Adding images and fixing links for multiple scripts

Author: MonjaSebela

sentinel-2/bais2/README.md

@@ -18,3 +18,9 @@ BAIS2 adapts the traditional BAI for Sentinel-2 bands, taking advantage of the w
 
 Values description: The range of values for the BAIS2 is -1 to 1 for burn scars, and 1 - 6 for active fires. Different fire intensities
 may result in different thresholds, the current values were calibrates, as per original author, on mostly Mediterranen regions.
+
+## Description of representative images
+
+Burned area index, Las Palmas de Grand Canaria. Acquired on 19.08.2019.
+
+![snow classifier](fig/fig1.png)

sentinel-2/bais2/fig/fig1.png

@@ -19,3 +19,9 @@ Cab (leaf cholrophyll content (μg / cm ^ 2)) corresponds to the content of chlo
 Note that the Cab script is as implemented in SNAP but without input and output validation!
 Input/output values which are suspect are not reported or changed. Most values, however, do not fall under this category.
 Visualized as an interval from 0-300. This can be adjusted in the evaluatePixel method.
+
+## Description of representative images
+
+Leaf chlorophyl index of Rome. Acquired on 8.10.2017.
+
+![CAB of Rome](fig/fig1.png)

sentinel-2/cab/README.md

@@ -37,6 +37,10 @@ The threshold for $\tau$ was chosen arbitrarily; a more educated guess would pro
 
 Try it on [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?lat=46.65120371539995&lng=13.809814453125&zoom=13&preset=CUSTOM&layers=B04,B03,B12&maxcc=50&time=2015-01-01%7C2017-06-06&evalscript=dmFyIGJSYXRpbyA9IChCMDIgLSAwLjE3NSkgLyAoMC4zOSAtIDAuMTc1KTsKdmFyIE5HRFIgPSAoQjAyIC0gQjAzKSAvIChCMDIgKyBCMDMpOwoKZnVuY3Rpb24gY2xpcChhKSB7CiAgcmV0dXJuIE1hdGgubWF4KDAsIE1hdGgubWluKDEsIGEpKTsKfQoKaWYgKEIxMT4wLjEgJiYgYlJhdGlvID4gMSkgeyAvL2Nsb3VkCiAgdmFyIHYgPSAwLjUqKGJSYXRpbyAtIDEpOwogIHJldHVybiBbMC41KmNsaXAoQjA0KSwgMC41KmNsaXAoQjAzKSwgMC41KmNsaXAoQjAyKSArIHZdOwp9CgppZiAoQjExID4gMC4xICYmIGJSYXRpbyA%2BIDAgJiYgTkdEUj4wKSB7IC8vY2xvdWQKICB2YXIgdiA9IDUgKiBNYXRoLnNxcnQoYlJhdGlvICogTkdEUik7CiAgcmV0dXJuIFswLjUgKiBjbGlwKEIwNCkgKyB2LCAwLjUgKiBjbGlwKEIwMyksIDAuNSAqIGNsaXAoQjAyKV07Cn0KCnJldHVybiBbMipCMDQsIDIqQjAzLCAyKkIwMl07){:target="_blank"} or download the script from [here](script.js){:target="_blank"}.   
 
+## Description of representative images
+
+Braaten-Cohen-Yang cloud detector, of Orbetello, Italy. Acquired on 6.10.2017.
+![Canopy chlorophyll index](fig/fig1.png)
 
 ## References
 - [1] Braaten J, Cohen WB, Yang Z. 2015. _Automated cloud and cloud shadow identification in Landsat MSS imagery for temperate ecosystems_. Remote Sensing of Environment. 169:128-138.

sentinel-2/cab/fig/fig1.png

@@ -19,3 +19,9 @@ CCC (Canopy Chlorophyll Content (μg / cm ^ 2)) is calculated here as the produc
 Note that the LAI and Cab scripts are as implemented in SNAP but without input and output validation!
 Input/output values which are suspect are not reported or changed. Most values, however, do not fall under this category.
 Visualized as an interval from 0-900. This can be adjusted in the evaluatePixel method.
+
+## Description of representative images
+
+Canopy chlorophyll index, Rome. Acquired on 8.10.2017.
+![Canopy chlorophyll index](fig/fig1.png)
+

sentinel-2/cby_cloud_detection/README.md

@@ -15,6 +15,12 @@
 
 The [False color](https://en.wikipedia.org/wiki/False_color) infrared product maps near-infrared spectral band B8 with red and green bands, B4 and B3, to [sRGB](https://en.wikipedia.org/wiki/SRGB) components directly. This product yields the image in which vegetation is shown in the red component.
 
