Observing Flooding Extent in South Florida from ‘Super Camera’ 700km above the Earth
Author: Boya Zhang
Looking at the title, you must be thinking I am crazy. And you will confirm that I am crazy, if I tell you this will be part of my PhD dissertation. You may also be wondering what is ‘super camera’? Why it is flying or floating in the 700 km in the outer space? Even if it exists, why and how to use this strange thing to observe South Florida flooding? Let me solve the puzzle.
The ‘super camera’ is not like a Canon digital camera. Indeed, it is a radar, which is short for ‘radio detection and ranging’. Simply speaking, one of the basic tasks of radar is to detect the signal and measure the distance. But, detect what signal, and measure the distance of what? My research uses a special type of radar, and it has a very unfriendly name- ‘Synthetic Aperture Radar’ or SAR. (Let’s skip the meaning of the first two words of the name, because it may take another article to explain!) SAR is able to actively transmit microwave signal towards the Earth surface. Indeed, the signal wavelength is very similar to the microwave oven at your home, but don’t worry, it will not cook the Earth like eggs, or heat anybody walking on the streets. The transmitted microwave is able to reach the Earth surface, interacts with objects on the ground and bounces back towards SAR (It sounds crazy, but believes me, it is true…). Therefore, the answers to the first question is that SAR detects the signal it transmits by itself. And the answer to the second question is: it measures the distance between itself and Earth surface.
You may be thinking that SAR is similar with other optical sensors like the popular Landsat. Indeed, SAR has both advantages and disadvantages when compared with the optical sensors. One of the advantages is that SAR also works during the night! It is simply because it transmits signal by itself, unlike the optical sensors, which rely on the sun light. Another advantage is that microwave is generally able to penetrate atmosphere, especially clouds. When the cloud is dense, the sight of optical sensors can be completely blocked. Especially, when there is heavy rainfall, the optical sensors can hardly take ground information. The disadvantage of SAR is that, it requires more complicated data processing.
Now, we know SAR is able to remotely sense the ground, and it is able to work regardless of illumination or clouds, but how does it observe the flood on the surface? Remember that previously, it is said SAR signal interacts with objects on the ground. The flood observation is associated with the interaction. But before we dig into the concepts, let’s take a look at some SAR images of South Florida, taken from a satellite called Sentinel-1, launched by European Space Agency.
|Fig 1.1: Aug 29th|
|Fig 1.2: Sept 10th|
Figure 1. Sentinel-1 SAR intensity image acquired in South Florida on Aug 29th (left) and Sep 10th (right), 2017 respectively
Just by looking at both figures, you can immediately tell that the left one is much brighter than the right one. Wait a minute, what does this brightness and darkness mean? The brightness means there is more energy bounced back to SAR, whereas the darkness means a lot of energy bounces away from SAR. Why the two images, only 12 days apart, have such a large difference? Do you remember where you were on Sep 10th, 2017? I remember it so clearly, because it was only 3 weeks after I moved to Miami and had just started my PhD program (with full excitement!). Hurricane Irma landed in Florida on that very day, Sep 10th, 2017! My wife and I had to escape to Orlando with ‘fear’ that Irma will catch up us on the highway. Now, it is so clear that the difference between the two images is attributed to flooding! I guess tons of rain fell in the Everglades and changed everything. But you may want to ask a deeper question: why did flooding make the image darker? Let’s take a look at Figure 2 below:
Figure 2 The interaction between the SAR signal and ground surface.
Fig 2.1 shows when SAR signal interacts with rough surface, it scatters and SAR is able to receive the portion of scattering back towards it. Fig 2.2 one shows when the surface is flooded, the water surface is like a mirror and the signal single-bounces away from the SAR. It actually explains the darkness of the Figure 1 Sep acquisition. Fig 3.3 shows, at the presence of a tree, the signal experiences double-bounce, at the water surface and then on the tree trunk, which makes high energy signal to bounce back to the satellite. It explains the bright part of the same figure, which is located at west and east parts. Indeed, this part can have higher intensity than the left plot of Figure 1. It does not look that bright, because of the stretch of pixel brightness for visualization effect. At last, I will show you two more figures.
Figure 3.1 Land Cover distribution in South Florida. Fig 3.2: Flooding detection result. Red patches mean higher SAR signal intensity during flooding comparing with the unflooded situation, whereas the blue patches mean lower intensity. Both red and blue patches are detected with flooding.
These two figures are from one of my publications (Zhang et al. 2018). It is interesting to see that the marshes are corresponding to the blue patches on the right figure, while mangroves in southwest, other woody vegetation in northwest, and urban areas in the east match with red patches. It is perfectly consistent with our model, that submerged marshes have single-bounce while flooded woody vegetation and urban areas have double-bounce effect (building plays the same role as tree trunk). In this way, we finally explain how we observe flooding extent in South Florida from ‘Super Camera’ 700km above! If you look at the Figure 3, there is a legend, which provides a range of an index, which is used to tell us whether there is flooding or not. The detail of this index is written in my paper ‘Mapping the Extent and Magnitude of Severe Flooding Induced by Hurricane Irma with Multi-Temporal Sentinel-1 SAR and InSAR Observations.’ This also includes zoom-in views of the three yellow frames. Feel free to contact me if you are interested and have more questions! My next blog will show what else SAR can bring to us and benefit our society!
Contact: Boya Zhang (Paul), PhD student in Florida International University, Earth and Environment Department. Email Address: firstname.lastname@example.org