A METHOD AND SYSTEM FOR BIDDING FOR THE ACTIVATION OF SURFACES The present invention relates to a method and system for bidding for the location for, or the activation of a surfaces on, which an Autonomous Vehicle (AV) or other method, may operate to deploy an advertising campaign, or for an event, or for other purposes. BACKGROUND: In more recent times, the key to a successful marketing campaign has been more than just a catchy slogan put in front of a TV audience on repeat. To build campaigns that drive marketing Return on Investment (ROI), brands have had to develop new channels for advertising, to ensure their on-brand messaging can make its way to their target audiences at the right time and for the right price. Media buyers oversee the media buying process, with input from a media planning team. With an understanding of marketing goals and target audience preferences given by the media planning team, media buyers execute the actual purchase of an advertisement (ad) space, on behalf of a brand owner, or agency, providing the instructions for the brand deployment and/or advertising campaign. A large part of the media buyer position is negotiating with the sites, networks, and other channels they want their ads to appear on. Media buyers also use known marketing performance tools to track key performance metrics and delivery, to ensure the ad is placed in accordance with the agreement and that it is meeting pre-defined campaign goals. The process of media planning is focused on establishing an audience, conducting market research, establishing a budget, and building out those campaign goals. Media planners work with their clients to understand who the target audience is for their offering, which digital channels that audience uses and at what times, and what type of messaging that audience is most likely to engage with. With this information, the planning team will select which channel they want to purchase ad space on, and for what price. ‘Digital Out-of-home’ (DooH) ads are also used to reach people outside of the home through mediums such as public billboards, or digital displays. Within the DOOH advertising industry, advertising campaigns may be purchased through marketing platforms which enable marketers to specify desired audience characteristics and automatically locate the required media solution to deliver that audience. These platforms also allow buyers (the demand side) to plan, execute and monitor campaigns across multiple media platforms (the supply side). Further DooH capabilities include the creation of measurable, highly targeted campaigns by utilizing geolocation data to activate the best DOOH digital screens in real-time based on consumer behaviour and audience movement patterns. However, DooH systems tend to be used only with digital screens and digital screens owned by one owner. Media channels are also maxed out, so media planners are always looking for new opportunities to reach new audiences. Brands want to be seen in high profile venues. Brand advertising in known locations is a $3/4Trilion market. $35bn is already spent on sports venue sponsorship. Many venues already use manual workers for ground brand and sponsor activations, including:- NFL, AFL, Golf, Soccer, Football, Rugby, F1, Motor Racing, Nascar, Cricket, Archery, Cycling, Drag Racing, Horse Racing, Marathons/ Triathlons, Monster truck, Volleyball, Motor Cross, Motor Cycling, Mountain Biking, Rodeo, Skiing, Sky Diving, Base Jumping, Olympics, Commonwealth Games, Tennis, World Records, Conferences, Product Launches, Airports, Car Parks, Music. Almost all venues use a combination of both digital LED and painted markings to maximise fan engagement and all-round experience on location and TV, often changing to accommodate broadcast or license deals associated with a particular event. This hunt for new places to advertise has recently extended to the MetaVerse, where the Sandbox is a large virtual world in terms of transaction volumes, with 65,000 transactions in virtual land totaling $350 million in 2021. It is a virtual land composed of 166,464 parcels of 96x96m, representing a virtual world of 40km x 40km, where participants can play games and participate in virtual experiences. In comparison, Decentraland—the second largest virtual world—saw 21,000 real estate transactions worth $110 million in 2021. Similarly to real life, landowners can also rent out their lands for others to design their own games, host events and other social activities. However, even in the real world, there is difficulty in understanding firstly who owns what land, plus what can be done to activate that land and bring in new revenue, as well as find new opportunities for brands to advertise. In the real world, a topographic survey is the delineation of horizontal and/or vertical locations of the existing natural or man-made features of a portion of the earth’s surface, subsurface or airspace and the graphic representation of the results of such delineation. Topographical surveys are used for construction, landscaping or for specific legal means. Usually, a licensed professional performs a topographic survey and as such, they take time and cost money. Thus it is complex to manage and is a huge overhead for more temporary events. Thus, there is a need to make it easier to democratise land advertising (both real and virtual), to make it more accessible to people who wish to use it. More specifically to find surfaces on which a suitable ground printer or drone display can be activated in the real world, as well as to make it easier for virtual lands to rent out surfaces temporarily for brand and event activations. Not just for brand activations, but also for events such a ground print for a birthday or a wedding, marking out stall positions at a local fete or sports competition. To understand the temporary (or not) nature of the activation and apply the right tool for the job. An example of a ground marking robotic autonomous vehicle (AV) is a type equipped to deposit materials such as ink, paint, or chemical treatment onto a ground surface is described in the Applicants co-pending applications. The ground marking robots create ground-printed images and are generally operated through a user-interface (UI) via a cloud-based SaaS or proprietary software system. The ground-printed images may be, for example, company logos printed on sports grounds for