+## Description of representative images
+
+False color composite of Rome. Acquired on 8.10.2017.
+
+![False color composite of Rome](fig/fig1.png)
+
 ## References
 - [1] Wikipedia, [False color](https://en.wikipedia.org/wiki/False_color). Accessed October 10th 2017.
 - [2] Wikipedia, [sRGB](https://en.wikipedia.org/wiki/SRGB). Accessed October 10th 2017.

sentinel-2/cby_cloud_detection/fig/fig.png

@@ -20,3 +20,9 @@ FAPAR is the fraction of incoming solar radiation absorbed for photosynthesis by
 Note that the FAPAR script is as implemented in SNAP but without input and output validation!
 Input/output values which are suspect are not reported or changed. Most values, however, do not fall under this category.
 Visualized as an interval from 0-1. This can be adjusted in the evaluatePixel method.
+
+## Description of representative images
+
+FAPAR visualization of Rome. Acquired on 8.10.2017.
+
+![FAPAR of Rome](fig/fig1.png)

sentinel-2/ccc/README.md

@@ -19,6 +19,11 @@ A paper about cloud detection [1], shows a fairly complex classification decisio
 
 The colours correspond to the colours from the article, apart from the colours for clear and shadow, which are made into natural (true) colour from red, green and blue bands.
 
+## Description of representative images
+
+Hollstein cloud detection, Slovenia. Acquired on 9.10.2017.
+
+![Hollstein](fig/fig1.png)
 
 ## References
 

sentinel-2/ccc/fig/fig1.png

@@ -20,3 +20,9 @@ LAI is a dimensionless index measuring the one-sided green leaf area over a unit
 Note that the LAI script is as implemented in SNAP but without input and output validation!
 Input/output values which are suspect are not reported or changed. Most values, however, do not fall under this category.
 Visualized as an interval from 0-3. This can be adjusted in the evaluatePixel method.
+
+## Description of representative images
+
+Leaf area index, Rome. Acquired on 08.10.2017.
+
+![snow classifier](fig/fig1.png)

