Month: June 2016

Keeping Earth up to date and looking great

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Three years ago Google introduced a cloud-free mosaic of the world in Google Earth. Now they have rolled out an even more beautiful and seamless version, with fresh imagery from Landsat 8 satellite and new processing techniques for sharper images than ever before. Satellite images are often cloudy, but not always over the same place, so they looked at millions of images and took the clearest pixels to stitch together this cloud-free and seamless image.

(First image using Landsat 7 image and Second image using Landsat 8 image. In the new view of New York City, details like skyscrapers, building shadows, and baseball and softball fields in Central Park shine through. Image credit: USGS)

Higher Quality Imagery
Landsat 8, which launched into orbit in 2013, is the newest sensor in the USGS/NASA Landsat Program—superior to its predecessors in many ways. Landsat 8 captures images with greater detail, truer colors, and at an unprecedented frequency—capturing twice as many images as Landsat 7 does every day. This new rendition of Earth uses the most recent data available — mostly from Landsat 8 — making it our freshest global mosaic to date. The previous mosaic used imagery from Landsat 7 only, which at the time was the best imagery of its kind. Unfortunately, Landsat 7 images captured after 2003 were affected by a hardware failure, resulting in large diagonal gaps of missing data.
Processing imagery with Earth Engine
To produce this new imagery, they used the same publicly available Earth Engine APIs that scientists use to do things like track global tree cover, loss, and gainpredict Malaria outbreaks, and map global surface water over a 30 year period. Like in previous mosaic, they mined data from nearly a petabyte of Landsat imagery—that’s more than 700 trillion individual pixels—to choose the best cloud-free pixels. To put that in perspective, 700 trillion pixels is 7,000 times more pixels than the estimated number of stars in the Milky Way Galaxy, or 70 times more pixels than the estimated number of galaxies in the Universe.

The new imagery is now available across all mapping products of Google. To check it out, open up Google Earth, or turn on the satellite layer in Google Maps.

India-Nepal border pillars to be GPS-enabled

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More than 8,000 pillars along the India-Nepal border will be linked to a Global Navigation Satellite System, allowing authorities for the first time to effectively manage the over 1,700-km-long porous boundary.Credit: InfoNepal

Nepal’s Ministry of Foreign Affairs said the Nepal-India Boundary Global Navigation Satellite System (NIB GNSS) will be used for the boundary pillars. The decision in this regard was made at the third meeting of Nepal-India Boundary Working Group (BWG) which concluded here yesterday, a statement from the ministry said.(Photo Credit: InfoNepal)

Krishna Raj BC, Director-General of the Survey Department, led the Nepali delegation during the three-day meeting while the Indian delegation was led by Swarna Subba Rao, Surveyor General of India. “The BWG meeting reviewed reports submitted before it by the SOC (Survey Officials’ Committee) and Joint Field Survey Teams (FST), and appreciated the progress made on the ongoing boundary work carried out at Nepal-India border,” it said.

“Both the delegations reaffirmed the importance of effective boundary management. In this context, they emphasised the importance of making local authorities and people living along the border aware of the field works being conducted by joint field teams,” it said.

Before the BWG meeting, the fourth meeting of Survey Officials’ Committee (SOC) was held here from 20 to 22 June. The two countries have decided that the SOC would next meet in September this year and the BWG in August 2017, in India.


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Yet another achievement of ISRO: Cartosat 2 Series Satellite

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The Cartosat-2 series satellite is the primary satellite carried by PSLV-C34. This satellite is similar to the earlier Cartosat-2, 2A and 2B. After its injection into a 505 km polar Sun Synchronous Orbit by PSLV-C34, the satellite will be brought to operational configuration following which it will begin providing regular remote sensing services using Panchromatic and Multispectral cameras.

The imagery sent by the satellite will be useful cartographic applications, urban and rural applications, coastal land use and regulation, utility management like road network monitoring, water distribution, creation of land use maps, precision study, change detection to bring out geographical and manmade features and various other Land Information System (LIS) and Geographical Information System (GIS) applications.

