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There is a crucial role of GIS and Remote Sensing tools for improved landslide inventory mapping and landslide assessment and susceptibility. In this concept note, the application of GIS is emphasized for the prediction and mapping of landslide susceptible areas in the Indian state of Himachal Pradesh.

Landslide is a general term used to describe the down-slope movement of soil, rock and organic materials under the influence of gravity (Varnes , 1984).

There are three major causes that create the occurrence of landslides – Geology, Morphology and Human activity.

Geological Causes
Geology refers to characteristics of the material itself. The earth or rock might be weak or fractured, or different layers may have different strengths and stiffness.

Morphological Causes
Morphology refers to the structure of the land. For example, slopes that lose their vegetation to fire or drought are more vulnerable to landslides. Vegetation holds the soil in a place and without the root system of trees, bushes, and other plants, the land is more likely to slide away or eroded by the rainfall. Other causes are: Climatic conditions, Earthquakes, Weathering, Erosion, Volcanoes, Forest fires and Gravity.

Human Activities
Human activities like agriculture and construction can increase the risk of a landslide. Mining activities utilizing blasting techniques contribute extremely to landslides. Vibration produced from the blasts weakens soils in nearby areas and make the land susceptible to landslides.

Types of Landslides
There are many ways to describe a landslide. The nature of a landslide’s movement and the type of material involved are two of the most common.

Landslide Movement: There are several ways of describing how a landslide moves. These include falls, topples, translational slides, lateral spreads, and flows.

In falls and topples, heavy blocks of material fall after separating from a very steep slope or cliff. For example, Boulder tumbling down a slope would be a fall or topple.

A lateral spread or flow is the movement of material sideways, or laterally. This happens when a powerful force, such as an earthquake, makes the ground move quickly, like a liquid.

Application of GIS and Remote Sensing in Landslide Hazard Zonation Mapping and Analysis
Landslides are one of the major disasters that occur in hilly region. They are unpredictable by nature and thus their analysis is complex to study. RS and GIS tools can be of utmost importance in analyzing the effect of factors on which the occurrence of a landslide event depends.

The definition of “Landslide Hazard Map” includes “zonation showing annual probability of landslide occurring throughout an area” (USGS). A landslide susceptibility map is a basic concept of landslide susceptibility (Radbruch 1970; Dobrovolny 1971; Brabb and Pampeyan 1972) includes the spatial distribution of factors related to the instability processes in order to determine zones of landslide-prone areas without any temporal implication. This approach is useful for areas where it is difficult to secure enough information concerning the historical record of landslide events ranks the slope stability of an area in categories that range from stable to unstable. Susceptibility maps show where landslides may occur.

Methodology Selection:
First the objective of the study is defined. Danger exists that the data that will be collected will not be in accordance with the scale of analysis, or the method of analysis. This might lead to a waste of time and money if too detailed data is collected, or an oversimplification if too general data is collected.

The following things should be considered:

-The objective of the study
-The scale of the study
-The type of analysis that will be followed
-The types of input data that will be collected

Defining Objective:

Landslide hazard studies can be made for many different purposes. Some of these might be:

-For an environmental impact study for engineering works;
-For the disaster management of a town or city;
-For the modeling of sediment yield in a catchment;
-For a watershed management project;
-For a community participation project in disaster management;
-For the generation of awareness among decision makers;
-For scientific purposes
-Each of the above objectives will lead to specific requirements with respect to the scale of work, the method of analysis and the type and detail of input data to be collected

Scales of Analysis
National scale:
Smaller than 1:1.000.000, covering an entire country, mainly intended to generate awareness among decision makers and the general public. Maps on this scale are often intended to be included in national atlases.

Regional scale:
Between 1:100.000 and 1:1.000.000, covering a large catchment area, or a political entity of the country. The maps at this scale are mostly intended for observation phases for planning projects for the construction of infrastructural works, or agricultural development projects.

Medium scale
Between 1:25.000 and 1:100.000, covering a municipality or smaller catchment area. Intended for the detailed planning phases of projects for the construction of infrastructural works, environmental impact assessment and municipal planning

Large scale
Between 1:2.000 and 1:25.000, covering a town or (part of) a city .They are used for disaster prevention and generation of risk maps, as well as for the design phase of engineering works.

Site investigation scale
Between 1:200 to 1:2000, covering the area where engineering works will be carried out, or covering a single landslide. They are used for the detailed design of engineering works, such as roads, bridges, tunnels, dams, and for the construction of slope stabilization works.

