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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.
North Eastern Space Applications Centre (NESAC) has been providing thunderstorm nowcasting (forecasting up to 4 hours) services for North Eastern Region (NER) of India since 2015 under the North Eastern Regional node for Disaster Risk Reduction (NER-DRR) initiatives. This was done using the data from satellite imager and sounder onboard INSAT-3D / INSAT-3DR, automatic weather station data, and by analysing numerical weather forecast data. However, it was difficult to detect, track and forecast using this data alone as most of the thunderstorms being a localised event, extending only over a few tens of km and having a lifetime of less than one hour. The availability of DWR data has opened a new window for precise identification of thunderstorm weather systems, track them and forecast the probable areas which may get affected, albeit with lesser lead time.
The first S-band dual-polarimetric Doppler Weather Radar (DWR) was installed at Cherrapunjee, Meghalaya which was dedicated to the nation by Shri Narendra Modi, Hon’ble Prime Minister of India on May 27, 2016. NESAC is operating the DWR continuously since then, and the data is made available in near real-time for the public through the MOSDAC (Meteorological and Oceanographic data archival centre) and IMD websites. The DWR is calibrated at regular intervals and the data and products are being validated. It has unobstructed coverage for the entire state of Meghalaya, Tripura, Southern Assam, and part of Mizoram and Manipur. For the western and central Assam region, the DWR has coverage beyond 3-degree elevation only. The DWR also sees a large part of India’s neighbouring country, Bangladesh. The radar completes one volume scan in 11 minutes, comprising of 360-degree azimuth scan for 10 elevation angles ranging from 0.5 to 21 degrees. It also allows sector scan (in both azimuth and elevation) for high temporal observation of any event. The DWR covers a distance of 250 km (up to 500 km only for Z) with a spatial resolution of 300 m.
A thunderstorm is a pre-monsoon season (April-May) phenomenon over the NER of India. The data collected by the DWR during 2016 was used to understand the thunderstorm and storm signatures and calibrate the nowcasting model. During 2017 the nowcasting service was made operational. Severe thunderstorm nowcasting services for Southern Assam, Meghalaya, and Tripura were done primarily using the DWR data and for the rest of the NER, the earlier methodology was used. In addition to the Z (radar reflectivity), S (spectral width) and V (velocity) data collected by the DWR, extensive use of the polarimetric data like ZDR (differential reflectivity) and ρHV (Correlation coefficient) were also made to differentiate thunderstorm clouds from non-thunderstorm clouds.
The use of the Cherrapunjee DWR data has improved the thunderstorm nowcasting accuracy over Meghalaya, Southern Assam, and Tripura states. Altogether 48 severe and very severe thunderstorms were forecasted in these three states during April 1 to June 15, 2017, period. The accuracy of nowcasting was more than 90% with lead time varying from 30 minutes to more than 2 hours. The nowcasting services were disseminated through NER-DRR website and also through direct communication to the concerned at the state level.
(The DWR, Cherrapunjee coverage for an elevation angle of 3 degrees (left). Calibration of the DWR using metal sphere attached to hydrogen gas-filled balloon & Pisharoty sonde (right))
(Max V (left) and Max S (right) data from DWR, Cherrapunjee. Max V is used to estimate the velocity at which a weather system is moving and Max S gives an idea about the internal turbulence within cloud system)
High-resolution optical imaging Earth Observation Satellite (EOS) systems such as CARTOSAT provide multi-spectral remote sensing data in the visible and near-infrared (VNIR) wavelengths of the order of sub-meter to few-meters. These datasets can be used in a variety of applications, particularly associated with precise mapping, monitoring and change detection of earth’s surface, if top of the atmosphere (TOA) measurements can be properly compensated for atmospheric absorption and scattering effects. Existing physics based atmospheric correction (AC) algorithms for multi/hyperspectral remote sensing data over land involves simultaneous use of visible and short-wave infrared (SWIR) channels to derive aerosol information. Hence, such algorithms cannot be used for AC of data acquired by VNIR sensors to derive “surface reflectance”.
