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Like every other machine, satellites do not last forever. Whether their job is to observe weather, measure greenhouse gases in the atmosphere, or point away from Earth to study the stars, eventually all satellites grow old, wear out, and die, just like old washing machines and vacuum cleaners.
So what happens when a trusty satellite’s time has come? These days there are two choices, depending on how high the satellite is. For the closer satellites, engineers will use its last bit of fuel to slow it down. That way, it will fall out of orbit and burn up in the atmosphere.
The second choice is to send the satellite even farther away from Earth. It can take a lot of fuel for a satellite to slow down enough to fall back into the atmosphere. That is especially true if a satellite is in a very high orbit. For many of these high satellites, it takes less fuel to blast it farther into space than to send it back to Earth.
Burning metal and “spacecraft cemeteries”
Getting rid of the smaller satellites in low orbits is simple. The heat from the friction of the air burns up the satellite as it falls toward Earth at thousands of miles per hour. Ta-da! No more satellite.
What about bigger things like space stations and larger spacecraft in low orbit? These objects might not entirely burn up before reaching the ground. There is a solution—spacecraft operators can plan for the final destination of their old satellites to make sure that any debris falls into a remote area. This place even has a nickname—the Spacecraft Cemetery! It’s in the Pacific Ocean and is pretty much the farthest place from any human civilization you can find.
What about those higher satellites we blast farther away? Those we send into a “graveyard orbit.” This is an orbit almost 200 miles farther away from Earth than the farthest active satellites. And it’s a whopping 22,400 miles above Earth!
So is that the end of it for these far-away satellites? As far as you and I are concerned it is! However, some of these satellites will remain in orbit for a very, very long time. Perhaps someday in the future, humans may need to send “space garbage trucks” to clean these up. But for now, at least, they will be out of the way.
In what’s being hailed as a “major breakthrough” in Maya archaeology, researchers have identified the ruins of more than 60,000 houses, palaces, elevated highways, and other human-made features that have been hidden for centuries under the jungles of northern Guatemala.
Using a revolutionary technology known as LiDAR (short for “Light Detection And Ranging”), scholars digitally removed the tree canopy from aerial images of the now-unpopulated landscape, revealing the ruins of a sprawling pre-Columbian civilization that was far more complex and interconnected than most Maya specialists had supposed.
(Image: Laser technology known as LiDAR digitally removes the forest canopy to reveal ancient ruins, showing that Maya cities such as Tikal were much larger than ground-based research had suggested. Source: National Geographic)
The project mapped more than 800 square miles (2,100 square kilometres) of the Maya Biosphere Reserve in the Petén region of Guatemala, producing the largest LiDAR data set ever obtained for archaeological research.
The results suggest that Central America supported an advanced civilization that was, at its peak some 1,200 years ago, more comparable to sophisticated cultures such as ancient Greece or China than to the scattered and sparsely populated city-states that ground-based research had long suggested.
In addition to hundreds of previously unknown structures, the LiDAR images show raised highways connecting urban centres and quarries. Complex irrigation and terracing systems supported intensive agriculture capable of feeding masses of workers who dramatically reshaped the landscape.
The ancient Maya never used the wheel or beasts of burden, yet “this was a civilization that was literally moving mountains,” said Marcello Canuto, a Tulane University archaeologist and National Geographic Explorer who participated in the project.
India’s Polar Satellite Launch Vehicle, in its 42nd flight (PSLV-C40), has launched the 710 kg Cartosat-2 Series Satellite for earth observation and 30 co-passenger satellites together weighing about 613 kg at lift-off. PSLV-C40 was launched from the First Launch Pad (FLP) of Satish Dhawan Space Centre (SDSC) SHAR, Sriharikota. In its first mission of 2018, the Indian Space Research Organisation (ISRO) successfully launched its 100th satellite. The mission comes a little over four months after the space agency’s unsuccessful launch of IRNSS-1H. Prime Minister Narendra Modi, congratulating ISRO for its success, said the launch signifies the bright future of India’s space programme.
(PSLV-C40 on First Launch Pad – Evening View. Source: ISRO)
The co-passenger satellites comprise one Microsatellite and one Nanosatellite from India as well as 3 Microsatellites and 25 Nanosatellites from six countries, namely, Canada, Finland, France, Republic of Korea, UK and USA. The total weight of all the 31 satellites carried onboard PSLV-C40 is about 1323 kg.
The 28 International customer satellites are being launched as part of the commercial arrangements between Antrix Corporation Limited (Antrix), a Government of India company under Department of Space (DOS), the commercial arm of ISRO and the International customers.
Cartosat-2 Series Satellite is the primary satellite carried by PSLV-C40. This remote sensing satellite is similar in configuration to earlier satellites in the series and is intended to augment data services to the users.
The imagery sent by satellite will be useful for cartographic applications, urban and rural applications, coastal land use and regulation, utility management like road network monitoring, water distribution, creation of land use maps, change detection to bring out geographical and manmade features and various other Land Information System (LIS) as well as Geographical Information System (GIS) applications.
