Τρίτη 27 Οκτωβρίου 2015

Using Unmanned Aerial Systems (UAS) for Remote Sensing of Archaeological Sites



BY RACHEL QUIST


Unmanned vehicles are becoming more widely available both in the military and civilian sectors for their usefulness for remotely acquiring a variety of data. Unmanned Aerial Systems (UAS), previously referred to as Unmanned Aerial Vehicles (UAV), are integrated ground, air, and data systems in which an aircraft (fixed wing or rotary) are either remotely piloted or operates autonomously and can perform a number of missions, including reconnaissance and remote sensing.

Beyond the military’s interest in UAS’s, the civilian sector has become increasingly aware of these systems and due to lower tech options; UAS’s have become useful in a number of scientific discipline studies.


RQ-8A FIRE SCOUT VERTICAL TAKEOFF AND LANDING TACTICAL UNMANNED AERIAL VEHICLE (VTUAV) SYSTEM. SOURCE: U.S. NAVY PHOTO BY PHOTOGRAPHER’S MATE 2ND CLASS DANIEL J. MCLAIN


Archaeological researchers are an early adopter of remote sensing technology but until the early part of the twenty-first century data was primarily limited to aerial/satellite imagery and photogrammetry. These methods were rather successful for a number of projects, most notably investigations of the geoglyphs of Nazca, Peru, but were still rather limiting in many ways.

Examining the Nazca case study, these archaeological features are highly unique and unusual and have been a bit of a mystery for the last century, largely due to the difficulty of recording these large features. The Nazca lines are huge, some measuring 200 meters, and are combinations of lines, trapezoids, stars, human figures, and animal figures. The geoglyphs are made by removing reddish pebbles of the high desert plateau and exposing the light colored ground underneath.


FIGURE IS KNOWN AS THE DOG, AN EXAMPLE OF NAZCA GEOGLYPHS LOCATED IN THE NAZCA DESERT, A HIGH ARID PLATEAU THAT STRETCHES 53 MILES BETWEEN THE TOWNS OF NAZCA AND PALPA ON THE PAMPAS DE JUMANA. SOURCE: COLEGTA (WIKIMEDAI COMMONS).

In a study published in 2000, Grün et.al used digital photogrammetric technology and integrated their data intovector and raster GIS data. This was the first time that these archaeological features were recorded using a GIS approach. Unfortunately, their study encountered a technological limitation of the computers at the time; their computer memory was limited to 64 MB which was not enough to render some of their graphics and data.

A few years later, in 2004, Eisenbeiss published a study in which a mini unmanned aerial vehicle was used for photogrammetric recording and documentation of a previously identified heritage site in Peru, Pinachango Alto. This study used a Copter 1B from Survey-Copter equipped with GPS/INS stabilized system, an onboard Cannon D10/D60 camera, and a ground control station by weControl. The flight plan was developed with predefined points and stopped and once programmed into the helicopter the flight path was automatically flown.

The project was able to successfully map the archaeological site and to render a 3D model of the settlement but they still had their share of technological difficulties. Their conclusions and recommendations noted that UAS’s used to map heritage sites should be able to fly longer than 15 minutes, which in their case required attaching a larger gas tank and then increasing engine power to carry the heavier payload.

In more recent years, a wide variety of UAS systems have been developed to address these early problems of duration, payload weight, and computer memory. In addition, GPS, LiDAR, photography, and wireless data integration have also improved allowing for viewing of real-time imagery from UAS’s for a period of several hours.

Thermal infrared photography from UAS’s is another improvement that has allowed archaeologists to see previously unknown and subtle features on top and beneath the surface landscape. Linear features such as prehistoric roads and canals can be easily detected as well as some subsurface features and burials using thermal infrared photography. Due to these improvements in the technology a number of archaeological survey and recording projects around the globe have used unmanned aerial systems to locate and map archaeological sites. In fact, the technique is becoming so widespread it has earned the name “aerial archaeology.”