Towards this, Space Applications Centre, Ahmedabad has developed a new algorithm for AC of high-resolution VNIR remote sensing data in which aerosol information is retrieved from sensor measurements in VNIR channels and by selecting appropriate aerosol optical properties from a set of defined aerosol models. The algorithm uses lookup tables generated with vector radiative transfer calculations. Derived aerosol information and pre-computed lookup tables are employed to derive surface reflectance. Good quality surface reflectances have been obtained when this algorithm was applied on Cartosat-2 Series Satellite data. It is found that this algorithm significantly removes the haze from the images, making surface features distinctly visible, and hence more useable for qualitative as well as quantitative analysis and further applications.
Following figures illustrate the drastically improved quality of the images after applying the AC algorithms, where the contribution of light due to molecular scattering and scattering from thick layer of aerosol to the sensor measurement at the top the of the atmosphere is removed.
(Parts of Ahmedabad as viewed from Cartosat-2 Series Satellite on 03/11/2016)
(Cartosat-2 Series Satellite View of Ahmedabad, Satellite Area on 03/11/2016)
Brandon Jarratt took GIS professionals behind the scenes of animated city creation at the Esri User Conference, being held this week in San Diego. Jarratt served as general technical director for Disney’s Zootopia, which won the 2016 Academy Award for Best Animated Feature Film. Jarrett took the stage during the plenary session to describe how the Zootopia team used Esri CityEngine software to create the complex city that serves as the backdrop for the movie.
Jarratt said Disney animated features need three elements: compelling stories, appealing characters, and believable worlds. That’s believable worlds, not realistic worlds.
In this case, the complex city of Zootopia had to be designed from the ground up as a complex city with various districts designed to accommodate the vast array of animal species. In the world of Zootopia, humans don’t exist. Transportation systems, houses, streets, and services need to accommodate animals as tall as giraffes and as small as a shrew. To meet these challenges, the designers turned to Esri CityEngine and its multi-scaling feature. The Zootopia world also needed to incorporate various habitats, or in this case, districts. At the centre a large complex city dominates.
CityEngine was used in the creation of the city in Big Hero 6 as well. In Big Hero 6, the base city geography used was San Francisco, upon which Japanese-style buildings were placed. In all, 80,000 buildings were incorporated into San Fransokyo.
(San Fransokyo in Big Hero 6. (Image: Disney))
Zootopia, on the other hand, was built from scratch – including the terrain. The team started with research of various landscapes to create a basemap.
(Zootopia concept map. (Photo: T. Cozzens))
At the city-building stage, CityEngine’s custom tool was used to lay down streets. Buildings were designed for each district. The building styles couldn’t be repeated too often, or the city would look unrealistic, Jarratt said. The designers used carefully calibrated mix rules to keep the cities lively.
(The desert area of Sahara Square is made of 61,000 parts, including buildings, wall segments and palm trees. (Image: Disney))
The ability in CityEngine to change the makeup of a city, adjusting the frequency of the various parts, made it easy for the illustration team to meet the art director’s requirements. When he wanted more skyscrapers or buildings of a certain design, the team was able to provide new concept images the same day.
(Zooptopia being built in Esri CityEngine. (Photo: T. Cozzens))
Esri’s CityEngine GIS technology is used by city planners to design our future smart cities. “It’s so similar to how city planners create real cities,” said Esri President Jack Dangermond. He then presented Jarratt with Esri’s first-ever Best Animated Feature Using GIS award.
The new Landsat Explorer web app from Esri enables users to wield Landsat imagery to explore geology, vegetation, agriculture, and cities anywhere in the world. The app, driven by publicly accessible image services, offers a way to better visualize the planet and understand how the earth has changed over time.
(A false color band combination, where vegetation appears in red, delineates the Exumas Islands in the Bahamas. With the Scatter Plot tool, users can select two bands to plot on a graph, with the more frequent occurrences appearing on this graph in red.)
Using the app is simple: Open it in a web browser, search for a location, and apply analysis tools on the fly to get immediate, dynamic results. With no download required, Landsat Explorer users get instant, interactive access to an extensive collection of multispectral, multi temporal Landsat imagery.
Landsat satellites have been collecting information about the earth’s surface for almost 45 years. Each Landsat image contains multiple bands of spectral data gathered at different wavelengths. More than just offering pictures of the planet, Landsat’s different bands can be combined and analyzed to learn about what is happening on the ground, beyond what the eye can see.
