- Author: Kathy Keatley Garvey
He delivered his virtual presentation in three parts: Parts 1-3 and Final Thoughts. They are now available on his website (http://chrnansen.wix.com/nansen2) as YouTube videos.
"I argue that, in the near future, we as university professors may have to look beyond publication of results in a research article--that students and society will likely demand more from us," Nansen said. "We can embrace and integrate technologies into what we do to create educational platforms, which include exposure to technologies and therefore enable students to acquire highly 'marketable' career skill sets. We can integrate discussions about entrepreneurship into our research and education--demonstrate to funding bodies, colleagues, and students that we take development and adoption of science-driven solutions seriously."
In his three-part lecture, Nansen provides examples of his research and approaches to university education.
"The lecture," he explains, "describes three elements in my program: optical sensing to diagnose insects, smartphone app development, and use of insect mass-rearing to biodegrade waste streams. Applied research, technology, innovation, and entrepreneurship are the denominators tying these three elements together."
In addition to insect ecology and remote sensing, Nansen's research interests include integrated pest management, host plant stress detection, host selection by arthropods, pesticide performance, and use of reflectance-based imaging in a wide range of research applications.
The three-part lecture:
- Introduction
- Part One: Optical or Remote Sensing
- Part Two: Smartphone App Development and Pesticide Sprays
- Part Three: Breeding of Insects to Bioconverte Waste
- Final Thoughts
Born and educated in Denmark, Nansen received his master's degree in biology from the University of Copenhagen in 1995 and his doctorate in zoology from the Royal Veterinary and Agricultural University in Denmark in 2000. He accepted positions in Portugal, Benin, United States, UK and Australia before joining the UC Davis Department of Entomology and Nematology in 2015 as an assistant professor. His international experience also includes being an international exchange student at the University of Lisbon, Portugal and a visiting professor at Northwest A&F University, Yangling, China.
- Author: Kathy Keatley Garvey
Nansen, associate professor in the Department of Entomology and Nematology, is serving as the guest editor of the issue "Remote Sensing to Detect and Diagnose Organismal Responses." The journal (impact factor 4.118) is a leading outlet for research articles and reviews on all aspects related to remote sensing.
"I'm inviting authors to submit studies that go beyond the detection of an optical reflectance response and tie a thorough analysis of remote sensing data to other types of data (physiological, molecular, genetic, biochemical)," Nansen said. "In other words, the special issue will embrace a phenomics approach, in which the overall goal is to, at least partially, explain why and how organisms exhibit an optical reflectance response to stressors and/or treatments."
As the guest editor, Nansen said he is seeking articles describing "exciting applications of remote sensing technologies to detect and diagnose differences and/or stress across all kingdoms."
Contributions are due by March 2020. For more information, visit https://www.mdpi.com/journal/remotesensing/special_issues/rs4organismal_response.
Nansen may be reached at chrnansen@ucdavis.edu.
- Author: Lynn Wunderlich
Agriculture today faces a huge challenge in labor shortages. Only recently have foothill growers been looking at investing in mechanical tools to help them get the work done. Last month I held a field day in collaboration with Patrick Tokar, viticulturalist for Rombauer, the same Napa Valley Rombauer that recently acquired the old Renwood winery and tasting room in Amador county. (I have a friend who only drinks Rombauer chardonnay-a classic buttery chard that's been
Rombauer's foothill operation, they've been growing Zinfandel in El Dorado county since about 2007, recently acquired a Pellenc "suck and pluck" style of leafer-a machine
In addition to leafing, Rombauer has been using remote sensing and aerial imaging to help them make decisions on the farm. I invited UCDavis Biological and Agricultural Engineering Specialist Ali Pourezza to explain the fundamentals of remote sensing. Ali is a recent addition to our ANR Specialist group and is a whiz in creating models of virtural orchards and vineyards and using sensing technology to solve agricultural problems (check out his video of our field day on Ali's twitter!).
Ali explained to the group that light behaves in 4 different ways when it interacts with plants: it is reflected (which is easy to measure), absorbed (which can be calculated based on reflection), scattered or transmitted. When using remote sensing, a multi-spectral camera is mounted on either a UAV or a plane, and images taken which give information dependent on the spectral resolution (or band width) of the camera. Models are developed to interpret this information, and, (this is super important), calibrated with accurate ground truth data. The calibration is also critical, and needs to include a "radiometric" calibration-that is, a calibration with the sun's position during the time of imaging (which won't be the same on any given 2 days).
