REMOTELY SENSED IMAGE FAST CLASSIFICATION AND SMART THEMATIC MAP PRODUCTION

Abstract. Apps available for Smartphone, as well as software for GNSS/GIS devices, permit to easily mapping the localization and shape of an area by acquiring the vertices coordinates of its contour. This option is useful for remote sensing classification, supporting the detection of representative sample sites of a known cover type to use for algorithm training or to test classification results. This article aims to analyse the possibility to produce smart maps from remotely sensed image classification in rapid way: the attention is focalized on different methods that are compared to identify fast and accurate procedure for producing up-to-date and reliable maps. Landsat 8 OLI multispectral images of northern Sicily (Italy) are submitted to various classification algorithms to distinguish water, bare soil and vegetation. The resulting map is useful for many purposes: appropriately inserted in a larger database aimed at representing the situation in a space-time evolutionary scenario, it is suitable whenever you want to capture the variation induced in a scene, e.g. burnt areas identification, vegetated areas definition for tourist-recreational purposes, etc. Particularly, pixel-based classification approaches are preferred, and experiments are carried out using unsupervised (k-means), vegetation index (NDVI, Normalized Difference Vegetation Index), supervised (minimum distance, maximum likelihood) methods. Using test sites, confusion matrix is built for each method, and quality indices are calculated to compare the results. Experiments demonstrate that NDVI submitted to k-means algorithm allows the best performance for distinguishing not only vegetation areas but also water bodies and bare soils. The resulting thematic map is converted for web publishing

Remotely sensed image fast classification and smart thematic map production

Apps available for Smartphone, as well as software for GNSS/GIS devices, permit to easily mapping the localization and shape of an area by acquiring the vertices coordinates of its contour. This option is useful for remote sensing classification, supporting the detection of representative sample sites of a known cover type to use for algorithm training or to test classification results. This article aims to analyse the possibility to produce smart maps from remotely sensed image classification in rapid way: The attention is focalized on different methods that are compared to identify fast and accurate procedure for producing up-To-date and reliable maps. Landsat 8 OLI multispectral images of northern Sicily (Italy) are submitted to various classification algorithms to distinguish water, bare soil and vegetation. The resulting map is useful for many purposes: Appropriately inserted in a larger database aimed at representing the situation in a space-Time evolutionary scenario, it is suitable whenever you want to capture the variation induced in a scene, e.g. burnt areas identification, vegetated areas definition for tourist-recreational purposes, etc. Particularly, pixel-based classification approaches are preferred, and experiments are carried out using unsupervised (k-means), vegetation index (NDVI, Normalized Difference Vegetation Index), supervised (minimum distance, maximum likelihood) methods. Using test sites, confusion matrix is built for each method, and quality indices are calculated to compare the results. Experiments demonstrate that NDVI submitted to k-means algorithm allows the best performance for distinguishing not only vegetation areas but also water bodies and bare soils. The resulting thematic map is converted for web publishing

The Effectiveness of Pan-Sharpening Algorithms on Different Land Cover Types in GeoEye-1 Satellite Images

In recent years, the demand for very high geometric resolution satellite images has increased significantly. The pan-sharpening techniques, which are part of the data fusion techniques, enable the increase in the geometric resolution of multispectral images using panchromatic imagery of the same scene. However, it is not trivial to choose a suitable pan-sharpening algorithm: there are several, but none of these is universally recognized as the best for any type of sensor, in addition to the fact that they can provide different results with regard to the investigated scene. This article focuses on the latter aspect: analyzing pan-sharpening algorithms in relation to different land covers. A dataset of GeoEye-1 images is selected from which four study areas (frames) are extracted: one natural, one rural, one urban and one semi-urban. The type of study area is determined considering the quantity of vegetation included in it based on the normalized difference vegetation index (NDVI). Nine pan-sharpening methods are applied to each frame and the resulting pan-sharpened images are compared by means of spectral and spatial quality indicators. Multicriteria analysis permits to define the best performing method related to each specific area as well as the most suitable one, considering the co-presence of different land covers in the analyzed scene. Brovey transformation fast supplies the best results among the methods analyzed in this study

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

In relation to 3D bathymetric modelling, this article aims to analyze the performance of Kriging approaches in dependence of the location and density of the measured depth points. The experiments were carried out on a multi-beam sonar (MBS) dataset that includes 240,000 soundings covering a sea-bottom area near Giglio Island (Italy). Seven subsets were derived in random way from the initial regular MBS dataset, selecting an increasing number of points uniformly spaced. Seven models were generated for both Ordinary Kriging and Universal Kriging. Each model was submitted to leave-one-out cross-validation to define the exactness of the predictive values and compared with the initial grid to better evaluate the accuracy in dependence of the point number and dissemination. To investigate this relationship, a new index called MVI (Morphological Variation Index) was introduced as a measurement of the level of variation of seabed morphology. The results validate the efficiency of the Kriging methods and remark the influence of the dataset distribution on the 3D model, highlighting MVI as a useful index to represent the seabed variation as a unique value. Finally, in no rugged areas using 1 point every 1000 m2, the RMSE of the differences between measured and interpolated values falls below 1 m, while a further increment of soundings is required in the presence of a high level of variation of seabed morphology

