HICO Image Processing System – Update

(14-Dec-2016) Please pardon the interruption. The HICO Image Processing System is currently being migrated to another hosting platform and will be back up and running soon. Stay tuned here for an announcement once the maintenance is complete. Thank you.

HICO IPS

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A Year of Hyperspectral Image Processing in the Cloud – HICO IPS reaches a milestone

It has been a little more than one year since we first launched the HICO Image Processing System (HICO IPS), and its performance continues to be exceptional. In fact, as a prototype, HICO IPS has exceeded all expectations, working flawlessly since it was first launched in May 2015.

HICO IPS

HICO IPS is a web-application for on-demand remote sensing image analysis that allows users to interactively select images and algorithms, dynamically launch analysis routines, and then see results displayed directly in an online map interface. More details are as follows:

  • System developed to demonstrate capabilities for remote sensing image analysis in the cloud
  • Software stack utilizes a combination of commercial and open-source software
  • Core image processing and data management performed using ENVI Services Engine
  • Operational system hosted on Rackspace cloud server
  • Utilizes imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), which was deployed on the International Space Station (ISS) from 2009-2014
  • Example algorithms are included for assessing coastal water quality and other nearshore environmental conditions
  • Application developed in collaboration between HySpeed Computing and Exelis Visual Information Solutions (now Harris Geospatial Solutions)
  • Project supported by the Center for the Advancement of Science in Space (CASIS)

And here’s a short overview of HICO IPS accomplishments and performance in the past year, including some infographics to help illustrate how the system has been utilized:

  • The application has received over 5000 visitors
  • Users represent over 100 different countries
  • System has processed a total of 1000 images
  • Equivalent area processed is 4.5 million square kilometers
  • The most popular scene selected for analysis was the Yellow River
  • The most popular algorithm was Chlorophyll followed closely by Land Mask
  • Application has run continuously without interruption since launch in May 2015

HICO IPS infographics

Try it out today for yourself: http://hyspeedgeo.com/HICO/

ISS National Lab Releases Gap Analysis on Earth Observation Capabilities from ISS

HySpeed Computing is proud to announce release of the “Campaign Good Earth, Gap Analysis Report” – authored by our own Dr. James Goodman. The report provides an investigative review of remote sensing capabilities from the International Space Station (ISS), including current facilities and resources as well as opportunities for future development.

Campaign Good Earth Gap Analysis Report

ISS National Lab, On Station (28 April 2016) – Last year, CASIS commissioned a study to evaluate the capabilities and limitations of the ISS as a host for commercial remote sensing payloads, including the products and needs of the data analytics community. A full report is now available detailing the findings of this study in the context of the expanding commercial market for Earth observation technologies and analysis.

The ISS provides a unique vantage point for Earth observation, and the ISS infrastructure itself provides many advantages as a robust platform for sensor deployment. Real-time and time-series information gathered from remote sensing applications have proven invaluable to resource management, environmental monitoring, geologic and oceanographic studies, and assistance with disaster relief efforts. This report, an analysis of the gaps between ISS capabilities and limitations in the remote sensing market, is meant to initiate a path toward optimal use of the ISS National Lab as a platform for project implementation and technology development. The report includes:

  • Expert contacts from NASA, CASIS, commercial leaders, and government agencies
  • Recommendations for how to support humanitarian and educational enrichment
  • Implementation strategies for hardware and technology adaptation on the ISS
  • Details on current and planned missions, data sources, and validation requirements

Download the report here.

Remote Sensing in the Cloud – Characterizing shallow coastal environments using HICO IPS

This is the last in a series of posts devoted to reviewing the algorithms currently implemented in the cloud-based HICO Image Processing System (HICO IPS). Links to the other posts in this series are provided below. Here we provide an overview of the algorithm utilized for retrieving multiple layers of water and habitat information for shallow coastal environments.

HICO IPS

Objective – Demonstrate the capability to simultaneously derive information on water properties, water depth and seabed features in shallow coastal environments using a complex hyperspectral image processing algorithm.

