The Role of UAS–GIS in Digital Era Governance. A Systematic Literature Review

Abstract

UAS (Unmanned Aircraft Systems) technologies, also known as UAV (Unmanned Aerial Vehicle), drones, or Remotely Piloted Aircraft System (RPAS) and GIS (Geographic Information System) are recognised for the value of the results that can be achieved by their combined use. However, their use and the results achieved are rarely framed within the context of Digital Era Governance (DEG), an undertaking that would significantly reduce the capabilities of knowledge transfer from the academic and/or private environment to the public domain. The purpose of this study was to highlight, by a bibliometric analysis, the areas of proposed use of this team of tools and the extent to which these can enter the sphere of interest of public administrations, especially local ones. From a methodological point of view, based on the 439 articles filtered from the Web of Science database where UAS/UAV and GIS technologies were used, several bibliometric analyses have emerged. VOSviewer and R (Bibliometrix tool) were used to conduct the bibliometric analyses. Most scientific publications that used UAV technology as a working tool have predominant applicability in photogrammetry, while GIS applications are found in publications dedicated to image processing, landslides, and cultural and archaeological heritage. We point out that from the point of view of international cooperation, at the level of institutions or countries, certain international organisations from the USA, China, and the central and northern European states have a high interest in this topic, and a low cooperation between academia and public administration is exhibited. The conclusion is represented by the apparent lack of framing of the results of UAS–GIS technologies usage into wider and more topical contexts, such as digital era governance, and also a reduced applicability of the research results.

1. Introduction

Digital era governance (DEG) is the descendant of New Public Management (NPM), a dominant set of theoretical and practical ideas related to management and governance from the 1985–2002 time period. DEG brings a new series of ideas and reform proposals, reaffirming the priorities neglected by NPM [1]. Digital era governance means an entire complex of changes, whose main core of concerns are the changes in IT and information management but develop simultaneously in more dimensions than in the previous case [1,2]. This concept is also associated with those of Public Value Management and New Public Governance, all three insisting on the cooperation in partnership, promoting governance, and innovation, and acknowledging the transformation potential of the digital technology [3]. According to Kosenkov et al. [4], digital governance has six dimensions: information dissemination, communication with citizens, service delivery, socioeconomic monitoring, advanced social analytics, and regulation of social life.

A sustainable transition from digital government to digital governance is the transition from a technical structure to multiple processes at different levels. From the current perspective, digital government is seen as a part of the digital governance concept, together with the business aspects and those related to political decision making (digital democracy) [5]. In more specific terms, the impact of DEG practices is translated by a reconfiguration of the electronic channels where the agency (institution) “becomes its Web site” [1].

Within digital governance, Artificial Intelligence (AI) is one of the technologies that attracts the interest of public administration due to its potential impact [3]. Three additional important terms are frequently mentioned in DEG, especially in view of the thick confusion, i.e., “digitisation”, “digitalisation”, and “digital transformation” [6,7]. The first term, digitisation, refers to the audio or video conversion into a digital format, while the third one, digital transformation, contains, de facto, a series of digitalisation projects [8]. Digital technology is ”implemented with the intent of establishing a communication infrastructure that connects various activities of the actor’s various processes” [7]. Some studies show that adoption of information innovation is often incomplete, with low impact on administrative tasks [9]. Moreover, many local administrations adopt technical innovations such as websites, while their implementation is achieved as a unidirectional source of information for residents with access to the internet.

In the context of digital governance, we can also discuss the technologies that facilitate the visualisation of some extended surfaces, at low cost, from a variable altitude (low altitude airspace-LAA), the purchase of high utility data in decision making and management of highly complex operations, which also provide solutions in data processing and analysis. Starting from this challenge, in our paper we analysed how frequently and in what combination are the UAV/UAS and GIS technologies used in the context of digitalisation through the lens of bibliometric maps. The complementarity of UAS–GIS is given by the fact that the first technology is mainly intended to collect spatial data and the second to highlight them. Reference is made to most applications, otherwise each of these technologies develops other capabilities: UAS processes the sensor-based information and GIS takes over through GNSS applications or other types of sensors. Visualisation of the relevant affiliations of the paper authors, the frequency of the co-keywords, and the international cooperation network became relevant indicators for the scientific production associated with the use of GIS–UAS as a team.

Two research questions were formulated:

(1)

When implemented, what are the main application sectors for the teaming of GIS–UAS/UAV in DEG?

(2)

What is the scientific production associated with the use of GIS–UAS and the main attributes of the working tools used?

1.1. Unmanned Aircraft Systems (UAS) and Unmanned Aircraft Vehicles (UAV)

Unmanned Systems (US) or Vehicles (UV) are defined as electromechanical systems without a human operator [10]. US can be remote (by a remote pilot) or can navigate autonomously based on preprogrammed plans, generated in First-Party Apps or Third-Party Apps [11,12] or in automatic, more dynamic, and more complex systems [13].

Unmanned Aircraft Systems (UAS), Unmanned Aerial Vehicles (UAV), Drones, or Remotely Piloted Aircraft Systems (RPAS) refer to the unmanned systems navigating in the air [14], capable of flying over hard-to-reach areas [15]. This study was based only on the references regarding civilian UAS, not those used in the military sector.

As the UAS application sectors diversify, their taxonomy also becomes more complex. So far, distribution into four main classes was proposed, based on embedded mechanism, power, user capabilities, and operating environment [16]. These make plausible the image of future smart cities where drone flights will become a normality, similar to road vehicles today [17], together with other technologies that include wireless sensor networks (WSNs), the Internet of Things (IoT), cloud computing, fog computing, and big data analytics. Among the expected applications in the literature, based on the use of UAV/UAS technologies, we mention: traffic monitoring and management, health emergency services, disaster management, security and crowd monitoring, UAS-based infrastructure inspections, agriculture management and environmental monitoring, tourism support, UAS-based surveying, merchandise order delivery, UAS-aided wireless communication, UAS taxi, virtual retrofitting applications, cinematography, human–robot interaction-based applications, UAS-based fog computing, both for urban and for rural residential environments [18,19,20,21].