Interpolating single-beam data for sea bottom GIS modelling

The “Istituto Idrografico della Marina Militare” (IIMM) secures the Italian hydrographic service through the execution of bathymetric surveys, the production of nautical charts and publications, and the dissemination of nautical information, aimed at the safety of navigation and of human life at sea. The datasets of depth points acquired with bathymetric surveys are useful to model sea-bottom starting from the interpolation methods available in Geographic Information System (GIS) software. In this paper, a single-beam dataset from IIMM is used with the aim to compare different interpolation methods for sea bottom GIS modelling. The study area is the sea close to the east coast of Isola del Giglio in Tuscan Archipelago (Italy). The following nine different interpolation methods are selected and applied using ArcGIS software, version 10.3.1: Inverse Distance Weighting (IDW), Local Polynomial Interpolations of different orders (from the first to the fifth order), Ordinary Kriging, with three different Variogram models (Gaussian, circular, exponential). The result accuracy is tested via cross-validation leave-one-out, so statistical values (minimum, maximum, mean and root mean square error) are calculated for each interpolation method, taking into account the residual given for each sampling point between measured and interpolated value. Finally, a 3D model is created from the best interpolating algorithm. The results remark the role of the cross validation as preliminary way to select the most preforming interpolation method that is difficult to identify in other way

Digital terrain model generalization for multiscale use

Geomatics 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

The importance of the coordinate transformation process in using heterogeneous data in coastal and marine geographic information system

Coastal and Marine Geographic Information Systems (CMGISs) permit to collect, manage, and analyze a great amount of heterogeneous data concerning coastal, sea, and ocean environments, e.g., nautical charts, topographic maps, remotely sensed images. To integrate those heterogeneous layers in CMGIS, particular attention is necessary to ensure the perfect geo-localization of data, which is a basic requirement for the correct spatial analysis. In fact, the above-mentioned types of information sources are usually available in different cartographic projections, geodetic datum, and scale of representation. Therefore, automatic conversions supplied by Geographic Information System (GIS) software for layer overlay do not produce results with adequate positional accuracy. This paper aims to describe methodological aspects concerning different data integration in CMGIS in order to enhance its capability to handle topics of coastal and marine applications. Experiments are carried out to build a CMGIS of the Campania Region (Italy) harmonizing different data (maps and satellite images), which are heterogeneous for datum (World Geodetic System 1984 and European Datum 1950), projection (Mercator and Universal Transverse of Mercator), and scale of representation (large and medium scale). Results demonstrate that automatic conversion carried out by GIS software are insufficient to ensure levels of positional accuracy adequate for large scale representation. Therefore, additional operations such as those proposed in this work are necessary

Integration of Nautical Charts and Satellite Images in Marine GIS of the Gulf of Naples

In the last decades Marine Geographic Information Systems (MGISs) have had an increasing diffusion because of their ability to store, manage and analyze a great amount of heterogeneous data concerning sea and ocean environments. To build a MGIS, nautical charts are fundamental: they provide useful information such as shoreline configuration, seafloor morphology, water depths, anchorages, and other features that are suitable not only for navigation, but for marine science applications, i.e. aquatic biology and ecology. Satellite images contribute to bring more information in MGIS concerning many aspects of the sea and ocean environment, so remotely sensed data in high quality, large quantity and multitemporal acquisition can be introduced in the database. For their correct usage, satellite images require pre-elaboration to overlay them to nautical charts: usually they are supplied in different cartographic projection as well as in different geodetic datum that nautical charts, so re-projection and datum transformation are necessary and not banal. This paper aims to describe the approach adopted in MGIS of the Gulf of Naples to harmonize heterogeneous data concerning nautical charts and satellite images, so to able its use for Marine Spatial Planning (MSP). Both large and medium scale maps are considered as well as remotely sensed images with high and medium resolution. The experiments demonstrate that adequate positional accuracy can be achieved for all layers compatibly with the scale of the representation

From electronic navigational chart data to sea-bottom models: Kriging approaches for the Bay of Pozzuoli

Electronic Navigational Charts (ENCs), official databases created by a national hydrographic office and included in Electronic Chart Display and Information System (ECDIS), supply, among essential indications for safe navigation, data about sea-bottom morphology in terms of depth points and isolines. Those data are very useful to build bathymetric 3D models: applying interpolation methods, it is possible to produce a continuous representation of the seafloor for supporting studies concerning different aspects of a marine area, such as directions and intensity of currents, sensitivity of habitats and species, etc. Many interpolation methods are available in literature for bathymetric data modelling: among them kriging ones are extremely performing, but require deep analysis to define input parameters, i.e. semi-variogram models. This paper aims to analyze kriging approaches for depth data concerning the Bay of Pozzuoli. The attention is focused on the role of semi-variogram models for Ordinary and Universal kriging. Depth data included in two ENCs, namely IT400129 and IT400130, are processed using Geostatistical Analyst, an extension of ArcGIS 10.3.1 (ESRI). The results testify the relevance of the choice of the mathematical functions of the semi-variogram: Stable Model supplies, for this case study, the best performance in terms of depth accuracy for both Ordinary and Universal kriging

Automation of pan-sharpening methods for pléiades images using GIS basic functions

Pan-sharpening methods allow the transfer of higher resolution panchromatic images to multispectral ones concerning the same scene. Different approaches are available in the literature, and only a part of these approaches is included in remote sensing software for automatic application. In addition, the quality of the results supplied by a specific method varies according to the characteristics of the scene; for consequence, different algorithms must be compared to find the best performing one. Nevertheless, pan-sharpening methods can be applied using GIS basic functions in the absence of specific pan-sharpening tools, but this operation is expensive and time-consuming. This paper aims to explain the approach implemented in Quantum GIS (QGIS) for automatic pan-sharpening of Pléiades images. The experiments are carried out on data concerning the Greek island named Lesbo. In total, 14 different pan-sharpening methods are applied to reduce pixel dimensions of the four multispectral bands from 2 m to 0.5 m. The automatic procedure involves basic functions already included in GIS software; it also permits the evaluation of the quality of the resulting images supplying the values of appropriate indices. The results demonstrate that the approach provides the user with the highest performing method every time, so the best possible fused products are obtained with minimal effort in a reduced timeframe