NDVI (normalized digital vegetation index), is the most common and uses near-infrared to red light wavelengths in a scale to tell if green (healthy) vegetation is present or not. Ali said that NDVI values below 0.1 indicate no vegetation, 0.2-0.5 indicate sparse vegetation, and 0.6-0.9 indicate healthy vegetation. Other, more advanced indices use other spectral bands, such as NDRE or "red edge". Ali has been doing some research on using hyper-spectral (thousands of bands!) imaging to detect N2 (nitrogen) deficiency in vineyards. Working with Viticulture Specialist Matthew Fidelibus, who ground-truths the sensing data by taking vine petioles for nutritional analysis, Ali is developing a model to predict
Rombauer is using Ceres Imaging to do their sensing and Jenna Rodriguez (one of our own UCDavis grads now working for Ceres) also spoke at my field day. After Ali's technical "nuts and bolts" talk, Jenna explained how her company uses remote sensing and modeling to interpret the images provided to clients such as Rombauer. For example, a blue line on a thermal imaging map was interpreted to be a leaky irrigation pipe. Low chlorophyll in one area of the vineyard could possibly be soil related.
The tools of precision agriculture and remote sensing can save labor and help pinpoint the need for applications such as fertilizer. Yet, there's no replacement for "keeping one foot in the furrow", as the late J.C. Walker of UW-Madison, my alma matter, used to say. Until next time...
- Author: Ben Faber
NASA's Maps of Global Soil Conditions
Are the
Future of Farming
Find water anywhere.
By Mary von Aue
The US Department of Agriculture (USDA) is now using data collected from the first NASA satellite mission dedicated to measuring the water content of soils. These maps created by the space agency will be used to monitor global croplands, make commodity forecasts, and will help the USDA forecast crops globally.
The Soil Moisture Active Passive mission, or SMAP, launched in 2015 in order to map the amount of water in soils worldwide. On Friday, NASA announced that the agency is providing the mission with new tools developed by NASA's Goddard Space Flight Center that will better predict where there could be too much or too little moisture in the soil to sustain farming.
“There's a lot of need for understanding, monitoring and forecasting crops globally,” said John Bolten, a research scientist at Goddard. “SMAP is NASA's first satellite mission devoted to soil moisture, and this is a very straightforward approach to applying that data.” NASA presents the satellite data in maps that are rendered to resemble watercolor paintings. Soils that are wetter than normal are seen in shades of greens, while those that are drier than normal are seen in shades of browns.
Before this collaboration, the USDA had used computer models that would incorporate precipitation and temperature observations to indirectly calculate soil moisture. However, this approach was prone to error in areas that lacked high-quality, ground-based instrumentation to collect the data. Now, NASA is incorporating direct SMAP data on soil moisture into Crop Explorer, the USDA's Foreign Agricultural Service website that reports on regional droughts, floods, and crop forecasts.
The SMAP viewer is still in beta but is expected to provide updated global coverage every three days once it launches. The maps will be managed for NASA's Jet Propulsion Laboratory and will provide Crop Explorer with timely updates that are essential for monitoring conditions and forecasting productivity.
This cross-agency collaboration will do more than help the USDA identify farming trends. By monitoring moisture in the soil globally, scientists can more accurately forecast conditions that could have tremendous economic and social impact.
https://www.inverse.com/amp/article/45498-nasa-maps-of-global-soil-conditions-future-of-farming
Map created with NASA's SMAP data from May 16-18, 2018
/h2>/h1>/h1>/h1>- Author: Bryon J. Noel
I’ve been away from the blog for awhile, but thought I’d catch up a bit. I am in beautiful Madison Wisconsin (Lake Mendota! 90 degrees! Rain! Fried cheese curds!) for the NASA LP DAAC User Working Group meeting. This is a cool deal where imagery and product users meet with NASA team leaders to review products and tools. Since this UWG process is new to me, I am highlighting some of the key fun things I learned.
What is a DAAC?
A DAAC is a Distributed Active Archive Center, run by NASA Earth Observing System Data and Information System (EOSDIS). These are discipline-specific facilities located throughout the United States. These institutions are custodians of EOS mission data and ensure that data will be easily accessible to users. Each of the 12 EOSDIS DAACs process, archive, document, and distribute data from NASA's past and current Earth-observing satellites and field measurement programs. For example, if you want to know about snow and ice data, visit the National Snow and Ice Data Center (NSIDC) DAAC. Want to know about social and population data? Visit the Socioeconomic Data and Applications Data Center (SEDAC). These centers of excellence are our taxpayer money at work collecting, storing, and sharing earth systems data that are critical to science, sustainability, economy, and well-being.
What is the LP DAAC?
The Land Processes Distributed Active Archive Center (LP DAAC) is one of several discipline-specific data centers within the NASA Earth Observing System Data and Information System (EOSDIS). The LP DAAC is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. LP DAAC promotes interdisciplinary study and understanding of terrestrial phenomena by providing data for mapping, modeling, and monitoring land-surface patterns and processes. To meet this mission, the LP DAAC ingests, processes, distributes, documents, and archives data from land-related sensors and provides the science support, user assistance, and outreach required to foster the understanding and use of these data within the land remote sensing community.
Why am I here?
Each NASA DAAC has established a User Working Group (UWG). There are 18 people on the LP DAAC committee, 12 members from the land remote sensing community at large, like me! Some cool stuff going on. Such as...