Hazard Zonation
Slope instability hazard zonation is defined as:

The mapping of areas with an equal probability of occurrence of landslides within a specified period of time (Varnes, 1984)

A landslide hazard zonation consists of two different aspects:

The assessment of the susceptibility of the terrain for a slope failure, in which the susceptibility of the terrain for a hazardous process expresses the likelihood that such a phenomenon occurs under the given terrain conditions or parameters.
The determination of the probability that a triggering event occurs.
Often slope instability hazard assessment uses the assumption:

Conditions which led in the past to slope failures, will also result in potential unstable conditions in the present.

Direct/Indirect Hazard Mapping:

Direct hazard mapping:

Experience driven applied geo-morphological approach, where the earth scientist evaluates the direct relationship between the landslides and the geo-morphological and geological setting during the survey at the site of the failure.

Indirect hazard mapping:

The mapping of a large number of parameters and the (statistical or deterministic) analysis of all these possible contributing factors in relation to the occurrence of slope instability phenomena, determining in this way the relation between the terrain conditions and the occurrence of landslides. Based on the results of this analysis statements are made regarding the conditions under which slope failures occur.

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Scotland/London, 6 March 2018 – Double recognition for Ecometrica, the downstream space and satellite mapping company, sees the business propelled onto the prestigious Inc.’s 5000 Europe ranking of the fastest-growing privately held companies on the European continent, which also includes notable firms such as HelloFresh, Dyson, Moo and Coolblue.

The firm has also earned a placed on the GP Bullhound Northern Tech Awards, which recognises the fastest growing exceptional technology companies in the North of England and Scotland.

A leading international provider of digital infrastructure for earth observation services, Edinburgh-headquartered Ecometrica, which has offices in London, Boston, Montreal and Mexico, has won a string of awards for its products and stellar growth, including the prestigious Environmental Leader Product of the Year Award for the second time in a row, and earned rankings in the FT1000 and Deloitte’s 500.

Gary Davis, chief executive of Ecometrica, said: “The recognition by both Inc. 5000 Europe and GP Bullhound’s Northern Tech Awards is further validation for Ecometrica and our talented team.

“What is most pleasing for me is that our growth is not at the cost of the planet or its resources. In fact the more we grow the more we are helping business, governments and society to understand, monitor and protect our planet’s resources for the benefit of existing and future generations.

“Huge advances in raw cloud-based computing power, machine learning and artificial intelligence, coupled with steep cost reductions for deploying sensors on the ground, on UAVs or in orbit, mean that we are now able to harness the power of earth observation data at ever greater spatial and temporal resolutions. One example of the kind of solutions we provide, based on our unique geospatial technology stack, is our Forests 2020 project, as part of the UK Space Agency’s International Partnership Programme, where we are helping a number of governments to manage and protect over 300 million hectares of tropical forests much more effectively.”

The exclusive Inc. 5000 Europe list has been compiled for 37 years. As an Inc. 5000 Europe honouree, with a confirmed position of 2747, Ecometrica now shares a pedigree with Intuit, Under Armour, Microsoft, Timberland, Pandora, Patagonia, Oracle, and dozens of other prominent recent U.S. alumni.

The median company on the Inc. 5000 Europe list increased sales by more than 254 percent since the start of 2013, while the average honouree grew a mind-boggling 473 percent. Those are results most companies could only dream of in the economy of the past three years.

The Northern Tech Awards have been running since 2011 and are part of the events portfolio of GP Bullhound, the leading international technology investment bank. Once a year the Top 100 Fastest Growing Technology Companies are ranked in the Tech 100 League Table by revenue growth over the last three years. The top 50 are invited to the Northern Tech Awards ceremony to receive an award – with the showcase presentations for 2018 taking place in Ecometrica’s home city of Edinburgh.

Distributed by The Communications Business on behalf of Ecometrica.

For further information or to set up an interview, please contact Denise Hannestad, The Communications Business tel: +44 (0) 131 208 1500 – deniseh @ thecommunicationsbusiness.com

About Ecometrica

Ecometrica, the downstream space and sustainability company, turns the vast and growing streams of observation data from space, air and land into actionable insights for business, government and society.
A leading provider of sustainability and earth observation services, its satellite mapping technology is being used to protect 300 million hectares of tropical forests as part of the Forests 2020 project, which Ecometrica is spearheading on behalf of the UK Space Agency’s International Partnership Programme (IPP).

