Natural Hazards Alerts

 

Natural Hazards Alerts

Natural hazards are associated with changes in ocean, land, atmosphere, and ionosphere. The ground, borehole, and satellite observations provide information at spatial and temporal resolution over the globe. Now optical and microwave satellites are capable in providing meteorological and atmospheric parameters at different pressure levels. With the sponsorship of an NSF Convergence Research grant, this virtual international workshop will brainstorm how to use various data available to scientists to develop or continue development on early warning systems that alert people in local communities, through various social and digital media of natural hazards. Early warning systems have already shown that damage to life and property can be minimized.

https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.agu.org%2FNatural-Hazards-Alerts&data=04%7C01%7Crsingh%40chapman.edu%7C75233defdb884fabd1aa08d9004a7dd1%7C809929af2d2545bf9837089eb9cfbd01%7C1%7C0%7C637541142212416467%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=1d0x7bGGRMKoBSKf%2FKuyxEd4EZ%2BmueDknUS51w5gfyw%3D&reserved=0

Open Source GIS

Alternatives to ArcGIS Desktop 

If you've ever worked with geographic data on the desktop, chances are that you used Esri's ArcGIS application in at least part of your work. ArcGIS is an incredibly powerful tool, but unfortunately, it's a proprietary product that is designed for Windows. Linux and Mac users are out of luck unless they want to run ArcGIS in a virtualized environment, and even then, they're still using a closed source product that can be very expensive to license. While their flagship product is closed source, I would be remiss not to note that Esri has made numerous contributions to the open source community.

Fortunately, GIS users have a few choices for using open source tools to design maps and work with spatial data that can be obtained under free and open source licenses and which run on a variety of different non-Windows operating systems. Let's take a look at some of the options.

GRASS

GRASS  stands for Geographic Resources Analysis Support System). It has a very long history, dating back to original development which began in 1982 under the US government. In the time since, GRASS has been adopted by the academic community, where its development continues today.

I mention this history because it will help you to understand the interface, which launches with a terminal window and asks you a few questions about setting up your project before launching a separate control and display window for working with your data. If the GUI feels like it was later tacked on to a powerful program working under the hood, well, that's probably what actually happened. While the interface may not feel as intuitive to newcomers as some other GIS applications, I like it for two reasons. One, since it really is just a GUI abstraction to the underlying Python commands, advanced users can easily manipulate data and display directly from the Python console, for speed, preciseness, and importantly for academic applications, easy replicability. The second reason I like the interface is that it exposes the wide and powerful array of data manipulation tools directly.

GRASS is definitely the winner when it comes to data analysis and geo-processing, and its tools can be used from external applications, making it an extremely extensible tool which is worth learning even if you don't take it on as your primary desktop GIS system. GRASS is written primarily in C/C++, although many of its modules are written in Python or other languages. 

QGIS

For many people, discovering QGIS is the end of their search for an ArcGIS alternative. It has a clean interface, it's easy to use, and it just works. QGIS supports a wide variety of raster and vector formats, and if you're a Linux user, there's a good chance that it's already packaged for your distribution's default repositories. In addition to Linux, downloads and instructions for macOS, Windows, BSD, and Android can be found on the project's website.

QGIS has great documentation which can be found in its user manual, as well as an active user community which has produced numerous tutorials, guides, and even books to help you succeed. There are also a huge number of plugins that add a ton of functionality not found in the base package, and its Python interface makes it relatively easy for newcomers to create new ones.

You can find the source code to QGIS, which is written primarily in C++, on GitHub under a GPLv2 license.

uDig

While I've been a user of both GRASS and QGIS for several years now, recently I've been trying to expand my horizon a bit and have been trying out uDig, which stands for User-friendly Desktop Internet GIS.

uDig different than the other two tools in that built more as an application framework than a complete solution. It is, in fact, a stand-alone program, and if you download it and fire it up you can begin adding and exploring your data like a more traditional desktop GIS tool.

But its strength comes in its framework design, being built around the same Eclipse IDE that many developers are familiar with already. In this way, uDig makes it easy to develop your own GIS application which meets the specific needs of your users. The project's gallery hosts many examples, from smart grid to forestry to logistics. uDig is jointly licensed under the Eclipse Public License and a BSD license, and you can find its Java-based source code on GitHub.

In addition to these desktop tools, there are numerous tools beyond the desktop that GIS users can take advantage of. There are libraries for developing web-based mapping tools like Leaflet and OpenLayers. On the database site, most major database systems will support basic X/Y coordinates, but PostGIS leads the pack with spatially-enabled open source databases by providing extensions on top of PostgreSQL. Libraries like GDAL/OGR provide base functionality to many other spatially enabled programs and have bindings for many popular programming languages. Projects like GeoServer and MapServer offer server-side spatial data hosting.

