PrecisionHawk develops data and safety tools to take drone use to the next level

By Aleks Buczkowski

For many years, remote sensing was directly connected to collecting data with satellites and manned aircraft. Originally this was a truly game changing technology, but it had its limitations. These data gathering technologies, while effective, can be expensive and, in many cases, time inefficient.

Traditional remote sensing multispectral images

Over the years market needs have evolved and today’s decision makers require hyper accurate, hi-resolution data in a near real-time, which is difficult to achieve using traditional methods. This is where drones, previously used for military reconnaissance, entered the remote sensing arena. UAV flights can be conducted daily, for smaller areas, at low altitudes, resulting in higher resolution imagery at a fraction of the cost..


PrecisionHawk – North Carolina-based start-up was one of the first who realised the potential of drones in remote sensing. In 2008 they started flying their first aircraft, The Lancaster, for commercial applications in Canada, specifically in the viticulture industry. The vision behind it was however much different from most of the players on the market. PrecisionHawk understood early on that the use of small UAVs goes far beyond data collection; the key is turning around actionable information, so a platform needs to include data processing and analysis. In the past, these functions were separated. Data was often collected by one company and then handed over to another organization for processing and analysis.

PrecisionHawk took a different approach and decided to build an end-to-end solution that did not require a pilot or remote sensing expert to operate and understand, but would allow an average grower to gather field data in the matter of minutes. Five years ago the idea seemed crazy, but today the approach introduced by PrecisionHawk is recognized as industry standard.

All you need is a tablet or laptop with the dedicated map platform where you mark area you need to survey. Than you simply throw the plane into the air. Everything else is done automatically. The aircraft computes flight paths, survey parameters, take-off and landing paths on its own. Once the survey is complete, the on-board computers will automatically connect to Wi-Fi networks and transfer all remote sensing data, flight information and diagnostics to remote servers, which can be accessed via its DataMapper platform. Moreover the drone sensors are fully customisable. Depending on your needs, you can buy extra sensors like Lidar and just plug it in. Sounds cool?

That’s not all. The PrecisionHawk software platform, DataMapper, is used for storing, processing and analysing remote sensing data features a really unique thing – a marketplace where a user can buy and sell your remote sensing algorithms. It is one of the first places where a user can easily commercialize it’s analysis tools and developments. But this is not the only area where the company is taking the approach to create an aerial information ecosystem. In early 2015, PrecisionHawk acquired TerraServer – a popular web portal to buy satellite images. In the future using TerraServer technology you will be able not only to buy satellite imagery, but order drone services from PrecisionHawk and other companies to get a higher-resolution picture of your desired location.

But building the end-to-end drone platform is just a beginning. In 2014 PrecisionHawk raised $11m in seed funding with the aim to go beyond being just an outstanding drone start-up. The company developed the first, automated air traffic control system for drones calledLATAS (Low Altitude Traffic and Airspace Safety) to help solve the safety issue presented when integrating drones into the airspace with competing obstacles.

The existing air traffic control system almost fully relies on ground radars. It works well with regular aircrafts, but small drones, flying at low altitudes are almost impossible to be detected. Besides, any system of human operators could not possibly scale to accommodate the millions of drones expected in years to come. LATAS on the other hand uses cellular and satellites technologies to manage millions of simultaneous connections between drones and other ground and air obstacles. By relaying on existing infrastructure the platform has the ability to scale and to accommodate the millions of drones expected in years to come.

The aim of the project is to safely integrate drones into the national airspace, and it is being tested together with United State’s FAA under the Pathfinder program.

From PrecisionHawk perspective LATAS is a strategic project as the safety requirements are still a key barrier for the industry. This doesn’t stop the company to expand from agricultural data collection business to new industries including construction, insurance and energy among other. Today PrecisionHawk’s client base includes several Fortune 500 companies in the US, Europe and Asia. Not to shabby.

