You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: CityGML Application Domain Extension (ADE): overview of developments 
Chapter Title:  Principal observations from the literature review 
1. Abstract of Cited Paper (BIB001):  In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market. 
2. Abstract of Cited Paper (BIB002):  Road traffic and industrial noise has become a major source of discomfort and annoyance among the residents in urban areas. More than 44t% of the EU population is regularly exposed to road traffic noise levels over 55 dB, which is currently the maximum accepted value prescribed by the Environmental Noise Directive for road traffic noise. With continuously increasing population and number of motor vehicles and industries, it is very unlikely to hope for noise levels to diminish in the near future. Therefore, it is necessary to monitor urban noise, so as to make mitigation plans and to deal with its adverse effects. The 2002/49/EC Environmental Noise Directive aims to determine the exposure of an individual to environmental noise through noise mapping. One of the most important steps in noise mapping is the creation of input data for simulation. At present, it is done semi-automatically (and sometimes even manually) by different companies in different ways and is very time consuming and can lead to errors in the data. In this paper, we present our approach for automatically creating input data for noise simulations. Secondly, we focus on using 3D city models for presenting the results of simulation for the noise arising from road traffic and industrial activities in urban areas. We implemented a few noise modelling standards for industrial and road traffic noise in CityGML by extending the existing Noise ADE with new objects and attributes. This research is a steping stone in the direction of standardising the input and output data for noise studies and for reconstructing the 3D data accordingly. 
3. Abstract of Cited Paper (BIB003):  The road towards achievement of the climate protection goals requires, among the rest, a thorough rethinking of the energy planning tools (and policies) at all levels, from local to global. Nevertheless, it is in the cities where the largest part of energy is produced and consumed, and therefore it makes sense to focus the attention particularly on the cities as they yield great potentials in terms of energy consumption reduction and efficiency increase. As a direct consequence, a comprehensive knowledge of the demand and supply of energy resources, including their spatial distribution within urban areas, is therefore of utmost importance. Precise, integrated knowledge about 3D urban space, i.e. all urban (above and underground) features, infrastructures, their functional and semantic characteristics, and their mutual dependencies and interrelations play a relevant role for advanced simulation and analyses. As a matter of fact, what in the last years has proven to be an emerging and effective approach is the adoption of standard-based, integrated semantic 3D virtual city models, which represent an information hub for most of the above-mentioned needs. In particular, being based on open standards (e.g. on the CityGML standard by the Open Geospatial Consortium), virtual city models firstly reduce the effort in terms of data preparation and provision. Secondly, they offer clear data structures, ontologies and semantics to facilitate data exchange between different domains and applications. However, a standardised and omni-comprehensive urban data model covering also the energy domain is still missing at the time of writing (January 2018). Even CityGML falls partially short when it comes to the definition of specific entities and attributes for energy-related applications. Nevertheless, and starting from the current version of CityGML (i.e. 2.0), this article describes the conception and the definition of an Energy Application Domain Extension (ADE) for CityGML. The Energy ADE is meant to offer a unique and standard-based data model to fill, on one hand, the above-mentioned gap, and, on the other hand, to allow for both detailed single-building energy simulation (based on sophisticated models for building physics and occupant behaviour) and city-wide, bottom-up energy assessments, with particular focus on the buildings sector. The overall goal is to tackle the existing data interoperability issues when dealing with energy-related applications at urban scale. The article presents the rationale behind the Energy ADE, it describes its main characteristics, the relation to other standards, and provides some examples of current applications and case studies already adopting it.

Literature Review:
With 44 identified ADEs developed for a variety of purposes, the ADE landscape is quite diverse. They have been developed for a range of applications from land administration to energy analyses, and generic purposes such as harmonisation of national data standards. Thanks to enriching the CityGML data model with new features, the ADEs enable new applications of CityGML data and enhance existing ones. While the ADE mechanism has been introduced to support applications, an interesting observation is that more than a third of instances identified in our review is generic, without a specific application in focus. Some of the ADEs are merely described in a subsection of a short paper without any published XSD/UML and are confined to being prototypes and early-stage proposals, while others are well documented and mantained, and some have even been adopted as national standards and are supported by software implementations. This results in a large difference between the maturity and adoption of ADEs, as it appears that several of them are very specialised and designed as pilot projects. The Energy ADE and UtilityNetwork ADE particularly differentiate themselves here, being developed by international consortia involving different types of stakeholders, and continuously being featured in publications (examples of papers are given in the previous section). Among a few others, these ADE can be considered as exemplary developments. ADEs in general focus on one thematic module (and that is mostly Building), which can be explained by the fact that most applications consider only that thematic aspect of 3D city models BIB002 . For example, indoor navigation usually does not require any other thematic class beyond buildings. Fig. 6 Example of the FME data inspector showing a dataset with attributes extended by the Noise ADE. Source of the dataset: OGC  At the side of levels of detail, the situation is mixed. Some ADEs do not account for LODs, while others are restricted to a particular LOD, especially those involving indoor data, which is relevant for the discussions about the conversion from IFC to CityGML and for indoor applications such as navigation. A shortcoming that we have noticed is the limited reach of ADE when it comes to open data. ADEenriched CityGML datasets are seldom available, indicating that while the development of the specification may be lively, their implementation and utilisation lag behind. Finally, an interesting differentiation is noticed when it comes to diversifying or focusing the scope of ADEs. For example, the Energy ADE BIB004 is developed with multiple use cases in mind. However, Prieto et al. BIB001 and Egusquiza et al.  resort to another philosophy, developing multiple 'mini-ADEs' within the same project, each with a specialised purpose, separate and complementing each other. In relation to such an approach, it is interesting to point out that certain ADEs have been created by extending existing ADEs, i.e. it is possible to create an ' ADE of an ADE' . For example, Kumar et al. BIB003 show the possibility of extending the existing Noise ADE with new elements and attributes, instead of creating a new extension from scratch. Such a notion of customising and/or extending an existing ADE allows designing a 'core' ADE that can serve as a base for multiple, more specialised ADEs, diminishing their overlap. Interestingly, we have also noticed a significant overlap of some ADEs. For example, there are three similar ADEs independently developed that even bear the same name (Cultural Heritage ADE).