Say "Hello, world!" with Google Earth Engine

See what I did there? For those of you who may not have taken a programming course before, you might not be familiar with “hello, world” – it’s the first program that essentially all coders learn how to write. It’s also how I felt while attending the Google Earth Engine User Summit at Google Headquarters in Mountain View, CA, after discovering that the world (in the form of satellite imagery) is at my fingertips!

Engineers, scientists, researchers, and practitioners from all over the globe congregated in Mountain View, CA, for the 2016 Google Earth Engine User Summit.

Access to satellite data has historically been limited due to the tremendous computational power needed for data download and processing. But the tide is turning. For the past few years, the Google Earth team has been uploading massive amounts of satellite data to the cloud. Google engineers created an online platform, called Google Earth Engine, to give researchers, engineers, geographers, and earth scientists a way to work with these cloud-based data.

Check out this video on "A Planetary Perspective: With Landsat and Google Earth Engine" for a visual overview of Google Earth Engine.

 

Making sense of satellite data

In addition to providing quick and easy access to decades of satellite data, the Google Earth Engine platform includes a suite of tools for data processing. In this case, “processing” means “writing simple code” for the purpose of extracting useful information from the historical record of satellite images. In true Google fashion, the tools are openly available to non-commercial users.

Just a few lines of code in the Earth Engine platform allows users to calculate the "Normalized Difference Vegetation Index" (NDVI), which serves as a measure of vegetation "greenness." Above, NDVI across Florida for January-March, 2016. 

Case studies: from Antarctic sea ice to cropland

Researchers and practitioners are using Google Earth Engine to address a wide variety of important issues. For example, researchers at the European Commission Joint Research Centre are using Google Earth Engine for large-scale crop monitoring to identify fallow land and farms with failed crops. These observations can be coupled with on-the-ground measurements to evaluate the efficacy of management practices, such as those related to irrigation. Imagine the possibilities! 

Guido Lemoine, European Commission’s JRC, speaking on how #GIS can help w #foodsecurity analysis #EEUS #copernicus pic.twitter.com/cPfT9J6h0D

— GoogleEarth Outreach (@earthoutreach) June 14, 2016

Beyond big data

The User Summit not only afforded me the opportunity to learn about the utility and potential of Google Earth Engine, but also gave me a glimpse into the future of satellite image collection. Luc Vincent, Director of Google Geo Imagery, discussed Google's “Terra Bella” division, which designs and manufactures low-cost satellites. Google will be sending enough of these cost-efficient satellites to capture global snapshots 2-3 times per day! At the moment, attaining global coverage with satellite imagery takes approximately 16 days, making Google's vision for satellite data collection particularly impressive (a 3200% improvement in temporal resolution!).

ICYMI: Here's a quick look at our new episode about @terra_bella's small imaging satellites https://t.co/wDDpNZD4Lj pic.twitter.com/8l8vNzSERe

— Nat and Lo (@NatAndLo) April 14, 2016

So you want to learn more about Earth Engine? Here are some resources:

• Google Earth Engine documentation, tutorials, and videos
• Alice Alonso, PhD Candidate in the Agricultural and Biological Engineering Department at UF, recently had an article accepted for publication in Transactions of ASABE that highlights the potential of Google Earth Engine as a tool for Agricultural and Biological Engineers. It's currently in press, but will be published soon! 
• Alonso, A., R. Muñoz-Carpena, K. Robert and C. Murcia. 2016. Wetland landscape spatio-temporal degradation dynamics using the new Google Earth Engine cloud-based platform: opportunities for non-specialists in remote sensing. Trans. ASABE
• In partnership with Science, an educational lab assignment based in Google Earth Engine was created, which also makes for a fun and easy introduction to the platform.
• There are also a lot of web apps that use Google Earth Engine to highlight specific issues, such as deforestation, climate, wildlife conservation, and more!

If you're interested in learning more about Google Earth Engine or the User Summit, reach out to me by email or on Twitter. Until next time!

Whether using reclaimed or potable, overwatering in the landscape is easily preventable

By Bernard Cardenas

Some homeowners with automatic irrigation systems are over-watering their lawns in Florida without even knowing it. To cope with this issue, researchers at UF have been testing different soil moisture sensors, a promising technology that can potentially reduce waste of irrigation water.

Examples of widely available soil moisture sensor devices

Purple Pipes Among Us

In Florida, an important number of homes use reclaimed water to irrigate their landscape. Using soil moisture sensors in this context could present a problem because reclaimed water may contain more salts than potable water, and these salts could alter sensor readings when measuring the soil water content.

Therefore, irrigation specialists evaluated the functionality of four soil moisture sensor brands under both reclaimed and potable water, and quantified their potential irrigation savings. They also analyzed the consistency of each brand to control irrigation and, finally, they compared the brands to see if all of them were effective, or not.

Research Mode

The study was carried out in Gainesville in turfgrass plots irrigated with potable water and reclaimed water (2009 and 2010 respectively). Four soil moisture sensor brands were tested and were compared to a treatment that had no sensor feedback, which is the most common situation in Florida.

All the soil moisture sensors tested applied significantly less water than the comparison treatment (which had no sensor feedback). This was a consequence of the soil moisture sensors not allowing irrigation when soil was wet enough.  

The water savings ranged from 46% to 78% under potable water, and from 45% to 68% under reclaimed water. This means that the tested soil moisture sensors could be used under reclaimed or potable water conditions. Even more promising: these important water savings were obtained during a mostly dry period.

Also important to mention is that these water savings were attained without compromising the turf quality, which always rated good or higher, during the 2 year study.

The Bottom Line

From these results, which are comparable to those achieved in other similar experiments, it is clear that soil moisture sensors can be a useful tool for conserving water on turfgrass irrigated with either potable or reclaimed water.

(Adapted from a recently published research article available here.)