Many of these open source projects find commercial support from companies like Boundless. The open source geospatial ecosystem is rich, and perhaps richer, than its closed-source counterpart. Several of the projects above fall under the umbrella of OSGeo, the Open Source Geospatial Foundation, which houses a number of different geographic tools and projects which are worth checking out.

High Resolution Mapping using UAS

UAS platforms are nowadays a valuable source of data for inspection, surveillance, mapping and 3D modeling issues. New applications in the short- and close-range domain are introduced, being the UASs a low-cost alternatives to the classical manned aerial photogrammetry. LIDAR has become the inevitable technology to provide accurate 3D data fast and reliably even in adverse measurement situations and harsh environments. It provides highly accurate point clouds with a significant number of additional valuable attributes per point compared to traditional digital photogrammetry based approach. UAS photogrammetry images generate the high resolution terrain visualisation, topographic data essential to detect precise asset locations, terrain modelling, geomorphological changes, vegetation dynamics and tree height models.

According to the new market research report  LiDAR market is expected to reach USD 1,809.5 Million by 2023 from USD 819.1 Million by 2018, at a CAGR of 17.2% during the forecast period.

The market for Solid-State LiDAR is expected to grow at the highest CAGR during the forecast period. The higher CAGR of the market for solid-state LiDAR during the forecast period is attributed to the increasing range of applications of this type in the automotive and robotics industries. The solid-state LiDAR systems were specially introduced for the automotive industry. These LiDAR systems can also be installed in economy cars due to their low costs.

On the basis of installation, ground-based LiDAR expected to grow with the highest CAGR during forecast period. The ground-based LiDAR systems are used in the applications including small area scanning, corridor mapping, volumetric mapping, and defense area surveying. Mobile ground-based LiDAR is a new and emerging technology used in many applications such as corridor mapping, transportation, hydrology, forestry, and construction. Mobile ground-based LiDAR systems are mounted on a mobile platform, preferably on a terrestrial vehicle. The advantage of being mounted on a vehicle is that it enables the LiDAR to scan large areas accessible by road. The automotive sector is emerging as an application area for the mobile ground-based LiDAR systems, and the number of premium cars equipped with advanced driver assistance systems (ADAS) is rising every year. This is expected to further boost the market for mobile ground-based LiDAR systems.

North America is expected to dominate the LiDAR during the forecast period. This growth can be attributed to the supportive government initiatives and increasing utilization of LiDAR systems by various institutes for various applications, such as corridor mapping, forestry, environmental, and exploration, along with some of the emerging applications including advanced driver assistance systems (ADAS) and urban planning.  The growing awareness regarding the benefits of LiDAR systems, which include easy functionality, better quality, less complexity, and improved features, can also be the driving factors for the growth of the LiDAR market in the US. In addition, major companies such as Trimble, Faro, and Velodyne are based in the US, which is also a key factor leading to the large share of the US in the LiDAR market.Major players operating in this market are Teledyne Optech (Canada), Leica Geosystems (Switzerland), Reigl Laser Measurement Systems (Austria), Trimble (US), Faro Technologies (US), Quantum Spatial (Aerometric) (US), Velodyne LiDAR (US), Beijing Surestar Technology (Isurestar) (China), Geokno (India), Sick AG (Germany). 

Temporal Analysis of Cape Town Drought

Cape Town is running out of water. After three years of intense drought, South Africa’s second-largest city is just a few months away from “Day Zero,” the day when the city government will shut off water taps for most homes and businesses.

The impacts of such a shutdown will be devastating. Citizens will have to wait in long lines at state-managed distribution points to receive a mere 25 liters of water per day, less than half the water needed for one average shower. Experts are already warning of public health concerns like poor sanitation leading to faster spreading of dangerous diseases, especially for the city’s poorest residents, and forecasting that pipes may crack from dry conditions, endangering future water distribution if and when the drought ends. The Western Cape Premier has warned that “normal policing will be entirely inadequate” to manage the chaos that could ensue.   

Although this instance is one of the most extreme, Cape Town is not the only city to suffer from intense water scarcity in recent years. From São Paulo to Los Angeles, cities around the world have made headlines due to severe droughts intensified by climate change and exacerbated by poor water management.

The loss of water can be seen most clearly with Cape Town’s biggest dam, Theewaterskloof. The reservoir now holds only 12 percent of its original capacity.
For more details visit..
https://www.washingtonpost.com/graphics/2018/world/capetown-water-shortage/?utm_term=.757d2010be6f

ISRO launched a record 104 satellites using a single rocket.

The satellites from seven countries were carried by the Indian Space Research Organization’s Polar Satellite Launch Vehicle on its 38th consecutive successful flight.

The mission reinforces India’s emerging reputation as a reliable and cost-effective option for launching satellites. In 2014, ISRO put a satellite into the orbit of Mars, becoming the first Asian country to reach the red planet at fraction of the cost of a similar launch in U.S. and Europe.