advertising a company during an event, general advertising on identified suitable spaces to attract optimal large numbers of viewers, pitch markings or road markings on highways, for efficient providing road markings with minimal disruption to traffic. SUMMARY OF INVENTION In a first aspect of the present invention, there is provided a system or method for bidding for the location for, or the activation of a surfaces on, which an Autonomous Vehicle (AV) or other method, may operate to deploy an advertising campaign, or for an event, or for other purposes, system or method further comprising: receiving location data about a surface upon which an activation is required from a first user; receiving an offer of consideration from a second user, wherein the second user wants to activate one or more of the surfaces; making available the offer of consideration to the first user; and if the offer is accepted, sending the acceptance of the offer to the second user. In a second aspect of the present invention, there is provided a system and method for campaign-based listing with bidding; the system and method comprising: receiving campaign data about a campaign from a first user; processing the campaign data; receiving a bid for a campaign from a second user; wherein the bid comprises geographical data about a location; the system and method collating all the bids within a specified time period, wherein the first user selects a best bid; and wherein the campaign is activated by a suitable deployment method. In a third aspect of the present invention, there is provided a system and method for a campaign agency pool model, the system and method comprising: receiving campaign data about an advertising campaign from a first user; processing said campaign data; generating price information or receiving price information; receiving an offer for a campaign from a second user; wherein the offer comprises geographical data about a location; processing said geographical data; wherein the first user selects the location; and wherein the processor matches the winning location(s) to a suitable deployment method for the deployment of the campaign. Preferably wherein the calculation of the value may take as a further input, activation data concerning an ease of access, surface, permanency, minimum time to fade, removal and/or turn around requirements and/or wherein the first user receives feedback post activation on the location, which may be used to increase or decrease the value and/or wherein the feedback may be related to the success and/or ease of install, and/or ease of activation removability. Further preferably, wherein receiving at least part of the geographical data comprises importing a topographical data set from a third-party entity. Also wherein the AV data may comprise a list comprising at least one of wheel or track dimension, traction, motor power, motor torque, power range, payload, surface clearance, vehicle speed, vehicle dimension and centre of gravity. Further preferably, wherein the area characteristic may comprise at least one of surface material, gradient, planarity, obstacles, geographical orientation, altitude, topography, population movement, travel networks and routes, size, shape and dimension. Advantageously wherein the suitable deployment method may be an autonomous vehicle and further comprising deploying at least one of said autonomous vehicles and/or wherein the, or each, autonomous vehicle is operable as a ground marking autonomous robotic vehicle. In a fourth aspect of the present invention, there is provided a computer program product comprising a non-transitory readable medium holding computer program instructions, the computer program instructions executed by a hardware processor to carry out the method of any of the preceding aspects. Also, one or more of the autonomous vehicles may have system receiving means operable to receive operational information relating to the determined suitable surface in said geographical area for said autonomous vehicle to operate. The operational information may include, for example, the topographical data and real-time and forecasted weather conditions, such that the autonomous vehicle can automatically adjust its settings and determine power requirements to undertake the required task. The method advantageously further comprises a user interface and communicating the determined suitable zone in said geographical area for said autonomous vehicle to operate to the user interface. The user interface advantageously comprises a map and the determined suitable zones in said geographical area for said autonomous vehicle to operate is displayed on the map. BRIEF DESCRIPTION OF THE DRAWINGS Embodiments of the invention will now be described by way of example and with reference to the following drawings, in which: Figure 1A is a diagram illustrating a method of matching surfaces to suitable (Autonomous Vehicles) AV’s, according to a first embodiment of the present invention; Figure 1B is a diagram illustrating example of a look-up table according to the method of Figure 1A; Figure 2 is a schematic drawing of a side view of a Surface Marking Robot (SMR) for use with the method of Figure 1A; Figure 3 is a schematic drawing showing a view from above of the SMR, of Figure 2, in use; Figure 4 is a schematic drawing of a system for implementing the method of Figure 1A; Figure 5 is a diagram illustrating an example user interface display, of Figure 4; Figure 6 shows a process diagram, describing steps related to the invention of Figure 5; Figure 7 is a process diagram, describing steps related to the invention of Figure 5, wherein users can decide whether to keep their locations privately managed, or to release a location into an auction, according to a second embodiment of the present invention; In Figure 8, is a flow diagram illustrating an example landowner location registration process, as may be implemented by the system of Figure 4; Figure 9 is a diagram illustrating an online auction system that allows campaign managers to bid on locations, according to a third embodiment of the present invention; and Figure 10 is a diagram illustrating an online auction system that allows campaign managers to bid on locations, according to the process of Figure 9. The present techniques will be described more fully hereinafter with reference to the accompanying drawings. Like numbers