Algorithm – Derives inherent optical properties for absorption and backscattering (phytoplankton absorption, detritus and gelbstoff absorption, particle backscattering, total absorption, and total backscattering [m-1]), bottom albedo (reflectance at 550 nm), and water depth (depth [m]) using a semi-analytical inversion model (Goodman and Ustin 2007; Lee et al. 1999, 1998).

Note that this algorithm uses a computationally intensive optimization scheme, which can result in long processing times for large areas. As a reference, the example shown here required approximately 15 minutes to generate output. It is suggested that users select relatively small regions-of-interest when implementing this algorithm.

Inputs – User specified HICO scene, with optional region-of-interest; optional NDWI land/water mask, with user adjustable NDWI threshold; and specification of desired output parameter.

HICO IPS Shark Bay subset

Output – Selected output parameter depicted using a blue-red color ramp, where blue represents low values and red represents high values. If the NDWI land/water mask was selected, then the selected optical property is only calculated and mapped for the water pixels.

HICO IPS Shark Bay aquacor

Try it out today for yourself: http://hyspeedgeo.com/HICO/

 

Related posts

Introducing the HICO Image Processing System

Calculating a land/water mask using HICO IPS

Deriving chlorophyll concentration using HICO IPS

Evaluating water optical properties using HICO IPS

 

References

Goodman J, Ustin SL (2007) Classification of benthic composition in a coral reef environment using spectral unmixing, Journal of Applied Remote Sensing, vol. 1(1), 011501-011501.

Lee Z, Carder KL, Mobley CD, Steward RG, Patch JS (1999) Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization, Applied Optics, vol. 38(18), 3831-3843.

Lee Z, Carder KL, Mobley CD, Steward RG, Patch JS (1998) Hyperspectral remote sensing for shallow waters. I. A semianalytical model, Applied Optics, vol. 37(27), 6329-6338.

Remote Sensing in the Cloud – Evaluating water optical properties using HICO IPS

This is part of an ongoing series dedicated to reviewing the algorithms currently implemented in the cloud-based HICO Image Processing System (HICO IPS). Links to additional posts in this series describing the other algorithms are provided below. Here we provide an overview of the algorithm utilized for evaluating water optical properties in coastal and oceanic water.

HICO IPS

Objective – Retrieve water optical properties for coastal and oceanic water from hyperspectral imagery using a generalized multi-band algorithm.

Algorithm – Estimate water optical properties for absorption and backscattering (specifically, total absorption, phytoplankton absorption, detritus and gelbstoff absorption, total backscattering, and particle backscattering) using the Quasi-Analytical Algorithm (QAA v5; Lee et al. 2009, 2002).

Inputs – User specified HICO scene, with optional region-of-interest; optional NDWI land/water mask, with user adjustable NDWI threshold; and specification of desired optical property.

HICO IPS Turkish Straits

Output – Selected water optical property at 438 nm (m-1) depicted using a blue-red color ramp where blue represents low values and red represents high values. If the NDWI land/water mask was selected, then the selected optical property is only calculated and mapped for the water pixels.

HICO IPS Turkish Straits QAA

Try it out today for yourself: http://hyspeedgeo.com/HICO/

 

Related posts

Introducing the HICO Image Processing System

Calculating a land/water mask using HICO IPS

Deriving chlorophyll concentration using HICO IPS

Characterizing shallow coastal environments using HICO IPS

 

References

Lee Z, Lubac B, Werdell J, Arnone R (2009) An update of the quasi-analytical algorithm (QAA_v5), International Ocean Color Group Software Report, 9 pp.

Lee Z, Carder KL, Arnone RA (2002) Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters, Applied optics, vol. 41(27), 5755-5772.

Constellations, Clouds & the Conundrum of Big Data Processing

HySpeed Computing is proud to be featured in the inaugural issue of UPWARD, the quarterly magazine of the ISS National Lab.

