The XII century towers, a benchmark of the Rome countryside almost cancelled. The safeguard plan by low cost uav and terrestrial DSM photogrammetry surveying and 3D Web GIS applications

“Giving a bird-fly look at the Rome countryside, throughout the Middle Age central period, it would show as if the multiple city towers has been widely spread around the territory” on a radial range of maximum thirty kilometers far from the Capitol Hill center (Carocci and Vendittelli, 2004). This is the consequence of the phenomenon identified with the “Incasalamento” neologism, described in depth in the following paper, intended as the general process of expansion of the urban society interests outside the downtown limits, started from the half of the XII and developed through all the XIII century, slowing down and ending in the following years. From the XIX century till today the architectural finds of this reality have raised the interest of many national and international scientists, which aimed to study and catalog them all to create a complete framework that, cause of its extension, didn’t allow yet attempting any element by element detailed analysis. From the described situation has started our plan of intervention, we will apply integrated survey methods and technologies of terrestrial and UAV near stereo-photogrammetry, by the use of low cost drones, more than action cameras and reflex on extensible rods, integrated and referenced with GPS and topographic survey. In the final project we intend to produce some 3D scaled and textured surface models of any artifact (almost two hundreds were firstly observed still standing), to singularly study the dimensions and structure, to analyze the building materials and details and to formulate an hypothesis about any function, based even on the position along the territory. These models, successively georeferenced, will be imported into a 2D and 3D WebGIS and organized in layers made visible on basemaps of reference, as much as on historical maps

THE EVALUATION OF MEASURING STREAM CHANNEL MORPHOLOGY USING UNMANNED AERIAL SYSTEM-BASED STRUCTURE-FROM-MOTION PHOTOGRAMMETRY

As part of a collaborative project at a stream segment reach on Proctor Creek in Atlanta, GA, UAV-based SfM photogrammetry was tested as a method for collecting fluvial topographic data relative to traditional USGS total station surveying methods. According to the USGS method, 11 transects were surveyed, and imagery was collected via a UAV to create a SfM DEM. The resulting DEM was incomplete but showed promise for the SfM method. Two additional stream segments were chosen in the Atlanta area, the first along SFPC in DHCL and the second along NFPC near Buford Hwy. For each site 11 transects were surveyed along with submerged GCPs so that the SfM DEMs could be compared to the surveyed data. The BW and BD values were collected from the TS transects and the DEM transects and compared according to the percent difference between the two. For SFPC, the average percent difference values for BW and BD were, respectively, 15.9 and 26.0 with standard deviations of 15.7 and 18.0. For NFPC, the BW and BD average percent difference values were 6.8 and 7.5 with standard deviations of 3.9 and 5.9. The GCPs were also compared for each site using linear regressions. There was no strong correlation for SFPC (R2 = 0.31 and p-value \u3e 0.05), but there was a strong relationship indicated for NFPC (R2 = 0.78 and p-value \u3c 0.05). While the results of this study are variable, the results do indicate promise for future work on this emerging method

Remote Sensing for River Restoration and Dam Removal Studies

Inspired by the influence of drone applications in scientific research, my Summer Undergraduate Research Fellowship (SURF) study aimed to improve the accuracy of riverine topographic modeling by testing the use of terrestrial and submerged aquatic ground control points (GCPs) in drone surveys of the Bellamy River Reservoir. Accurate mapping of riverscapes is critical to investigations of before-and-after management activities, such as dam removals, and to better understanding topographic features created by physical, chemical, and biological processes in rivers and watersheds. These studies build on our increasing understanding and quantification of the cycling of chemical and biological substances in rivers and the valuable ecological services that watersheds provide. The evolution of remote sensing, drone technology, and digital elevation models provide an alternative to conventional, labor-intensive ground survey measurements and are of increasing importance for creating topographic products valuable to studies of riverscapes and watershed processes. Land-based GCPs are routinely used to develop highly accurate models; however, in rivers we seek to accurately measure submerged topography, which has been done only in limited environments because of numerous technical challenges. Incorporating submerged GCPs into drone workflows may be a simple yet effective way to improve in-stream topography models. Results of this study are expected to contribute key information for restoration planning for rivers and other aquatic habitats and studies of land use and impacts of human infrastructure, especially dams, in the hopes of creating and maintaining a more sustainable relationship with our natural environment

High resolution geomatics techniques for coastline detection and monitoring: Boccasette and Barricata case studies (Po River Delta, Rovigo, Italy).