Despite these improvements, use of unmanned aerial systems is largely restricted to being used to locate and record very large archaeological sites and generally those sites that contain remains of structures. These types of archaeological sites, although very impressive and widespread throughout the world, are not the most common site type. More typically, archaeologists record artifact concentrations associated with specific activity types in the past; these may include hunting sites, tool resharpening stations, toolstone quarrying, plant gathering and processing stations, and ceremonial locations. At this point in time, the best method to locate these discrete clusters of small artifact remnants is with the unaided human eye during a pedestrian survey.

Other uses for UAS technology are quickly becoming evident and entering the civilian sector through private corporations marketing directly to specific industries. Current and future applications of UAS’s will include forest fire detection, fire fighting, emergency mountain rescue, avalanche survivor search, crop dusting, pollution monitoring, natural disaster monitoring, delivery of emergency medical/food supplies, road traffic surveillance, poaching patrol, and weather data and research.

References:
Eisenbeiss H., 2004. A mini unmanned aerial vehicle (UAV): system overview and image acquisition. International Workshop on “Processing and visualization using high-resolution imagery”.

Grün, A, Bär, S., Beutner, S., 2000, Signals in the sand: 3-D recording and visualization of the Nasca geoglyphs. PFG, Vol. 6

Using Remote Sensing to Measure Land Deformation



BY CAITLIN DEMPSEY MORAIS


The European Space Agency has developed a new land data processor to create maps of land deformation. Called Wide Area Processor (WAP), the processes uses radar data to measure millimeter terrain deformations. Changes in the surface height of a landscape occur over time. Sinking of the earth can happen as a result of mining, earthquakes, or natural gas extraction. Expanding volcanoes or the collision between tectonic plates can result in the rising of the earth. The development of WAP allows for the measurement at the millimeter level of changes in the earth’s surface over large swaths of area.

Using a remote sensing technique called ‘persistent scatterer interferometry’, WAP is able to measure changes in height over time. Persistent scatterers are features such as buildings on the landscape that are stable, enduring, and reflect radar well. These characteristics present a measurable feature as the satellite orbits the earth.

For the pilot study, the WAP measured over a million persistent scatterers over half of Greece’s mainland (a land area of 65,000 km2) , pulling radar data from ERS-1 and ERS-2. Both of these remote sensing satellites house earth observation instruments including Synthetic Aperture Radar (SAR) which can detect changes in surface heights with sub-millimeter precision. With ERS-1 having orbited from 1991 to 2000, and ERS-2 still orbiting (launched in 1995), both earth observation satellites provide the ESA with long term data with which to study land deformation. For the initial study, over 360 gigabytes of raw radar data from the ERS-1 and -2 satellites was used. Rural areas averaged 10 scatterers per square kilometer. Urban areas such as the capitol, Athens, averaged 200 scatterers per square kilometer.

The study found that over a ten year period, areas in parts of Greece are sinking by about 10 mm per year. The areas of greatest subsidence were found in the cities Athens and Larissa, and around the Gulf of Corinth. The city of Thessaloniki showed areas experiencing both subsidence and uplift.


EXAMPLE OF WIDE-AREA MAPPING OF TERRAIN DEFORMATIONS OVER MAINLAND GREECE. THIS GPS-CALIBRATED DEFORMATION MAP COVERS 65 000 SQ KM – APPROXIMATELY HALF OF THE COUNTRY’S TERRITORY. THIS MAP WAS CREATED USING 10 INDIVIDUAL ERS-1/2 STACKS, EACH STACK BEING A TIME SERIES OF 58 TO 76 SAR IMAGES ACQUIRED FROM 1992 TO 2003 FOR A TOTAL OF 671 IMAGES. SOURCE: ESA.
WAP can be used to process data from other satellites such as ALOS, TerraSAR-X and the future Sentinel-1. Sentinel-1 is being developed under Europe’s Global Monitoring for Environment and Security (GMES) program and will provide additional C-band synthetic aperture radar data. The first Sentinel-1 will be launched in 2013 and the second in a few years.


Source: GIS Lounge - Maps and GIS








Water Utilities: GIS has Changed Have You?