India’s Polar Satellite Launch Vehicle, in its thirty sixth flight (PSLV-C34), will launch the 727.5 kg Cartosat-2 series satellite for earth observation and 19 co-passenger satellites together weighing about 560 kg at lift-off into a 505 km polar Sun Synchronous Orbit (SSO). PSLVC34 will be launched from the Second Launch Pad (SLP) of Satish Dhawan Space Centre (SDSC) SHAR, Sriharikota. It will be the fourteenth flight of PSLV in ‘XL’ configuration (with the use of solid strap-on motors). The co-passenger satellites are from USA, Canada, Germany and Indonesia as well as two satellites from Indian University/Academic Institute. The total weight of all the 20 satellites carried onboard PSLV-C34 is about 1288 kg.

Spationet community heartily congratulates ISRO and all scientists/staff  involved in the mission.


PSLV-C34 brochure

Cartosat-2 series satellite curtain raiser video

Launch video

Stanford researchers calculate groundwater levels from satellite data

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A new computer algorithm that can “fill in” underground water levels in areas where quality data is not available could lead to improved models of groundwater flow in regions where pumping and aquifer depletion are a concern.

California landscape

(Researchers from Stanford’s School of Earth, Energy & Environmental Sciences have used satellite data and a new computer algorithm to gauge groundwater levels in Colorado’s San Luis Valley agricultural basin. (Image credit: Flickr)

A new computer algorithm developed at Stanford University is enabling scientists to use satellite data to determine groundwater levels across larger areas than ever before.

The technique, detailed in the June issue of the journal Water Resources Research, could lead to better models of groundwater flow. “It could be especially useful in agricultural regions, where groundwater pumping is common and aquifer depletion is a concern,” said study coauthor Rosemary Knight, a professor of geophysics in the Stanford School of Earth, Energy & Environmental Sciences.

The team was able to calculate surface deformations – and, by extension, groundwater levels – for the entire agricultural basin of the San Luis Valley, an area covering about 4,000 square kilometers – or about five times greater than the area for which groundwater levels were calculated in the prior study. What’s more, the team members were able to show how groundwater levels in the basin changed over time from 2007 to 2011 – the years when InSAR data that could be analyzed by the algorithm were available.

They want to take the information about groundwater levels and aquifer characteristics extracted from InSAR satellites and incorporate it with data from other sources to develop improved models of groundwater flow.


Mapping Water Use: Landsat and America’s Water Resources

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As droughts rage and aquifers dwindle, people may wonder: Is there enough water to meet all our needs?  Landsat satellites are helping to answer that question.

Water is one of the most important natural resources, one that’s long been considered inexhaustible. Yet changes in land use, climate, and population demographics are placing unprecedented demands on America’s water supplies.

Water Use Mapping

Using Landsat satellite data, scientists with the U.S. Geological Survey (USGS) have helped to refine a technique called evapotranspiration (ET) water-use mapping to measure how much water crops are using across landscapes and through time. These ET water-use maps are created using a computer model that integrates Landsat and weather data.

A pair of ET water-use maps show crop water use in California’s San Joaquin Valley in 1990 (left) and 2014 (right).

(This pair of ET water-use maps shows crop water use in California’s San Joaquin Valley in 1990 (left) and 2014 (right). Comparing the maps reveals changes in irrigation patterns during this period. Notice, for example, that water use intensified in many places (increase in blue areas) and some irrigated lands (green in 1990) transitioned out of agricultural production (reddish brown) by 2014.)

Crucial to the process is Landsat’s thermal (infrared) band. Thanks to that thermal band with its 100-meter resolution, water-use maps can be created at a scale detailed enough to show how much water crops are using at the level of individual fields anywhere in the country.

How Water-Use Maps Help

USGS scientists can map water use at different scales to address different water resource questions and concerns. Field-scale maps, for example, are powerful tools for estimating and managing water consumption on irrigated croplands. They can help answer questions such as:

  • Where is water being used, how much, and by whom?
  • Which types of crops are using the most, or least, water?
  • Can water be used more efficiently without impacting crop yields?