On the other hand, the UAS currently address some challenges such as the prevention of risks that define rural spaces or aspects regarding the quality of life and conservation of cultural heritage [22]. Furthermore, the applicability of the UAS technology is proved also in the case of ensuring their IoT sustainability, thus making efficient the energy consumption of some IoT devices for data transmission [23]. UAS contribute also to the configuration of the future 6G internet network, a component of the Internet of Everything (IoE), a new paradigm that provides ubiquitous connections, aerial intelligence, self-maintenance of communications, sensor powering, and deployment [24,25].

We believe that all these advantages of the UAS will be powerful enough to overcome all existing barriers (threats to the data privacy and security, lack of procedures, public perception, environmental, or even technical aspects), by implementing drones in the logistics industry [17,26]. Special attention is paid to Unmanned Aerial Vehicle Regulation Policies and Technologies in Urban Low Altitude [27], because the urban environment is the testing environment of most of the technological progress elements, in the context of complexity and diversity of needs that need to be solved. Use of UAS images and the structure in motion photogrammetry with stereo multi-view (SfM-MVS) enables rapid reconstructions of the surface geometry (digital elevation models, orthophotoplans) based on the achieved and overlapped images [14].

1.2. Geographic Information Systems (GIS)

Information gathered in digital format with the sensors carried by UAS, processed in photogrammetry software, become, most of the time, an alternative to existing topographic and planimetric maps. In addition, digital maps are often used in GIS and CAD applications for design analysis [14]; in this case, we refer to monitoring or data collection activities [17].

At the same time, GIS also represents a frontier technological discipline based on information theory, cybernetics, system engineering, and artificial intelligence [28], with established implications in land management, urban and rural planning, traffic management, and environmental management [29]. A more complex image of GIS applicability, as was already provided by Usmani et al., would include five domains, each with a few distinct subdomains, such as: (a) environmental and natural resource management, (b) decision system, (c) planning and engineering, (d) street network, and (e) facilities management. Another important aspect to pursue is also the positive impact of the large databases in the GIS industry, with beneficial results in all application sectors [30].

Aside from the partnership between UAS (mainly as data processing means) and GIS (means of spatial data storage, processing, and visualisation), the latter work instrument has multiple applications. It is worth mentioning that this teamwork is not established in all application sectors. Sometimes, even if the visualisation component has become more important over the last years, the main advantage of GIS derives from its capacity to conduct complex spatial analyses. A bibliometric analysis of spatial analyses in the 1950–2019 interval highlights the utility of this tool for ecology, geography, or interdisciplinary fields such as environmental sciences, public environmental and occupational health, and multidisciplinary geosciences [31].

Spatial analyses present a high degree of utility, belonging to the Spatial Multicriteria Evaluation (SME) or GIS Multicriteria Evaluation (GME) equation, one of the most valuable techniques for management planning and decision making [32,33]. Going further, one of the development tendencies of GIS is Question Answering (QA), a process for the identification of valid answers to the questions asked by the user in natural language. This implies that the analyst may interrogate certain pieces of spatial information regarding the use of geographical resources, without having the necessary knowledge for understanding the GIS working techniques [34] or the online access to a GIS environment by inexperienced users [35].

The sample outlined communities (smart cities/smart villages) would be GIS-based, while an enterprise architecture framework/EAF would be proposed for the smart cities, supported by a hybrid model based on GIS and graphic databases (GDB). Therefore, the augmented space model created is based on the principles of an augmented and virtual reality, which include, in turn, augmented systems, maps, images, and models [36]. Applicability of the GIS tools was also proven in the implementation of sustainable development principles for rural environments [37]. When it comes to spatial data, the development trend needs to be directed towards the infrastructure of spatial data activated in the cloud (SDI), due to the numerous advantages that they imply, including the possibility of integrating with the IoT [38].

If we refer to the need of managing a territory, the basis of a twin digital model is represented by Land Information System (LIS), whose key/basic component is the cadastral survey. This begins to manage 3D, 4D (time) [39], or even 5D (level of detail) information [40]. Today, an LIS cannot be imagined without the combined contribution of GIS (which provides a macro representation of the external environments of some buildings) and BIM (which focuses on the microscale representation of the buildings), which provides an overview of a built environment based on integrated data, supporting the transition towards the architecture, engineering, and construction industry (AEC) in the digital era [41]. Cooperation between BIM and GIS is not fruitful only for the maintenance of LIS, but also for the automation of construction, especially if we consider the accelerated evolution rhythm of robots [42].

Public health policies represent one of the sectors where the geographical aspects have an increased importance. GIS becomes, in this case, a decision instrument for the remediation of some aspects related to the geographical heterogeneity, neighbourhood effect, small population problem, health-care market delineation, and planning towards equality [41,43]. Consequently, web mapping made possible the transmission of data associated with the realtime monitoring of the COVID-19 crisis, at various detail scales [44].

GIS, considered among the important big data technologies, together with remote sensing imagery, social media data, crowdsourced data, and mobile data, can be easily used also in various disaster management phases and in resilience building or in the testing of some prediction models [45,46,47,48].

2. Materials and Methods

From a methodological point of view, literature analysis was based on several work stages, from data collection to data reclassification and the actual development of the bibliometric analyses (Figure 1). The Web of Science database was used due to the high visibility of the scientific publications but also due to the acknowledgment of their impact at international level. No other databases (Scopus, ERIH, etc.) were used in order to avoid the juxtaposition of publications. The VOSviewer 1.6.15 and Bibliometrix 3.1 (R-tool) software were used to conduct the bibliometric analyses and their visualisation. The main work stages used were:

(i)

data collection, for which the following words were used as search criteria: “GIS” AND “UAV”, “GIS” AND “UAS”, “GIS” AND “Drone”, “GIS” AND “RPAS” (

Table 1. The frequency of using the words associated with the filter criteria of the scientific publications, except GIS.