According to Engadget in March 2017, there are over 770,000 drone owners registered to fly in the US. That’s up from 670,000 at the beginning of 2017, meaning 100,000 users signed up in just three months alone. The FAA has also issued 37,000 Remote Pilot Certificates that let drone owners do the filming, inspection and other commercial operations. So, it’s not only our roads that are congested.
The growing popularity of drones, whether for leisure or commercial use, has highlighted the challenge of facilitating traffic in very-low- altitude airspace. As they are airborne objects, drones fall under aviation law. However, that’s only part of the challenge for drone flyers. Because they fly in the low level airspace, drones also need to take into account obstacles, buildings and people’s privacy.
(Image Source: https://360.here.com)
For autonomous drones to operate safely and predictably, access to rich and accurate data sources is key. Standards to support interoperability, just like those practiced by the aviation industry, are also needed. To meet these needs, they HERE is teaming up with UNIFLY, the Unmanned Traffic Management (UTM) platform, to develop 3D airspace maps for drones.
In the first phase of their collaboration, the companies plan to enable an airspace map for drones that covers both rural and urban areas, and marks out no-fly zones, such as airports, residential areas and sensitive government installations.
In the second phase, the companies plan to further develop the system to support the management of drone traffic flow and even collision avoidance, much like air traffic controllers do for the airline industry today. Longer-term, the aim is to explore how drone transportation and logistics can be integrated seamlessly into the broader transportation system.
The Unifly UTM platform connects relevant local and aviation authorities with drone pilots to safely integrate drones into the airspace. HERE, meanwhile, is developing the Reality Index™, a rich real-time digital representation of the physical world. Based on the companies’ commercial agreement, Unifly will integrate HERE map and location data from the Reality Index™ into its applications to provide a more and more robust picture of the low-altitude airspace.
Drones: the ultimate users of the Reality Index™
A drone generally needs a map from the ground up to an altitude of about 150 meters; in future, a flying taxi may need the map to extend higher. Drones need to take into account obstacles, buildings and people’s privacy. As airborne objects, they are also subject to various airspace regulations.
(A 3D visualization of the world, Image Source: https://360.here.com)
For drones to operate safely and predictably, access to rich and accurate data sources is paramount. These data sources must also be kept updated to ensure usefulness. Just as HERE today turns the real-time sensor data generated by millions of vehicles on the road into map information and new location services for drivers and passengers, drones themselves could also be employed to enable the self-healing of the airspace map. Equipped with various sophisticated sensors, drones could detect changes in the real-world environment and feed data back to the cloud to support map updates.
By aggregating data from many drones, the airspace map could also be enriched with precise information about hyperlocal weather conditions, potential hazards and the best navigable routes.
New technologies such as Artificial Intelligence (AI), Cloud Machine Learning, Satellite Imagery and advanced analytics are empowering small-holder farmers in India to increase their income through higher crop yield and greater price control, Microsoft India said.
(Photo Source: ICRISAT)
In a few dozen villages in Telengana, Maharashtra and Madhya Pradesh, farmers are receiving automated voice calls that tell them whether their cotton crops are at risk of a pest attack, based on weather conditions and crop stage. In Karnataka, the government can get price forecasts for essential commodities such as tur (split red gram) three months in advance for planning the Minimum Support Price (MSP).
“Sowing date as such is very critical to ensure that farmers harvest a good crop. And if it fails, it results in loss as a lot of costs are incurred for seeds, as well as the fertilizer applications,” Suhas P. Wani, Director, Asia Region, of the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT), said in a Microsoft blog post.
The non-profit ICRISAT conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. In collaboration with ICRISAT, Microsoft has developed an AI-Sowing App powered by Microsoft Cortana Intelligence Suite including Machine Learning and Power BI.
“The app sends sowing advisories to participating farmers on the optimal date to sow. The best part – the farmers don’t need to install any sensors in their fields or incur any capital expenditure. All they need is a feature phone capable of receiving text messages,” the company said.
To calculate the crop-sowing period, historic climate data spanning over 30 years – from 1986 to 2015 – for the Devanakonda area in Andhra Pradesh was analysed using AI. To determine the optimal sowing period, the Moisture Adequacy Index (MAI) was calculated. MAI is the standardised measure used for assessing the degree of adequacy of rainfall and soil moisture to meet the potential water requirement of crops. This data is then downscaled to build predictability and guide farmers to pick the ideal sowing week.
This year, ICRISAT has scaled sowing insights to 4,000 farmers across Andhra Pradesh and Karnataka for the Kharif crop cycle (rainy season). Predictive analysis in agriculture is not limited to crop growing alone. The Karnataka government will start using price forecasting for agricultural commodities, in addition to sowing advisories for farmers in the state. Commodity prices for items such as tur, of which Karnataka is the second largest producer, will be predicted three months in advance for major markets in the state, Microsoft said.
