Biophysical Remote Sensing and Continuous Scene Models
a project with a background image
I explored how in-situ measurements can be used to find correlations with remotely sensed satellite data. The purpose of this is to explore whether we can measure biophysical parameters using satellite imagery. If a statistical relationship is found, biophysical parameters can be modelled and estimated based solely on satellite data, eliminating the need for constant in-situ monitoring and dramatically reducing costs associated with these types of studies.
Using remote sensing to accurately measure biophysical parameters at a fine scale is incredibly complex and difficult. Most natural processes cannot be modelled with a simple linear equation, which is further proven by the low statistical relationships and inaccuracies of these results. More robust field sampling should be done along with using imagery at finer resolutions to more accurately measure local biophysical parameters at the scale that remote sensing offers.
You can also put regular text between your rows of images, even citations (Einstein & Taub, 1950). Say you wanted to write a bit about your project before you posted the rest of the images. You describe how you toiled, sweated, bled for your project, and then… you reveal its glory in the next row of images.
The code is simple. Just wrap your images with <div class="col-sm"> and place them inside <div class="row"> (read more about the Bootstrap Grid system). To make images responsive, add img-fluid class to each; for rounded corners and shadows use rounded and z-depth-1 classes. Here’s the code for the last row of images above:
<div class="row justify-content-sm-center">
<div class="col-sm-8 mt-3 mt-md-0">
{% include figure.liquid path="assets/img/6.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
<div class="col-sm-4 mt-3 mt-md-0">
{% include figure.liquid path="assets/img/11.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
</div>