Terms		2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2007	2006	2005	2004	2003	2002	Marginal Row Totals
																						No.	%
UAS		3	4	1	3	3	3	4	2	2		1										26	5.7
UAV		28	48	35	25	21	33	18	4	10	2	5	4	2	1	4	4	1	1	2	2	250	55.1
Drone		10	15	21	17	14	8	7	1	1												94	20.7
RPAS				2																		2	0.4
UAS and UAV				2	1	2	3	1		2		1										12	2.6
UAS and Drone			3		1	1	1															6	1.3
UAV and Drone		5	12	7	10	5	9	1	1													50	11.0
UAV and RPAS			2		2	2																6	1.3
UAS and UAV and Drone		2		3	1						1											7	1.5
UAS and UAV and Drone and RPAS									1													1	0.2
Marginal Columns Totals	Nr.	48	84	71	60	48	57	31	9	15	3	7	4	2	1	4	4	1	1	2	2	454	100
	%	10.6	18.5	15.6	13.2	10.6	12.6	6.8	2.0	3.3	0.7	1.5	0.9	0.4	0.2	0.9	0.9	0.2	0.2	0.4	0.4	100

). This was performed after the search for the “Digital era governance” AND “GIS” AND “UAV” criterion displayed no results. The initial selection criteria regarding the characteristics of these scientific publications took into consideration only the publications in English.

(ii)

reclassification of data, a necessary step, given the fact that the literature search displayed 454 elements, exported in an Excel document, and that many of these elements were doubled (n = 109 doubled elements) (Table 1). A secondary filtering criterion was applied to the same studies, as the publications that were eliminated were incorrectly catalogued in the Web of Science database. The abbreviation used had a different connotation than that investigated or the keyword mentioned was written differently (n = 15). Table 1 highlights the frequency of using each of the four terms associated with drone and the cases where at least two terms are interrogated and selected. For each exported publication, the collected data were the title, authors’ affiliation, abstract, keywords, year of publication, source, type of document, etc.

(iii)

data visualisation, conducted by bibliometric maps associated with the investigated topics, by means of the cluster technique.

The limitations of the study derive from the use of a single international database (Web of Science), but this does not mean that it underestimates the relevance.

3. Results

3.1. Scientific Literature Profile

The analysis of the 2052 keywords found in the 454 scientific publications associated with the investigated topics, provided information related to their main content. Of the total, only 81 keywords met the minimum threshold of five words in terms of frequency, thus resulting in seven clusters (Figure 2,

Table 2. Clusters of keywords.

Cluster	Number of Keywords	Selected Keywords
1	14	Airborne LIDAR, algorithm, forest fire, impact, LIDAR, model, parameter, rates, reflectance, remote sensing, risk assessment, satellite, satellite imagery, simulation
2	13	Archaeological site, area, city, cultural heritage, DEM, erosion, GIS, GPS, hazard, image processing, landslide, orthophoto, river
3	13	Classification, crop, design, NDVI, precision agriculture, resolution, sensor, system, UAS, vegetation, water, webgis, yield
4	12	Dynamics, evolution, forest, GIS analysis, imagery, monitoring, prediction, RPAS, SFM, slope, susceptibility, UAV photogrammetry
5	11	Augmented reality, BIM, biodiversity, conservation, ecology, information, management, morphology, restoration, technology, UAV imagery
6	10	3D accuracy, basin, DSM, photogrammetry, point cloud, reconstruction, soil erosion, tool, topography
7	8	3D GIS, 3D model, 3D reconstruction, archaeology, drone, landscape, mapping, UAV

). The size of the nodes reflected the frequency of the keywords, while the thickness of the line is directly proportional to the interrelation degree of the keywords. Most representative clusters were those dominated by UAV (cluster seven, with 79 links) and GIS (cluster two, with 76 links), followed by the clusters governed by photogrammetry (cluster six) and remote sensing (cluster one). While most of the scientific publications use the UAV technology as a working tool predominantly in photogrammetry and DEM generation (cluster seven), GIS applications were found to a greater extent in publications dedicated to image processing, landslides, cultural and archaeological heritage.

The reporting of the analysed studies to DEG or to associated concepts is poor, no matter what field we are talking about (

Table 3. The number of articles in which the concept of DEG or associated terms appears.

Terms	Cultural Heritage Preservation	Forestry	Land Use Management	Geomorphology	Hydrography	Engineering	Medicine	Nature and Eco-Friendly Practices	Risk Management	Smart Cities	Tourism	Virtual Cinematography	Virtual Reality
e-Government
e-Governance
Governance								1					1
Digital Governance
Digital era
Digital era governance
Digitisation	4		5	3	5	3		5	1
Digitalisation	2	1	1		1	1							1
Digital transformation
Big Data	3		1	2	1			2		2
Artificial Intelligence			1	2	1	1		2	1				1
Digital Twin													1
Internet of Things			2							1

). With the exception of “digitisation” and “digitalisation” (which are often confused), the others appear in few or even no articles. The situation has two explanations: (a) the authors of the studies do not intend to report by integrating the results to wider known frameworks (DEG, Digitalisation); (b) other newer concepts (Digital Twin, Internet of Things), in full theoretical development, hardly reach the “table” of overspecialised authors. A logical solution in such situations is the collaboration between the UAS and GIS operators, the specialists in public management, a situation in which both camps would win.

3.2. Cooperation Network

Another important indicator associated with the scientific production is that related to international cooperation created on a certain research topic, demonstrating on the one hand the existing research potential, and, on the other hand, being a benchmark for the identification of possible research networks. The relationships between the keywords, countries, and sources were viewed by means of the Sankey diagram (Three Fields Plot) (Figure 3). In this case, the most representative elements were highlighted on the graphic by means of coloured triangles. The height of a rectangle depends on the intensity of the existing relationships between the pursued elements. We signal the fact that, although at institutional or country level, certain international organisations stand out, from the USA, China, and the central and north European states, we notice a high polarisation coming from Romanian researchers, who, starting in 2015, have been using more and more the GIS–UAV combination of technologies.