Microsoft has developed a multivariate agricultural commodity price forecasting model to predict future commodity arrival and the corresponding prices. The model uses remote sensing data from geo-stationary satellite images to predict crop yields through every stage of farming. The model currently being used to predict the prices of tur, is scalable, and time efficient and can be generalised to many other regions and crops.
India has the highest net cropland area while South Asia and Europe are considered agricultural capitals of the world. A new map was released on 14th November 2017, detailing croplands worldwide in the highest resolution yet, helping to ensure global food and water security in a sustainable way.
The map establishes that there are 1.87 billion hectares of croplands in the world, which is 15 to 20 percent—or 250 to 350 million hectares (Mha)—higher than former assessments. The change is due to the more detailed understanding of large areas that were never mapped before or were inaccurately mapped as non-croplands.
Earlier studies showed either China or the United States as having the highest net cropland area, but this study shows that India ranks first, with 179.8 Mha (9.6 percent of the global net cropland area). Second is the United States with 167.8 Mha (8.9 percent), China with 165.2 Mha (8.8 percent) and Russia with 155.8 Mha (8.3 percent). Statistics of every country in the world can be viewed on an interactive map.
(This map shows cropland distribution across the world in a nominal 30-meter resolution. This is the baseline product of the GFSAD30 Project. Source: USGS)
South Asia and Europe can be considered agricultural capitals of the world due to the percentage of croplands of the total geographic area. Croplands make up more than 80 percent of Moldova, San Marino and Hungary; between 70 and 80 percent of Denmark, Ukraine, Ireland and Bangladesh; and 60 to 70 percent of the Netherlands, United Kingdom, Spain, Lithuania, Poland, Gaza Strip, Czech Republic, Italy and India. For comparison, the United States and China each have 18 percent croplands.
The study was led by the USGS and is part of the Global Food Security-Support Analysis Data @ 30-m (GFSAD30) Project. The map is built primarily from Landsat satellite imagery with 30-meter resolution, which is the highest spatial resolution of any global agricultural dataset.
Importance of Monitoring Croplands in Great Detail
“The map clearly shows individual farm fields, big or small, at any location in the world,” said Prasad Thenkabail, USGS research geographer and Principal Investigator for the GFSAD30 Project Team. “Given the high resolution of 30 meters and 0.09 hectares per pixel, a big advantage is the ability to see croplands in any country and sub-national regions, including states, provinces, districts, counties and villages.”
With the global population nearing the 7.6 billion mark and expected to reach 10 billion by 2050, it is of increasing importance to understand and monitor the state of agriculture across the world in great detail. This new research is useful to international development organizations, farmers, decision-makers, scientists and national security professionals.
“This map is a baseline and starting point for higher level assessments, such as identifying which crops are present and where, when they grow, their productivity, if lands are left fallow and whether the water source is irrigated or rain fed,” said Thenkabail. “Comparisons can be made between the present and past years as well as between one farm and another. It is invaluable to know the precise location of croplands and their dynamics to lead to informed and productive farm management.”
Critical for Water Security
Not only does this map and accompanying data have significant food security implications, but it is also critical as a baseline for assessing water security. Nearly 80 percent of all human water use across the world goes towards producing food, and this research provides insight on “crop per drop,” which is an assessment of the number of crops produced per unit of water.
Download data through the Land Processes Distributed Active Archive Center.
A new datum or geospatial reference system is being introduced in the United States to become the official datum in 2022. At GIS in the Rockies, Pam Fromhertz of the NOAA National Geodetic Survey gave an overview of the reasoning behind the new datum, technical details about the change and some practical implications.
Most people in the geospatial sector in the U.S. are aware of the datums NAD27 and NAD83 which have been the reference points for all surveys performed in the U.S. NAD83 was defined primarily using terrestrial surveying techniques. NAD83 has been updated several times since being introduced in 1983 but is based on an ellipsoid that is non-geocentric and is tilted slightly. The new datum or North American Terrestrial Reference Frame of 2022 (NATRF2022) is based on gravity which means that “sea level” is now represented by an equipotential gravity surface rather than the Earth’s ellipsoid. The new reference frames will rely primarily on Global Navigation Satellite Systems (GNSS) such as the Global Positioning System (GPS) as well as an updated and time-tracked geoid model. Importantly, the new datum means that Mexico, Canada, and the U.S. will share a common datum. The gravity-based vertical datum will be accurate at the 2 cm level for much of the U.S. Gravity data is currently being captured across the U.S. and its territories as part of the Grav-D project.
Practically, this means that elevations may change by up to a meter and horizontal location by up to 1.5 meters. The actual corrections to elevations and horizontal locations will depend on where you are in North America. The greatest changes are in the Pacific Northwest and the least in the southeastern U.S. At the hotel in Inverness, Colorado where the GIS in the Rockies conference took place this year, the corrections were 1.36 m horizontally and -0.67 m vertically. The NOAA National Geodetic Survey web site (geodesy.noaa.gov) has tools to perform conversions from NAD83 to the new 2022 datum.