The topic studied in this thesis aims to analyze an experimental approach for the definition of a methodology that allows the identification of the coastline, or instantaneous coastline, perceived as a land-sea-air interface. As we will see its geographical boundaries are not easily defined in a universal way, we will see through the comparison between three different methodologies, including the GNSS system the classical topography and the methodology of photogrammetric survey Sfm (structure from motion), the difficulties encountered in defining an extension to land and sea that delimits the coastline in a unique way. The treated area concerns areas on the Po delta, specifically the beaches of Boccasette and Barricata. In the chapters will be addressed the various aspects, first analyzing the context of reference, identifying the location, with an introduction to the coastal reality in question, characterized by phenomena such as subsidence, a worrying phenomenon for the Po delta area, monitored by several studies over the years. The various methodologies applied in the context will be explained, exposing the characteristics of the same to understand their potential in the case study, then passing to the software used to process data and obtain the output. The data obtained with the various methodologies have been compared with each other in GIS thanks to the potential that the software offers, proving practical and fast. The approach of the study mainly uses the distance and the area between the segments joining the points detected, evaluating the differences in terms of mean and standard deviation, to establish, also on the basis of the operator’s interpretation, which of the following methodologies is the most practical, precise and fast for monitoring purposes. We then went on to compare and discuss the results obtained with the various methods, highlighting the more or less significant variations. As we will see, there is a certain difference between the methodologies used directly in the field, by measuring the physical points and the Sfm technique, influenced as we will see by many factors. The coastline at zero level obtained through a DTM (Digital Terrain Model) was subsequently superimposed and compared with the coastline extracted from a LiDAR survey performed in 2018. This second activity allowed, through appropriate processing, a four-year multi-time analysis of coastline changes and the identification and classification of areas of expansion and erosion. The research thus made it possible to: - A comparison between the different methodologies comparing their applicability and limits; - Evaluate and define the most appropriate relevant technique to study and identify the coastline; - Define the accuracy parameters for modelling the detected elements; - The creation of a database for possible future comparisons of coastal variations; - The possibility of conducting a multi-temporal analysis with available LiDAR data.The topic studied in this thesis aims to analyze an experimental approach for the definition of a methodology that allows the identification of the coastline, or instantaneous coastline, perceived as a land-sea-air interface. As we will see its geographical boundaries are not easily defined in a universal way, we will see through the comparison between three different methodologies, including the GNSS system the classical topography and the methodology of photogrammetric survey Sfm (structure from motion), the difficulties encountered in defining an extension to land and sea that delimits the coastline in a unique way. The treated area concerns areas on the Po delta, specifically the beaches of Boccasette and Barricata. In the chapters will be addressed the various aspects, first analyzing the context of reference, identifying the location, with an introduction to the coastal reality in question, characterized by phenomena such as subsidence, a worrying phenomenon for the Po delta area, monitored by several studies over the years. The various methodologies applied in the context will be explained, exposing the characteristics of the same to understand their potential in the case study, then passing to the software used to process data and obtain the output. The data obtained with the various methodologies have been compared with each other in GIS thanks to the potential that the software offers, proving practical and fast. The approach of the study mainly uses the distance and the area between the segments joining the points detected, evaluating the differences in terms of mean and standard deviation, to establish, also on the basis of the operator’s interpretation, which of the following methodologies is the most practical, precise and fast for monitoring purposes. We then went on to compare and discuss the results obtained with the various methods, highlighting the more or less significant variations. As we will see, there is a certain difference between the methodologies used directly in the field, by measuring the physical points and the Sfm technique, influenced as we will see by many factors. The coastline at zero level obtained through a DTM (Digital Terrain Model) was subsequently superimposed and compared with the coastline extracted from a LiDAR survey performed in 2018. This second activity allowed, through appropriate processing, a four-year multi-time analysis of coastline changes and the identification and classification of areas of expansion and erosion. The research thus made it possible to: - A comparison between the different methodologies comparing their applicability and limits; - Evaluate and define the most appropriate relevant technique to study and identify the coastline; - Define the accuracy parameters for modelling the detected elements; - The creation of a database for possible future comparisons of coastal variations; - The possibility of conducting a multi-temporal analysis with available LiDAR data