sentinel-2/false_color_infrared/README.md

@@ -8,7 +8,7 @@
 </div>
 
 ## Evaluate and visualize
- - [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?source=S2&lat=41.9027835&lng=12.496365500000024&zoom=12&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/customScripts/master/sentinel-2/ndvi/script.js){:target="_blank"}
+ - [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?source=S2&lat=41.9027835&lng=12.496365500000024&zoom=12&preset=CUSTOM&layers=B01,B02,B03&maxcc=20&gain=1.0&gamma=1.0&time=2019-05-01%7C2019-11-04&atmFilter=&showDates=false&evalscript=CmxldCBuZHZpQ29sb3JNYXAgPSBbCglbLTEuMCwgMHgwMDAwMDBdLAoJWy0wLjIsIDB4RkYwMDAwXSwKCVstMC4xLCAweDlBMDAwMF0sCglbMC4wLCAweDY2MDAwMF0sCglbMC4xLCAweEZGRkYzM10sCglbMC4yLCAweENDQ0MzM10sCglbMC4zLCAweDY2NjYwMF0sCglbMC40LCAweDMzRkZGRl0sCglbMC41LCAweDMzQ0NDQ10sCglbMC42LCAweDAwNjY2Nl0sCglbMC43LCAweDMzRkYzM10sCglbMC44LCAweDMzQ0MzM10sCglbMC45LCAweDAwNjYwMF0KXTsKCmZ1bmN0aW9uIGluZGV4KHgsIHkpIHsKCXJldHVybiAoeCAtIHkpIC8gKHggKyB5KTsKfQoKZnVuY3Rpb24gdG9SR0IodmFsKSB7CglyZXR1cm4gW3ZhbCA%2BPj4gMTYsIHZhbCA%2BPj4gOCwgdmFsXS5tYXAoeCA9PiAoeCAmIDB4RkYpIC8gMHhGRik7Cn0KCi8vIFdlIHNob3VsZCBpbnRlcnBvbGF0ZSBiZXR3ZWVuIG5laWdoYm9yaW5nIGNvbG9ycwpmdW5jdGlvbiBmaW5kQ29sb3IoY29sVmFsUGFpcnMsIHZhbCkgewoJbGV0IG4gPSBjb2xWYWxQYWlycy5sZW5ndGg7Cglmb3IgKGxldCBpID0gMTsgaSA8IG47IGkrKykgewoJCWlmICh2YWwgPD0gY29sVmFsUGFpcnNbaV1bMF0pIHsKCQkJcmV0dXJuIHRvUkdCKGNvbFZhbFBhaXJzW2ktMV1bMV0pOwoJCX0KCX0KCXJldHVybiB0b1JHQihjb2xWYWxQYWlyc1tuLTFdWzFdKTsKfQoKcmV0dXJuIGZpbmRDb2xvcihuZHZpQ29sb3JNYXAsIGluZGV4KEIwOCwgQjA0KSk7Cg%3D%3D&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/customScripts/master/sentinel-2/ndvi/script.js){:target="_blank"}
  - [EO Browser](http://apps.sentinel-hub.com/eo-browser/#lat=41.9&lng=12.5&zoom=10&datasource=Sentinel-2%20L1C&time=2017-10-08&preset=CUSTOM&layers=B01,B02,B03&evalscript=CmxldCBuZHZpQ29sb3JNYXAgPSBbCglbLTEuMCwgMHgwMDAwMDBdLAoJWy0wLjIsIDB4RkYwMDAwXSwKCVstMC4xLCAweDlBMDAwMF0sCglbMC4wLCAweDY2MDAwMF0sCglbMC4xLCAweEZGRkYzM10sCglbMC4yLCAweENDQ0MzM10sCglbMC4zLCAweDY2NjYwMF0sCglbMC40LCAweDMzRkZGRl0sCglbMC41LCAweDMzQ0NDQ10sCglbMC42LCAweDAwNjY2Nl0sCglbMC43LCAweDMzRkYzM10sCglbMC44LCAweDMzQ0MzM10sCglbMC45LCAweDAwNjYwMF0KXTsKCmZ1bmN0aW9uIGluZGV4KHgsIHkpIHsKCXJldHVybiAoeCAtIHkpIC8gKHggKyB5KTsKfQoKZnVuY3Rpb24gdG9SR0IodmFsKSB7CglyZXR1cm4gW3ZhbCA%2BPj4gMTYsIHZhbCA%2BPj4gOCwgdmFsXS5tYXAoeCA9PiAoeCAmIDB4RkYpIC8gMHhGRik7Cn0KCi8vIFdlIHNob3VsZCBpbnRlcnBvbGF0ZSBiZXR3ZWVuIG5laWdoYm9yaW5nIGNvbG9ycwpmdW5jdGlvbiBmaW5kQ29sb3IoY29sVmFsUGFpcnMsIHZhbCkgewoJbGV0IG4gPSBjb2xWYWxQYWlycy5sZW5ndGg7Cglmb3IgKGxldCBpID0gMTsgaSA8IG47IGkrKykgewoJCWlmICh2YWwgPD0gY29sVmFsUGFpcnNbaV1bMF0pIHsKCQkJcmV0dXJuIHRvUkdCKGNvbFZhbFBhaXJzW2ktMV1bMV0pOwoJCX0KCX0KCXJldHVybiB0b1JHQihjb2xWYWxQYWlyc1tuLTFdWzFdKTsKfQoKcmV0dXJuIGZpbmRDb2xvcihuZHZpQ29sb3JNYXAsIGluZGV4KEIwOCwgQjA0KSk7Cg%3D%3D){:target="_blank"}
 
 ## General description
@@ -18,6 +18,12 @@ $$NDVI := \mathtt{Index}(B8,B4) = \frac{B8-B4}{B8+B4}.$$
 
 It is a good proxy for live green vegetation; see [1] for details.
 
