Our Data Capturing, Analytics, and Application Capabilities

Data driven future

Urban Hawk gives you control of your business’ future.

Effective competition is the key to our very survival as brands in a increasingly mobile and digitised economy. This is particularly true, sadly, in what is at best a saturated and at worst an uncertain and volatile market and post Brexit economy.

But don’t panic. We hear your concerns. We’re here to help.

Urban Hawk will help you to boost your efficiency, fly over the threats and turn those into assets; soaring above your competitors.

We are most grateful for your consideration, and looking forward to working with you.

What and How do we do?

We observe

esa copernicus usgs landsat DigitalGlobe StereoLabs

Space

We have a core ability in space based satellite data extraction as well as access to up to date and historical satellite imagery thanks to our world leading satellite data suppliers:

low orbit satellites with spatial resolution down to 30 cm per pixel

Aerial & Ground

We extract depth information from ground photos and video captures, drone footage, and camera networks.

We don't rely on Lidar. By deploying techniques such as stereo cameras, structure from motion, deep learning (AI) models, we get the results in the resolution and accuracy we need for each use case.

drones and depth sensing cameras

We 3d map

Using computer vision and artificial intelligence (AI) we automatically fetch ground photos and video captures, drone footages, and satellite imagery into highly efficient spatial data structures, ready for use. We call them spatial digital twins. Nevertheless, we are non-stop working on ever newer shape approximation techniques to make visualisation more simplistic and superb.

digital twins

We collate

We locate your relevant urban data (with geo and time stamp) in the ever growing big data sets collected world wide. We fuse with our spatial digital twins, collate and then display in 3D with time-lapse.

historical and live data sets

Transport; Pollution; Crime; Sanitation; Business profiling (local closures, employment figures); Veracity of local review bases (we will crawl reviews in mass and harness algorithms to separate the spurious from accurate).

We Apply

You and your developers can then monitor and apply relevant urban statistics in revolutionary and accessible detail.

You and your operators can profit from the arising automation opportunities through the range of our premium products we have been developing and providing on top.

commercial applications of data

In a new world of possibility through new technologies all businesses face new opportunities for growth and a need for increased vigilance against competition and ever more creative methods in surviving through saturated markets and the white noise of comms and data.

We will help you turn threat to opportunity and the potential weakness to certain strength. The tools of data and automation: on a large scale, applied to the needs of your small to medium enterprise or corporate organisation.

Case studies

Case specific examples:

  • Increase your situational awareness, act quicker, understand dynamics, prevent recurring incidents.

  • Automate, turn your planning into data driven processes.

  • Validate through trusted data!

  • Reduce the use of manual surveying fieldwork when quantifying assets and their status.

  • Critical infrastructure monitoring for Rail.

  • Evaluate the accessibility and resilience of infrastructure.

  • Obstruction by overhanging vegetation.

  • Run more accurate deterioration models and build better predictive maintenance plans to reduce cost and replace more assets at the optimal point, before they fail.

  • Monitor competitor activity and performance.

  • Are you in the real-estate business? Understand properties and neighbourhoods in context.

  • Market research: collect more field evidence for your business plan.

  • Urban mobility.

  • Guidance.

  • Logistics tracking and monitoring.

  • Multi-modal transport.

  • Maritime logistics.

  • Maritime berth utilisation.

  • Maritime port automation.

  • Sea traffic management.

  • Risk asessment.

  • Data for Insurtech.

  • Claim validation

  • Flood modelling.

  • Post disaster (ex. flooding) assessment.

  • Urban change detection for planning enforcement.

  • Urban green spaces planning and management.

  • Improve your decision-making by easy access to consistent and authoritative spatial data.

  • Identification of solar panels.

  • Detection of deteriorating roads.

  • Or just get a read out of changes that might impact your business.

+ Many-many more tailored to your business, interests, and needs.

coming soon

The sub-section is under constant construction. Check back from time to time.

The present and future of Urban Landscape monitoring

More than half of the world's population now lives in cities. In the developed world, many cities which were seen as being in relative decline – such as London in the 70s – are now driving national economies.1 Therefore it is common interest to focus our resources on the urban landscape instead of rural.

Mapping the future of the UK's cities is a multi-faceted problem. Which of them will grow, both physically and in population, and which will shrink? Where will there inhabitants come from? How will their economies and governance evolve? How will we move around them? Who will provide their essential services? How will environmental concerns shape them? The answers are complex, overlapping and contingent on a multitude of variables.

A 2014 working paper, The Evolving Economic Performance of UK Cities2, observes: “In the UK there is no single consistent or official definition that is used as the basis for public policy interventions. This makes analysis, especially over time far from straightforward”.

When even definitions and policies vary it is understandable that the available data sets are fragmented, formats differ, etc. (similarity with weather, climate, environment, vegetation data sets in other Earth Observation fields). Difficult for insiders and outsiders to assess.

Cities

A city is a system made up of interdependent elements: population, housing, employment and access to services, including utilities, education and health, and transport. Cities are part of a national system connected through air, road and high-speed rail.

Our knowledge of cities

There is an embryonic science through which we know quite a lot, though much of our knowledge is parcelled into disciplines and one challenge is to draw this together and to integrate it. In all cases, our knowledge is partial. Demographers for example, have good theoretical models of population change. However, these depend on assumptions about birth, death and migration rates. The first two follow historical time trends pretty well, but the third is very difficult and throws considerable uncertainty on forecasts. We have knowledge at different scales. Sociologists can focus on how individuals and families live in cities. Economists are typically micro or macro focused and yet much of the interest in urban economics can be seen as in between. Geographers fill this gap to some extent. We need the knowledge of engineers on how infrastructure functions and how to articulate the challenges and opportunities both present and future, especially in relation to technological change. In some cases we have accurate computer models, of transport flows for example; and most large retailers would now use these kinds of model to optimise their networks. This kind of analysis tells us how cities work and provides a basis for articulating the challenges, present and future.

1 Citation from “Moving beyond smart cities” by Alan Wilson; Sir Alan Wilson is Professor of Urban and Regional Systems at University College London and until recently was Chair of the Lead Expert Group of the Government Office for Science Foresight Project on the Future of Cities.

2 The Evolving Economic Performance of UK Cities: city growth patterns 1981-2011 by Professor Martin, Department of Geography, University of Cambridge, by Ben Gardiner, Cambridge Econometrics, and Department of Geography, University of Cambridge, and by Professor Peter Tyler, Department of Land Economy, University of Cambridge.