It first released its main cargo, ISRO’s 714 kilogram Cartosat-2 series satellite, which will be used for earth observation. It then released two smaller ISRO satellites, followed by the remaining 101 nano satellites, one each from Israel, Kazakhstan, Netherlands, Switzerland, United Arab Emirates, and 96 from the U.S. As many as 88 of the nano satellites belonged to U.S.-based company Planet Inc.

ISRO said the satellites went into orbit 506 kilometers from earth, inclined at an angle of 97.46 degrees to the equator–very close to the intended orbit–after a flight of nearly 17 minutes. In the subsequent 12 minutes, all 104 satellites were successfully separated from the rocket in sequence, it said.

After separation, the two solar panels of ISRO’s Cartosat-2 series satellite were deployed and the space agency’s command center in Bangalore took control. In the coming days, the satellite will begin to provide start sending back black and white, and color pictures, ISRO said.

ISRO has now put 226 satellites into orbit, including 180 from foreign nations. The global space industry was estimated to be worth $323 billion in 2015, the latest year for which data are available, according to the Space Foundation, a U.S.-based research group. Commercial space business comprised as much as 76% of the industry.

Revenues from Geospatial Analytics industry to top $72.21 Billion in 2020

According to a new market research report  published by Marketsandmarkets, the Geospatial Analytics Market is expected to grow from USD 27.42 billion in 2015 to USD 72.21 billion by 2020, at a CAGR of 21.4% from 2015 to 2020. 

Download Free PDF brochure : http://tinyurl.com/jal4omf 

GIS technology to play a key role in the geospatial analytics market

GIS technology has given a significant boost to the geospatial analytics market due to developments in several trends, such as increase in the amount of geospatial information gathered through smartphones, GPS devices, and social media, among others. An increase in the accuracy of data gathered; advancements in hardware technologies, are additional factors influencing the demand of GIS technology.

Business vertical holds the largest share in the Geospatial Analytics Market

The business vertical holds the largest market share among all the verticals. This large share is attributed to the increasing deployment of geospatial technologies in verticals, such as retail, manufacturing, real estate, healthcare, and so on. In retail, GIS technology is used to discover the best possible site for the location of a new shopping mall.

Europe emerged as the leading region in terms of adoption and implementation of geospatial services

Europe accounted for the largest share in the global geospatial analytics market in 2015. This high market share is mainly attributed to huge investments made in the field of geospatial analytics by key players in European countries.

Major players of the geospatial analytics market covered in the report include Trimble Navigation, Ltd., Hexagon AB, General Electric, RMSI, Bentley Systems, Inc., ESRI, MDA Corporation, Fugro N.V., Harris Corporation, and WS Atkins Plc. Some of the other players are TomTom, Digital Globe, Critigen, AAM, and Nokia.

Restructuring loan without Discoms Business Process Re-engineering is a doomed Idea

With a three-year government rescue package coming to a close, the highly indebted state of Rajasthan is getting tough - it's demanding farmers start paying for their electricity.

In a country where rural communities have become used to free power, the state that is home to some 70 million is tasking private firms with running power distribution in its big cities as it tries to recoup what it's owed.

Restructured power distribution debts alone amount to a quarter of Indian banks' problematic loans, and Rajasthan's state-run utilities owe about Rs 61,000 crore, with some Rs 3,000 crore due by end-March. While Rajasthan dropped an earlier plan to actually raise existing tariffs after opposition from farmers.

With these debt levels echoed across the country, Indian states have little choice but to find ways, extreme or otherwise, to face up to a long-ignored problem. Bad debts aren't just threatening banks - with electricity utilities central to the problem, Prime Minister Narendra Modi's electoral promise of power for all could be jeopardised.

The Reserve Bank of India (RBI) warned in June that the risk of states failing to repay loans on time was "very high", as a three-year rescue package launched in 2012 comes to an end - the source of Rajasthan's urgency on collecting fees for electricity. And the central government has identified the power utility sector as critical to solving banks' bad debt problems.

States who cannot pay banks what they owe over the next few years could be forced to turn to the central government for help, putting pressure on India's consolidated fiscal deficit. The centre has ruled out a rescue package along the lines of the 2012 scheme launched under the previous government.

The responsibility under the federal system for reform lies with states - all with different appetites for change, and for pursuing villagers who fail to pay.

Decades of mismanagement and political meddling have left utilities selling electricity below cost and turning a blind eye to rampant theft. The result is state distributors are sitting on $66 billion (nearly Rs 4.38 lakh crore) worth of debt, according to rating agency CRISIL, double the level four years ago.

Rajasthan's drive to collect payments from farmers and call in private firms to help run power distribution replicates reforms made a decade ago in PM Modi's home state of Gujarat. Distributors there are now largely profitable, and power is reliably available across most of the state.

But reform has proved tough and not all states are willing to take difficult steps. In largely agricultural Uttar Pradesh, farmers pay a fixed fee for unlimited power, equating to about one rupee per unit of electricity, a sixth of the generation cost. The state power company's finance director says it has no plans to raise prices to close that gap.