Multi-scale digital terrain model generation using Cartosat-1 stereo images for the Mausanne les Alpilles test site

Cartosat-1 is the first Indian Remote Sensing satellite able to collect in-track high resolution stereo images with a 2.5m pixel size. Since Cartosat-1 has no multispectral cameras, it was mainly developed for topographic mapping and Digital Terrain Model (DTM) generation. In the framework of the Cartosat-1 Scientific Assessment Programme, the Politecnico di Milano University (Italy) evaluated as Co-Investigator the performances of the Cartosat-1 satellite in the generation of DTMs from stereo-couples. This paper describes in detail the outcomes for the Mausanne les Alpilles (France) test site, with respect to existing standards and products actually used in France and also provides a comparison with the global Shuttle Radar Topography Mission’s DTM supplied by NASA and widely used in the remote sensing community

Monsoon Flooding Response: a Multi-scale Approach to Water-extent Change Detection

This paper has the aim of illustrating an automatic and speditive way for retrieving inundation extent from multispectral and multitemporal satellite data, together with land-cover changes caused by flooding events, which is a fundamental issue for managing a reconstruction plan after the event. A straightforward method to map inundated areas was applied in the North-Eastern region of Bangladesh, heavily struck by monsoonal rains in September 2000. This method in based on the Principal Components Transform (PCT) of multispectral satellite data, in its Spectral-Temporal implementation, followed by logical filtering and image segmentation, in order to reach the needed coherency of the results. The use of multiresolution data (28.5-meters ground resolution Landsat-7/ETM+ and 1,100-meters ground resolution NOAA-14/AVHRR) makes possible to evaluate hazard affected areas at different scales. Comparison to RADARSAT-derived water extension maps assessed an Overall Accuracy between 86.4% (for the flood map derived with NOAA-14/AVHRR data over the whole Bangladesh) and 90.6% (for the flood map derived with Landsat-7/ETM+ data over the North-East part of the country)

Inundated Area Delineation Using MODIS Data: Towards a Global Scale Geo-Database of Flood Events

The availability of global and accurate information is the primary factor affecting the possibility of planning and managing effective disaster response strategies, above all in less developed countries. The second determinant factor that avoids the full spreading of remote sensing technologies is cost-effectiveness and steadiness of results. This paper illustrates a straightforward method for rapid retrieval of inundation maps at regional and global scale by processing MODIS data with the Spectral-Temporal Principal Components Analysis and Digital Terrain Model filtering. Case studies are presented for three different vulnerable regions in developing countries struck by a severe river flood during the last year (2005, from spring to fall): India, Pakistan and Romania. For all the events studied it was obtained an overall accuracy greater than 95% and a kappa coefficient grater than 0.70, demonstrating this methodology is very accurate in mapping inundated areas. Moreover, the integration with vector data (such as roads, railways or urbanized areas) may be used to fast detect infrastructure damages at regional and global scale. This work is the first step to develop a global geo-database of flood-affected areas, a basic tool for helping public administrators in efficiently managing natural hazards. This is especially useful for less developed countries, which unfortunately suffer the heaviest damages because of the high density of population and the scarcity of prevention and rapid response strategies

Calibration of close-range thermal imagery for integration into 3D VR models

The appearance of terrestrial laser scanners (TLS) has provided a new data source of geometric information. Several TLS allow to be equipped by a calibrated camera, whose images may be directly mapped on the DSM as photo-texture. Here a further improvement is proposed, i.e. the integration of thermal imagery into the 3D model in order to acquire knowledge about internal stratigraphy of walls, floors, ceilings and other ancient structures. Obviously, a fundamental pre-requisite to obtain this task is the calibration of thermal sensor and the orientation of each image into the object reference system of the TLS data. Unfortunately, due to the poor radiometric and geometric quality of themal images, their integration into the TLS 3D model is a complex task; moreover, looking for control points which could be measured on both 3D model and thermal image is not trivial. This leads to the failure of methods performing calibration and orientation in a unique task, such as self-calibration approaches. Calibration has to be performed in laboratory. We have performed the calibration of a thermal camera NEC Thermotracer TH 7102 WX by means of a calibration dig and the computation of inner calibration in a bundle block l.s. adjustment. Data processing has been performed by using a low-cost photogrammetric commercial software

A new methodology for in-flight radiometric calibration of the MIVIS imaging sensor

Sensor radiometric calibration is of great importance in computing physical values of radiance of the investigated targets, but often airborne scanners are not equipped with any in-flight radiometric calibration facility. Consequently, the radiometric calibration or airborne systems usually relies only on pre-flight and vicarious calibration or on indirect approaches. This paper introduces an experimental approach that makes use of on-board calibration techniques to perform the radiometric calibration of the CNR’s MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) airborne scanner. This approach relies on the use of an experimental optical test bench originally designed at Politecnico di Milano University (Italy), called MIVIS Flying Test Bench (MFTB), to perform the first On-The-Fly (OTF) calibration of the MIVIS reflective spectral bands. The main task of this study is to estimate how large are the effects introduced by aircraft motion (e.g., e.m. noise or vibrations) and by environment conditions (e.g., environment temperature) on the radiance values measured by the MIVIS sensor during the fly. This paper describes the first attempt to perform an On-The-Fly (OTF) calibration of the MIVIS reflective spectral bands (ranging from 430 nm to 2.500 nm). Analysis of results seems to point out limitations of traditional radiometric calibration methodology based only on pre-flight approaches, with important implications for data quality assessment

