Floodplain Settlement Dynamics in the Maouri Dallol at Guéchémé, Niger: A Multidisciplinary Approach

In Sahelian Africa, rural centers have been hit by catastrophic floods for many years. In order to prevent the impact of flooding, the flood-prone areas and the settlement dynamics within them must be identified. The aim of this study is to ascertain the floodplain settlement dynamics in the Maouri valley (135 km2) in the municipality of Guéchémé, Niger. Through hydraulic modeling, the analysis identified the flood-prone areas according to three return periods. The dynamics of the settlements in these areas between 2009 and 2019 were identified through the photointerpretation of high-resolution satellite images and compared with those in the adjacent non-flood-prone areas. Spatial planning was applied to extract the main dynamics. The synergic application of these disciplines in a rural context represents a novelty in the research field. Since 2009, the results have shown a 52% increase of the built-up area and a 12% increase in the number of buildings, though the increase was higher in the flood-prone areas. The factors that transform floods into catastrophes were identified through perceptions gathered from the local communities. Three dynamics of the expansion and consolidation of buildings were observed. Specific flood risk prevention and preparation actions are proposed for each type of dynamic

ARE MEASURED GROUND CONTROL POINTS STILL REQUIRED IN UAV BASED LARGE SCALE MAPPING? ASSESSING THE POSITIONAL ACCURACY OF AN RTK MULTI-ROTOR PLATFORM

The estimate of External Orientation (E.O.) parameters for a block of images is a crucial step in the photogrammetric pipeline and the most demanding in terms of required time and human effort, both during the fieldwork and post-processing phases. Different researchers developed strategies to minimize the impact of this phase. Despite the achievement of good results, it was not possible until now to completely cancel the effect of this step. However, the efforts of the researchers in these years have also been devoted to the implementation of direct photogrammetry strategies, in order to almost completely automate the E.O. of the photogrammetric block. These new approaches were made possible also thanks to the latest developments of commercial UAVs, especially in terms of the installed GPS/GNSS (Global Positioning System/Global Navigation Satellite System) hardware. The aim of this manuscript is to evaluate the different perspectives and issues connected with the deployment of a UAV (Unmanned Aerial Vehicle) equipped with a multi-frequency GPS/GNSS receiver. Starting from the considerations mentioned above and leveraging previous works based on a fixed-wing platform, the focus of this contribution is the assessment of the real performances of an RTK multi-rotor platform addressing several questions. Is it possible to generate added-value products with centimetre 3D accuracies without measuring any ground control point? Which are the operational requirements to be taken into account in the planning phase? Are consolidated UAV mapping operational workflows already available to enable a robust direct georeferencing approach

Boosting the timeliness of UAV large scale mapping. Direct georeferencing approaches: operational strategies and best practices

3noThe use of unmanned aerial vehicles (UAVs) is nowadays a standard approach in several application fields. Researches connected with these systems cover several topics and the evolution of these platforms and their applications are rapidly growing. Despite the high level of automatization reached nowadays, there is still a phase of the overall UAVs' photogrammetric pipeline that requires a high effort in terms of time and resources (i.e., the georeferencing phase). However, thanks to the availability of survey-grade GNSS (Global Navigation Satellite System) receivers embedded in the aerial platforms, it is possible to also enhance this phase of the processing by adopting direct georeferencing approaches (i.e., without using any ground control point and exploiting real time kinematic (RTK) positioning). This work investigates the possibilities offered by a multirotor commercial system equipped with a RTK-enabled GNSS receiver, focusing on the accuracy of the georeferencing phase. Several tests were performed in an ad-hoc case study exploiting different georeferencing solutions and assessing the 3D positional accuracies, thanks to a network of control points. The best approaches to be adopted in the field according to accuracy requirements of the final map products were identified and operational guidelines proposed accordingly.openopenLorenzo Teppati Losè; Filiberto Chiabrando; Fabio GIulio TonoloTEPPATI LOSE', Lorenzo; Chiabrando, Filiberto; GIULIO TONOLO, Fabi

A low cost mobile mapping system (LCMMS) for field data acquisition: a potential use to validate aerial/satellite building damage assessment

Among the major natural disasters that occurred in 2010, the Haiti earthquake was a real turning point concerning the availability, dissemination and licensing of a huge quantity of geospatial data. In a few days several map products based on the analysis of remotely sensed data-sets were delivered to users. This demonstrated the need for reliable methods to validate the increasing variety of open source data and remote sensing-derived products for crisis management, with the aim to correctly spatially reference and interconnect these data with other global digital archives. As far as building damage assessment is concerned, the need for accurate field data to overcome the limitations of both vertical and oblique view satellite and aerial images was evident. To cope with the aforementioned need, a newly developed Low-Cost Mobile Mapping System (LCMMS) was deployed in Port-au-Prince (Haiti) and tested during a five-day survey in FebruaryMarch 2010. The system allows for acquisition of movies and single georeferenced frames by means of a transportable device easily installable (or adaptable) to every type of vehicle. It is composed of four webcams with a total field of view of about 180 degrees and one Global Positioning System (GPS) receiver, with the main aim to rapidly cover large areas for effective usage in emergency situations. The main technical features of the LCMMS, the operational use in the field (and related issues) and a potential approach to be adopted for the validation of satellite/aerial building damage assessments are thoroughly described in the articl

