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A major use of remote sensing data is to compare images of an area taken at different times and identify the changes it underwent. With a wealth of long-term satellite imagery in open use, detecting such changes manually would be time-consuming and most likely inaccurate.

To address this, EOS Data Analytics has introduced an automated Change Detection tool to its flagship product Land Viewer, a cloud tool for satellite imagery search and analysis in today’s market.

Unlike the methods involving neural networks that identify changes in the previously extracted features, the change detection algorithm implemented by EOS is using a pixel-based strategy, meaning that changes between two raster multi-band images are mathematically calculated by subtracting the pixel values for one date from the pixel values of the same coordinates for another date.

This new signature feature is designed to automate a change detection task and deliver accurate results in fewer steps and in a fraction of the time needed for change detection in most image-processing software.

Change detection interface: Images of Beirut city coastline selected for tracing the developments of the past years. (Image: Land Viewer)

Change detection interface: Images of Beirut city coastline selected for tracing the developments of the past years. (Image: Land Viewer)

Applications from farming to environmental monitoring

One of the main goals set by EOS team was to make the complex process of change detection in remote sensing data equally accessible and easy for non-expert users coming from non-GIS industries.

With Land Viewer’s change detection tool, farmers can quickly identify the areas on their fields that were damaged by hail, storm or flooding. In forest management, satellite image detection of changes will come in handy for estimation of the burned areas following the wildfire and spotting the illegal logging or encroachment on forest lands.

Observing the rate and extent of climate changes occurring to the planet (such as polar ice melt, air and water pollution, natural habitat loss due to urban expansion) is an ongoing task of environmental scientists, who may now have it done online in a matter of minutes. By studying the differences between the past and present using the change detection tool and years of satellite data in Land Viewer, all these industries can also forecast future changes.

Top change detection use cases: Flood damage and deforestation

A picture is worth a thousand words, and the capabilities of satellite image change detection in Land Viewer can be best demonstrated on real-life examples.

Forests that still cover around a third of the world’s area are disappearing at an alarming rate, mostly due to human activities such as farming, mining, grazing of livestock, logging, and also the natural factors like wildfires. Instead of massive ground surveying of thousands of forest acres, a forestry technician can regularly monitor the forest safety with a pair of satellite images and the automated change detection based on NDVI (Normalized Difference Vegetation Index).

How does it work? NDVI is a known means of determining vegetation health. By comparing the satellite image of the intact forest with the recent one acquired after the trees were cut down, Land Viewer will detect the changes and generate a difference image highlighting the deforestation spots, which can further be downloaded by users in JPG, PNG or TIFF format. The surviving forest cover will have positive values, while the cleared areas will have negative ones and be shown in red hues indicating there’s no vegetation present.

A difference image showing the extent of deforestation in Madagascar between 2016 and 2018; generated from two Sentinel-2 satellite images. (Image: Land Viewer)

Another widespread use case for change detection would be agricultural flood damage assessment, which is of most interest to crop growers and insurance companies. Whenever flooding has taken a heavy toll on your harvest, the damage can be quickly mapped and measured with the help of NDWI-based change detection algorithms.

Results of Sentinel-2 scene change detection: The red and orange areas represent the flooded part of the field,; the surrounding fields are green, meaning they avoided the damage. California flooding, February 2017. (Image: Land Viewer)

How to run change detection in Land Viewer

There are two ways you can launch the tool and start finding differences on multi-temporal satellite images: by clicking the right menu icon “Analysis tools” or from the Comparison slider ‒ whichever is more convenient. Currently, change detection is performed on optical (passive) satellite data only; addition of the algorithms for active remote sensing data is scheduled for future updates.

A guide to Land Viewer is available here.

The post Land Viewer’s new change detection tool runs in a browser appeared first on Geospatial Solutions.

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Esri is partnering with the Jane Goodall Institute to develop a set of tools that will help communities map and manage the ecosystems around them through a collaborative design and planning approach, aided by GIS software.

According to the partners, these tools will help communities map, monitor, and better manage their natural resources from community forests and wildlife reserves, to water catchment and flood control areas, as well as human settlement, agriculture and agroforestry spaces.