Beyond enabling users to instantly view half a million Landsat images using different band combinations or enhancements, Landsat Explorer offers extensive analytical capabilities. The visualization and analysis tools let users do the following, all on the spot:
- Visualize the data using custom indexes and band combinations
- Filter and select specific dates to analyze and compare
- Interactively compare two images using a swipe tool
- Create custom masks
- Perform change detection
- Generate spectral and temporal profiles
- Create scatter plots using spectral bands
- Add data (city roads, for example) from ArcGIS Online
Landsat Explorer joins Esri’s existing suite of Landsat apps, including the Landsat Arctic and Antarctic Apps. Whether users answer their own questions by applying Landsat Explorer’s powerful analysis tools or take the small leap to create their own imagery apps, it’s never been simpler to instantly visualize and dynamically analyze the earth’s surface.
ISRO’s new communication satellite
- Launched on: June 29 at 2.45 a.m. [IST]
- Mass: 3,477 kg
- Life: 15 years
- Cost: ₹ 1,013 crore, including launch fee
- Launch vehicle: European booster Ariane-5 ECA / VA238
GSAT-17, the country’s newly launched communication satellite, will soon join the fleet of 17 working Indian communication satellites in space and augment their overall capacity to some extent. The 3,477-kg spacecraft was released into a temporary orbit in space as planned at 2.45 a.m. [a.m.] IST on Thursday about 39 minutes after launch from the European spaceport of Kourou in French Guiana. It was dusk at the South American near-equatorial spaceport.
(Image Source: The Hindu (www.thehindu.com)
GSAT-17 was sent up as the second passenger on the European booster, Ariane-5 ECA VA-238, according to ISRO and the European launch company Arianespace. GSAT-17, built mainly for broadcasting, telecommunication and VSAT services, carries over 40 transponders. It also has the equipment to aid Meteorology forecasts and search and rescue operations across the sub-continent.
“GSAT-17 is designed to provide continuity of services of operational satellites in C, extended C and S bands,” ISRO said. The satellite was released into what is called a temporary `geosynchronous transfer orbit’ or GTO, where it started orbiting distant 249 km at the near end to Earth and 35,920 km at the farthest point. Its operations were immediately taken over by the spacecraft command team at the ISRO Master Control Facility in Hassan.
“Preliminary health checks of the satellite revealed its normal functioning. In the coming days, orbit raising manoeuvres will be performed to place GSAT-17 in the geostationary orbit (36,000 km above the equator) by using the satellite’s propulsion system in steps,” ISRO said.
It normally takes around two weeks to reach and settle in its planned slot over India at 93.5° East longitude. Meanwhile, its various functional appendages such as antennas and solar arrays are deployed. The spacecraft was approved in May 2015 with an outlay of ₹1,013 crore, including its launch fee and insurance. Its co-passenger was the 5,700-kg Hellas Sat 3-Inmarsat S EAN shared by two satellite operators.
ISRO Chairman A.S. Kiran Kumar has earlier said they need double the number of communication spacecraft to support various users across the country. ISRO does not yet have a launcher that can lift payloads above 2,000 kg. As such it must hire foreign launch vehicles — mostly of Arianespace — to put its heavier communication spacecraft in orbit. Only this month, it tested its first GSLV-Mark III vehicle which can do this job for it.
“Today, GSAT-17 became India’s third communication satellite to successfully reach orbit in the past two months,” said an official release. It launched GSAT-19 on the new MkIII on June 5 and the 2,230-kg GSAT-9 or the South Asia Satellite on May 5, both from Sriharikota.
Designed and assembled at the ISRO Satellite Centre in Bengaluru, GSAT-17 has been at the Kourou space port since May 15, undergoing pre-launch checks and tests. Project Director Prakash Rao and a rotating team of over 20 ISRO engineers were attending to it during the period, said an ISRO official.
GSAT-17’s co-passenger has two operators. Hellas Sat 3 provides direct to home television and telecom services across Europe, West Asia and South Africa. Global satellite operator Inmarsat will provide in-flight Internet facilities for European airlines, as signified in the satellite’s tag EAN or European Aviation Network.