+## Description of representative images
+
+NDVI of Rome. Acquired on 8.10.2017.
+
+![NDVI of Rome](fig/fig1.png)
+
 ## Color legend
 <table>
   <tr>

sentinel-2/false_color_infrared/fig/fig1.png

@@ -31,6 +31,12 @@ where $\Delta_{B4}$ and $\Delta_{B8}$ are uncertainties of red and near infrared
 The script encodes the uncertainty with darkness, as can be seen in following figure [[2]](#ref2)  
 ![Color map of the NDVI uncertainty script from [2][1]](fig/cmap.jpg)
 
+## Description of representative images
+
+NDVI with uncertainty of Madrid. Acquired on 10.26.2019.
+
+![NDVI of Rome](fig/fig1.png)
+
 ## References
 <a name="ref1"></a>[1] Wikipedia, [Normalized Difference Vegetation Index
 ](https://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index). Accessed on October 4th 2017.   

sentinel-2/fapar/README.md

@@ -2,7 +2,7 @@
 
 ## Evaluate and visualize
  - [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?source=S2&lat=43.514198796857976&lng=16.601028442382812&zoom=11&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/custom-scripts/master/sentinel-2/ndwi/script.js){:target="_blank"}    
- - [EO Browser](http://apps.sentinel-hub.com/eo-browser/#lat=41.9&lng=12.5&zoom=10&datasource=Sentinel-2%20L1C&time=2017-10-08&preset=CUSTOM&layers=B01,B02,B03&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/customScripts/master/sentinel-2/ndwi/script.js){:target="_blank"}   
+ - [EO Browser](https://apps.sentinel-hub.com/eo-browser/?lat=41.9000&lng=12.5000&zoom=10&time=2017-10-08&preset=CUSTOM&datasource=Sentinel-2%20L1C&layers=B01,B02,B03&evalscript=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%3D){:target="_blank"}   
 
 
 ## General description of the script
@@ -13,5 +13,11 @@ One is used to monitor changes in water content of leaves, using near-infrared (
 
 Another is used to monitor changes related to water content in water bodies, using green and NIR wavelengths, defined by McFeeters (1996).
 
+## Description of representative images
+
+NDWI of Rome. Acquired on 8.10.2017.
+
+![NDVI of Rome](fig/fig1.png)
+
 ## References
 Source: https://en.wikipedia.org/wiki/Normalized_difference_water_index

sentinel-2/fapar/fig/fig1.png

@@ -27,5 +27,12 @@ _Poor Man's Atmospheric Adjustment for a Pretty Glacier Picture_ (see <a href="h
 
 The product produces natural color images using Sentinel-2 bands 4, 3 and 2. It performs a very basic linear atmospheric correction, and applies a curve to the color components to enhance details in the dark areas, while preserving contrast in very bright snow-covered slopes. It has been fine-tuned to use on the Sentinel-2 image of Monte Sarmiento in Tierra del Fuego taken 2016-05-05.
 
+## Description of representative images
+
+Color correction of Rome. Acquired on 8.10.2017.
+
+![Color correction of Rome](fig/fig1.png)
+
 ## References
  - Sentinel Hub Blog, [Color Correction with Sentinel Hub](https://medium.com/p/d721e12a919).
+ 

sentinel-2/hollstein/README.md

@@ -18,5 +18,12 @@ $$PSRI = \frac{B04-B02}{B06}.$$
 
 It is used for studying vegetation; see [1] for details.
 
+## Description of representative images
+
+PSRI of Rome. Acquired on 8.10.2017.
+
+![PSRI of Rome](fig/fig1.png)
+
+
 ## References
  [1] Index DataBase, [index.de: PSRI](https://www.indexdatabase.de/db/i-single.php?id=69). Accessed on February 20th 2019.

sentinel-2/hollstein/fig/fig1.png

@@ -9,12 +9,16 @@
 ## Evaluate and visualize
  - [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?source=S2&lat=43.514198796857976&lng=16.601028442382812&zoom=11&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/custom-scripts/master/sentinel-2/sipi/script.js){:target="_blank"}    
  - [EO Browser](http://apps.sentinel-hub.com/eo-browser/#lat=41.9&lng=12.5&zoom=10&datasource=Sentinel-2%20L1C&time=2017-10-08&preset=CUSTOM&layers=B01,B02,B03&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/custom-scripts/master/sentinel-2/sipi/script.js){:target="_blank"}   
-
+ When EO Browser loads, switch to **code view**, then check the **Use URL** checkbox and press **Refresh**.
 