The Jane Goodall Institute’s community-centered conservation approach — Tacare — partners local communities and governments to create sustainable livelihoods while planning for and advancing environmental protection. The Tacare approach also achieves conservation results and addresses environmental threats — including incompatible expansion of agriculture, human settlements, harvesting forest products, disease, wildlife trafficking and illegal bushmeat trade — by consulting communities about their needs and priorities, and working together to collaboratively plan for and implement land use practices that enable their own development.

“A key component of our success is that we work to help villagers find ways to make livelihoods that do not destroy the environment, and help them understand that protecting the environment not only conserves wildlife, but their own future,” said Dr. Jane Goodall, DBE, founder of the Jane Goodall Institute and United Nations Messenger of Peace.

The Jane Goodall Institute uses Esri’s ArcGIS platform and Survey123 mobile app to help communities and governments in western Tanzania, Uganda and other countries in Africa to plan, monitor and protect chimpanzee populations in local protected forests outside designated national parks.

“Conservation at the community level is essential to sustaining our natural world,” said Jack Dangermond, Esri founder and president. “Protecting global ecosystems cannot work on a global scale unless it starts locally, which is why we are honored to work with our friend and partner, the Jane Goodall Institute, on this collaboration, leveraging their years of experience working at the local scale in pursuit of conservation, balanced with the needs of human communities.”

The post Esri, Jane Goodall Institute partner to protect ecosystems appeared first on Geospatial Solutions.

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Photo: Viametris

Viametris has launched the second-generation version of the vMS3D, its urban and road lidar scanner.

The second-generation version of the 3D mobile vehicle scanner has been redesigned to be more compact. The system has been simplified considerably in both electronic and ergonomic terms to make it more robust and stable in adverse conditions and challenging environments.

Despite being lighter, the second generation offers the same technological capacities as its predecessor, but is simpler to use and can be mounted on a vehicle in minutes.

The system component (including the sensors) and the element to affix the device to the vehicle (the frame) previously formed one unit, but are now separated.

  • The redesigned system is much lighter (9 kg) and more compact.
  • The mechanism to fix the scanner to the vehicle, which formed part of the system in the first-generation version, has been transformed. A rigid metal frame, fixed onto two roof bars, now holds the system, which fits into a dedicated compartment in seconds. As the frame is rigid, it limits vibrations between the system and the vehicle and prevents any strain on the mechanics during acquisition.
  • The second auxiliary antenna, which measures the heading by satellite, is discreet and non-removable, and fixed directly to the vehicle chassis.

The new design makes it easier to mount and use the system, a task that can be accomplished by a single person in under three minutes. Alignment takes place the first time the system is mounted and does not need to be repeated, saving valuable time each start.

Technological features

The vMS3D comprises a new set of components that are more robust and stable in difficult conditions.

  • The integrated connectors are next-generation and embedded-grade.
  • The control box for power supply and communication with the tablet has been moved inside the vehicle to offer increased comfort to the user.

Specifications

Receiver : GPS+GLONASS+BeiDou+Galileo, 448 channels – L1/L2, B1/B2, E1/E5B, RAW

IMU : SBG-Systems Ellipse2-D

Scanner : 700,000 points per second

Centimeter precision

Panoramic 30MP FLIR Ladybug 5+ camera

Double antenna

SLAM compatible

The post Viametris launches new version of urban and road scanner appeared first on Geospatial Solutions.

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Image: Raytheon

Raytheon Company has signed a strategic agreement with AirMap, an airspace intelligence platform for drones, to collaborate on projects to safely integrate unmanned aerial systems (UAS) into the national airspace system. This will help unlock the positive economic and social benefits of expanded commercial drone operations, the companies said.

Unmanned air traffic control advances will unlock safe, efficient, and scalable drone operations with a myriad of economic and social benefits.

“AirMap is ushering in a new era in drone aviation,” said Matt Gilligan, vice president of Raytheon’s Intelligence, Information and Services business. “Drones must safely operate in an already complex ecosystem, which is where our experience matters.”

The agreement combines the two companies’ expertise:

  • Raytheon’s Standard Terminal Automation Replacement System, or STARS, is used by air traffic controllers across the U.S. to provide safe and efficient aircraft spacing and sequencing guidance for more than 40,000 departing and arriving aircraft daily at both civilian and military airports.
  • AirMap is the leading global provider of airspace intelligence for UAS operations, with over 250,000 registered users. In 2018, the majority of U.S. registered commercial drone pilots used AirMap to request over 45,000 automated authorizations to fly in controlled airspace.