Of the 107 states that have cooperated in the drafting of at least one scientific publication, we notice an increased interest for the approach of GIS and UAV technologies among some researchers in China and the USA or other European states (Italy, Switzerland, and The Netherlands) or Italy and other central-northern European states (Figure 4). The same trend is similar for the affiliations of the authors (Figure 5). A lack of cooperation between academic professionals and government entities was also highlighted.

4. Discussion

In order for the digital government to become digital governance, some internal aspects (creation of a decision-making culture based on the data at administrative level) need to be considered, together with some external ones (governance of various stakeholders that are meant to integrate the various data sources). Another challenge for digital government that is valid also for digital governance is represented by Big Data implementation. For this undertaking, the number of scientists that know how to work with such data is limited, the management technologies are not mature enough, and the resources meant to create technologies and talents are scarce [5].

The relationship between the dimension of the department in an institution and the administrative capacity has been demonstrated for one part of U.S. cities, where it was proven that the implementation of the open data platform varied depending on the resources of the department [9]. In the rural environment, where the overall administration capacity is similar to a department of a local urban administration, the reduction in digital gaps between the urban and the rural environment is all the more necessary [49].

Today, more and more researchers use the combination of UAV and GIS technologies for the mapping of some territorial elements, for the testing of some prediction models, creation of evolution scenarios, 3D modelling of space objects, etc. (

Table 4. Main content of the investigated scientific publications (2016–2021).

