Download NDVI image using GEE & Visualize using ArcGIS

In this video tutorial, I will demonstrate how to perform NDVI (Normalized Difference Vegetation Index) and download it using Google Earth Engine (GEE). We will then visualize the downloaded NDVI image in ArcGIS.
----------------------------------------------------------------------------------
Sharable Code for Practice: https://code.earthengine.google.com/b...
----------------------------------------------------------------------------------
Join this channel to get access to perks:
   / @terraspatial  
----------------------------------------------------------------------------------
00:00 Introduction
01:41 Importing Landsat 8 image
01:58 Cloud Filtering
02:07 Choosing Study Area
03:15 NDVI Analysis
04:42 Setting Visualizing Parameter / Color
05:58 Exporting NDVI image
06:47 Running Code
06:58 Visualizing Result Image
08:45 Downloading NDVI image / Earth Engine
10:27 Visualizing NDVI image in ArcGIS

**************************************
More Information on TOPIC NDVI:
**************************************
NDVI stands for Normalized Difference Vegetation Index. It's a numerical indicator used in remote sensing and satellite imagery analysis to assess and monitor the health and abundance of vegetation in a particular area. NDVI is calculated using the reflectance values of visible and near-infrared light captured by remote sensors.
Here's how NDVI is calculated:

NDVI = NIR-Red / NIR+Red

Where:
• NIR (Near-Infrared) is the reflectance value in the near-infrared spectrum (typically around 800-900 nm).
• Red is the reflectance value in the red spectrum (around 600-700 nm).
NDVI values typically range from -1 to +1, with meaningful values falling between -0.1 and 0.9. The interpretation of NDVI values is as follows:
• High Negative Values (-1 to -0.1): These areas usually represent water bodies or surfaces with little to no vegetation.
• Low Values (-0.1 to 0.2): These areas might include bare soil, rocks, or sparse vegetation.
• Moderate Values (0.2 to 0.5): These values indicate moderate levels of vegetation cover, such as grasslands and shrublands.
• High Values (0.5 to 0.9): These areas typically represent dense and healthy vegetation, such as forests or croplands.

----------------------------------------------------------------
NDVI is widely used for various applications, including:
----------------------------------------------------------------
1. Assessing Vegetation Health: NDVI can help monitor changes in vegetation health over time, including stress caused by factors like drought, disease, or pollution.
2. Land Use Planning: NDVI can be used to map land cover types, helping urban planners and land managers make informed decisions about land use and development.
3. Agriculture: Farmers and agronomists use NDVI to monitor crop health, identify stress or nutrient deficiencies, and make decisions about irrigation and fertilization.
4. Ecology and Conservation: NDVI is used to study ecosystems, track deforestation, and monitor habitat changes for various species.
5. Climate Change Studies: NDVI data can be used to analyze the impact of climate change on vegetation patterns and biodiversity.
6. Disaster Management: NDVI can aid in assessing the extent of damage caused by natural disasters like wildfires, hurricanes, and earthquakes.

Overall, NDVI is a valuable tool in the field of remote sensing, providing critical information about the state of vegetation and the environment.


#googleearthengine #ndvi #download #visualize #ArcGIS #geospatial #earthengine