“Raytheon technology has helped safely and effectively manage airspace in the most complex, dense controlled airspace in the world for decades,” said Ben Marcus, AirMap co-founder and chairman. “They are an ideal partner to join AirMap on the path toward enabling safe, efficient, and scalable drone operations in U.S. low-altitude airspace between 0 and 400 feet.”

The two companies are working toward an integrated demonstration that will showcase how AirMap’s unmanned aircraft traffic management platform can increase air traffic controllers’ awareness of potential conflict between drones and manned aircraft near airports to ensure overall safety of the airspace.

The post Raytheon, AirMap work on integrating drones into national airspace appeared first on Geospatial Solutions.

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A major use of remote sensing data is to compare images of an area taken at different times and identify the changes it underwent. With a wealth of long-term satellite imagery in open use, detecting such changes manually would be time-consuming and most likely inaccurate.

To address this, EOS Data Analytics has introduced an automated Change Detection tool to its flagship product LandViewer, a cloud tool for satellite imagery search and analysis in today’s market.

Unlike the methods involving neural networks that identify changes in the previously extracted features, the change detection algorithm implemented by EOS is using a pixel-based strategy, meaning that changes between two raster multi-band images are mathematically calculated by subtracting the pixel values for one date from the pixel values of the same coordinates for another date.

This new signature feature is designed to automate a change detection task and deliver accurate results in fewer steps and in a fraction of the time needed for change detection in most image-processing software.

Change detection interface: Images of Beirut city coastline selected for tracing the developments of the past years. (Image: LandViewer)

Change detection interface: Images of Beirut city coastline selected for tracing the developments of the past years. (Image: LandViewer)

Applications from farming to environmental monitoring

One of the main goals set by EOS team was to make the complex process of change detection in remote sensing data equally accessible and easy for non-expert users coming from non-GIS industries.

With LandViewer’s change detection tool, farmers can quickly identify the areas on their fields that were damaged by hail, storm or flooding. In forest management, satellite image detection of changes will come in handy for estimation of the burned areas following the wildfire and spotting the illegal logging or encroachment on forest lands.

Observing the rate and extent of climate changes occurring to the planet (such as polar ice melt, air and water pollution, natural habitat loss due to urban expansion) is an ongoing task of environmental scientists, who may now have it done online in a matter of minutes. By studying the differences between the past and present using the change detection tool and years of satellite data in LandViewer, all these industries can also forecast future changes.

Top change detection use cases: Flood damage and deforestation

A picture is worth a thousand words, and the capabilities of satellite image change detection in LandViewer can be best demonstrated on real-life examples.

Forests that still cover around a third of the world’s area are disappearing at an alarming rate, mostly due to human activities such as farming, mining, grazing of livestock, logging, and also the natural factors like wildfires. Instead of massive ground surveying of thousands of forest acres, a forestry technician can regularly monitor the forest safety with a pair of satellite images and the automated change detection based on NDVI (Normalized Difference Vegetation Index).

How does it work? NDVI is a known means of determining vegetation health. By comparing the satellite image of the intact forest with the recent one acquired after the trees were cut down, LandViewer will detect the changes and generate a difference image highlighting the deforestation spots, which can further be downloaded by users in JPG, PNG or TIFF format. The surviving forest cover will have positive values, while the cleared areas will have negative ones and be shown in red hues indicating there’s no vegetation present.

A difference image showing the extent of deforestation in Madagascar between 2016 and 2018; generated from two Sentinel-2 satellite images. (Image: LandViewer)

Another widespread use case for change detection would be agricultural flood damage assessment, which is of most interest to crop growers and insurance companies. Whenever flooding has taken a heavy toll on your harvest, the damage can be quickly mapped and measured with the help of NDWI-based change detection algorithms.

Results of Sentinel-2 scene change detection: The red and orange areas represent the flooded part of the field,; the surrounding fields are green, meaning they avoided the damage. California flooding, February 2017. (Image: LandViewer)

How to run change detection in LandViewer

There are two ways you can launch the tool and start finding differences on multi-temporal satellite images: by clicking the right menu icon “Analysis tools” or from the Comparison slider ‒ whichever is more convenient. Currently, change detection is performed on optical (passive) satellite data only; addition of the algorithms for active remote sensing data is scheduled for future updates.