Ecometrica is one of the world’s top sustainability brands, as named by industry analyst Verdantix. It is the only CDP Gold Software Partner for its climate change, forests and water programmes. Ecometrica’s geospatial data mapping services, which support all aspects of sustainability planning, operations and reporting by businesses and public organisations, are available worldwide, through offices in the UK, USA, Canada and Mexico.

The firm is a winner of the prestigious Environmental Leader Product of the Year Award two years in a row, for its Ecometrica Platform. It is also ranked on the FT1000 list of Europe’s fastest growing companies and Deloitte’s Technology Fast 500.

Founded in 2008, Ecometrica’s formidable story derives directly from the vision of its founding members and leadership – executive chairman Dr Richard Tipper, chief executive Gary Davis and chief product officer Bertrand Revenaz. Backed by a team of recognised experts, Ecometrica has unrivalled experience in environmental sustainability accounting and reporting.

The Ecometrica Platform, a web-based accounting and sustainability management solution, combines earth observation data from satellites with local information and business intelligence, to bring clarity to environmental and natural resource challenges facing corporates and governments alike. It helps businesses to easily track and map their impact on natural capital assets, like forests and water, tracking supply chain activity, verifying sustainable product sourcing, and environmental reporting to established sustainability frameworks. It makes the terabytes of raw data being sent to Earth by satellites easily accessible, bringing limitless possibilities for its application. It is the only sustainability software solution with audit-ready assurance from a Big Four auditor (PwC). For the largest customers who get their accounts externally audited, this means avoiding costly pre-audit fees that often run into hundreds of thousands of pounds per year.
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How can we make cities more eco-sustainable?

Our cities are getting hotter and hotter. Buildings, air conditioning systems, traffic and industrial activities release heat that changes the energy balance of urban areas, affecting the environment and the health of citizens.

How can we make cities more eco-sustainable? This is the answer that the URBANFLUXES project is looking for.

Getting our cities more suitable for urban living at a time of climate change is crucial.

UN forecasts say that, by 2050, around 70% of the world’s population will be living in urban areas. This highlights the importance of managing urban-made heat fluxes.

“The URBANFLUXES project is important because for the first time, using satellite data, we are able to estimate the energy balance and its time distribution,” said Nektarious Chrysoulakis,Project Coordinator, UrbanFluxes
Physicist, FORTH.

“We can also accurately estimate, on a local scale, highly concentrated heat spots and high emissions of anthropogenic heat.”

Several environmental monitoring stations have been installed in several hotspot on the Greek island of Crete.

“From this system, we receive data in our laboratory over the internet; we can get the different (heat) fluxes in the city in real time, then we compare them with the satellite data and we produce an global evaluation,” said Stavros Stagakis, Biologist, FORTH (Foundation for Research and Technology)

Remote sensing data systems have been also tested in the highly urbanized cities, such as London and Basel. They collect meteorological data, such as air speed, wind direction, air temperature and rate of humidity.

URBANFLUXES investigates in depth the cities’ warming by combining in-situ meteorological measurements with imagery from some of the Earth Observation satellites working within the Copernicus Program.

The rate of warming in cities is higher than the average global warming and, especially during heat waves, this may significantly influence human mortality.

This methodology is expected to be easily transferable to any city.

By taking into account these studies, local communities may be able to support sustainable urban development strategies focused to reduce climate change.
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Space information network (SIN) is a promising networking architecture to significantly broaden the observation area and realize continuous information acquisition for Earth observation. Over the dynamic and complex SIN environment, it is a key issue to coordinate multi-dimensional heterogeneous network resources (e.g., observation resource and transmission resource) in the presence of multi-resource variations and severe conflicts, such that diverse Earth observation service requirements can be satisfied. To this end, this paper studies the multiresource coordinate scheduling problem in SINs. Specifically, we first characterize the relationship among multi-resource using an event-driven time-expanded graph (EDTEG). Based on the EDTEG, observation resource and transmission resource are jointly considered, and an integer linear programming optimization problem is formulated to maximize the sum priorities of successfully scheduled tasks. An iterative optimization technique is employed to decompose the problem into separate observation scheduling and transmission scheduling sub-problems, which can be efficiently solved by extended transmission time sharing graph and directed acyclic graph methods, respectively. Simulation results demonstrate the effectiveness of the proposed algorithm and performance impacts of different network parameters.