Application Fields	Specific Contents	Methodological Tools (UAV, Sensors, GIS)	Location	References
Cultural heritage preservation	3D archaeological or architectural reconstruction	UAV (DJI Phantom 4, DJI Phantom 3 Advanced, DJI Phantom 3 Pro), LiDAR, GIS (QGIS, City Engine, ArcGIS 10.3), Google Earth	Romania, China, Italy, Bulgaria, Malaysia, Portugal, Ireland, Australia, Russia	[50,51,52,53,54,55,56,57,58,59,60]
	Mapping cultural landscapes (Maya or Amerindian landscapes, open spaces)	UAV (DJI Phantom 4, DJI Phantom 2, DJI Mavic Pro, eBee Plus RTK-PPK), LiDAR, GIS (QGIS, ArcGIS 10.3, 3D GIS), GRASS	Mexico, Italy, Dominican Republic, Spain, China, Palestine, USA, Australia, Slovakia	[61,62,63,64,65,66,67,68,69,70]
	Creating viewshed analysis	UAV, GIS	Peru	[71]
	Mapping archaeological sites	UAV (SenseFly eBee, DJI Phantom 4 K, DJI Mavic Pro), LiDAR, GIS (QGIS)	Turkey, Chile, Afghanistan, Italy, SUA, Greece, South Africa, Spain	[72,73,74,75,76,77,78,79,80,81,82]
	Building facade inspections	UAV, GIS (2D GIS)	N/A	[28]
	Extracting road surface distress	DJI GS RTK, GIS	Turkey	[83]
Forestry	Monitoring uncontrolled forest	UAV, GIS (ArcGIS, QGIS)	Poland, New Zealand	[84,85]
	3D forest modelling	UAV (DJI S800, DJI Mavic Pro), GIS (ArcGIS)	Norway, Czech Republic, USA	[86,87]
	Estimating the biomass of riparian forests	SenseFly eBee, RGB SenseFly SODA, GIS	Portugal	[88,89]
Land use management	Monitoring crop factors, parameters, attributes	UAS (DJI Phantom, DJI S1000, DJI Inspire 1, AF1000), RGB and Thermal sensors, GIS (ArcGIS)	Greece, Poland, China, Saudi Arabia, Czech Republic, Taiwan	[90,91,92,93,94,95,96,97]
	Assessing land suitability	Supercam S250F UAV, GIS (ArcGIS 10)	Russia, Italy	[98]
	Land cover classification	UAV (RPAS eBee), GIS (ArcGIS), Google Earth	N/A	[99,100,101]
	Improving farming practices	DJI Matrice 100, GIS	Greece, Russia	[102,103]
	Developing predictive agricultural models	UAV (DJI Phantom 4, DJI Matrice 210 V2, DJI Phantom 3 professional, DJI Phantom 2, DJI Inspire 1), GIS (QGIS), GRASS	Portugal, Italy, Greece, Ecuador	[104,105,106,107,108,109]
	Assessing tundra degradation	Supercam S 250, GIS (ArcGIS 10.2)	Russia	[110]
Geomorphology	Monitoring erosion or landslide activity	UAV (Pegasus F-1000, DJI Mavic 2 Pro, DJI Matrice 600, DJI Phantom 4, GIS Velodyne VLP-16, RPAS, DJI Phantom 2, AscTec Falcon, ATyges FV-8), LiDAR, Micasense RedEdge Sensor, GIS (SAGA GIS, QGIS 3.8., Quantum GIS, ArcGIS 10.2, 10.5), GRASS	Nepal, Iran, China, Greece, Indonesia, Russia, Italy, Canada, Saudi Arabia, Czech Republic, Romania, Spain	[111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132]
	Monitoring topography	UAV (DJI Phantom 2 Vision+, DJI Phantom 4 Pro), GIS (ArcMAP 10.6)	Norway, Greenland, Indonesia	[133,134,135]
	Monitoring different geomorphological processes (debris accumulation, fluvial forms, earthquakes)	UAV (DJI Inspire 1 v2.0, eBee Plus RTK, DJI Mavic Pro 2, DJI Phantom 2), LiDAR, GIS (QGIS 3, ArcGIS), Google Earth	Poland, Brazil, Greece, Portugal, Austria, Italy, USA, Canada	[136,137,138,139,140,141,142,143,144,145]
	Mapping glacial-related landforms	DJI Phantom, GIS	Norway	[146,147]
	Mapping volcanic processes	UAV (Blade 350 QX2, DJI Phantom 4), GIS (ArcGIS Pro, ArcGIS 10.2)	USA, New Zealand	[148,149]
Hydrography	Flood modelling	UAS (SenseFly eBee, DJI Phantom 3 Professional), GIS	Central Asia, Spain, Greece, Turkey, China	[150,151,152,153]
	Mosquito disease mitigation	Multispectral sensor MicaSense, Drone, GIS	Australia	[154]
	Monitoring the batimetry and the surface area of reservoirs	UAV (Droning D650, Droning D-820, WingtraOne, DJI Phantom IV Pro, BRV-03F), GIS (ArcGIS 1.3.2.)	Spain, Bulgaria	[155,156,157]
	Restoration of freshwater inflows for wetlands	Quadcopter (NAZA M V2), GIS (ArcGIS 10.6)	USA	[158]
	Monitoring marine and coastal activities	UAV (DJI Mavic Pro), GIS (ArcGIS)	Cyprus, Scotland, Spain, Portugal, Greece, India	[159,160,161,162,163,164,165]
Engineering	Modelling different infrastructure works	UAV, GIS	Poland, Greece	[166,167,168]
	Designing emergency maps	UAV (DJI Phantom 4 Pro), CMOS sensors, GIS (ArcMap 10.5, ArcGIS, 2D-GIS), Google Earth	Italy, Greece	[169,170,171,172]
	Supervising road and railway maintenance works	UAV (Cumulus One, md4-1000 drones), GIS (ArcGIS)	Malaysia, Japan, Croatia	[173,174]
	Digital surveying of pipelines	UAV, GIS	N/A	[175]
	Estimating solar and wind energy potential	UAV (Gatewing X100), GIS (ArcGIS), GRASS	Colombia	[176,177,178]
	Mapping quarries	UAV (SenseFly eBee, DJI Phantom 3 Pro), RGB and multispectral sensors, GIS, Google Earth	Spain, Greece	[179,180]
	Cadastre mapping	DJI Phantom 4 Pro, GIS (QGIS)	India	[181,182]
Medicine	Testing high-incidence areas	DJI Matrice Pro 600, GIS (ArcGIS Pro)	Sweden	[183]
	Testing medical drones for emergency purpose	UAV, GIS (ArcGIS 10)	USA, Sweden	[184,185,186]
Nature and eco-friendly practices	Monitoring coastal landscapes	UAV (DJI Phantom 4 Pro, DJI Zenmuse X3-FC350), GIS (QGIS v.2.18)	Italy, Bulgaria, Iran	[187,188,189]
	Detecting invasive species	UAV (DJI Phantom 4, DJI Inspire 2), Multispectral sensor (Parrot Sequoia), GIS (QGIS 2.18)	Germany, China, Canada	[190,191,192]
	Monitoring and modelling environmental contamination (landfills, pollution sources)	UAV (Trimble UX5, DJI Phantom 4), GIS, Methane sensor (TGS 2611/MQ-2)	UK, China, Ukraine, Germania, Lithuania, China	[193,194,195,196,197,198,199,200]
	Monitoring ecosystem services	UAV (DJI Phantom 4 Advanced, DJI Phantom 3 Pro, DJI Matrice M100), GIS (ArcGIS, QGIS), Google Earth	Russia, South Africa, USA, China, Germany, Chile, Serbia, Canada, Australia, Republic of Korea	[201,202,203,204,205,206,207,208,209,210,211,212,213]
	Measuring microtopography	DJI Phantom 4 Pro, GIS (ArcGIS)	Canada	[214]
	Asssessing the noise-impact	UAV, GIS	Croatia	[215,216]
Risk management	Monitoring forest fires	UAV (CESSNA 310Q), GIS	Croatia, Netherlands, Greece, Indonesia	[217,218,219]
	Monitoring preventive actions (flood prone areas, tsunami evacuation plans)	UAV, GIS, Google Earth	Afghanistan, Nepal, Romania, Haiti, USA, Taiwan, Italy, France	[220,221,222,223,224,225]
	Testing scenarios for real-life postdisaster situations	UAV, GIS	Brazil, Italy	[226]
Smart cities	Controlling traffic management	UAV (Topcon Falcon 8), Sensors (MEMS-based IMU), GIS	Slovenia	[227,228,229]
Tourism	Examining the profile of UAV photographers	UAV (DJI), GIS	N/A	[230]
	Creating touristic story maps	DJI Phantom 4 Pro Plus, GIS (ArcGIS)	Greece	[28]
	Mapping old hiking trails	DJI Mavic 2 Pro, GIS	China	[231,232]
Virtual cinematography	Modelling autonomous driving and human–robot interaction	DJI M210, GIS	N/A	[233]
Virtual reality	3D archaeological and architectural reconstruction	UAV (3DR Pixhawk autopilot system, DJI Phantom 4, DJI Inspire 2), FARO Focus X330 scanners, GIS (City Engine), Google Earth	Portugal, Greece, Italy, Spain, Indonesia	[231,234,235,236,237,238,239,240,241,242,243]

). In summary, the main application sectors of these technologies refer to:

• the preservation of cultural heritage, from the mapping of various cultural landscape elements, either applied to some ancient civilisations or to some contemporary cultural landscape, to the 3D modelling of some heritage assets, mostly found in archaeological sites;
• forestry, through the testing of some applications designed to identify the areas of illegal cutting, fires, or biomass resources;
• land use management, focused mostly on the testing of some agricultural prediction models, but also on land favourability analyses for certain crops or monitoring of various parameters that can influence the stages of crop growth;
• risk management, including, the testing of possible models for the monitoring and prediction of some extreme phenomena and postdisaster scenarios, on the other hand;
• geomorphology, where there is a propensity of scientists to map landslide areas and, to a lesser extent, for the identification of other geomorphological processes, among which earthquakes are the most common;
• engineering, infrastructure maintenance works, and estimation of new energy sources;
• medicine, where the large advantage of drone usage is the coverage of less-accessible areas, which facilitates the saving of lives;
• tourism, with 3D modelling or creation of virtual tours;
• environmental-friendly practices intended to map the ecosystem services of some areas, to identify the pollution sources or invasive species, or even to assess the noise-impact.