New Sensors
Two upcoming launches are super interesting and important to what we are working on. First, GEDI (Global Ecosystem Dynamics Investigation) will produce the first high resolution laser ranging observations of the 3D structure of the Earth. Second, ECOSTRESS (The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station), will measure the temperature of plants: stressed plants get warmer than plants with sufficient water. ECOSTRESS will use a multispectral thermal infrared radiometer to measure surface temperature. The radiometer will acquire the most detailed temperature images of the surface ever acquired from space and will be able to measure the temperature of an individual farmer's field. Both of these sensors will be deployed on the International Space Station, so data will be in swaths, not continuous global coverage. Also, we got an update from USGS on the USGS/NASA plan for the development and deployment of Landsat 10. Landsat 9 comes 2020, Landsat 10 comes ~2027.
Other Data Projects
We heard from other data providers, and of course we heard from NEON! Remember I posted a series of blogs about the excellent NEON open remote sensing workshop I attended last year. NEON also hosts a ton of important ecological data, and has been thinking through the issues associated with cloud hosting. Tristin Goulden was here to give an overview.
Tools Cafe
NASA staff gave us a series of demos on their WebGIS services; AppEEARS; and their data website. Their webGIS site uses ArcGIS Enterprise, and serves web image services, web coverage services and web mapping services from the LP DAAC collection. This might provide some key help for us in IGIS and our REC ArcGIS online toolkits. AppEEARS us their way of providing bundles of LP DAAC data to scientists. It is a data extraction and exploration tool. Their LP DAAC data website redesign (website coming soon), which was necessitated by the requirement for a permanent DOI for each data product.
User Engagement
LP DAAC is going full-force in user engagement: they do workshops, collect user testimonials, write great short pieces on “data in action”, work with the press, and generally get the story out about how NASA LP DAAC data is used to do good work. This is a pretty great legacy and they are committed to keep developing it. Lyndsey Harriman highlighted their excellent work here.
Grand Challenges for remote sensing
Some thoughts about our Grand Challenges: 1) Scaling: From drones to satellites. It occurs to me that an integration between the ground-to-airborne data that NEON provides and the satellite data that NASA provides had better happen soon; 2) Data Fusion/Data Assimilation/Data Synthesis, whatever you want to call it. Discovery through datasets meeting for the first time; 3) Training: new users and consumers of geospatial data and remote sensing will need to be trained; 4) Remote Sensible: Making remote sensing data work for society.
A primer on cloud computing
We spent some time on cloud computing. It has been said that cloud computing is just putting your stuff on “someone else’s computer”, but it is also making your stuff “someone else’s problem”, because cloud handles all the painful aspects of serving data: power requirements, buying servers, speccing floor space for your servers, etc. Plus, there are many advantages of cloud computing. Including: Elasticity. Elastic in computing and storage: you can scale up, or scale down or scale sideways. Elastic in terms of money: You pay for only what you use. Speed. Commercial clouds CPUs are faster than ours, and you can use as many as you want. Near real time processing, massive processing, compute intensive analysis, deep learning. Size. You can customize this; you can be fast and expensive or slow and cheap. You use as much as you need. Short-term storage of large interim results or long-term storage of data that you might use one day.
Image courtesy of Chris Lynnes
We can use the cloud as infrastructure, for sharing data and results, and as software (e.g. ArcGIS Online, Google Earth Engine). Above is a cool graphic showing one vision of the cloud as a scaled and optimized workflow that takes advantage of the cloud: from pre-processing, to analytics-optimized data store, to analysis, to visualization. Why this is a better vision: some massive processing engines, such as SPARC or others, require that data be organized in a particular way (e.g. Google Big Table, Parquet, or DataCube). This means we can really crank on processing, especially with giant raster stacks. And at each step in the workflow, end-users (be they machines or people) can interact with the data. Those are the green boxes in the figure above. Super fun discussion, leading to importance of training, and how to do this best. Tristan also mentioned Cyverse, a new NSF project, which they are testing out for their workshops.
Image attribution: Corey Coyle
Super fun couple of days. Plus: Wisconsin is green. And warm. And Lake Mendota is lovely. We were hosted at the University of Wisconsin by Mutlu Ozdogan. The campus is gorgeous! On the banks of Lake Mendota (image attribution: Corey Coyle), the 933-acre (378 ha) main campus is verdant and hilly, with tons of gorgeous 19th-century stone buildings, as well as modern ones. UW was founded when Wisconsin achieved statehood in 1848, UW–Madison is the flagship campus of the UW System. It was the first public university established in Wisconsin and remains the oldest and largest public university in the state. It became a land-grant institution in 1866. UW hosts nearly 45K undergrad and graduate students. It is big! It has a med school and a law school on campus. We were hosted in the UW red-brick Romanesque-style Science Building (opened in 1887). Not only is it the host building for the geography department, it also has the distinction of being the first buildings in the country to be constructed of all masonry and metal materials (wood was used only in window and door frames and for some floors), and may be the only one still extant. How about that! Bye Wisconsin!