UPWARD

Constellations, Clouds & the Conundrum of Big Data Processing

“For millennia, humans have looked up to the sky to find constellations of stars, wondering what mysteries they hold. Today, we live in a world where constellations of satellites look down on us, hoping to unravel mysteries as well – by capturing highly complex images of Earth.

“In the commercial remote sensing market, the imaging of Earth from space has experienced a technical tsunami, giving rise to a population explosion of smaller but far more capable satellites with new sensing and communication capabilities. In the near future, constellations of nano-, micro-, and other small-sats will swarm low Earth orbit like drones filling the skies on Earth.”

See the full article beginning on page 10…

Conundrum of Big Data Processing

Remote Sensing in the Cloud – Deriving chlorophyll concentration using HICO IPS

Continuing our review of the algorithms currently implemented in the cloud-based HICO Image Processing System (HICO IPS), here we provide an overview of the two algorithms utilized for deriving estimates of chlorophyll concentration in oceanic water.

HICO IPS

Objective – Implement multiple algorithms for estimating chlorophyll concentration, as well as a methodology for evaluating the difference between these algorithms.

Algorithms – Derive estimates of surface chlorophyll-a concentration using one of two ocean color algorithms, OC4 (O’Reilly et al. 2000) or OCI (Hu et al. 2012); or for comparison, the difference between these two algorithms (OC4 – OCI). These algorithms first perform spectral resampling of the HICO hyperspectral data to the multispectral SeaWiFS bands on which the algorithms are based.

Inputs – User specified HICO scene, with optional region-of-interest; optional NDWI land/water mask, with user adjustable NDWI threshold; and specification of desired chlorophyll algorithm.

HICO IPS Chesapeake Bay

Output – Surface chlorophyll-a concentration (mg/m^3) depicted using a blue-red color ramp where blue represents low chlorophyll concentration and red represents high concentration. If the NDWI land/water mask was selected, then chlorophyll concentrations are only calculated and mapped for the water pixels (as is logical).

HICO IPS Chesapeake Bay Chlorophyll

Try it out today for yourself: http://hyspeedgeo.com/HICO/

 

Related posts

Introducing the HICO Image Processing System

Calculating a land/water mask using HICO IPS

Evaluating water optical properties using HICO IPS

Characterizing shallow coastal environments using HICO IPS

 

References

Hu C, Lee Z, Franz BA (2012) Chlorophyll-a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference, Journal of Geophysical Research, vol. 117(C1), 25 pp.

O’Reilly JE, Maritorena S, O’Brien MC, et al. (2000) SeaWiFS postlaunch calibration and validation analyses, Part 3, NASA Technical Memorandum 2000-206892, vol. 11, 49 pp.

Remote Sensing in the Cloud – Calculating a land/water mask using HICO IPS

Last year we launched the HICO Image Processing System (HICO IPS) – a prototype web application for on-demand remote sensing data analysis in the cloud.

HICO IPS

To demonstrate the capabilities of this system, we implemented a collection of coastal remote sensing algorithms to produce information on water quality, water depth and benthic features using example imagery from the HICO instrument on the International Space Station.

As the HICO IPS approaches its one year anniversary, and continues its excellent performance, we’d like to take a moment to highlight each of the algorithms currently implemented in the system.

Here we begin with an overview of the land/water mask utilized in the HICO IPS.

Objective – Implement an automated algorithm for classifying land versus water, thereby masking land pixels from further analysis and allowing subsequent processing steps to focus on just water pixels.

Algorithm – Generates a binary mask differentiating land from water using the Normalized Difference Water Index (NDWI; McFeeters 1996). This algorithm can be implemented on its own, or as a pre-processing step in other algorithm workflows.

Inputs – User specified HICO scene, with optional region-of-interest; and user adjustable NDWI threshold, where -1.0 ≤ NDWI ≤ 1.0, land ≤ threshold < water, and default threshold = 0.0.

HICO IPS Christchurch

Output – Binary land/water mask (0 = land; 1 = water), where land is displayed in the online map using a black mask and water remains unchanged.