refer to like elements throughout. Parts of the autonomous ground printer are not necessarily to scale and may just be representative of components of the ground print machines, or other described entities. DETAILED DESCRIPTION: Referring to Figures 1A and 1B, a method 100 for identifying suitable zones for Autonomous Vehicle (AV) operation in a geographical area, according to the present invention, includes receiving geographical data associated with a geographical area 102. The geographical data may include one or more of, for example, topographical data, proprietary data, and/or commercial data. Suitable zones include two-dimensional or three-dimensional areas or spaces, or a combination of the two. For example, a suitable zone may include a suitable surface on which an Unmanned Ground Vehicle (UGV) operates, or an aerial space in which an Unmanned Aerial Vehicle (UAV) operates. The topographical data includes for example, surface material, surface gradient, surface planarity, obstacles, geographical orientation of surface, surface altitude, size, shape, and dimension. It may also include identification of specific common surfaces such as, for example, flat roofs, walls, commercial buildings, car parks and/or municipal playing fields and/or the airspace above such surfaces. The topographical data is derived from mapping data and/or satellite data imported digital image processing is used to process the mapping/satellite data. The mapping/satellite data may be imported from a third-party entity, such as for example, Google® Maps and Apple® Maps or other similar map/satellite data provider. Google® Maps and Apple® Maps are examples of web mapping services which offer satellite imagery, aerial photography, 360 ^o interactive panoramic views of streets, real time traffic conditions and route planning. In an alternative embodiment, the topographical data is derived from aerial data collected from one or more data collection unmanned aerial vehicles (UAV). The, or each, data collection UAV may include one or more LiDAR devices and multispectral cameras. The aerial data is processed using a photogrammetry system to provide the topographical data. The proprietary data may include data indicative of the land or building or airspace ownership which may be derived from public databases such as, for example, The Land Registry in the United Kingdom. This data may also include the type, size and value of the land or building or airspace. The proprietary data may also include data concerning a plot, or space, in the MetaVerse. The commercial data may include any data which is indicative of a commercial value proposition of using a specific autonomous vehicle and/or an autonomous vehicle system in that specific geographical area. This may include, for example, one or more of: population density; population demographics; consumer population and demographic by type; population movement; consumer movement; and travel networks and routes, such as for example, passenger plane flight paths. Data relating to passenger plane flight paths may include, for example, number of flights, height of aeroplane, type of aeroplanes, and times of flights, at identifiable points or zones in the geographical area. The commercial data may also include a surface value, that is details with regards to the value of a particular surface to a brand owner. This could be a combination of marketing information (football, viewing figures, number of people and who can see it), plus ease of installation, cost of deployment. The method further comprises processing the geographical data to determine one or more combined area characteristics 104. The combined area characteristic may be a unitary area characteristic, which represents two or more of the topographical data, proprietary data and the commercial data, or the area characteristic may include a topographical area characteristic, a proprietary area characteristic and a commercial area characteristic. Location owners, or other third parties on their behalf, may also submit geographical and/or proprietary data into the database about a specific location, as exemplified with reference to Figures 5 & 7. The method 100 preferably further comprises sorting the area characteristics into zone utility groups 106, based on the determined one or more combined area characteristics. The, or each, zone utility group is associated with possible operational requirements and/or limitations of autonomous vehicles and/or potential commercial opportunities. As an example, a zone utility group may be: a ground print utility zone group indicative of operational suitability for a Surface Marking Robot (SMR), for example, a sports stadium, or golf course; or an air space zone, suitable for operating a drone (UAV) display. Other advertisement ‘deployment methodologies’ could also be included, such as billboards, and/or an AR/VR overlay, via a TV camera, to a viewer of a sports competition, for example. The method 100 further comprises receiving vehicle data associated with the operation and utility of specific autonomous vehicles 108 and storing the vehicle data on a database 110. The vehicle data may include, for example, one or more of the utilities of the vehicle, the operating parameters or limitations of the vehicle, and the operating, hire or job costs which may be provided per square area (e.g. m ² ). Referring particularly to Figure 1B, an autonomous vehicle (AV) utility look-up table 112 may be generated from an autonomous vehicle (AV) specification table 116 having lists including the technical operating parameters and limitations of each autonomous vehicle. The operating parameters or limitations of the specific autonomous vehicle may include, for example, wheel or track dimensions, traction, motor power, motor torque, power range, payload, surface clearance, maximum speed, vehicle dimension, centre of gravity. It will be appreciated that other operating parameters and limitations may be included, and any one or more may be excluded, depending on the specific application and utility of the autonomous vehicle. A suitable zone utility look-up table 118 may be generated from an area characteristic look- up table 120 and commercial characteristics look up table 122. The area characteristic look- up table 120 may include zone-related listings including, for example, any one or more of surface details, gradient, obstacles, geographical