The post Landviewer’s new change detection tool runs in a browser appeared first on Geospatial Solutions.

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Screenshot: Mapitude

Maptitude for Redistricting is designed specifically for anyone involved in or preparing for the 2020 redistricting cycle, from novice to professional users.

Maptitude for Redistricting 2019 has new partisan competitiveness reports, adds access to imagery layers, and allows users to save and share their plans in a variety of formats.

New features include:

  • Speed improvements provide faster access to maps and geographic analysis.
  • Expanded file support for Excel worksheets, Google Earth Documents (KML/KMZ) attribute data fields, and MapPoint files.
  • New partisan competitiveness reports and measures of compactness for analyzing redistricting plans,
  • Integrated satellite imagery from a variety of sources for giving a better view of district composition.
  • The latest Census geography and data, including current ACS data.

Maptitude for Redistricting is a professional tool for political redistricting. It provides measures and reports that support the creation of fair and balanced districts.

Maptitude is constantly enhanced and provides tools such as the Efficiency Gap Measure for exploring redistricting problems.

Maptitude was used to democratize redistricting in California and is used by the majority of redistricters, from independent commissions, non-profits, and civil rights groups, to the courts and political parties.

The post Maptitude for Redistricting ready for 2020 cycle appeared first on Geospatial Solutions.

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Photo: Phase One Industrial

Phase One Industrial has expanded its RS and RSM lens offering with three new high performance lenses for high-altitude aerial photography and long-range aerial and ground inspection applications.

The 300mm AF, 180mm, and 150mm MK II lenses are designed to enhance the performance and flexibility of Phase One Industrial’s iXM-RS and iXM aerial camera series. Each offers precision imagery, taking advantage of the cameras’ ultra-high resolution backside-illuminated (BSI) CMOS sensors, to maintain a smaller ground sample distance (GSD) while flying at higher altitudes, the company said.

Phase One RSM 300mmAF. With the longest focal length in the line-up, this lens offers a 5 cm GSD from 13,000 feet. It fits both iXM and iXM-RS camera models and produces superb image quality by enhancing the cameras’ ultra-high resolution BSI CMOS sensors (3.76 µm pixels).

The lens is designed for both high-altitude 2D and 3D mapping and long-range ground inspection. The motorized lens offers a focus range of 10 m to infinity within which a predefined distance can be set remotely. A self-locking mechanism is built in to secure the focus position against vibrations.

  • 5 cm GSD from 13,000 feet
  • 10 m to infinity focusing range
  • f/8 – f/32 aperture range
  • 1/2000 sec exposure time
  • RS Shutter reliability – 500,000 actuations

Rodenstock RS 180mm. Specified by Phase One and built by Rodenstock Photo Optics, Germany, this lens reaches a 5 cm GSD from 8,000 feet when used with the iXM-RS150F camera. The lens supports the camera’s ultra-high resolution BSI sensor for greater image quality and is integrated with a Phase One RS reliance shutter for speed and reliability. The RS 180mm enhances high-altitude aerial 2D and 3D mapping and improves efficiency in oblique configurations.

  • 5 cm GSD from 8,000 feet
  • f/6.3 – f/22 aperture range
  • 1/2000 sec exposure time
  • RS Shutter reliability – 500,000 actuations

Phase One RS 150mm MK II. A 5 cm GSD from 6,500 feet is achievable with the RS 150mm MK II lens. It complements the iXM-RS150F camera’s ultra-high 150-megapixel resolution BSI CMOS sensor for acquiring quality images for high-altitude aerial 2D and 3D mapping.

  • 5 cm GSD from 6,500 feet
  • f/5.6 – f/22 aperture range
  • 1/2500 sec exposure time
  • RS Shutter reliability – 500,000 actuations

Every Phase One Industrial lens is rigidly built for robustness against vibrations and shocks to meet RTCA DO160G standards, and is individually tested for performance and high-modulation across the whole image area.

The post Phase One offers 3 high-performance, high-altitude lenses appeared first on Geospatial Solutions.