HICO IPS Christchurch mask

Reference – McFeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, International Journal of Remote Sensing, vol. 17(7), 1425-1432.

Try it out today for yourself: http://hyspeedgeo.com/HICO/

 

Related posts

Introducing the HICO Image Processing System

Deriving chlorophyll concentration using HICO IPS

Evaluating water optical properties using HICO IPS

Characterizing shallow coastal environments using HICO IPS

2015 ISS R&D Conference – Evolution or Revolution

The 2015 International Space Station Research & Development Conference (ISS R&D) took place recently in Boston, MA from July 7-9.

It was an amazing week of insights and information on the innovations and discoveries taking place on board the ISS, as well as glimpses of the achievements yet to come.

2015 ISS R&D

A highlight of the first day was a conversation with Elon Musk, who mused on his initial commercial forays into space, the state of his transformative company SpaceX, and a view of his vision for the future of space travel, research and exploration.

Core topics discussed at ISS R&D 2015 included everything from biology and human health, to materials development and plant science, to remote sensing and Earth observation, to space travel and human exploration. Here are a few of the top highlights:

  • NASA and its partner agencies have transitioned from assembling an amazingly complex vehicle in space to now utilizing this vehicle for the benefit of humanity.
  • The feat of building and maintaining the International Space Station is often underrated and overlooked, but it’s an incredible achievement, and everyone is encouraged to explore the marvels of what has been, and continues to be, accomplished.
  • We are advancing to a future where space transport will become commonplace, and it is the science, humanitarian, exploration and business opportunities that will be the new focus of ISS utilization.
  • The ISS is an entrepreneur engine, as evidenced in part by the rise of the new space economy. For example, new markets are emerging in the remote sensing domain, with NanoRacks, Teledyne Brown Engineering and Urthecast all making investments in expanding Earth observation from the ISS.
  • The future of the ISS, and its continued operation, is a direct function of the success or failure of what is happening on the ISS right now. The greater the success, the brighter the future.

Throughout the week a question was often asked whether the ISS is evolutionary or revolutionary… and in the end the answer was both!

Interested in learning more about the ISS? Visit the recently launched website  spacestationresearch.com to “explore the new era of science in space for life on Earth”.

Also, save the data for next year’s conference, which is taking place July 12-14, 2016 in San Diego, California. See you there!

“Space is now closer than you think.”

Astronaut Photography – Your access to stunning views from space

Astronauts have busy schedules in space – system operations, maintenance, repairs, science experiments – but did you know they also acquire hundreds of photos during each mission?

Reid Wiseman , Astronaut Photography

From stunning views of Earth’s natural features to glimpses of your favorite city at night, and from pure artistry to applied science, these photos offer a remarkable perspective of our planet’s surface as well as a valuable historical record of how and where our planet is changing.

There are now two great resources available for viewing this photography:

Both websites provide access to thousands of photos, are free to use, allow users to search photos or browse by category, and even provide options to download images for your own use (but be sure to read through the conditions of use on both websites).

We’ve spent countless hours browsing through these stunning image collections, and encourage you to take a look for yourself.

We hope you enjoy!

Gateway to Astronaut Photography of Earth

“The Gateway to Astronaut Photography of Earth hosts the best and most complete online collection of astronaut photographs of the Earth from 1961 through the present. This service is provided by the International Space Station program and the JSC Earth Science & Remote Sensing Unit, ARES Division, Exploration Integration Science Directorate.” – http://eol.jsc.nasa.gov/

Windows on Earth

“Windows on Earth is an educational project that features photographs taken by astronauts on the International Space Station.  Astronauts take hundreds of photos each day, for science research, education and public outreach.  The photos are often dramatic, and help us all appreciate home planet Earth. The site is operated by TERC, an educational non-profit, in collaboration with the Association of Space Explorers (the professional association of flown astronauts and cosmonauts), the Virtual High School, and CASIS (Center for Advancement of Science in Space).” – http://www.windowsonearth.org/

Windows on Earth featured