By Matt Sheenan



Water utilities both big and small are faced with a range of different challenges. A recent American Water Works Association (AWWA) report listed but a few:

1. Condition of water/wastewater infrastructure
2. Water scarcity/supply
3. Drought potential
4. Customer/community relations
5. Emergency planning and response
6. Government regulations
7. Managing assets

New technology is today helping to provide solutions to these challenges. Key among these technologies is GIS.

Water Utilities: GIS has Changed Have You?
GIS is not new. It is a technology which today is undergoing dramatic changes. Changes which are making it easier to afford, access and use. So what are these changes?

Cloud Based GIS is a Game Changer
Gone are the days when you as an organization need to deal with the complexity and expense of setting up and hosting a GIS internally. Cloud based GIS is now here. That means others maintaining your GIS, simply set up a subscription to Esri’s ArcGIS for example and go. Its as simple as that. GIS subscriptions are very affordable even to the smallest utilities. Internal staff are no longer required to maintain and update your GIS. Maybe most importantly it has never been easier to administer a GIS and publish maps.

If cloud based GIS solutions are not your cup of tea, with releases like Portal for ArcGIS, you can now host your own version of ArcGIS Online inside your firewall.

No More Data Silos
We once lived in a world where authoritative data was hard to find. Reliable water main data was over here, updated valve inspection data over there. A GIS provides a central system for all your data. Your organizations authoritative data or system of record. Anybody in your organization who needs access to any asset or asset related data can simply access your GIS.

Mobile Maps, Mobile GIS Apps
Mobile devices – smartphone, and tablets – are transforming society. Today we all carry miniaturized computers, which know through GPS where they are at all times. Apps which provide interactive maps are extremely popular. GIS not only provides maps, it allows water utility field staff to better get their jobs done.


We have been building a simple asset management mobile ArcGIS application for utilities which works both online and offline, is configurable and runs on any device and any platform (Apple, Android, Windows). Its an elegant solution for those who are looking to move away from ArcPad or cannot afford enterprise GIS asset management platforms.

New Configurable Applications for Water Utilities
There has been a new move in the world of GIS to provide focused, targeted configurable applications. Esri have been particularly busy here. ArcGIS for Water Utilities is a suite of applications designed to solve specific challenges. Whether it is tracing illicit discharge, finding polluters, analyzing water loss, responding to emergencies, generating water reports or connecting with customers. There is an easy to set up application designed for that purpose.


We have been working with a number of utilities helping them take advantage of these solutions.

GIS has come a long way in the last 2 years. More affordable, easier to access and use. If you are not actively using GIS and the new tools available to manage your water utility, you are missing out on a crucial time and cost saving technology.


Contact us for more information on 801-733-0723.

Δευτέρα 26 Οκτωβρίου 2015

From Big Data to Big Action: Tackling Poverty and Inequality Using Data Visualization



By Matthew Tyler.



“It’s not about big data, it’s about big understanding… Understanding strengthens the link between data tools and policy action.” These were the reflections of Jack Dangermond, Founder and President of the Esri, at the 14th convening of the Project on Municipal Innovation Advisory Group (PMI-AG). Dangermond was joined by leaders from America’s largest cities to discuss how municipal Chief Data Officers can impact policy, emphasizing ways that data – and in particular, data visualization – might be used in the fight against poverty and inequality.

Big data analytics and data visualization have made great strides in recent years. Building and food inspections are better targeted; congestion on roads and public transport is monitored in real time; natural disasters are preemptively simulated; and city “story maps” are used to engage citizens in municipal service delivery, small business decisions, and land use planning. However, the palpable sense of anticipation among PMI participants suggested that using big data and data visualization to tackle deeper systemic issues proves more difficult.


“Understanding strengthens the link between data tools and policy action,” Dangermond said.

With regards to poverty and inequality, progress in data visualization has been largely limited to what several participants described as “sad maps.” Maps for crime rates, school retention, and infant mortality measures all tell similar geographical stories: the darkest shades of the map, indicating the most severe disparities, represent the same few neighborhoods. Participants agreed that all too often these maps prompt concern, but offer few suggestions on how to shape policy.