orientation, and dimensions. The commercial characteristics look up table 122 may include one or more of population density, population demographic, consumer population, consumer demographic, population movement, consumer movement, travel networks and routes, ease of access, or planning permission requirements, local legislation, for example. The activation characteristics look up table 114 includes details about the available paint types (or other deposition materials), in relation to various surfaces, lighting and/or whether the activation deposition may produce a semi-permanent or permanent display. These parameters are calculated accounting for different paint types, finishes/applications, plus accounting for location variables (e.g. water hardness), whether paint mixing or tinting is capable, and/or whether paint shading is an available capability. What deposition materials are to be used, such as paints, paper, glue, their environmental impact, the length of time the image remains before fading away, and/or needs to be removed. The suitable zone utility group look-up table 118 is indicative of the suitable utility for each zone. Where one or more zones are determined to be suitable for more than one utility group, they may be classified as multi-utility group zones and presented accordingly. For example, a zone may be identified as suitable for a grass ground printer and a different zone may be identified as a Tarmac® surface and so best for a heated plastics deposition printer. Both the grass zone and the road surface zone may be classified as suitable zones for operation of a surface marking UGV, for printing advertisements on, for example, the surface of a sports arena and/or printing markings on a road surface, respectively. A zone might also be classified as best for the activation of pitch side display screens, digital signage, a pop-up display and/or an autonomous drone display, for example. Other characteristics could be included, such as the ‘install ease’ - which is the ease of access or the complexity of the print or display set up, the turnaround time between events, post activation removal requirements, temperature, weather conditions etc. Advert deposition/activation removal requirements could also be added, including water removal (flushing away a print with high powered water jets), or chemical removals, scraping, peeling for example, plus the advert’s impact on the environment. Referring to Figures 1A and 1B, the method 100 further comprises comparing the automated vehicle utility group look-up table 112 with the suitable zone utility group look-up table 118 for each geographical area 124 and matching suitable zones for an autonomous ground printer to operate 126. The look up table might also be used to match other display activation mechanisms with the requirements of the location, such as those mentioned above. Comparing the automated vehicle utility group look-up table 112 with the suitable zone utility group look-up table 118 thereby comprises matching suitable autonomous ground printers with suitable utility zones, indicative of suitable zones in which the selected autonomous vehicles are operable and can activate, or deploy, a required ad campaign. Accordingly, a list of stored vehicle data is compared with the area characteristics for each geographical area to determine a suitable autonomous vehicle for operating or undertaking a job in a zone of a specified geographic area. Similarly, suitable geographical areas can be determined for utilising a specific autonomous vehicle. The method 100 further comprises building a suitable zone map for the geographical area 128. Layers of information can be added to overlie a base layer map to provide visual information associated with the topographical data, proprietary data and the commercial data, as required. Regarding the passenger flight path data, flight paths of passenger planes can be tracked and built up on the map and represented as a heat map to show where and to quantify passenger movements relative to suitable zones. The suitable zone map has a zoom in/out function. The suitable zone map is interactively presented to end users through a User Interface (described with reference to Figure 5) which is accessed through an end-to-end Cloud SaaS (Software as a Service). Referring also to Figures 2 and 3, an embodiment of the present invention may include an autonomous vehicle 200 such as, for example, a horizontal surface marking robot (SMR) 202. The SMR 202 is operable to print or deposit materials on specified non-vertical surfaces to provide, for example, ground-printed text and images. Such images may be, for example, advertisements on viewable surfaces, such as logos on surfaces of sport/event arenas or any non-vertical surface which may be viewed by the public such as, for example, a building rooftop viewable from a passenger aeroplane. The SMR 202 has a communication module 204 for communicating with a remote resource such as the cloud. The cloud may comprise any suitable data processing device or embedded system which can be accessed from another platform such as a remote computer, content aggregator or cloud platform. Where there is a plurality of ground marking, or aerial, autonomous vehicles, each vehicle has communications means 204 operable to enable communication between each other. This enables the plurality of autonomous vehicles to work together to provide quicker and more efficient completion of a task, such as a printing or arial display, task. In such an embodiment, the plurality of autonomous vehicles will communicate with each other through a local peer- to-peer network to fully activate the campaign. Also, one or more of the autonomous vehicles may have system receiving means operable to receive operational information relating to the determined suitable surface in said geographical area for said autonomous vehicle to operate. The operational information may include, for example, the topographical data and/or real-time and forecasted weather conditions, such that the autonomous vehicle can automatically adjust its settings and determine power requirements to undertake the required activation. The SMR 202 also has a position sensor 206, which comprises a Global Positioning System (GPS) device for navigation through satellite positioning or a local triangulation system. In use, the position