comparison between the automatic extracted coastline and the manually delineation of it, is used to evaluate the accuracy of the results. Both indices permit to obtain acceptable results reporting accuracy values less than the pixel dimension. However, the accuracy level of NDWI is slightly higher than NDVI
The Influence of Interpolation Methods and point density on the Accuracy of a Bathymetric Model
No full textThe construction of three-dimensional models of the seabed starting from sample data requires the use of interpolators to calculate the depth where it has not been measured. The accuracy of the model depends on several factors, e.g., the interpolation method, the seabed morphology, the density and distribution of the samples. This article aims to investigate the accuracy of bathymetric models in relation to the interpolation methods and the number of points available. Eight different methods available in ArcGIS software are analyzed in this study, including 6 deterministic methods, i.e., Inverse distance weighting (IDW), and 5 variations of Radial Basis Functions (RBFs). Additionally, two stochastic methods, such as Universal Kriging (UK) and Ordinary Kriging (OK), are also examined. The experiments are carried out using the bathymetric information from an Electronic Navigational Chart (ENC) at a scale 1:30,000 concerning the north-eastern sector of the Gulf of Naples. The 12,638 depth points including in the ENC are organized in four datasets presenting different data density (25%, 50%, 75% and 100% of the available data respectively). The results of the study confirm that the accuracy of the models improves as the number of points used increases. Specifically, RBF interpolators are found to be more effective than other methods at low density values (25% and 50% of available data) while Kriging interpolators outperform other methods when using large numbers of points (75% and 100% of available data)
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