Many of the possible uses of the two components are presented separately in the articles due to the high degree of focus of the subject. However, the significant number of articles that see this tandem as a solution for managing different territorial phenomena is an argument for several directions of the present study: (a) identification for each area revealed here, but also for others, of those utilities of UAS whose results can be capitalised on in the GIS environment; (b). identifying other possible applications in the digital context. The 454 studies that consider UAS and GIS as compatible technologies do not necessarily see their usefulness in a broader context [1], although connecting the two technologies can increase the rate of knowledge transfer to the public and private environment. This picture describing the usefulness of the technological tandem discussed must be promoted through activities to popularise science among the population in general and administration, in particular.

In addition, for the areas of applicability, it will be possible to create complex spatial databases that allow realtime digitisation and monitoring, without which we cannot offer a real digitalisation. Moreover, a digitalisation preceded by digitisation and continued by monitoring will generate a digital twin. The scalability of the results of UAS–GIS collaboration is emphasised by the diversity of current applicability and by the expected technical progress. Significant results can be obtained through simultaneous bottom-up and top-down reactions from all stakeholders.

The main findings and further recommendations associated with the use of UAS and GIS technology are also provided in

Table 5. Main findings and further recommendations of the investigated scientific publications (2016–2021).

Application Fields	Specific Contents	Current Findings of UAV and GIS Technologies	Further Investigations	References
Cultural heritage preservation	3D archaeological or architectural reconstruction	The use of UAV and GNSS technologies in field survey and the construction of high-resolution DEM allowed a more detailed study of the fortified settlements territory and defensive structures. Combining laser scanner and drone photogrammetric information provide 3D models.	Wider campaigns of 3D models; Performing automated methods	[59,60]
	Mapping cultural landscapes (Maya or Amerindian landscapes, open spaces)	UAV-DP high resolution surfaces granted the coverage of the entire slope and allowed the hydromodeling analysis to provide the mapping of an ephemeral stream network up to the 5th order. This lower-technology solution improves the management and conservation of cultural landscapes by providing 3D models for different time periods, seasons of the year, or yearly intervals. Using UAV in the case of imaging a small area of polygons is much more effective than with the use of civil aircraft, in terms of financing of aerial work, human resources, fuel, and operating costs.	N/A	[67,68,69,70]
	Mapping archaeological sites	The combination of UAV-derived land surface modelling and nearest neighbour analysis of point-provenienced archaeological surface distributions allows us to make better-informed decisions about future research priorities at open-air archaeological sites in arid and semiarid environments. Aerial imagery is useful in identifying and marking site boundaries even in heavily disturbed contexts such as plowzone sites that dominate Chesapeake archaeology.	N/A	[80,81,82]
	Building facade inspections	2D spatial modelling method simplifies the UAV-image registration problem within a 2D plane to reduce complicated 3D spatial relationships and provides sources for the documentation of building façade anomalies.	Developing applications for automated detection	[28]
	Extracting road surface distress	A high-density 3D model of the road was created from UAV images with the SfM pipeline and an analgorithm was developed and applied to detect road distress over the extracted road surface and to determine the perimeter, diameter, length, and depth of the road distress.	New parameters	[83]
Forestry	Monitoring uncontrolled forest	Using LiDAR data showed a continuous increase in the analysed forest area caused by the succession of forest vegetation in agricultural areas.	Training offers relating to geospatial technologies	[84,85]
	3D forest modelling	UAV can be used for monitoring urban forests, possibly gathering tree data.	N/A	[87]
	Estimating the biomass of riparian forests	The suitability of multispectral UAV imagery data to indirectly estimate tree AGB via a priori riparian species classification.	N/A	[89]
Land use management	Monitoring crop factors, parameters, attributes	UAV imagery and spatial image analysis based on GIS proved to be a fast and accurate method to evaluate if patch-sprayed herbicides are targeted at the locations given by preloaded prescription maps. Using unmanned aerial vehicle photogrammetry in a post-earthquake scenario provide reliable information about the state of the damaged structures and infrastructures. UAS data were analysed with soil and crop parameters in two cotton fields during a growing period and it offers a quick and reliable way to monitor soil and plant capital.	Incorporating new parameters (fields, crops, growing seasons) Translating the outcomes of soil and crop monitoring through expert decision-making tools	[95,96,97]
	Assessing land suitability	GIS-MCDA method weighted linear combination was used to calculate the land suitability index of Western Siberian forest-steppe lands.	N/A	[98]
	Land cover classification	By combining UAV and MMS technology, an orthophotoplan was created, but also other aspects related to vegetation.	N/A	[101]
	Improving farming practices	Object based image analysis of the field was a highly effective way of creating polygons of the tree canopy and depicting each one of them in the best possible way.	N/A	[103]
	Developing predictive agricultural models	An efficient combination of UAV/RPAS and NDVI enables important savings in productivity factors, promoting sustainable agriculture both in ecological and economic terms, and proposes a webGIS and user-friendly solution for smart farming. An open-source application, QVigourMap, developed under QGIS software, is free to use, intuitive, and has a tutorial to support the user; it can be updated at any time and by any other user.	Testing the workflow in terms of effectiveness and replicability Targeting a wider audienceCreating new web service New methods, indicators, and analysis tools Improving application’s usability Providing more customisation options to the user	[106,107,108,109]
	Assessing tundra degradation	UAV and GIS technologies are used for monitoring Arctic landscape changes under the influence of global warming.	N/A	[110]
Geomorphology	Monitoring erosion or landslide activity	By acquiring high-resolution images and terrain data by UAVs, a typical evolution model of the loss disaster chain was proposed. High-resolution data and GIS-based modelling were used for an improved understanding of spatial erosion processes, aiming to promote environmentally sustainable viticulture. Planoaltimetric changes computed from multi-source DTM analysis can be used for monitoring the space–time morphological changes of landslides. The combination of UAV-based imagery and SfM algorithms were utilised for 2D and 3D surface reconstruction.	Integrated analysis based on hydraulic modelling and nonstructural design	[116,124,125,126,127,128,129,130,131,132]
	Monitoring topography	Repeated UAV surveys provide a unique opportunity to investigate geomorphic changes that result from an extreme event.	N/A	[135]
	Monitoring different geomorphological processes (debris accumulation, fluvial forms, earthquakes)	The joint use of UAV and GIS methodologies proved to be a useful tool, not only for the rapid analysis of spatial data from a large population of sinkholes but also for providing an objective approach with consistent measurement and calculation processes. The methodology for Rockfall Susceptibility Assessment for 3D slope models in the form of point clouds can be used to refine the identification of potential rockfall source areas. A geological–geometrical and kinematical model of the Marzellkamm rock slide are the basis for subsequent numerical modelling campaigns that adopt the discrete element method, which is used to provide data for a comprehensive site-specific hazard assessment. High spatial resolution images obtained by UAVs can be of great use for the characterisation of microreliefs.	Validating methodology in rocky slopes with different discontinuity characteristics	[138,139,140,141,142,143,144,145]
	Mapping glacial-related landforms	With the use of low-cost UAVs equipped with a consumer-grade camera it is possible to map glacial-related landforms.	N/A	[146,147]
	Mapping volcanic processes	Small UAV offer a cost-effective alternative to traditional manned aerial surveying and produce measurement logs for mapping volcanic areas.	Technological improvements; Developing high accuracy automatic grain measurements	[148,149]