“A million-dollar idea” for a start-up needs to have a clear vision which either solves an existing problem or generates a new desire. PrecisionHawk is a model example of that sort of thinking. The company’s founders had a clear vision and found a proper people to make it happen. Today PrecisionHawk is one of the industry leaders and it sets standards for everyone else.

Source: Geoawesomeness

Trends in warm days across Europe

How to read the map: Warm days are defined as being above the 90th percentile of the daily maximum temperature. Grid boxes outlined in solid black contain at least 3 stations and so are likely to be more representative of the grid-box. Higher confidence in the long-term trend is shown by a black dot.

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Metadata
Last upload:

     22 Jun 2015

Temporal coverage: 

     1960-2014

Tags:

      climate change | climate | extreme temperatures

Geographic coverage:

  Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic,Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Kosovo (UNSCR 1244/99), Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Montenegro,Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden,Switzerland, The Former Yugoslav Republic of Macedonia, Turkey, United Kingdom

Units:

    days/decade

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Access is managed by the owner mentioned below. Please contact the owner for more information about their data policy. Owners:Royal Netherlands Meteorological Institute (KNMI)UK Met Office Processors:European Environment Agency (EEA)Permalink to this versionabdcc122d76140479fc0e74abbe73113Permalink to latest versionD702EDEE-08D7-4687-B717-690A71819BA8 Figure type:Map

Additional information

Geographical coverage note: Europe

Source: EEA

Data versus documents

By George Demmy




An overused, over-abused word we have today is “data”. Often people say they “just want to see the data”, but that is almost never what they mean. What they really mean, is “show me the data in a picture arranged just so that I don’t have to read anything to understand it”. That may sound cynical, and I don’t mean it cynically, but that is my experience. Every now and again you’ll get a scientist or someone with a truly scientific bent who really does want to see the data, but they’re not common, and certainly not as might be implied by all of the Church of Data blog posts and manifestos might have you believe. Now, with GIS and geo-writ-large, the connection to data is explicit and apparent, and some are prone to obsess over data, its forms and formats, interfaces for access and frobbing, to the point of distraction. For some, data is the end, it’s their product. But if it really is data, then that’s only a point, or narrow band, on a wide spectrum spanning from data to information to knowledge to wherever that knowledge might take you: insight, action, wisdom, understanding. That’s the point. While the generation of data might put bread on some analyst’s table, it only does so because that data is part of a larger whole. Yes, carefully designed and developed, high-quality, accurate data sets are valuable, but only for what you can do with them. To that end, it’s very important to make it accessible – the lower the barriers to access data enhance the possibilities for its use. If things are locked up in proprietary systems and locked away behind proprietary interfaces, it’s harder to make use of the data and necessarily limiting its utility and value.



As you move up the spectrum, something interesting happens. The point is not to share data (although that certainly might be part of the process), but to communicate information and knowledge. Knowledge necessarily requires the synthesis and distillation of data into something more general and abstract, and much more powerful. Knowledge and how it’s presented to whom are not portable or skinnable the way that views on data can be. It can be as much of a design process as a scientific exercise, requiring consideration of audience and motivation for presenting the information in the first place. Think about the difference between a sensor, say a recording thermometer, and Edward Tufte. That’s the difference between the generation of data and the generation of contextualized presentations of information for a specific purpose. In general, I’m far more interested in the latter. It’s from the presentation of information perspective that I tend view the world that TerraGo serves.