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2019 Aquatic Airshow participants at Androscoggin River in Auburn, Maine, on May 1. (Photo: Mario Martin-Alciati, USGS)

The U.S. Geological Survey (USGS) and independent scientists gathered in Auburn, Maine, to evaluate the use of sensor-mounted unmanned aircraft systems (UAS) to gauge stream stage, velocity, bathymetry and discharge.

The technology is being evaluated and modeled to determine whether it will support the fast, accurate and safe measurement of rivers, especially when they are flooded or contain floating trees, ice or other debris.

Close to two dozen hydrologic, geospatial and scientific experts gathered in what has been dubbed the “2019 Aquatic Airshow” to assess the technology. They were led by John Fulton of the USGS Colorado Water Science Center, Jack Eggleston of the USGS Water Mission Area Hydrologic Remote Sensing Branch, and Joe Adams and Sandy Brosnahan of the USGS National UAS Project Office.

The USGS Water Mission Area works with partners to monitor, assess, research and report on a wide range of water resources and conditions, including streamflow, groundwater, water quality, water use and water availability.

The testing involved equipping drones with noncontact sensors, including ground-penetrating radar for measuring river depths, doppler velocity radar and cameras with velocimetric analysis for measuring water surface velocities and calculating mean-channel velocities; and high-resolution cameras for photogrammetric mapping of surface topography and vegetation structure.

Team members from the USGS Water Science Centers in Colorado, New England and Virginia collected ground-truth river monitoring data with acoustic doppler current profilers deployed from a boat and multiple other surveying techniques to verify the accuracy of the drone-based stream data.

Woolpert Chief Scientist Qassim Abdullah was one of two scientists from the private sector asked to participate in the airshow. Abdullah has more than 40 years of experience in analytical photogrammetry, digital remote sensing, and civil and surveying engineering.

For the event, Abdullah devised a process in which the data collected by the drones underwent Pix4D triangular adjustment to produce three-dimensional models of the water surface and river edges to assist the modeling of river velocity using the drone-based doppler velocity radar and large-scale particle image velocimetry.

USGS scientists are in the process of evaluating the data and modeling produced by this testing to conclude whether this technology will prove beneficial.

Abdullah said the airshow was a success due to the varied contributions from each member of the team, their diverse backgrounds and their shared focus on water research.

“This was a great example of how a public-private partnership can work together to activate and elevate necessary, groundbreaking technologies to address worldwide issues,” Abdullah said. “Airshow team members brought different perspectives, processes and applications to the testing, which not only proved essential for this project but will help with many others moving forward. I love working with this group and look forward to continuing to help advance these vital technologies.

The post USGS, scientists test drone-based river analysis appeared first on Geospatial Solutions.

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With more than 80 percent of the world’s oceans unmapped, the deep ocean is one of the last unknown areas on Earth. On May 31, teams with unique exploration solutions were honored with the Shell Ocean Discovery XPRIZE.

XPRIZE is a global competition to advance ocean technologies for rapid, unmanned and high-resolution ocean exploration and discovery. The teams invented new technologies for rapid, unmanned and high-resolution ocean exploration and discovery.

The results were revealed at an awards ceremony hosted at the Oceanographic Museum of Monaco, part of the Oceanographic Institute, Prince Albert I of Monaco Foundation.

The grand prize winner, receiving a total of $4 million, was GEBCO-NF Alumni, an international team based in the United States, while KUROSHIO, from Japan, claimed $1 million as the runner-up.

GEBCO-NF Alumni was led by Rochelle Wigley, Ph.D., and Yulia Zarayskaya, Ph.D. The 14-nation team integrated existing technologies and ocean-mapping experience with a robust and low-cost unmanned surface vessel, the SeaKIT, along with a novel cloud-based data processing system that allows for rapid seabed visualization, to contribute towards comprehensive mapping of the ocean floor by 2030.

Runner-up was KUROSHIO, from Yokosuka, Japan, led by Takeshi Nakatani, Ph.D. The team integrated technologies from their partners to create a surface vessel and software platform that can operate with different autonomous underwater vessels, which increases the versatility of their technology.