Shallow Water Bathymetry Mapping from UAV Imagery based on Machine Learning

The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research. UAV imagery processed with Structure from Motion (SfM) and Multi View Stereo (MVS) techniques can provide a low-cost alternative to established shallow seabed mapping techniques offering as well the important visual information. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this paper, in order to overcome the water refraction errors, we employ machine learning tools that are able to learn the systematic underestimation of the estimated depths. In the proposed approach, based on known depth observations from bathymetric LiDAR surveys, an SVR model was developed able to estimate more accurately the real depths of point clouds derived from SfM-MVS procedures. Experimental results over two test sites along with the performed quantitative validation indicated the high potential of the developed approach.Comment: 8 pages, 9 figure

Integrated imaging approaches supporting the excavation activities. Multi-scale geospatial documentation in hierapolis (TK)

The paper focuses on the exploration of the suitability and the discretization of applicability issues about advanced surveying integrated techniques, mainly based on image-based approaches compared and integrated to range-based ones that have been developed with the use of the cutting-edge solutions tested on field. The investigated techniques integrate both technological devices for 3D data acquisition and thus editing and management systems to handle metric models and multi-dimensional data in a geospatial perspective, in order to innovate and speed up the extraction of information during the archaeological excavation activities. These factors, have been experienced in the outstanding site of the Hierapolis of Phrygia ancient city (Turkey), downstream the 2017 surveying missions, in order to produce high-scale metric deliverables in terms of high-detailed Digital Surface Models (DSM), 3D continuous surface models and high-resolution orthoimages products. In particular, the potentialities in the use of UAV platforms for low altitude acquisitions in aerial photogrammetric approach, together with terrestrial panoramic acquisitions (Trimble V10 imaging rover), have been investigated with a comparison toward consolidated Terrestrial Laser Scanning (TLS) measurements. One of the main purposes of the paper is to evaluate the results offered by the technologies used independently and using integrated approaches. A section of the study in fact, is specifically dedicated to experimenting the union of different sensor dense clouds: both dense clouds derived from UAV have been integrated with terrestrial Lidar clouds, to evaluate their fusion. Different test cases have been considered, representing typical situations that can be encountered in archaeological sites