Hydrography	Flood modelling	DEM produced from different sources have different capabilities to represent topographic surfaces.	Optimising representation of topographic characteristics of the flow domain	[152,153]
	Mosquito desease mitigation	Satellite remote sensing provide potential in mapping mosquito breeding habitats.	Technological improvements	[154]
	Monitoring the batimetry and the surface area of reservoirs	Improvements in understanding and monitoring the water reservoirs.	N/A	[155]
	Restoration of freshwater inflows for wetlands	The combination of spatial technologies provides a template for future work in similar sheet flow-fed landscapes affected by hydrologic disconnection and modification.	N/A	[158]
	Monitoring marine and coastal activities	The use of UAV combined with other techniques expand the knowledge about rocky coasts and boulders displacements.	Increasing processing capabilities and applying multispectral cameras	[164]
Engineering	Modelling different infrastructure works	Data integrator allows user to automate the updating infrastructure data.	N/A	[167]
	Designing emergency maps	An automated building seismic damage assessment method provide a useful tool for the rapid regional seismic damage assessment of buildings and assist the contingency response and management.	N/A	[172]
	Supervising road and railway maintenance works	The usage of UAV is more efficient than the conventional method; it saves cost, produces accurate data, and verifies road maintenance work systematically.	N/A	[174]
	Estimating solar energy potential	The UAV-DSM method improves the estimates of the radiation potential from a highly detailed inexpensive 3D model, and these solar maps become tools for planning disciplines.	New parameters used in estimating solar energy potential	[176,177]
	Mapping quarries	The photogrammetric and GIS methods provides an accurate assessment of open-pit mining. A UAS-based protocol allows fast monitoring land restoration and synthesis of various remote sensing applications into a single workflow in order to obtain cartographic products.	Obtaining new products like soil losses by erosion or vegetation change maps	[179,180]
	Cadaster mapping	A semi-automated technique reduces manual efforts and human interventions, and there is a substantial reduction in time as there is a limited digitisation process.	Detecting segment quality parameters	[182]
Medicine	Testing high-incidence areas	Small number of drone systems increase national coverage of OHCA substantially.	Prospective real-life studies	[183]
	Testing medical drones for emergency purposes	Identification of possible drone network configurations that can reduce life-saving equipment travel times for victims of cardiac arrest.	Legal and technical improvements	[184,185,186]
Nature and eco-friendly practices	Monitoring coastal landscapes	Improvements of the accuracy of raster map for monitoring inaccesible coastal areas. UAV is an affordable and fast survey technique that can rapidly increase the number of studies on cliff habitats and improve ecological knowledge on their plant species and communities.	Improving sensor and drone technology	[187,189]
	Detecting invasive species	Use of a multidisciplinary methodology to quantitatively evaluate the role of plant species in ecosystems, including invasive species (density, clustering, and spread). UAV low-altitude remote sensing allows monitoring without destroying vegetation because of its noncontact characteristic.	Improving the efficiency and scalability of the image analysis	[190,191,192]
	Monitoring and modelling environmental contamination (landfills, pollution sources)	Use of remote sensing techniques shows the different spatial scales of high risk areas. Drone monitoring has the potential to expand spatial coverage to larger areas, monitor fragile or inaccessible sites, and provide maps of litter abundance and distribution.	Testing new methods for litter detection and classification	[195,196,198,199,200]
	Monitoring ecosystem services	Use of a low-cost UAV with an RGB camera UAV to quantify floral resources has potential as an efficient method for predicting pollinator populations over large spatial scales. Considering the low-cost and portable characteristics of the UAV-borne lidar system, it opens new possibilities to provide comprehensive 3D habitat information for biodiversity studies. UAV imagery is sufficiently applicable for analysing the distribution of aquatic plants.	Improving processing data Integrating the floral resource estimates with decision-making tools for improving habitat structure in landscapes. Ssurveying the observer’s visual experience and psychological feelings about the scenery.	[202,206,209,210,211,212,213]
	Measuring microtopography	Measuring microtopography with a UAV and SfM, this technology has the potential to emerge as a useful Digital Terrain Analysis tool in other studies of habitat selection.	Extending capabilities of larger and more powerful UAV	[214]
Risk management	Monitoring forest fires	Application of UAV contribute to reducing the probability of errors, shortening reaction time, increasing accuracy in decision making, and shortening load of people and techniques in peak days. The operationalisation of the peatland combustion algorithm for providing peatland fire information is possible for the whole Indonesian archipelago, including other tropical peatland areas such as Malaysia.	Improving infrastructure (public server) so that data can be appropriately delivered to the users in the field.	[217,218,219]
	Monitoring preventive actions (flood prone areas, tsunami evacuation plans)	3D reconstruction process based on UAV technology and the interpolation algorithm ‘‘Daisy’’ is cheap, relying on open-source solutions and the procedure is of noninvasive nature and is applicable in the areas difficult to reach or inaccessible by traditional technology. Drone offers a new complementary means of surveying which can map broad areas efficiently while being more flexible and easier to operate than other airborne means. UAV imagery for assessing the hazard of the coastal settlements is not only intuitive, effective and fast, but also meets the needs of assessing the exposure and resilience of vulnerable coastal settlements.	Integrating more groundtruth data Providing donors, governments, and communities in developing nations access to low-cost data collection and analysis tools to assess and minimise disaster risk	[220,221,223,225]
	Testing scenarios for real-life postdisaster situations	The use of UAV technology sped up the process of evaluation of the floods, which occurred in Duque de Caxias in 2013.	N/A	[138]
Smart cities	Controlling traffic management	Data gathering times for simulated traffic accidents are shorter in comparison to classical police work with measurement type with the UAV technology support. Presence of sensor measurement integration with map data to achieve navigation in areas with intermittent GNSS availability during a flight of an aerial vehicle. Drone-following models have been developed to manage drones in urban air traffic flows based on the principle that keeps a safe distance according to relative velocity.	Integrating data	[227,228,229]
	Measuring unauthorised buildings	After computer-automated processing, new DSM data were obtained from elevation differences in two-stage images and illegal buildings could be identified.	N/A	[230]
Tourism	Examining the profile of UAV photographers	Investigating the photography behaviour and preferences of emerging tourist groups by introducing AI computing methods	Qualitative analyseswith UAV photography tourists	[28]
	Creating touristic story maps	Creation of a web map, while providing information to a broad audience.	N/A	[231]
	Mapping old hiking trails	Developing a methodology to assess the safety and suitability of an old close-downed forest trail as an evocation to reopen it as a hiking trail.	N/A	[233]
Virtual reality	3D archaeological and architectural reconstruction	The use of advanced data acquisition and analysis techniques offers considerable promise in assisting the reconstruction of past landscapes. The generalised models and test datasets construct individual image representations of the depth and color of roof shapes. Immersive data visualisation of the geospatial GIS plant data may be rendered in a game engine with high information fidelity to achieve sensory accuracy.	Integrating image processing and machine learning approaches. Introducing new cost functions that penalise inter-drone collisions Introducing slight modification in the definition of artistic parameters that define the desired artistic shot for our motion planner. Creating volumetric reconstruction of dynamic scenes in natural environments in real-life conditions. Learning the artistic reasoning behind human choices. New algorithms to simulate the natural world	[231,234,235,236,237,238,239,240,241,242,243]