NOAA prize bonus testing in Puerto Rico. (Photo: XPRIZE)

Field Testing. To determine winners, the panel of independent judges reviewed data from field testing conducted in Kalamata, Greece, and Ponce, Puerto Rico. In Kalamata, teams had up to 24 hours to map at least 250 square kilometers of the ocean seafloor at five meters horizontal resolution or higher.

The gold-standard high-resolution baseline maps, against which the team maps were judged, were provided by Ocean Infinity and Fugro, while Esri, the global leader in geographic information system (GIS) software and geodatabase management, donated its ArcGIS Online platform for the teams and judges to use.

NOAA Prize. The $1 million National Oceanic and Atmospheric Administration (NOAA) Bonus Prize went to teams for developing technology that could detect a chemical or biological signal underwater and autonomously track it to its source. The award was split between junior high school team Ocean Quest from San Jose, California, which claimed $800,000 as the winner, and Tampa Deep Sea Xplorers, from Florida, taking $200,000 as runner-up.

Additionally, the judges unanimously recommended a $200,000 Moonshot Award for Team Tao from the United Kingdom for its unique approach to seafloor mapping, even though they did not meet the criteria of the competition.

As part of the total $7 million prize purse, four teams opted to compete for the $1 million NOAA Bonus Prize. In a field test in Ponce, Puerto Rico, teams needed to demonstrate that their technology can “sniff out” a specified object in the ocean by first detecting and then tracing a biological or chemical signal to its source.

ODXP Competition Final Round 2 Testing in Kalamata, Greece. (Photo: XPRIZE)

The judges determined that no single team was able to trace the signal to its source in the timeframe allowed, so the prize was divided among the two teams that came the closest. In 2018, nine finalist teams were awarded an equal share of the first $1 million of the $7 million prize purse, in recognition of their progress-to-date and to support the teams’ continued technological development.

Seabed 2030 and science fiction. As part of its post-prize impact work, XPRIZE announced a partnership with Seabed 2030, a collaborative project between The Nippon Foundation and The General Bathymetric Chart of the Oceans (GEBCO) to inspire the complete mapping of the world’s ocean by 2030 and to compile all bathymetric data into the freely-available GEBCO Ocean Map.

Additionally, and in anticipation of World Oceans Day on June 8th, XPRIZE will launch a science fiction ocean anthology featuring 19 original short stories and artwork set in a future when technology has helped unlock the secrets of the world’s oceans.

Meet the Shell Ocean Discovery Finalist Teams - YouTube

The post Ocean mapping, exploration inventions honored with XPRIZE appeared first on Geospatial Solutions.

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The new senseFly Solar 360 UAV is designed to enable the automated and efficient inspection of solar farms.

Photo: SenseFly

SenseFly has introduced its new senseFly Solar 360. Created in collaboration with software company Raptor Maps, the new offering is an efficient thermal drone solution that enables the automatic assessment of solar plant performance at a sub-module level.

Created by combining eBee X fixed-wing drone technology, senseFly’s Duet T thermal mapping camera and Raptor Maps’ software, senseFly Solar 360 is a fast and fully automated drone. It is easily integrated into solar management workflows without requiring either drone piloting skills or the manual analysis of aerial solar farm data.

“At senseFly we are continually looking across the industry to identify new commercial partners with whom we can bring to market what our customers need, which is vertically-focused end-to-end solutions,” said Gilles Labossière, CEO of senseFly.

“With Raptor Maps, we are collaborating with a true solar industry pioneer,” Labossière said. “Their software takes the guesswork out of solar farm inspection and, crucially, speeds up this process — from days down to hours. This efficiency, combined with the eBee X’s large coverage and reliability, ensures that farm owners and operators — or the drone service providers they employ — can inspect utility-scale solar farms more quickly, easily, and accurately than ever before.”

“Solar power is the largest source of new energy generation in the world,” said Nikhil Vadhavkar, CEO of Raptor Maps. “This rapid growth has fueled demand for industry-specific solutions to allow solar customers to scale. Our enterprise-grade software has been deployed across six continents and 25 million solar panels to increase power production and reduce risk and maintenance cost across solar portfolios. We are proud to collaborate with senseFly, the industry leaders in commercial fixed-wing drones, to increase access to Raptor Maps while providing a comprehensive, end-to-end solution that scales with the solar industry.”

The post Thermal drone designed for efficient solar farm inspections appeared first on Geospatial Solutions.

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