Over the course of the panel, however, it became clear that several emerging data-orientated approaches have the potential to shape policies that address poverty and inequality:

  • Overlay “sad maps” with the existing geographical distribution of service delivery to inform future budget allocations. Several participants are in the process of using maps to determine whether there is underlying discrimination in infrastructure investments.
  • Use spatial correlation analysis to identify and understand positive deviance. That is, given what we know about a neighborhood’s context, which areas are performing better than they ought to be? For instance, what can we learn from high poverty neighborhoods where obesity is low?
  • Use regression over space and time to identify root causes. In doing so, the most important lead indicators can be used to identify those who may benefit most from early intervention. In Chicago, intensive academic tutoring is targeted at those who fail Algebra 1; the best predictor of school dropout. A similar approach is being employed to analyze patterns of eviction in New York that are most likely to lead to homelessness.

These approaches are only a starting point. To create real change, a symbiotic dance must take place between policy officers and data officers. Policy officers must identify the information products needed to inform decision making. Conversely, data officers need to help point out caveats and suggest how additional analysis could tease out further conclusions. In turn, policy officers complement data analyses with their nuanced research knowledge to build a causative narrative of what are almost always endogenous problems – and this narrative can spring to life with data visualizations or story maps developed in data shops. This is the back and forth of problem solving that translates analysis to action.

Similarly, getting the best out of big data requires engagement with the public. Several Chief Data Officers explained that they spend a lot of time talking with the public to understand what is happening “on the ground.” Data is only one piece of the puzzle. In a bid to share costs and broaden capabilities, a growing number of cities are partnering with leading research universities through the White House backed MetroLab network. It is hoped that these partnerships will underpin the transition of big data and data visualization across mayoral administrations.

Like e-mail, big data and data visualization will likely become ubiquitous. For systemic policy issues though, moving from data to information products and ultimately to policy action is no easy task. The ideas raised during the PMI-AG discussion suggests big data and data visualization have the potential to improve policies targeting poverty and inequality. With that said, there is much work and discovery to come before we can make firm conclusions about their efficacy. In the words of Thomas Edison – “the value of an idea lies in the using of it.”

Source: Public CEO

A Genetic Atlas of Human Admixture History



Research article by:

Garrett Hellenthal1,
George B. J. Busby2,
Gavin Band3,
James F. Wilson4,
Cristian Capelli2,
Daniel Falush5,*,
Simon Myers3,6,*,†


1UCL Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK.
2Department of Zoology, Oxford University, South Parks Road, Oxford OX1 3PS, UK.
3Wellcome Trust Centre for Human Genetics, Oxford University, Roosevelt Drive, Oxford OX3 7BN, UK.
4Centre for Population Health Sciences, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK.
5Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.
6Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK.
↵†Corresponding author. E-mail: myers{at}stats.ox.ac.uk


↵* These authors contributed equally to this work.




ABSTRACT
Modern genetic data combined with appropriate statistical methods have the potential to contribute substantially to our understanding of human history. We have developed an approach that exploits the genomic structure of admixed populations to date and characterize historical mixture events at fine scales. We used this to produce an atlas of worldwide human admixture history, constructed by using genetic data alone and encompassing over 100 events occurring over the past 4000 years. We identified events whose dates and participants suggest they describe genetic impacts of the Mongol empire, Arab slave trade, Bantu expansion, first millennium CE migrations in Eastern Europe, and European colonialism, as well as unrecorded events, revealing admixture to be an almost universal force shaping human populations.

The in-Laws Through History
Admixture, the result of previously distant populations meeting and breeding, leaves a genetic signal within the descendants' genomes. However, over time the signal decays and can be hard to trace. Hellenthal et al. (p. 747) describe a method, using a technique called chromosome painting, to follow the genetic traces of admixture back to the nearest extant population. The approach revealed details of worldwide human admixture history over the past 4000 years.

Received for publication 22 July 2013.
Accepted for publication 20 December 2013.

For full text, follow the link here.

For the genetic atlas of human admixture history website, click here.