examples update in ReadME

README.md

@@ -1,5 +1,5 @@
 
-# OpenEOcubes: OpenEO Compliant Lightweight R Platform for Processing Time Series Satellite Images
+# OpenEOcubes: openEO Compliant Lightweight R Platform for Processing Satellite Image Time Series 
 
 The service integrates STAC API (using Rstac package), the OpenEO standardized API, and data cubes concepts (using gdalcubes R package) to be a lightweight platform to enable analysis of time series satellite images via OpenEO Compliant RESTful endpoints using R-Client. It also supports users to run their custom R functions.
 
@@ -89,8 +89,79 @@ docker-compose build --no-cache && docker-compose up
 ```
 
 ## Getting Started:
-### Example Script in R-Studio using OpenEO R-Client
-Using openeo client version 1.1.0, the R scripts provided below has a user-defined function that uses bfast library to monitor changes on time series of Sentinel-2 imagery from 2016 to 2020. The study area is the region around the new Berlin-Brandenburg Tesla Gigafactory. You can run the  code on your R-studio. 
+
+### Example 1:  NDVI Script in R-Studio using OpenEO R-Client
+Using openeo client version 1.3.0, the R scripts provided below calculate a 1-year period NDVI in a section of Amazonia in Brazil. 
+
+```bash
+library(openeo)
+
+# connect  to the back-end when deployed locally
+ con = connect("http://localhost:8000")
+# connect  to the back-end when deployed on aws
+# con = connect("http://<AWS-IPv4-ADDRESS>:8000")
+
+# basic login with default params
+login(user = "user",
+      password = "password")
+
+# get the collection list
+collections = list_collections()
+
+# to check description of a collection
+collections$`sentinel-s2-l2a-cogs`$description
+
+# Check that required processes are available.
+processes = list_processes()
+
+# to check specific process e.g. ndvi
+describe_process(processes$ndvi)
+
+# get the process collection to use the predefined processes of the back-end
+p = processes()
+
+# load the initial data collection and limit the amount of data loaded
+datacube_init = p$load_collection(id = "sentinel-s2-l2a-cogs",
+                                spatial_extent = list(west=-7338335,
+                                                      south=-1027138,
+                                                      east=-7329987,
+                                                      north=-1018790),
+                                temporal_extent = c("2021-05-01", "2022-06-30"),
+                                # extra args for data cubes regularization -> courtesy of gdalcubes
+                                pixels_size = 30,
+                                time_aggregation = "P1Y",
+                                crs = 3857)
+
+# filter the data cube for the desired bands
+datacube_filtered = p$filter_bands(data = datacube_init, bands = c("B04", "B08"))
+
+
+# ndvi calculation
+datacube_ndvi = p$ndvi(data = datacube_filtered, red = "B04", nir = "B08")
+
+# supported formats
+formats = list_file_formats()
+
+# save as GeoTiff or NetCDF
+result = p$save_result(data = datacube_ndvi, format = formats$output$GTiff)
+
+# Process and download data synchronously
+start.time <- Sys.time()
+compute_result(graph = result, output_file = "amazonia_2022_ndvi.tif")
+end.time <- Sys.time()
+time.taken <- end.time - start.time
+time.taken
+print("End of processes")
+
+```
+
+Visualization of the output from the above process:
+
+![NDVI in Amazonia](docs/amazoniandvi.png)
+
+
+### Example 2:  BFAST change detection in R-Studio using OpenEO R-Client
+Using openeo client version 1.3.0, the R scripts provided below has a user-defined function that uses bfast library to monitor changes on time series of Sentinel-2 imagery from 2016 to 2020. The study area is the region around the new Berlin-Brandenburg Tesla Gigafactory. You can run the  code on your R-studio. 
 
 ```bash
 library(openeo)