.

Aside from the further recommendations listed (Table 5), such as technical improvements, testing new parameters, indicators, algorithms, or methods in order to increase data accuracy, integrating different kind of data, we highlight the following features:

• promoting remote sensing study for crossdisciplinary research through new curricula, education programs, and inclusion in projects which will increase the responsibility of local communities for their natural environment [212,228];
• reducing the time required for the decision-making process and for preparation of the response operation achieved by the adoption of UAVs and GIS technologies [138];
• geospatial technologies support decision makers in order to implement a “culture of prevention” instead of a “culture of reaction” [160].

If the combined usage of the two technologies (UAV and GIS) has become more frequent over in recent years (2019), we can currently notice a trend of the research fields towards the management of some phenomena and 3D modelling of some spatial objects (Figure 6).

Among the vulnerabilities associated with DEG we mention: (a) adaptation of organisations, (b) information overload, and (c) data protection.

(a) In the context of the need identified by the United States Navy, in 2002: “ […] We need an organization that is very adaptive, that is very agile and is quick. Instead of having cycles that take years, we need cycles that take months because the threat changes […]”. The government sector includes obvious changes of organisations and organisational culture. Another common problem of the modern administration, regardless of the level, is not as much the increase in the costs related to the employees’ wages, but the artificial development by some of the employees of some “boutique-bureaucracies” and the fragmentation of the decision-making process [2].

(b) The sudden transition from a quasi-lack of information to data overload, amplified especially by social media, accelerates the need for data and information that are scientifically validated. A paradox is highlighted in the context of Big Data’s existence, which is considered to be able to solve the lack of data problem in the digital era [5]. Data warehousing sounds simple, but in the context of most of the national taxation, social security, immigration, and defence systems, especially in developed countries, it needs further development, with radical implications. The warehousing manner must activate the anticipation of the citizens’ needs [2,4], including among other aspects, real-time government data-pooling by means of big data, from the local to regional level, open book government and citizen surveillance, open data initiatives, government cloud, etc. [1].

(c) The transition towards an open government will not be possible without an efficient protection of data and a free regime of the information for citizens [2]. With digitalisation, the individual will have more power to influence the policies of administration, the entrepreneurs will be able to manage business by avoiding excessive bureaucracy, and governments will be able to take more efficient measures in various sectors (public health, climate, and traffic). There is a risk deriving from this that government services remain inefficient [5].

5. Conclusions

Despite some uncertainties and alternatives, DEG continues to remain unique. It keeps the promise of a possible transition towards a more integrated administration, whose organisational operations are visible in detail both for the staff operating in the public domain, and for the citizens and organisations of civil society. Changes brought by DEG are closely correlated and will be strictly carried out in parallel with the increase in autonomous capacities of the citizens for the solving of social problems. The challenge for public managers will be to help the stakeholders of civil society [1]. DEG provides the theoretical and practical means for economies to shift from extractive economies into inclusive economies [244]. This statement is valid also for institutions, the result being the increase in their innovation capacity [5] because the digital infrastructure alone is not sufficient. Equally important are the digital skills that enable the use of digitalisation advantages [49].

Future research may focus on the ways to involve UAS and GIS users in the creation of digital twin models or the encouragement of direct democracy, an attempt to return to Athenian democracy, but by means of the current digital tools.