 ## General description of the script
 
 The SIPI index maximizes sensitivity to the ratio of bulk carotenoids to chlorophyll while minimizing the impact of the variable canopy structure. It is very useful in areas with high variability in the canopy structure, or leaf area index..
 
 Values description: The range of a SIPI is from 0 to 2, where healthy green vegetation is from 0.8 to 1.8.
 
+## Description of representative images
+
+SIPI of Rome. Acquired on 8.10.2017.
 
+![NDVI of Rome](fig/fig1.png)

sentinel-2/lai/README.md

@@ -11,7 +11,7 @@
 
 ## Evaluate and visualize
  - [Sentinel Playground](https://apps.sentinel-hub.com/sentinel-playground/?source=S2&lat=41.9027835&lng=12.496365500000024&zoom=12&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/customScripts/master/sentinel-2/snow_classifier/script.js){:target="_blank"}    
- - [EO Browser](http://apps.sentinel-hub.com/eo-browser/#lat=41.9&lng=12.5&zoom=10&datasource=Sentinel-2%20L1C&time=2017-10-08&preset=CUSTOM&layers=B01,B02,B03&evalscripturl=https://raw.githubusercontent.com/sentinel-hub/customScripts/master/sentinel-2/snow_classifier/script.js){:target="_blank"}   
+ - [EO Browser](https://apps.sentinel-hub.com/eo-browser/?lat=46.35647&lng=13.47542&zoom=13&time=2019-10-26&preset=CUSTOM&datasource=Sentinel-2%20L1C&layers=B01,B02,B03&evalscript=ICB2YXIgTkRTSSA9IChCMDMgLSBCMTEpIC8gKEIwMyArIEIxMSk7CnZhciBORFZJID0gKEIwOCAtIEIwNCkgLyAoQjA4ICsgQjA0KTsKdmFyIGdhaW4gPSAyLjU7CgpmdW5jdGlvbiBzaShhKSB7CiAgICByZXR1cm4gKGE%2BPTAuNCkgPyAxIDogKE1hdGguYWJzKE5EVkkgLSAwLjEpIDw9IDAuMDI1ID8gMSA6IDApOwp9CgpmdW5jdGlvbiBicihhKSB7CiAgICByZXR1cm4gYT4wLjM7Cn0KICAgCnZhciB2ID0gc2koTkRTSSkgJiYgYnIoQjAzKTsKCnJldHVybiAodj09MSkgPyBbMS4wLDAuOCwwLjRdIDogW0IwNCwgQjAzLCBCMDJdLm1hcChhID0%2BIGdhaW4gKiBhKTs%3D){:target="_blank"}   
 
 ## General description of the script
 
@@ -28,6 +28,12 @@ Difference Vegetation Index (NDVI) value is close enough to 0.1.
 
 This algorithm classifies pixels based on all three values. Different brightness and NDSI thresholds were tested and 0.3 and 0.4, respectively, proved to give the best results.
 
+## Description of representative images
+
+Snow classifier, Bovec, Slovenia. Acquired on 26.10.2019.
+
+![snow classifier](fig/fig1.png)
+
 ## References
 [1] Olivier Hagolle, Mireille Huc, Camille Desjardins, Stefan Auer, & Rudolf Richter. (2017, December 7). MAJA Algorithm Theoretical Basis Document (Version 1.0). Zenodo. http://doi.org/10.5281/zenodo.1209633
 

sentinel-2/lai/fig/fig1.png

@@ -90,6 +90,12 @@ Example response:
 ```
 </details>
 
+## Description of representative images
+
+Vegetation condition index of Rome. Acquired on 8.10.2017.
+
+![Vegetation condition index of Rome](fig/fig1.png)
+
 ## References
 
 [1] https://www.indexdatabase.de/db/i-single.php?id=249