Скачать или смотреть Remote Sensing using GEE to identify algae bloom in Lake Erie.

The purpose of the project is to create an R Shiny application to monitor and investigate the growth of Algae blooms in water bodies using the satellite images captured using remote sensing. Harmful Algae Blooms (HABs) affect the aquatic ecosystem seriously and cause losses to the industries dependent on the water body. This tool could be used to study the causes and take preventive measures to control the growth of Harmful Algae Blooms.
Lake Erie in Canada is taken as the study area and different areas of the lake are selected for analysis and to study the growth of Algae Blooms over the period 1st January 2020 to 3rd June 2021. The preferred locations are selected using spatial polygons in the interactive map of the R shiny application. The satellite images for the locations from SENTINEL-2 collected through remote sensing are accessed from the Google Earth Engine (GEE) platform using the functionalities of RGEE package in R Studio. The index used for detecting the presence of algae bloom on the water body is Normalized Difference Vegetation Index (NDVI) which could be calculated from the bands B4 and B8 extracted from the satellite images.
The NDVI value for each image of the locations over the specific time period are calculated and a time series plot is constructed corresponding to each location. Exponential smoothing is used to do the time series analysis. Trend analysis and seasonal behaviour of the growth of the Algae Blooms could be investigated from the time series plots. This could be used to understand the causes and contributing factors for the Algae blooms and forecast the future growth.
The R shiny application could be further modified and enhanced to study the different issues like Forest fires, Farmland monitoring, Urbanisation, melting of ice covers etc., by using the corresponding indices or a combination of indices.