sensor 206 is operable to position and reposition the SMR 202 to deposit/print material, as required. The SMR 202 has a chassis supporting a ground wheel arrangement 208 and a print head 210 disposed on a traverse guide 212 and displaceable along the traverse guide 212 beyond the width of the wheel arrangement 208. The drawings only show two side wheels. However, it will be appreciated that the wheel arrangement may also include two other wheels on the opposing hidden side or may even comprise a caterpillar track-based system, as described in the Applicant’s other co-pending applications. Referring to Figure 3 specifically, the SMR 202 prints a strip 214 of image wider than the width of the ground wheel arrangement 208 and when a strip 214 of image has been printed the SMR 202 turns around to print an adjacent strip. In this way, the ground wheel arrangement 208 does not run over any part of the freshly painted ground. As can be seen in Figure 3, the outer tracks 216 of the ground wheel arrangement 208 is well within the width of the strips 214. The SMR 202 is specifically designed and operable to deposit or print text and images from the print head onto specified non-vertical surfaces as the SMR 202 moves over the surface. The SMR 202 has an operational specification which includes, for example, one or more of operating limitations such as, for example, surface material, gradient, and altitude. To utilise the SMR 202, it is necessary to identify surfaces within its operational specification and also identify surfaces which maximise the commercial utilisation of the autonomous vehicle, as well as the surface itself. Referring to Figure 4, there is shown a system 300, for identifying and matching suitable zones 302, for a specific autonomous vehicle operation in a specific geographical area 304, including an autonomous vehicle 200, such as the SMR 202, in communication with a remotely located edge device 306 through a communication network 308. The edge device 306 may be a computer, laptop, tablet or mobile phone. The communication network 308 may be a cloud- based communication network. A computer processor 310 (further comprising a database, not shown in this diagram) is also operable to communicate through the communication network 308 with the SMR 202 and the edge device 306. A graphical user interface (GUI) can be deployed on the edge device, and/or duplicated on a monitor screen attached to the communications network 308 and is described in further detail with respect to Figure 5. The computer processor 310 stores computer program instructions which, when executed, carries out the method 100, as shown in Figures 1A and 1B. Upon execution of the computer program instructions, the computer processor 310 receives geographical data associated with the geographical area 304. The geographical data may include one or more of, for example, topographical data, proprietary data, and commercial data of surface areas. The topographical data includes for example, surface material, surface gradient, surface planarity, geographical orientation of surface and surface altitude. It may also include identification of specific common surfaces such as, for example, flat roofs, walls, commercial buildings, and municipal playing fields. The topographical data is derived from mapping data and/or satellite data. The mapping/satellite data may be imported from a third-party entity, such as for example, Google® Maps and Apple® Maps or other similar map/satellite data provider. Google® Maps and Apple® Maps are examples of web mapping services which offer satellite imagery, aerial photography, 360 ^o interactive panoramic views of streets, real time traffic conditions and route planning. In an alternative embodiment (not shown in drawings), the topographical data is derived from aerial data collected from one or more unmanned aerial vehicles (UAV). The, or each, UAV may include one or more LiDAR devices and multispectral cameras. The aerial data is processed using a photogrammetry system to provide the topographical data as a map. The proprietary data may include data indicative of the land or building ownership which may be derived from public databases such as, for example, The Land Registry in the United Kingdom. This data may also include the type, size and value of the land or building. The proprietary data may also include data concerning a plot, or space, in the MetaVerse. The commercial data may include any data which is indicative of a commercial value proposition of using a specific autonomous vehicle and/or an autonomous vehicle system on that specific geographical area. This may include, for example, one or more of: population density; population demographics; consumer population and demographic by type; population movement; consumer movement; and travel networks and routes, such as for example, passenger plane flight paths. The commercial data may also include a surface value, that is details with regards to the value of the surface to a brand owner. This could be a combination of marketing information (football, viewing figures, number of people and who can see it), please ease of installation, cost to deploy). For example, high market value, low costs to deploy and easily accessed and low removals costs if a very high value site. This might be determined by a site survey and then the results can be stored in the database of the computer processor 310, along with the location and ownership details of the surface, for example. Additional capabilities may be therefore provided including a Return on Investment (ROI) configurator, where a user can add multiple images to a ‘virtual pitch” and attach a price to each image to determine what image would fetch the best price in which location. The geographical data is processed to determine one or more combined area characteristics. The combined area characteristic may be a unitary area characteristic, which represents two or more of the topographical data, proprietary data and the commercial data, or the area characteristic may include a topographical area characteristic, a proprietary area characteristic and a commercial area characteristic. Area characteristics may also be uploaded by a landowner who wishes to generate a further income from their surfaces, as exemplified with reference to the description of Figures 7 & 8. The identified suitable zones are sorted into