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Code for Africa, the continent’s largest federation of civic technology and data journalism labs, and Radiant.Earth, a non-profit advocating for open geospatial data for positive global impact, announced their partnership to harness open Earth imagery and tools for improved decision-making, as well as better insight and transparency.

Their combined efforts will focus on research for new and innovative applications of Earth observation data to support investigative journalism and storytelling, as well as capacity development.

Both organizations aim to transform the way data are consumed by civil society to empower informed decision-making, efficient service delivery, and location-based analytics to solve social, economic, and environmental challenges. However, while Radiant.Earth has a global focus, Code for Africa directs its attention to affiliate labs in Cameroon, Ethiopia, Ghana, Kenya, Nigeria, Sierra Leone, South Africa, Tanzania, and Uganda.

Code for Africa’s integrated approach to civic technology development in Africa is breaking new ground every day. Their method is to empower ordinary citizens by creating technological capacity within civil society and the media, to enable them to produce extensive knowledge that will help them shape governments and improve their services to citizens.

“Media organizations are constantly evolving, worldwide. Journalists, as well as citizens, now have access to an immense volume of data. It is essential to build their capacities and equip them with the knowledge and tools to research, refine, visualize and interpret the data,” says Jacopo Ottaviani, CCO of Code for Africa. “We are thrilled about our new partnership with Radiant.Earth, because we believe that geospatial data and open Earth imagery can be turned into a crucial tool for storytelling. Radiant.Earth’s team of experts can lead us to new, groundbreaking discoveries in Africa and beyond.”

Radiant.Earth is well-positioned to support Code for Africa’s efforts, as the two organizations share a desire for transparency to enact change. Radiant.Earth offers an open technology platform that facilitates innovation and solutions by combining the best in discovery and dissemination with the latest trends in image processing and analysis. Radiant.Earth strives to identify and connect new users interested in serving citizens facing socio-economic and environmental challenges using geospatial technology.

“We are looking forward to working with Code for Africa,” says Anne Hale Miglarese, Founder and CEO of Radiant.Earth. “They are changing the way information is disseminated and consumed in Africa, leading the charge for transformative impact locally. Together, we can strengthen our capabilities and cultivate a community of practitioners dedicated to transparency and accountability on the ground.”

The sharing of tools and ideas will augment each organization’s mission through capitalizing on the unique resources and knowledge-base that they bring to this partnership. The identified thematic areas for cooperation include humanitarian disaster management, conflict monitoring, urbanization and population growth, health, climate change, sustainability, land rights, agriculture, conservation, and the environment.

How can asylum and migration flows into Europe be detected earlier? This was the central question in a successful feasibility study conducted recently by Statistics Netherlands (CBS) and IT company CGI, using data collected from earth observation satellites and social media. The study was commissioned by the European Space Agency, ESA. Project leader for CBS Bob van den Berg and CGI business consultant Bernd Burger provide details of this innovative experiment.

ESA tender

Bob van den Berg works at the Centre for Big Data Statistics (CBDS), which is part of CBS. ‘One of our missions at the CBDS is to harness new data sources such as big data to create new statistics. This involves working with various national and international partners to exchange knowledge and expertise.’ At the end of 2016, ESA issued a tender for a feasibility study on utilisation of new data sources, including satellite data, to uncover migration flows more quickly. ‘IT company CGI drew our attention to this tender, and we decided to pursue this project together.’ Van den Berg – on behalf of CBS – and CGI then held talks with various parties including the Dutch Ministry of Justice and Security to see which information was needed and whether these parties would participate in the project. As of that moment, Arno Sprangers – CBS statistical expert at the CBS Legal protection and security team – became involved with the project as well.

Feasibility study

Van den Berg: ‘At the start of 2017, we submitted our proposal to ESA. The project was awarded to us and we started in April.’ The project leader describes the objective of the project as twofold: ‘First of all, we wanted to see what was technically feasible based on available resources. We also held workshops together with the various parties – the policy division at the Ministry, the Immigration and Naturalisation Service (IND), police and military police – to try and ascertain what information they needed. In addition, through ESA we spoke to a number of international organisations: the International Organisation for Migration (IOM), the European Border and Coast Guard Agency (Frontex), the European Union Satellite Centre (SatCen) and the European Asylum Support Office (EASO).’

