## 1 Locating the Internet of Things  
The Internet of Things (IoT) includes technologies and research disciplines that enable the Internet to reach out into the real world of physical objects [1]. IoT-based projects are increasing in number and scope for various application domains such as smart homes [2], urban environments [3] and smart agriculture [4]. Internet-enabled things are equipped with sensors, measuring with high precision the state of the physical world such as temperature, humidity, radiation, electromagnetism, noise, chemicals, etc. Moreover, the rise of multi-sensory mobile phones offers advanced sensing capabilities, such as measuring proximity, acceleration and location; recording audio/noise; sensing electromagnetism; or capturing images and videos [5].  
An important characteristic of the measurements performed by Internet-enabled things (i.e., sensors, mobile phones, cameras, etc.) is the geographic location of each measurement. For location-based services, geographic information is crucial in understanding the local environment [6], enabling the development of powerful context-aware, personalized applications [7, 8], especially in relation to mobile phone computing [9]. Location sensing has been facilitated in recent years because of the evolvement of various outdoor (as well as indoor) positioning technologies and techniques [10].  
As the physical or artificial environments are generally complex and characterized by a wide variety of parameters, a rich collection of measurements in space and time is necessary to model and understand these ecosystems [11]. Hence, sensory-based IoT information needs to be aggregated, stored and analyzed for more elaborate and holistic reasoning and inference. For example, a route planner application needs input from various traffic sensors placed around a city [12], combining this information with air quality or weather forecasting to give more complete and personalized recommendations to the user [13, 14].  
To exploit this variety of IoT measurements in type, space and time, geospatial analysis is used to provide answers and insights to complex queries and research questions [15]. This paper examines the relationship between geospatial analysis and the IoT, and identifies current trends and future research directions and applications. It analyzes the IoT focusing on location, examining the various geospatial analysis techniques employed. Our contribution lies in investigating the potential of location-aware IoT for geospatial analysis, studying the possibilities of research in this intersection. Although IoT data are often geospatial, there has been little (conscious) interaction between the two domains, i.e., IoT and geoscience. This paper expands the preliminary work on the topic published in [16], presenting a more elaborate survey of geo-enabled IoT projects, categorized according to the type of geospatial analysis used. The guiding questions for this work are:  
1. What is the role of IoT in geospatial research at the moment with respect to analysis methods, applications, and geographic scales?
2. What are the IoT characteristics with respect to location and geospatial data, i.e., device/data types, reliability and accuracy, security and privacy, device settings and deployment aspects?
3. What are the challenges and opportunities of using IoT for geospatial research in the future?  
We start by determining what the current usage of IoT is, with respect to geospatial research as reported in the literature. We examine IoT usage with respect to geographic analysis methods and application domains. Next, we present the characteristics of IoT devices being used (including reliability and accuracy, privacy and security), the type of data they create, and the standards in operation (e.g., with respect to interoperability). Finally, we identify challenges and opportunities, discussing current trends in IoT research and likely future directions.