Documentation of Complex Environments Using 360° Cameras. The Santa Marta Belltower in Montanaro

Low-cost and fast surveying approaches are increasingly being deployed in several domains, including in the field of built heritage documentation. In parallel with mobile mapping systems, uncrewed aerial systems, and simultaneous location and mapping systems, 360° cameras and spherical photogrammetry are research topics attracting significant interest for this kind of application. Although several instruments and techniques can be considered to be consolidated approaches in the documentation processes, the research presented in this manuscript is focused on a series of tests and analyses using 360° cameras for the 3D metric documentation of a complex environment, applied to the case study of a XVIII century belltower in Piemonte region (north-west Italy). Both data acquisition and data processing phases were thoroughly investigated and several processing strategies were planned, carried out, and evaluated. Data derived from consolidated 3D mapping approaches were used as a ground reference to validate the results derived from the spherical photogrammetry approach. The outcomes of this research confirmed, under specific conditions and with a proper setup, the possibility of using 360° images in a Structure from Motion pipeline to meet the expected accuracies of typical architectural large-scale drawings

Structural Building Damage Detection with Deep Learning: Assessment of a State-of-the-Art CNN in Operational Conditions

Remotely sensed data can provide the basis for timely and efficient building damage maps that are of fundamental importance to support the response activities following disaster events. However, the generation of these maps continues to be mainly based on the manual extraction of relevant information in operational frameworks. Considering the identification of visible structural damages caused by earthquakes and explosions, several recent works have shown that Convolutional Neural Networks (CNN) outperform traditional methods. However, the limited availability of publicly available image datasets depicting structural disaster damages, and the wide variety of sensors and spatial resolution used for these acquisitions (from space, aerial and UAV platforms), have limited the clarity of how these networks can effectively serve First Responder needs and emergency mapping service requirements. In this paper, an advanced CNN for visible structural damage detection is tested to shed some light on what deep learning networks can currently deliver, and its adoption in realistic operational conditions after earthquakes and explosions is critically discussed. The heterogeneous and large datasets collected by the authors covering different locations, spatial resolutions and platforms were used to assess the network performances in terms of transfer learning with specific regard to geographical transferability of the trained network to imagery acquired in different locations. The computational time needed to deliver these maps is also assessed. Results show that quality metrics are influenced by the composition of training samples used in the network. To promote their wider use, three pre-trained networks—optimized for satellite, airborne and UAV image spatial resolutions and viewing angles—are made freely available to the scientific community

THERMAL AND OPTICAL DATA FUSION SUPPORTING BUILT HERITAGE ANALYSES

The recent developments of passive sensors techniques, that have been able to take advantage of the technological innovations related to sensors technical features, sensor calibration, the use of UAV systems (Unmanned Aerial Vehicle), the integration of image matching techniques and SfM (Structure from Motion) algorithms, enable to exploit both thermal and optical data in multi-disciplinary projects. This synergy boost the application of Infrared Thermography (IRT) to new application domains, since the capability to provide thematic information of the analysed objects benefits from the typical advantages of data georeferencing and metric accuracy, being able to compare results investigating different phenomena. This paper presents a research activity in terrestrial and aerial (UAV) applications, aimed at generating photogrammetric products with certified and controlled geometric and thematic accuracy even when the acquisitions of thermal data were not initially designed for the photogrammetric process. The basic principle investigated and pursued is the processing of a photogrammetric block of images, including thermal IR and optical imagery, using the same reference system, which allows the use of co-registration algorithms. Such approach enabled the generation of radiance maps, orthoimagery and 3D models embedding the thermal information of the investigated surfaces, also known as texture mapping; these geospatial dataset are particularly useful in the context of the built Heritage documentation, characterised by complex analyses challenges that a perfect fit for investigations based on interdisciplinary approaches

Rapid Mapping: geomatics role and research opportunities

In recent years an increasing number of extreme meteorological events have been recorded. Geomatics techniques have been historically adopted to support the different phases of the Emergency Management cycle with a main focus on emergency response, initial recovery and preparedness through the acquisition, processing, management and dissemination of geospatial data. In the meantime, the increased availability of geospatial data in terms of reference topographic datasets, made available by authoritative National Mapping Cadastre Agencies or by Collaborative Mapping initiatives like OpenStreetMap, as well as of remotely sensed imagery, poses new challenges to the Geomatics role in defining operational tools and services in support of emergency management activities. This paper is mainly focused on the role of Geomatics in supporting the response phase of the Emergency Management cycle through Rapid Mapping activities, which can be defined as “the on-demand and fast provision (within hours or days) of geospatial information in support of emergency management activities immediately following an emergency event” (source: European Union, http://emergency.copernicus.eu/mapping/ems/service-overview). Management of geospatial datasets (both reference and thematic), Remote Sensing sensors and techniques and spatial information science methodologies applied to Rapid Mapping will be described, with the goal to highlight the role that Geomatics is currently playing in this domain. The major technical requirements, constraints and research opportunities of a Rapid Mapping service will be discussed, with a specific focus on: the time constraints of the service, the data quality requirements, the need to provide replicable products, the need for consistent data models, the advantages of data interoperability, the automation of feature extraction procedures to reduce the need for Computer Aided Photo Interpretation, the dissemination strategies