Planning Today for Water Tomorrow

According to a recent Government Accountability Office report, 40 of 50 state water managers expect water shortages in their states between now and 2023. Addressing concerns about America’s water resources begins with a clearer understanding of water availability and water-use trends. Mapping water use based on Landsat satellite data has demonstrated immense potential at local and regional scales, and will soon become the basis for monitoring and assessing water use across the nation.


Landsat: Continuing to Improve Everyday Life

Landsat Mission

Monitoring Pipelines from Space

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Dutch company Orbital Eye has developed a service that uses satellites to monitor gas and oil pipelines. A major African pipeline operator has already signed up for the service. Worldwide, gas and oil pipelines extend two million km. In most cases, this network is not very deep: just 1.5 m below our feet.

Gas pipes in the EU alone stretch 140000 km, another 40000 km carry oil and related products. In addition, there are the final distribution lines to our homes and places of work. For pipeline operators, safety is paramount. Accidents tend to be serious enough to endanger people and the environment, as well as to damage the pipeline itself.

(Pipeline can be seen in overlayed results)

In Europe, almost half of all failures in high-pressure gas transmission pipelines are caused by excavations, construction work, and deep ploughing. Operators reduce such incidents through aerial surveys from helicopters along the entire pipeline route at least every three weeks.

The new system uses radar images from satellites in combination with smart software to detect potential threats as well as the slightest ground movement. Pipeline operators, alerted to suspicious events, then dispatch field personnel to find reported or detected hazards using a tablet app. The app can connect to the central database via terrestrial networks and satcoms and can, therefore be used even in remote locations such as desert areas.

“We have been using Sentinel-1A imagery since the satellite was launched, and the results have been very positive,” noted Jan Ridder, Managing Director at Orbital Eye.

ESA’s Olivier Becu commented: “Our Integrated Applications Promotions programme gives promising start-ups such as Orbital Eye the opportunity to develop and deploy new space-based services in an operational setting in order to prove their products together with users.”


Download Sentinel-1 Data

Flood Preparedness – There’s a New USGS Map (or App) for That

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During the recent Texas flooding, the U.S. Geological Survey unveiled a new tool that gives users real-time water, weather and National Weather Service flood forecast information all in one place. When water levels are rising, it can be hard to quickly get all the information you need about your area, especially when you’re not in front of a computer.

The new USGS Texas Water Dashboard is a cutting-edge map that provides critical current water information and NWS forecast data at your fingertips on a desktop, smartphone or other mobile devices. This is a first-generation product that brings real-time USGS data together in a web mashup with information from the NWS and other sources. The USGS will explore the potential value of this product to the public, and could possibly expand its reach to include the rest of the nation in the future.

A graphic showing how the Texas Water Dashboard is used.

Useful for Cities, Outdoor Recreationists, Landowners and More!

The Twitter feeds and Texas Water Dashboard can do more than assist residents during flooding. Understanding weather and streamflow can help determine the best places to go boating, fishing or hiking. It can also help recreationists and landowners understand if stream levels are rising or falling at any given time. Real-time groundwater levels can also be found on the map. This information could be useful for water managers in making informed decisions about local resources.

Can you find places with increasing versus decreasing flow?
Here’s how you can search:A graphic showing the Texas Water Dashboard Monitoring Map.

(Sample search result)

Can you find the USGS station that tweeted information most recently?A photo highlighting the USGS Twitter feed on left hand side of the map.

(Sample result from the portal)

The Texas Water Dashboard uses data from the USGS National Water Information System (NWIS). The NWIS dataset includes information from more than 1.5 million sites, some in operation for more than 100 years. For more information visit the USGS NWIS website.

Sources of map information include: the National Weather Service, Iowa Environmental Mesonet, Interior Geospatial Emergency Management System, the DOI Office of Emergency ManagementNational Drought Mitigation Center at the University of Nebraska-Lincoln, the United States Department of Agriculture and the Iowa Environment Mesonet.