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In the perspective of long and dense time-series analyses for environmental monitoring applications, this article discusses a cross-comparison analysis between the different instruments of Landsat and Sentinel missions [thematic mapper (TM), enhanced thematic mapper plus (ETM+), operational land imager (OLI), and multispectral instrument (MSI)]. The level-2 surface reflectance (SR) products were considered (in particular, the reprocessed Collection-2 for Landsat). The calibration coefficients for four of the most popular vegetation indexes [normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), soil adjusted vegetation index (SAVI), and normalized difference moisture index (NDMI)] were estimated, with the aim of harmonizing and minimizing radiometric differences for the combined use of these sensors. For this purpose, more than 20000 pairs of images almost simultaneously acquired (±1-day tolerance window) were selected over a period of several years (depending on the lifespan overlap of every sensor pair). Vegetation indices (VIs) were computed for each image, and for each cross comparison, 100 random extractions of 300 000 sample pixels were performed all over the European continent. Linear transformation functions for each VI and between each sensor couple were computed by regression analyses, also assessing the repeatability of the estimation. Furthermore, the stability over time of the obtained coefficients was assessed when enough years of corresponding observations are available.

The new geomatic techniques and technologies for surveying an archeological excavation are not limited to obtaining more accurate data or more precisely geo-referenced positions on a map, as they can lead to new approaches and, indeed, raise the concept of different dimensions relating to the handled information. The techniques on offer are now fully 3D and, even more interestingly, can also permit to handle temporal information, that is, the evolution of operations over time. This allows scholars and technicians to build and maintain a wealth of vital knowledge documenting what happens during an excavation. This is further true when these are in urban areas, often known as “emergency excavations” from their distinctive logistics and timing constraints. The aim of this paper is to present, in a practical context, some of the many capabilities of 3D surveying performed through digital photogrammetry based on multi-view structure-from-motion approach in the field of urban emergency archeology. The information that can be derived from exploring three-dimensional models allows us to interact with realities that no longer exist, with the possibility not merely of recording their memory, but also of further studies and insights, even after a long period of time. In addition, the excavation itself is documented as it evolves, thus allowing the main phases of the process to be reconstructed retrospectively. The study case examined covers a small necropolis discovered in Rimini (Italy) in 2015. The results and the 3D final products can be managed through Geographic Information System (GIS) tools and, therefore, can easily be interfaced and integrated with other types of information on a different scale.

Slurry microsurfacing is an economical maintenance intervention that provides effective skid resistance and surface evenness in a thin layer, thus improving the road safety. Researchers aimed to develop an innovative application of slurry seal, capable of gathering in a single material some technical solutions for various functional and environmental aspects. The purposes of this intervention are: restoring skid resistance, sealing surface cracking, reducing tire/pavement noise, adding crumb rubber from tires as a recycling material and reducing atmospheric emissions using the cold technique. A 3D laser scanner device has been used to evaluate the surface texture and analyze the roughness parameters.

This paper presents a methodology for quantifying the number of buildings that collapsed following the Bam earthquake. The approach is object rather than pixel-oriented, commencing with the inventory of buildings as objects in high-resolution QuickBird satellite imagery captured before the event. The number of collapsed structures is computed based on the unique statistical characteristics of these objects/buildings within the “after” scene. A total of 18,872 structures were identified within Bam, of which the results suggest that 34% collapsed—a total of 6,473. Preliminary assessments indicate an overall accuracy for the damage classification of 70.5%.

Simple but objective criteria for evaluating the quality of DTMs, derived from digital contour lines, are defined. Such criteria are then applied to terrain models, obtained by means of four different procedures, which refer to three sample areas characterized by complex morphological settings. The results of the comparison shows that each DTM is affected by one or more types of error or pitfall; however, one TIN generator and one grid interpolator proved to be capable of effectively producing terrain models which largely reflect the ground morphology as expressed by the input contour lines.

Nowadays, a growing necessity for preservation and documentation of the Cultural Heritage is related to the precise 3D surveys as the input for multidisciplinary analysis. An efficient tool that meets the aforementioned requirement is the HBIM approach, linked to numerical models for structural analysis. In this context, the innovative CLOUD2FEM procedure, which semi-automatically generates numerical models from point clouds, has been applied to the surveyed point clouds - obtained by laser scanning - in a complex case study of a damaged building: the San Felice sul Panaro Fortress (Italy), hit by a severe earthquake in 2012. The numerical model generated is employed in the framework of advanced seismic nonlinear analysis. The promising results show the effectiveness of the method.

The assessment of surface water salinity is a long standing feature request for water quality assessment by remote sensing. The aim of the present work is to test an empirical method for surface water salinity retrieval by means of multispectral satellite images at medium resolution (30 m). For this purpose, two case studies were selected: the first is Lake Qarun (Egypt), the second is an on-shore tract of central Adriatic Sea, located between the mouths of Tronto and Salinello Rivers (Italy). For the experimentation ALI (Advanced Land Imager) and Landsat ETM imagery was collected. Field data were acquired at both sites by means of in situ conductivity measurements, for calibration purpose. The model applied to convert atmospherically corrected reflectance value in practical salinity units (PSU) has been developed analysing the correlation between field data and an expressly defined salinity index. First results show a promising overall correlation (R2= 0.85), even if further work is required to provide a better validation.