One of the questions that we hear fairly regularly, is how is your PDF better than someone else’s PDF. Well, it depends, I suppose. Maybe it’s not better for your purpose. If they made it right it conforms to ISO 32000 just like ours do. Maybe theirs is smaller because they haven’t preserved layers for view at different zoom levels, or they just rasterized it all for quick visualization on a handheld, and doesn’t have any layers at all. That PDF actually may be better for that purpose than a full bells-and-whistles GeoPDF document made in Publisher. Naturally, we give you controls in Publisher to configure your GeoPDF to your diverse purposes, which is the whole point. If you don’t care what the users will do with the PDF or what you want to have done with it, it’s hard to argue that one’s better than the other. However, if you want to create location-enabled documents that present GIS-derived information in interactive, intuitive ways familiar to anyone who is familiar with PDF, then we have a matchless system. The interactive features that you get with Reader or any PDF consuming device are considerable on their own (hyperlinks, bookmarks, layering and it’s design and control, etc.), but it’s the dynamic interaction with coordinates, measurements, GeoPackage feature attributes with a client application that free for end users to download and install which makes the experience so rich. The question should not be one PDF versus another, which more often than not is an uninteresting and often nonsensical question, but rather how do you effectively communicate location-based information to as wide an audience as possible? Documents have not outlived their usefulness, and as long as they haven’t GeoPDF will have a role to play helping people understand location-based information more quickly, thoroughly, and effectively.

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Free Data from Indian Resourcesat-2 Satellite via INPE

By Stefan Mühlbauer



In December 2014, The National Institute for Space Research of Brazil (Instituto Nacional de Pesquisas Espaciais, INPE) announced the distribution of images deriving from the Indian Resourcesat-2 satellite. The images are received and collected at the ground station in Cuiabá, capital of the federal state of Mato Grosso, which is run by INPE. The images can be ordered for freeat http://www.dgi.inpe.br/CDSR/ , only registration is required.

Resourcesat-2 is an orbiting Indian Earth Observation satellite and was launched in 2011 as a follow-on mission to the Indian Resourcesat-1 satellite increasing the observation timeliness (repetivity) in tandem with ResourceSat-1. It carries three imaging sensors LISS-3 (Linear Imaging Self Scanning Sensor), LISS-4 and AWiFS (Advanced Wide Field Sensor). While the resolution diminishes from 5,8m (LISS-4) and 23,5m (LISS-3) to 56m (AWiFS), the swath enhances from 70km and 141km to 740km respectively. All sensors record in the green, red and near infrared bands, whereas the latter two sensors also record in the short wave infrared spectrum. The ResourceSat data find their application in several areas like agricultural crop discrimination and monitoring, crop acreage/yield estimation, precision farming, water resources, forest mapping, rural infrastructure development, disaster management etc.

INPE also distributes satellite images from the CBERS missions (China and Brazil), LANDSAT missions and Resourcesat-1. Hence, the Brazilian Institute for Space Research constitutes one of the most complete remote sensing catalogues in the world with images starting in 1973 right after the launch of LANDSAT-1.

LISS-4 image (Mx mode, 6 m) of the Sharjah International Airport of the United Arab Emirats on May 8, 2011. Source: eoPortal

LISS-3 image (23,5m) from the interior of São Paulo State on September 22, 2014. Source: INPE

AWiFS image (56m) from the Corumbá region in the federal state of Mato Grosso do on September 30, 2014. Source: INPE

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Mastering Waves of Data

Hexagon Geospatial and rapidlasso GmbH Partnership





As a result of a recent partnership between Hexagon Geospatial and rapidlasso GmbH, the latest release of rapidlasso´s LAStools contains a new toolbox for ERDAS IMAGINE 2014, with a 2015 release expected this summer. Now, analysts can create Spatial Models within one interface that chain together the operators added by LAStools with the raster and vector operators in ERDAS IMAGINE to create models that describe their specific workflow.





Figure 1: Sample LAStools workflow created with the Spatial Modeler of ERDAS IMAGINE. First a point density raster of the input LAZ is computed for quality checking by 'lasgrid'. Next, the file is ground classified by 'lasground'. Then the “height above ground” of each point is computed by 'lasheight' and used to classify building and vegetation points by 'lasclassify'. Then a 0.5 meter DSM hillshade is produced with 'blast2dem' and a 0.5 meter DTM hillshade is produced by 'las2dem', both in PNG format. Finally, two shapefiles with polygons marking the building footprints and the vegetation areas are computed by 'lasboundary'.



