representative images

Author: Monja Sebela

sentinel-2/cyanobacteria_chla_ndci_l1c/README.md

@@ -72,6 +72,15 @@ Table 1: Predictive capability of calibrated NDCI model
 |----------|----------|--------------|----------|-------------------|
 | 0.0023   | 42.3     | 84.2         | 0.99     | 95.8              |
 
+## Representative Images
+
+Cyanobacteria Chlorophyll-a NDCI L1C applied to lagoons of Northeastern Italy. Image acquired on 2022-02-12.
+
+![Cyanobacteria chlorophyll-a Italy2](fig/fig1.jpg)
+
+Cyanobacteria Chlorophyll-a NDCI L1C applied to Roper river, Australia. Image acquired on 2019-02-23.
+
+![Cyanobacteria chlorophyll-a Italy1](fig/fig2.jpg)
 
 ## Citation
 If making use of this algorithm, please cite as follows: 

sentinel-2/cyanobacteria_chla_ndci_l1c/figures/calibration.png renamed to sentinel-2/cyanobacteria_chla_ndci_l1c/fig/calibration.png

@@ -26,6 +26,18 @@ or MODIS.
 Uses the [water bodies mapping](https://github.com/sentinel-hub/custom-scripts/tree/master/sentinel-2/water_bodies_mapping-wbm) 
 technique of Mohor Gartner. It visualises land using a simple RGB approach. 
 
+## Representative Images
+
+Bloom Index applied to Tevere river, Italy. Image acquired on 2017-10-08.
+
+![Maximum Peak Height Bloom Index Italy2](fig/fig1.jpg)
+
+Bloom Index applied to Syvash lagoon, Ukraine. Image acquired on 2022-02-15.
+
+![Maximum Peak Height Bloom Index Italy1](fig/fig2.jpg)
+
+## Credits
+
 Credit CyanoLakes, Jeremy Kravitz, Mark Matthews.
 
 ## References