Finally create this Apps for creating "Chart NDVI Over Time in Bangladesh from 2013 to 2020'" Click your location on the map and get the Chart NDVI over time for your desire geographic location as well as downloads the NDVI value in csv format file.
LAI time series mean visualization and making chart
This Apps demonstrates how to use the drawing tools API with a custom interface to make a simple Earth Engine App that charts LAI time series for a user-drawn geometry. The app provides options for drawing a rectangle, polygon, or point. It listens for when a user draws a geometry and displays the LAI Map as well as a chart of mean LAI for pixels intersecting the drawn geometry.
Night Light Map of Bangladesh.
This data was obtained from the Defense Meteorological Program (DMSP) Operational Line-Scan System (OLS). DMSP data collected by US Air Force Weather Agency. Image and data processing by NOAA’s National Geophysical Data Center. It is now available in Google Earth Engine. The DMSP-OLS has a unique capability to detect visible and near-infrared (VNIR) emission sources at night.
This collection contains global nighttime lights images with no sensor saturation. The sensor is typically operated at a high-gain setting to enable the detection of moonlit clouds. However, with six bit quantization and limited dynamic range, the recorded data are saturated in the bright cores of urban centers. A limited set of observations at low lunar illumination were obtained where the gain of the detector was set significantly lower than its typical operational setting (sometimes by a factor of 100). Sparse data acquired at low-gain settings were combined with the operational data acquired at high-gain settings to produce the set of global nighttime lights images with no sensor saturation. Data from different satellites were merged and blended into the final product in order to gain maximum coverage. For more information, see this read me file from the provider.
Water Class Transition of Dhaka City.
The water transition layer captures changes between three classes of water occurrence (not water, seasonal water, and permanent water) along with two additional classes for ephemeral water (ephemeral permanent and ephemeral seasonal).