Those who balance out their intense geospatial careers with surfing the world's oceans often describe the moment of catching a wave as feeling absolutely in tune with the forces of nature. As the wave comes closer you paddle and position your board to carve out a niche in the wave using the skills and experiences acquired on numerous waves before. Each wave has its own identity, so you need to adjust your moves to ride a wave to shore. Becoming one with the ocean like that is an incredible experience.

Waves and waves of geospatial data are rolling in on those working in today's geospatial analysis industry. There is not just one but three different kind of data crashing upon our shores: raster, vector, and point cloud data. For a smooth ride during geospatial data analysis, people require multiple and modular software packages that effectively work together. They must be adjusted as needed to synthesize the input streams into one cohesive answer. The ability to edit and classify in the point domain, then run analysis on a raster and feed that information into vector analysis is crucial for making sense of the choppy seas of data and painting the bigger picture our decision-makers need.

Position Yourself in Data Waves
This is where ERDAS IMAGINE Spatial Modeler comes to the rescue. By allowing you to quickly and easily string together geoprocesses in an easy and intuitive fashion, it frees your mind to focus on riding even the biggest geospatial data waves in the most efficient way. It replaces the traditional dialog-driven workflow with modular and customizable pipelines that provide your geospatial senses with a streamlined and repeatable means of getting the answer.

The Spatial Modeler has an extensive library of geo-processing operators that work on all three waves of data. But its real power comes from its extensibility, allowing users and domain experts to add their own operators, including tools from other software. This can be done by running external command line tools within the Spatial Modeler environment, by creating Python operators, or by using the Spatial Modeler SDK to build new operators.

Carving Out Your Niche
That’s why Hexagon Geospatial and rapidlasso GmbH decided to team up. ERDAS IMAGINE is a powerful tool used in the Remote Sensing industry, and LAStools by rapidlasso GmbH is a popular LiDAR processing software suite – a robust collection of extremely efficient, batch-scriptable, multi-core command line tools. Together, we can merge our strengths to simplify the system.

Balancing the daily developments with a few hours of surfing in their secret laboratories in the Philippines, Hexagon Geospatial and rapidlasso GmbH used the inspirations of their exotic location to leverage the extensibility of Spatial Modeler and make the powerful command line tools from LAStools available within the ERDAS IMAGINE Spatial Modeler framework. The latest release of LAStools from rapidlasso GmbH contains a new toolbox for ERDAS IMAGINE 2014, with a 2015 release expected this summer.

Now, analysts can create Spatial Models within one interface that chain together the operators added by LAStools with the raster and vector operators in IMAGINE to create models that describe their specific workflow. These models can then be saved, reused, and shared across departments. They can even be customized so non-technical specialists can use them to adapt as conditions change.

Riding Smooth Whatever Water
This combination makes complete sense. “This kind of partnership is part of a growing strategy to extend the utility of ERDAS IMAGINE and position the Spatial Modeler as a platform to provide our customers with powerful capabilities not supported in ERDAS IMAGINE. Many current ERDAS IMAGINE customers already use LAStools for their Point Cloud processing, and this collaboration provides them—and future customers—with a seamless interaction between point cloud, raster and feature analytics,” said Steve du Plessis, Director of Remote Sensing for Hexagon Geospatial.

“With the huge breadth of ERDAS IMAGINE’s Geospatial users and capabilities we cannot always meet the detailed requirements of our customers. Martin Isenburg has a very close relationship with his user community and provides concise market-driven functionality. This partnership with rapidlasso makes for the perfect mix,” added du Plessis.

Calming Choppy Geospatial Seas
By putting together a platform like the Spatial Modeler and powerful domain tools like LAStools, a system that has long been divided is now unified. The goal is to harmonize different geospatial workflows that have traditionally been separated no matter what waves of data users are exposed to. By simplifying and de-cluttering a workspace, users are allowed to focus on riding their geospatial waves to shore, opening new and innovative moves to unlock the wealth of information locked inside in new and innovative ways.

For more information, have a look at: http://rapidlasso.com and http://hexagongeospatial.com


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