utility groups 106, based on the determined one or more combined area characteristics. The, or each, utility group is associated with possible operational requirements and limitations of autonomous vehicles and/or potential commercial opportunities. The computer processor 310 further receives vehicle data and commercial requirements, associated with the operation of one or more specific autonomous vehicles such as the SMR 202 and records the vehicle data on a database. The vehicle data may include, for example, one or more of the utilities of the vehicle, the operating parameters or limitations of the vehicle, and the operating, hire or job costs which may be provided, for example, per square area (e.g. m ² ). The vehicle data may also include the deployment means, such as paint type, number of colours available, coverage, and/or removal means. The stored vehicle data is compared with the area characteristics for each geographical area to determine suitable zones for the autonomous vehicle (SMR 202) to operate. Alternatively, a list of stored vehicle data is compared with the area characteristics for each geographical area to determine a suitable autonomous vehicle for operating or undertaking a job on a zone of a specified geographic area. The suitable zone utility groups of the geographical areas are compared and matched with the automated vehicle utility groups, as previously described with reference to Figures 1A and 1B. Digital images of locations either submitted by the user, or from alternative sources, are run through an image processing engine using artificial intelligence, machine learning and computer vision techniques. From these input images, the image processing engine then generates location data, including the forms previously described that can enable decision making processes on the form and method of ground activation. Information gleaned from digital image analysis can include 3D mapping techniques based off photogrammetry, weather and seasonal visibility data based on image date and foot-fall based off of recognition of people, animals or vehicles in the image. A suitable zone map is built off a base layer map for the geographical area. Layers of information can be added to overlie the base layer map to provide visual information associated with the topographical data, proprietary data, and the commercial data, as required. Regarding the passenger flight path data, flight paths of passenger planes can be tracked and built up on the map and represented as a heat map to show where and to quantify passenger movements relative to suitable zones. The suitable zone map has a zoom in/out function. The suitable zone map is displayed to an end user through a User Interface which is accessed through an end-to-end Cloud SaaS (Software as a Service), the user interface, as described in further detail with reference to Figure 5. Figure 5 is a diagram illustrating an example user interface display 10, according to the present invention. In which it is shown a series of User Interface screens 10a, b, c, d, e, f which are accessed through the end-to-end Cloud SaaS (Software as a Service) of Figure 4. Firstly, the system can use known RAS (Remote Access Server) techniques to handle user and account management as shown in screens 10a & 10b. Via the interfaces (10 a – f), a user, such as a media planner, can perform various activities, for example access different reports about the current brand activations, upcoming planned brand activations, new bids, newly available locations, or events. The user can also add new brand locations, new event bookings, new brand agencies, or deployment sub-contractors for example, using interface 10c. Using interface 10d, reports can also be accessed, such as Ad Space (inventory) usage, Space performance, as well as feedback on the success of a recent brand activation. As mentioned previously, additional capabilities may include a Return on Investment (ROI) configurator, where a user can add multiple images to a ‘virtual pitch” and attach a price to each image to determine what image would fetch the best price in which location. User interface 10e shows that a suitable zone is selectable by a user on the suitable zone map and the selected suitable zone is assignable to the user’s account. An autonomous vehicle can then be assignable for use at the selected suitable zone to undertake the required ground surface print, or brand activation activity. For a specific autonomous vehicle, such as the SMR 202 of Figure 2, a user can view the suitable zone map showing the most suitable zones on which to operate the vehicle in a geographical region, based on the autonomous vehicle specification and the commercial opportunity, activation requirements and cost. A user zooms in to a geographical region in which they are interested. Once the user has decided on a suitable zone, that suitable zone is selected on the suitable zone map and assigned to the user’s account. An autonomous vehicle (e.g. SMR 202) is then assigned for use on the selected suitable zone. In the case of the SMR 202, the user can upload an image, such as a brand logo or other advertisement to the computer processor 310. The computer processor 310 processes the image and communicates the processed image to a SMR 202 (of Figure 2) for operating on the selected suitable surface to print the processed image thereon. ‘Subcontract’ management can also be incorporated for the actual activation itself, for example to perform an access permission verification to the location site, assess viewing positions, TV camera and/or lighting positions, and/or whether a more detailed site survey and or further local Government or State permits and/or licenses will be needed. With reference to Figures 6 - 9 following, the term ‘zone’ has been split into three subcategories: ‘Location’, ‘Site’ and ‘Inventory’. A "location" is a coordinate that defines location on surface of a globe for an area of interest where customer can place advertisement. However, because a print location can still be a large surface area, a second order term (lower- level term) is also used to define a coordinate for an area of interest that is located under the umbrella of a single print location that is called a “site". A single user can have many print sites under one print location. A "site" can still be a large area (for example the main stadium for a large