Using Normalized Difference Water Index (NDWI)

Introduction

A  ^{spectral index is a mathematical equation that is applied on the various spectral bands of an image per pixel. The purpose of using a spectral index is to extract meaningful information from the data that may not be immediately apparent from the raw image. Spectral indices are often used to extract information about vegetation, soil moisture, water content, and other features of interest. For example, the Normalized Difference Vegetation Index (NDVI) is a commonly used spectral index that measures the difference between the reflectance of red and near-infrared light to estimate the density and health of vegetation. Spectral indices can be calculated using various mathematical formulas, such as ratios, differences, and normalized ratios of the data in different bands or channels. These indices are powerful tools for interpreting remote sensing data and extracting information about the Earth's surface.} 

 _{A satellite-derived indicator using the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels is called the Normalized Differential Water Index (NDWI) (Gao, 1996). Whereas the NIR reflectance is influenced by changes in leaf internal structure and dry matter content but not water content, the SWIR reflectance reflects changes in both vegetation water content and the spongy mesophyll structure in vegetation canopies. The accuracy of determining the vegetation water content is improved by the combination of the NIR and SWIR, which eliminates variances brought on by changes in leaf internal structure and leaf dry matter content (Ceccato et al. 2001). The spectral reflectance in the SWIR region of the electromagnetic spectrum is substantially governed by the quantity of water present in the interior leaf structure. SWIR reflectance thus has a bad relationship with leaves.} 

 _{For the purpose of this project, the Sentinel-2 data was used to carry out the NDWI analysis. Sentinel-2 is an Earth observation mission within the Copernicus Program that regularly collects optical images with a high spatial resolution (10 m to 60 m) over land and coastal waterways. The constellation for the project now consists of the satellites Sentinel-2A and Sentinel-2B.} 

The Normalized Difference Water Index (NDWI) method is an index for delineating and monitoring content changes in surface water. It is computed with the NIR and green bands.

NDWI = (Green - NIR) / (Green + NIR)

How to calculate NDWI using different satellite

The NDWI equation looks like this:

NDWI = (Green – NIR)/(Green + NIR)

For Landsat 7 data:

NDWI = (Band 2 – Band 4)/(Band 2 + Band 4)

For Landsat 8 data:

NDWI = (Band 3 – Band 5)/(Band 3 + Band 5)

For Sentinel 2 data:

NDWI= (Band 3 – Band 8)/(Band 3 + Band 8) 

Typical use of NDWI

• Water resource management: is aided by the use of NDWI to track changes in water bodies like rivers, lakes, and reservoirs.

• Monitoring and evaluation of flooding: NDWI can track flooding by locating locations that have been flooded.

• Agricultural monitoring: NDWI can be used to evaluate the health of the crops and the stress on the plants, particularly in regions with low water supplies.

• Wetland mapping: NDWI can be used to map and monitor wetlands, which are important habitats for many different plant and animal species.

• Land use and land cover mapping: It is crucial for land use and land cover mapping to be able to distinguish between different types of land cover and water bodies using NDWI.

• Urban planning: NDWI can help identify regions with poor drainage and those that are prone to floods, information that may be utilized for both disaster management and urban development.

NDWI Map of the study Area

Interpretation of the Index value

 _{The values of this index range from -1 to +1. Also, it plays a big role in agricultural monitoring, drought, and flood forecasting, predicting forest fires, managing water supplies, and other tasks involving natural resources. Observations NDMI can predict impending drought or flood conditions before other, more conventional signs are set off. The index is inverted relative to the other water vegetation indices; higher values indicate greater water stress and less water content.}  

Limitations

Impacts other than drought can stress plant canopies, but it is challenging to identify them using simply NDWI. Satellite data only cover a little time span, making climatic studies challenging. There are other causes besides drought and water stress that can reduce NDWI results and anomalies. Such variations in the signal may also be brought on by changes in the land's cover or the presence of pests and diseases. Consequently, to identify whether the fluctuation in the vegetation response (signal) is associated with a drought event or not, this indicator must be utilized in conjunction with other indicators providing information on the deficit of rainfall/soil moisture.