Three case studies

CBS and CGI studied the relative growth of refugee camps and migration crossroads, focusing especially on regions that draw less attention because none of the well-known (welfare) organisations are represented locally. ‘We worked out this project by way of three case studies. One historical case study in which we tried to find answers to the question: could we have anticipated the asylum flows as a result of the Syria crisis at an earlier stage? The second case study was related to recent developments in Africa. Using satellite images and social media, we looked at how the migration flows developed in Niger. The third case study focused on the refugee reception centre in Heumensoord near Nijmegen. This study enabled us to assess our approach and verify already available information with the help of satellite and Twitter data.’

Faster delivery of policy information

Bernd Burger works at the ‘Space’ division of CGI Netherlands. He is excited about the results of the feasibility study funded by ESA. ‘These show that pairing satellite and social media data generates useful information that can provide overviews of migrant flows. CGI mainly fulfills the role of information provider, Burger explains. ‘Satellites produce radar and optical images of the earth; we analyse and interpret those images. This allows us to compare optical images in time frames to one another, creating visible movements. By linking the images to Twitter and Google data and combining that with available statistical data and information from news media, for example, we obtain faster and more accurate indications of migration flows.’

Early detection

This is good news, says Burger. ‘The production of reliable asylum and migration forecasts is an extremely complex matter. Using valuable input from satellites, we would have more solid data to underpin such forecasts for the short term.’ He refers to the peak in the number of Syrian refugees in 2015. ‘That came as a complete surprise, but it had a major impact. Reception centres had to be rolled out rapidly, buildings had to be remodeled, new staff had to be hired and trained. When the flow dried up, the government was stuck with long-term contracts and empty shelters. Therefore, it is imperative that we detect changes in migration flow forecasts which could have consequences for the Netherlands and the rest of Europe at an earlier stage.’

Work for the public good

Now that the feasibility has been demonstrated, it is time for the second phase. Van den Berg: ‘That is to build a demonstration product; we are raising funds for this among various international parties at the moment. If this is successful, our final goal is to make our product operational.’ There is still some way to go, but both Van den Berg and Burger are already eagerly looking forward. Cooperation between the two partners is excellent. Van den Berg: ‘To CBS, this has been an exciting project because we work for the public good together with a commercial party. That is relatively new to us. In addition, privacy aspects must be considered, and the end product we envisage is different from the usual statistical products at CBS.’ Burger, too, is very positive about the partnership: ‘CBS is extremely competent in the analysis of data using social media and Google; they also possess a great deal of knowledge about migration and its impact on the Netherlands and on Europe.’

The prevalence of dengue fever poses a global health issue, with half the world’s population now estimated to be at risk from this mosquito-borne viral infection (WHO Dengue Factsheet, April 2017). Found in tropical and sub-tropical climates worldwide, mostly in urban and semi-urban areas, the infection causes a flu-like illness which can develop into a potentially lethal complication known as severe dengue. HR Wallingford is leading a new project utilising Earth Observation technology, and funded by the UK Space Agency’s International Partnership Programme, to develop an early warning system which will help to predict dengue fever outbreaks in Vietnam.

anoi in Vietnam faces regular dengue fever outbreaks

In 2016, there were over 120,000 cases of dengue fever in Vietnam, an increase of over 25% on the previous year (Ministry of Health, Vietnam). Currently, there is no operational early warning system in the country to forecast the probability of future dengue outbreaks. This new project will develop innovative tools which will allow beneficiaries to issue alerts for dengue epidemics. This will help public health authorities to mobilise resources to those most in need. The same methods could also be used to forecast outbreaks of Zika, which is transmitted by the same type of mosquito, and which has recently begun to be reported in Vietnam.

In the course of the project, Earth Observation datasets will be combined with health and water availability information to produce a new integrated dengue forecasting model to understand and predict the impacts of the main environmental factors influencing the likelihood of future dengue epidemics. These include water availability, land-use and climate, since more rain, rapid urbanisation, and higher temperatures can all promote the breeding of the virus-carrying mosquitoes. The tools produced will be used to understand changing health risks posed by dengue for different temporal and spatial scales under future climate change scenarios. In addition, forecasts of water scarcity will be made and incorporated in the dengue early warning tool.