football team, their training ground and other facilities owned by the club) for actual advertisement application. As such a third-order term (lowest-level term) has been defined, called "inventory" where a user is able to identify all the possible activatable real estate that can be activated to generate revenue, such as a personalised car park bays, the little area behind the goal posts, the centre pitch area, the area in front of main dug-out etc. Again, it is a case where a user can define multiple print inventories under single print site. It should be clear to someone skilled in the art that any useful term can be used, and many different levels of location category can be utilised to suit the specific need of the user’s implementation. Figure 6 shows a process diagram, describing steps related to the invention of Figure 5, wherein users can see all their managed locations and can create, retrieve, edit, update and delete them, plus activate their surfaces and review their location, site and/or inventory usage, as described previously with reference to Figure 5. Process Start Step 1. Create Location - Users can search and select a location where they want to create a site(s), and inventor(y/ies). For example, the Google® Maps suite of development and API tools may be used to allow the user to search for accurate locations. The ‘Create location’ function then uses JavaScript to extract the latitude and longitude of the marker and send it to the cloud, where it is validated and stored in the database of the computer processor 310 of Figures 4 & 10. Step 2. Create New Sites – allows users to identify sites at their location(s) and draw them onto the Google map interface. The latitude and longitude of each point is then extracted and stored in a JSON structure that can be transmitted over the cloud and is also stored in the database of the computer processor 310 of Figures 4 & 10. A person skilled in the art should know that any other data structure can be used to transmit the required data such as XML, SOAP. Step 3. Create Print Inventory – Users can identify an inventory or inventories at their site and draw them onto the google map. An Inventory has additional characteristics such as description of the surface, for example grass, Astroturf®, Tarmac® etc, which is also stored on the database 310 of Figures 4 & 10. Step 4. Editing, Update, Delete – a user can edit, update and delete the location(s), site(s) and inventor(y/ies) they created. Information is retrieved from the database regarding the location(s), site(s) and inventor(y/ies) from the database and for example, JavaScript functions can be used iterate the data and draw the location(s), site(s) and inventor(y/ies) on the Google® Map. Step 5: Inventory Activation – a user can use brand images and load the images directly to the inventory, where they can manipulate the size and rotation of the image. JavaScript® is used to place the image on the first latitude and longitude of the inventory. The latitude(s), longitude(s), image(s), rotation(s), and name(s) are saved in a JSON structure transmitted over the cloud where validation takes place and is saved on the cloud database. Step 6 –Schedule Activation - users can see saved activations and hide/show locations. The user can visualise what their prints will look like on their real estate and then schedule the prints for deployment at a time that suits the brand activation requirements. The system passes this information to the AV that has been matched to carry out the activation (with respect to Figures 1-5) Step 7 – Review Inventory Utilization. The user can see a timeline of the location(s), site(s) and inventor(y/ies) and see what prints have been scheduled and grasp an idea on availability, of their inventory, as well as availability of suitable/accessible AV machines. Information concerning the scheduled prints, location(s), site(s) and inventor(y/ies) can be pulled from the database and created into a JSON structure, and then displayed on a screen, again using HTML tools and web page creation methods, as known in the art. End of Process. It should be clear to someone skilled in the art, that the process steps of Figure 6 can be followed in several different orders, depending upon the exact workflow and needs of a user. Figure 7 is a process diagram, describing steps related to the invention of Figure 5, wherein users can decide whether to keep their locations privately managed, or to release a location into an auction, according to a second embodiment of the present invention. There will be described the following process steps. Process Start Step 1. Register – a registration step which applies to a new location owner. Step 2. Login – applies to an existing location owner only. As previously explained, the system can use known RAS techniques to handle user and account management for Steps 1 & 2. Step 3. Create Print Location - Users can search and select a location where they want to create a site(s), and inventor(y/ies). For example, the Google® Maps suite of development and API tools may be used to allow the user to search for accurate locations and draw them onto a Google® Map interface. The latitude and longitude of each point is then extracted and stored in a JSON structure that can be transmitted over the cloud and is also stored in the database of the computer processor 310 of Figures 4 & 10. A person skilled in the art should know that any other data structure can be used to transmit the required data such as XML, SOAP. Step 4. Create Print Site – allows users to identify sites at their location(s) and draw them onto the Google map interface. The latitude and longitude of each point is then extracted and stored in a JSON structure that can be transmitted over the cloud and is also stored in the database 310 of Figures 4 & 10. Step 5: Create Print Inventory Users can identify an inventory or inventories at their site and draw them onto the Google® map. An Inventory has additional characteristics such as description of the surface, for example grass, Astroturf®, Tarmac® etc, which is also stored on the database 310 of Figures 4 & 10. Step 6: Mark Inventory Auction-able Users can identify a particular inventory, site, or location which they wish to submit into an auction (of the type described with reference to Figure 8). Thus, this step allows a user to keep the inventory ‘private’ or ‘public’, so that it can be auctioned, or advertised via a website, or other means. Additionally, an inventory location owner can enable a print inventory to be public for temporary or scheduled period. For example, for a period outside of a football season, or prior to maintenance work on the surface, resurfacing, grass cutting, re-seeding, or for any other reason. End of Process. As should be clear to someone skilled in the art, a user is able to edit, update and delete the location(s), site(s) and inventor(y/ies) they created. Information is retrieved from the database regarding the location(s), site(s) and inventor(y/ies) and for example, JavaScript functions can be used iterate the data and draw the location(s), site(s) and inventor(y/ies) on the Google® Map. With reference to Figures 5, 6 & 7, Google® Maps API is used to render the map and draws the location(s), site(s), and inventor(y/ies). Web technologies such as JavaScript® and HTML support the creation of the interface. JavaScript® and HTML are used the dropdown menu to toggle on/off the location(s), site(s), and inventor(y/ies) on the map. It should be clear to someone skilled in the art that other suitable tools could be used. Figure 8 is a flow diagram showing an example landowner location registration process, according to one embodiment of the present invention, wherein the following steps are shown: S1. Register – a registration step which applies to a new location owner. S2. Login – applies to an existing location owner only. As previously explained, the system can use known RAS techniques to handle user and account management for Steps 1 & 2. S3. Create new location – allows a location owner to create a new location record in the database 310 of Figures 4 & 8, which would then be assigned to the location owner’s account. S4. Select/submit details of a new location variables, for example the GPS coordinates, the size of the location; characteristics of location, such as topological or surface type (with reference to Figure 2); S5. Enter location to be advertised as available into an Auction/bid process for an event (reference: Figure 8) – may include payment(s) depending on what level of advertising. Further, the location owner can pay to have their site activated and to pay more to further promote their site as a suitable activation surface (reference Figure 7). A Location owner may also receive revenue from a brand activation events (or events), receive feedback on success and/or ease of an install, and/or ease of activation removability post activation, which may be used to promote their location(s) further. S6. Wait for media planners to bid on, or request details of, the submitted location. S7. Matched to media planner’s requirements, activation details and to an AV (ref: figures 1a, 1b, & 2) – steps 6 and 7 can be reversed in order. S8. Payment facilitated, actions taken such as a decision as to whether a site survey is needed, and/or a third party (or a subcontracted) deployment is needed. End of Process. In Figure 9, there is shown a bidding process where brand manager/planners compete for ‘prime’ location activations, or for an event, such as the Olympics for the external to sites grass activations, or road activations. Or for example for Cheltenham races, the Masters Golf events, the Rugby World or Soccer World Cups. Step 1. Register – a registration step which applies to a new location owner. Step 2. Login – applies to an existing location owner only. As previously explained, the system can use known RAS techniques to handle user and account management for Steps 1 & 2. Step 3. Create Event/Campaign – this term is an umbrella for all locations and is used as a way to identify and categorise what prints are for what event and in which locations etc. Step 4. Search for Locations - All public inventory locations (see Step 6 of Figure 7) will be listed and available for searching. Step 5. Place or increase bid - User can decide place a bid, increase a bid or do not do anything. Step 6. Match Location and Activation Requirements to an AV (see Figures 1 to 4). End of Process Figure 10 is a diagram illustrating an online auction system that allows campaign managers to bid on locations, according to the process of Figure 9. Users, such as a media planner, can create their campaign using web-based bidding portal 370. Campaigns created by the user are added to BIDS database 320. When user searches for a particular query, core advertising engine 330 processes campaign details from database of a computer processor 310, based on certain parameters like keywords, campaign description. The advertising engine 330 then would respond with a list of the most relevant locations from the database 310, based on the data as described with reference to Figures 1a, 1b and 2. The system 300 also has a management console 340, which helps to manage the items such as rules, length of the bidding, and any other relevant factors at run time. Those skilled in the art will appreciate that while the foregoing has described what is considered to be the best mode and where appropriate other modes of performing present techniques, the present techniques should not be limited to the specific configurations and methods disclosed in this description of the preferred embodiment. Those skilled in the art will recognise that present techniques have a broad range of applications, and that the embodiments may take a wide range of modifications without departing from any inventive concept as defined in the appended claims. In a further aspect of the present invention, there is provided a system and method for identifying a suitable surface at a location, wherein an autonomous vehicle (AV) may operate to activate the surface, the system and method comprising: receiving geographical data associated with a location, the geographical data comprising topological data; receiving AV data related to one or more AV machines, wherein the AV data includes one or more activation capabilities; processing said geographical data to find one or more surfaces suitable for an activation; processing said AV data; matching an AV to the one or more surfaces, and deploying the AV to activate one or more surfaces at the location. Preferably wherein in all of these further aspects, the location is a surface or a three- dimensional space and is in the real world or the metaverse (a virtual world).