Published on May 12, 2020 | Bikesh Bade | 1372 Views
Normalized Difference Water Index (NDWI), introduced for the first time in 1996 in Gao (Gao), reflects moisture content in plants and soil It is known to be strongly related to the plant water content. It is, therefore, a very good proxy for plant water stress. It is remote sensing derived index estimating the leaf water content at the canopy level. It is derived index from the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels. It is also known as Land Surface Water Index (LSWI)
What is NDWI in remote sensing?
The NDWI is a remote sensing-based indicator sensitive to the change in the water content of leaves. It is derived index from the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels. The SWIR reflectance reflects changes in both the vegetation water content and the spongy mesophyll structure in vegetation canopies, while the NIR reflectance is affected by leaf internal structure and leaf dry matter content but not by water content. The combination of the NIR with the SWIR removes variations induced by leaf internal structure and leaf dry matter content, improving the accuracy in retrieving the vegetation water content
How to calculate NDWI?
NDWI is computed using the near-infrared (NIR) and the short wave infrared (SWIR ) reflectances.
NIR - near-infrared range with wavelengths in the range of 0.841 - 0.876 nm
SWIR - a part of the range with wavelengths in the range of 1.628-1.652 nm
How does NDWI work?
The NDWI product is dimensionless and varies between -1 to +1, depending on the leaf water content but also on the vegetation type and cover. High values of NDWI (in blue) correspond to high vegetation water content and to high vegetation fraction cover. Low NDWI values (in red) correspond to low vegetation water content and low vegetation fraction cover. In the period of water stress, NDWI will decrease. The NDWI index for assessing the risk of fire is used to determine the presence of moisture in vegetation cover. Higher NDWI values indicate sufficient moisture, while a low value indicates water stress.
How to interpret NDWI images?
The results of NDWI can be presented in the form of maps and graphs, providing information on both the spatial distribution of water stress on vegetation and its temporal evolution over long periods of time. Traditionally, NDWI results are presented as a color map, where each color corresponds to a certain range of values. There’s no standard color palette, but most software uses the color palette similar to NDWI.
What are the alternatives to NDWI?
Modified NDWI (MNDWI), and Automated Water Extraction Index (AWEI) are alternatives to NDWI. MNDWI and AWEI are derived to solve the problems in urban areas. MNDWI and AWEI are used to detect mixed pixels along with environmental noise.
Application of NDWI
NDWI has mostly been used for assessments of
Water and agricultural management
Drought monitoring and mapping
Water Stress measurement of crop
To detect the flood events
To study wetland and natural water resources
Some studies use NDWI to detect the swimming pool.
Agricultural monitoring for crop irrigation and pasture management
Forest monitoring for assessing fire risk
Stress to plant canopies can be caused by impacts other than drought, and it is difficult to discern them using only NDWI. The period of record for satellite data is short, with climatic studies being difficult. Drought and water stress are not the only factors that can cause a decrease of NDWI values/anomalies. Change in land covers or pests and diseases can also be responsible for such variation of the signal. Therefore this indicator must be used jointly with other indicators giving information on the deficit of rainfall /soil moisture in order to determine if the variation in the vegetation response (signal) is linked with a drought event or not.