Determination of Elevations for Excavation Operations Using Drone Technologies

Using deep learning technology to rapidly estimate depth information from a single image has been studied in many situations, but it is new in construction site elevation determinations, and challenges are not limited to the lack of datasets. This dissertation presents the research results of utilizing drone ortho-imaging and deep learning to estimate construction site elevations for excavation operations. It provides two flexible options of fast elevation determination including a low-high-ortho-image-pair-based method and a single-frame-ortho-image-based method. The success of this research project advanced the ortho-imaging utilization in construction surveying, strengthened CNNs (convolutional neural networks) to work with large scale images, and contributed dense image pixel matching with different scales.This research project has three major tasks. First, the high-resolution ortho-image and elevation-map datasets were acquired using the low-high ortho-image pair-based 3D-reconstruction method. In detail, a vertical drone path is designed first to capture a 2:1 scale ortho-image pair of a construction site at two different altitudes. Then, to simultaneously match the pixel pairs and determine elevations, the developed pixel matching and virtual elevation algorithm provides the candidate pixel pairs in each virtual plane for matching, and the four-scaling patch feature descriptors are used to match them. Experimental results show that 92% of pixels in the pixel grid were strongly matched, where the accuracy of elevations was within ±5 cm.Second, the acquired high-resolution datasets were applied to train and test the ortho-image encoder and elevation-map decoder, where the max-pooling and up-sampling layers link the ortho-image and elevation-map in the same pixel coordinate. This convolutional encoder-decoder was supplemented with an input ortho-image overlapping disassembling and output elevation-map assembling algorithm to crop the high-resolution datasets into multiple small-patch datasets for model training and testing. Experimental results indicated 128×128-pixel small-patch had the best elevation estimation performance, where 21.22% of the selected points were exactly matched with “ground truth,” 31.21% points were accurately matched within ±5 cm. Finally, vegetation was identified in high-resolution ortho-images and removed from corresponding elevation-maps using the developed CNN-based image classification model and the vegetation removing algorithm. Experimental results concluded that the developed CNN model using 32×32-pixel ortho-image and class-label small-patch datasets had 93% accuracy in identifying objects and localizing objects’ edges

Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)

Nowadays, emerging technologies, such as long-range transmitters, increasingly miniaturized components for positioning, and enhanced imaging sensors, have led to an upsurge in the availability of new ecological applications for remote sensing based on unmanned aerial vehicles (UAVs), sometimes referred to as “drones”. In fact, structure-from-motion (SfM) photogrammetry coupled with imagery acquired by UAVs offers a rapid and inexpensive tool to produce high-resolution orthomosaics, giving ecologists a new way for responsive, timely, and cost-effective monitoring of ecological processes. Here, we adopted a lightweight quadcopter as an aerial survey tool and object-based image analysis (OBIA) workflow to demonstrate the strength of such methods in producing very high spatial resolution maps of sensitive marine habitats. Therefore, three different coastal environments were mapped using the autonomous flight capability of a lightweight UAV equipped with a fully stabilized consumer-grade RGB digital camera. In particular we investigated a Posidonia oceanica seagrass meadow, a rocky coast with nurseries for juvenile fish, and two sandy areas showing biogenic reefs of Sabelleria alveolata. We adopted, for the first time, UAV-based raster thematic maps of these key coastal habitats, produced after OBIA classification, as a new method for fine-scale, low-cost, and time saving characterization of sensitive marine environments which may lead to a more effective and efficient monitoring and management of natural resource

POINT CLOUD-BASED SURVEY FOR CULTURAL HERITAGE. AN EXPERIENCE OF INTEGRATED USE OF RANGE-BASED AND IMAGE-BASED TECHNOLOGY FOR THE SAN FRANCESCO CONVENT IN MONTERUBBIANO

The paper aims at presenting some results of a point cloud-based survey carried out through integrated methodologies based on active and passive 3D acquisition techniques for processing 3D models. This experiment is part of a research project still in progress conducted by an interdisciplinary team from the School of Architecture and Design of Ascoli Piceno and funded by the University of Camerino. We describe an experimentation conducted on the convent of San Francesco located in Monterubbiano town center (Marche, Italy). The whole complex has undergone a number of substantial changes since the year of its foundation in 1247. The survey was based on an approach blending range-based 3D data acquired by a TOF laser scanner and image-based 3D acquired using an UAV equipped with digital camera in order to survey some external parts difficult to reach with TLS. The integration of two acquisition methods aimed to define a workflow suitable to process dense 3D models from which to generate high poly and low poly 3D models useful to describe complex architectures for different purposes such as photorealistic representations, historical documentation, risk assessment analyses based on Finite Element Methods (FEM)