Darren Lumbroso, Technical Director in the Water Management Group at HR Wallingford, said: “We are delighted to be leading this ground-breaking project where, for the first time, an Earth Observation-based forecasting system will allow decision makers to identify areas of high risk for disease epidemics before an outbreak occurs, in order to target resources so as to reduce an epidemic spreading and to increase disease control.“

Forecasts of dengue epidemics with an eight-month lead time will be distributed to all national dengue response authorities. At the same time, the work will also help to improve water management in Vietnam’s transboundary river basins, where there is currently a lack of hydro-meteorological information. This will benefit local authorities’ planning by providing scenarios of the main stressors and their impacts on health and water security.

The ‘Integrated dengue early warning system driven by Earth Observations in Vietnam’ project is funded by the UK Space Agency’s International Partnership Programme and led by HR Wallingford, working with the London School of Hygiene and Tropical Medicine, the Met Office and Oxford Policy Management in the UK, and with the following international partners: the United Nations Development Programme, the World Health Organisation, the Vietnamese Institute of Meteorology, Hydrology and Climate Change, the Pasteur Institute Ho Chi Minh City, and the National Institute of Hygiene and Epidemiology in Vietnam.

HR Wallingford will be leading a second UK Space Agency project aimed at minimising the risk of tailings dam failures (earth embankments used to store toxic mine waste) through the use of remote sensing data in Peru. This project will use Earth Observation and Global Navigation Satellite System technologies to allow for more effective monitoring of the dams and therefore quicker action to avoid the tailings dam failures. The project will help to reduce damage to ecosystem services downstream of mines upon which many vulnerable communities rely for both their source of water and their livelihoods.

Radiant Solutions announced a contract with the U.S. National Geospatial-Intelligence Agency (NGA) to provide more than 1 million labeled objects within high-resolution satellite images that will be used to accelerate the development of machine learning algorithms that can extract valuable information from imagery at scale.

DigitalGlobe’s WorldView 2 satellite captured this image of Boston, Massachusetts in July 2014. Photo: DigitalGlobe.

NGA is partnering with Defense Innovation Unit Experimental (DIUx) to launch the 2018 DIUx xView Detection Challenge to spur innovation that will ultimately support national security and humanitarian missions. With the challenge, individuals and global academic, commercial and research organizations will use 30 cm commercial satellite imagery from DigitalGlobe to train algorithms to automatically identify dozens of objects that are relevant to pressing global challenges, such as stopping the spread of disease and improving infrastructure in the developing world.

The DIUx Detection Challenge follows in the footsteps of earlier training datasets Radiant Solutions released under the SpaceNet and Intelligence Advanced Research Projects Activity (IARPA) Functional map of the World (FMOW) challenges, for which participants applied machine learning to satellite imagery to address a range of important applications. The xView dataset is licensed to NGA under a Creative Commons non-commercial license and contains more than 1 million labeled objects across 60 object classifications, such as damaged buildings, construction equipment and tents.

“Access to satellite imagery at increasingly high spatial and temporal resolutions, coupled with rapid advances in machine learning algorithms for object detection, has created a disruptive opportunity for NGA and other agency customers to see, understand and anticipate humanitarian and defense activities at a global scale,” said Tony Frazier, president of Radiant Solutions. “Our vision is that xView becomes a trusted resource for accelerating open innovation in machine learning.”
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With the aim of making the best possible use of existing satellites, ESA and Canada have made a deal that turns Swarm into a four-satellite mission to shed even more light on space weather and features such as the aurora borealis.

Cassiope carries e-POP

In orbit since 2013, ESA’s three identical Swarm satellites have been returning a wealth of information about how our magnetic field is generated and how it protects us from dangerous electrically charged atomic particles in the solar wind.

Canada’s Cassiope satellite carries three instrument packages, one of which is e-POP. It delivers information on space weather which complements that provided by Swarm. Therefore, the mission teams began looking into how they could work together to make the most of the two missions.

To make life easier, it also just so happens that Cassiope’s orbit is ideal to improve Swarm’s readings.

And now, thanks to this international cooperation and formalised through ESA’s Third Party Mission programme, e-POP has effectively become a fourth element of the Swarm mission. It joins Swarm’s Alpha, Bravo and Charlie satellites as Echo.

Josef Aschbacher, ESA’s Director of Earth Observation Programmes, noted, “This is a textbook example of how virtual constellations and collaborative initiatives can be realised, even deep into the missions’ exploitation phases.

“We embrace the opportunity to include e-POP in the Swarm mission, especially because it is clear that the more data we get, the better the picture we have of complex space weather dynamics.

“ESA is looking forward to seeing the fruits of this collaboration and the improved return on investment for both Europe and Canada.”