AUTOMATIC REGISTRATION OF MULTI-SOURCE MEDIUM RESOLUTION SATELLITE DATA

Multi-temporal and multi-source images gathered from satellite platforms are nowadays a fundamental source of information in several domains. One of the main challenges in the fusion of different data sets consists in the registration issue, i.e., the integration into the same framework of images collected with different spatial resolution and acquisition geometry. This paper presents a novel methodology to accomplish this task on the basis of a method that stands out from existing approaches. The whole data (time series) set is simultaneously co-registered with a two-dimensional multiple Least Squares adjustment with different geometric transformations implemented. Some tests were carried out with different geometric transformation models (including similarity, affine, and polynomial) and variable matching thresholds. They showed a sub-pixel precision after the computation of multiple adjustment. The use of multi-image corresponding points allowed the improvement of the registration accuracy and reliability of a time series made up of data imaged with different sensors

A DNA algorithm for the batimetric mapping in the lagoon of Venice using QuickBird multispectral data.

During the last decade, several studies have focused on the use of passive multispectral remote sensing to derive the bathymetry in coastal zone. In particular, data acquired with the SPOT and the Landsat TM/ETM+ sensors have been used to derive models of bathymetry at medium scales. Until now, the successful application of passive remote sensing techniques to bathymetry mapping was restricted to costal zones with clear water and small changes in the seabed, but with the availability of the high resolution satellites (IKONOS, Eros-A1, QuickBird, SPOT-5), researchers have a new powerful tools to study environmental phenomenon at large scale. This paper focus on the use of high resolution imagery to estimate water depths in a lagoon environment. Starting from the depth of penetration zone method proposed by Jupp for costal bathymetry mapping, a new genetic algorithm was developed for lagoon bathymetry mapping. The potential use of the QuickBird multispectral data, together with the new algorithm developed, was tested in a complex environment such as the lagoon of Venice (Italy). Several tests have been performed into five different test sites (S.Erasmo littoral, Treporti canal, S. Felice canal, Canesa canal and Bari canal), where 18 radiometric transects were traced to study the lagoon bathymetry. The accuracy of the batimetric measures was assessed by using other known soundings depth points within the test area. An interesting correlation between the real and the computed bathymetry was found. The limit of a such analysis lies in the correct calibration of the model, that, for the complex lagoon ecosystem, is not a simple task

A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2values obtained for both optical and radar images

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

The spaceborne imaging spectroscopy mission PRecursore IperSpettrale della Missione Applicativa (PRISMA), launched on 22 March 2019 by the Italian Space Agency, opens new opportunities in many scientific domains, including precision farming and sustainable agriculture. This new Earth Observation (EO) data stream requires new-generation approaches for the estimation of important biophysical crop variables (BVs). In this framework, this study evaluated a hybrid approach, combining the radiative transfer model PROSAIL-PRO and several machine learning (ML) regression algorithms, for the retrieval of canopy chlorophyll content (CCC) and canopy nitrogen content (CNC) from synthetic PRISMA data. PRISMA-like data were simulated from two images acquired by the airborne sensor HyPlant, during a campaign performed in Grosseto (Italy) in 2018. CCC and CNC estimations, assessed from the best performing ML algorithms, were used to define two relations with plant nitrogen uptake (PNU). CNC proved to be slightly more correlated to PNU than CCC (R-2 = 0.82 and R-2 = 0.80, respectively). The CNC-PNU model was then applied to actual PRISMA images acquired in 2020. The results showed that the estimated PNU values are within the expected ranges, and the temporal trends are compatible with plant phenology stages

Mapping Asbestos-Cement Roofing with Hyperspectral Remote Sensing over a Large Mountain Region of the Italian Western Alps

The World Health Organization estimates that 100 thousand people in the world die every year from asbestos-related cancers and more than 300 thousand European citizens are expected to die from asbestos-related mesothelioma by 2030. Both the European and the Italian legislations have banned the manufacture, importation, processing and distribution in commerce of asbestos-containing products and have recommended action plans for the safe removal of asbestos from public and private buildings. This paper describes the quantitative mapping of asbestos-cement covers over a large mountainous region of Italian Western Alps using the Multispectral Infrared and Visible Imaging Spectrometer sensor. A very large data set made up of 61 airborne transect strips covering 3263 km2 were processed to support the identification of buildings with asbestos-cement roofing, promoted by the Valle d’Aosta Autonomous Region with the support of the Regional Environmental Protection Agency. Results showed an overall mapping accuracy of 80%, in terms of asbestos-cement surface detected. The influence of topography on the classification’s accuracy suggested that even in high relief landscapes, the spatial resolution of data is the major source of errors and the smaller asbestos-cement covers were not detected or misclassified