Andrew Yau from the University of Calgary added, “Swarm and e-POP have several unique measurement capabilities that are highly complementary.

“By integrating e-POP into the Swarm constellation, the international scientific community will be able to pursue a host of new scientific investigations into magnetosphere–ionosphere coupling, including Earth’s magnetic field and related current systems, upper-atmospheric dynamics and aurora dynamics.”

John Manuel from the Canadian Space Agency noted, “We are pleased to see e-POP join ESA’s three Swarm satellites in their quest to unravel the mysteries of Earth’s magnetic field.

“Together, they will further improve our understanding of Earth’s magnetic field and role it plays in shielding Canada and the world from the effects of space weather.”

Giuseppe Ottavianelli, Third-Party Mission Manager at ESA concluded, “I am pleased that the e-POP ensemble is now formally integrated into our Swarm constellation.

“This milestone achievement confirms the essential role of ESA’s Earthnet programme, enabling synergies across missions, fostering international cooperation, and supporting data access.”

While e-POP changes its name to Echo as part of the Swarm mission, it will also continue to provide information for its original science investigations.

ON A TRIP to Silicon Valley last year, Defense Secretary James Mattis openly envied tech companies’ superior use of artificial intelligence technology. To help close the gap, one Pentagon unit is now offering $100,000 in prizes to develop algorithms that can interpret high-resolution satellite images.

Oroville Dam in California in September 2016. Photo: Planet
The contest is called the xView Detection Challenge, and starts next month. Entrants will use a trove of hand-annotated satellite images released by the Pentagon to train algorithms to identify details relevant to disaster relief or humanitarian missions. Objects of interest include damaged buildings, utility trucks, and fishing boats.

The project is being run by DIUx, an organization started by former Defense Secretary Ashton Carter to make it easier for his department to work with technology companies, particularly startups. The need to close the Pentagon’s AI gap with industry was a major motivation for the creation of DIUx, says Brendan McCord, head of machine learning at the organization.

DIUx’s challenge is a partnership with the National Geospatial-Intelligence Agency, which serves the US military and intelligence apparatus. The competition is modeled on the NGA’s work after events such as hurricane Irma, which swept a trial of destruction and flooding from the Bahamas to Florida last year. Each day, a team of 10 analysts scrutinized hundreds of high-resolution satellite images of the disaster zone, grading damaged or destroyed buildings, and annotating details like impassable roads or bridges. The data was passed onto other agencies helping with the clean up, including FEMA.

One goal of the challenge is to automate such work. McCord says algorithms developed for the xView challenge could help NGA after future disasters. If software could make a first pass at annotating new images for damaged buildings and the like, for example, analysts could be more productive.

Algorithms good at tagging items of humanitarian interest might also be re-trained to aid other work, such as NGA’s core mission of supporting U.S. warfighters and intelligence analysts. The contest rules grant NGA license to both use and build on winning software. DIUx says winners may be offered the chance to do follow-on work on other defense missions. It is also offering a special prize of $5,000 for the best open source entry, to encourage sharing of ideas created for the contest. The satellite images for the contest are released under a public, noncommercial license for anyone to use.

Anyone hoping to win money in the challenge should start by checking their nationality. Contest rules disqualify entrants from several countries, including Cuba and Iran. For those whose papers are in order, the next step is to download a cache of satellite images covering 1,400 km2 from locations around the world at a resolution of 30 centimeters (1 foot). The images cover both visible and infrared light, and have been hand-annotated with a million examples of 60 different objects. Entrants will use the labeled images to train their algorithms; their software will be tested against a collection of images not made public. The contest will be judged on accuracy, but DIUx also wants the software to be practical, says McCord.

Software competing in the challenge must identify and distinguish objects such as trucks with tanker trailers and cement mixers. The objects were chosen to be relevant to humanitarian projects, and push the limits of existing image-processing algorithms.

Stefano Ermon, a professor at Stanford, says that the challenge and dataset could become an important contribution to both machine-learning research, and humanitarian projects worldwide. His research group has developed machine-learning software that maps areas of poverty in African countries using clues such as roads and waterways.

The most mature image-recognition technology is focused on online consumer and product photos, thanks to the piles of readily available data, and strong commercial interest from internet companies such as Google. Much less work has been done on interpreting satellite imagery, and the data needed to do so is scant, says Ermon. “We don’t have a lot of labeled data, which is crucial,” he says.
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