ENVI provides the following indices that measure miscellaneous features:
Methane Index
This index detects concentrated sources of CH4 emissions based on the absorption of CH4 in the shortwave infrared (SWIR) region.
The Methane Index needs to use radiance data, not reflectance data.
References:
Xiao, C, B. Fu, H. Shiu, Z. Guo, and J. Zhu. "Detecting the Sources of Methane Emission from Oil Shale Mining and Processing Using Airborne Hyperspectral Data." Remote Sensing 12, No. 3 (2020): 537.
Modified Normalized Difference Water Index (MNDWI)
This index enhances open water features while suppressing noise from built-up land, vegetation, and soil. Xu (2006) reported that the MNDWI produced better results than the Normalized Difference Water Index (McFeeters 1996) in enhancing and extracting water from a background that is dominated by build-up land areas.
Here are some guidelines for interpreting MNDWI results:
- Open water has greater positive values than NDWI, as it absorbs more shortwave-infrared (SWIR) wavelengths than near-infrared (NIR) wavelengths.
- Built-up features have negative values.
- Soil and vegetation have negative values, as soil reflects more SWIR wavelengths than NIR wavelengths.
The MNDWI was originally developed for use with Landsat TM bands 2 and 5. However, it will work with any multispectral sensor with a green band between 0.5-0.6 µm and a SWIR band between 1.55-1.75 µm.
References:
Xu, H. "Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery." International Journal of Remote Sensing 27, No. 14 (2006): 3025-3033.
McFeeters, S. "The use of Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features." International Journal of Remote Sensing 17 (1996): 1425-1432.
Normalized Difference Built-Up Index (NDBI)
This index highlights urban areas where there is typically a higher reflectance in the shortwave-infrared (SWIR) region, compared to the near-infrared (NIR) region. Applications include watershed runoff predictions and land-use planning.
The NDBI was originally developed for use with Landsat TM bands 5 and 4. However, it will work with any multispectral sensor with a SWIR band between 1.55-1.75 µm and a NIR band between 0.76-0.9 µm.
Reference: Zha, Y., J. Gao, and S. Ni. "Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery." International Journal of Remote Sensing 24, no. 3 (2003): 583-594.
Normalized Difference Mud Index (NDMI)
This index highlights muddy or shallow water pixels. This index was originally designed as a filter to exclude those pixels and to improve the accuracy of QUick Atmospheric Correction (QUAC).
See Narrowband Definitions for the allowable range of wavelengths.
Reference: Bernstein, L. S., X. Jin, B. Gregor, and S. Adler-Golden. "Quick Atmospheric Correction Code: Algorithm Description and Recent Upgrades." Optical Engineering 51, No. 11 (2012): 111719-1 to 111719-11.
Normalized Difference Snow Index (NDSI)
This index highlights snow cover using a combination of visible (typically green) and shortwave-infrared wavelengths. This version of NDSI was originally designed for use with MODIS bands 4 (0.555 µm) and 6 (1.64 µm). However, it will work with any multispectral sensor with a green band ranging from 0.5 to 0.6 µm and a SWIR1 band ranging from 1.55 to 1.75 µm.
References:
Hall, D., G. Riggs, and V. Salomonson. "Development of Methods for Mapping Global Snow Cover Using Moderate Resolution Imaging Spectroradiometer Data." Remote Sensing of Environment 54, No. 2 (1995): 127-140.
Salomonson, V., and I. Appel. "Estimating Fractional Snow Cover from MODIS Using the Normalized Difference Snow Index." Remote Sensing of Environment 89 (2004): 351-360.
WorldView Built-Up Index (WV-BI)
This index uses WorldView-2 bands to compute a Normalized Difference Built-Up Index (NDBI).
WorldView Non-Homogeneous Feature Difference (WV-NHFD)
This index uses WorldView-2 bands to identify features that contrast highly against the background. Examples include roofs, vehicles, and paved surfaces.
Reference: Wolf, A. Using WorldView 2 Vis-NIR MSI Imagery to Support Land Mapping and Feature Extraction Using Normalized Difference Index Ratios. Unpublished report, Longmont, CO: DigitalGlobe (2010).
WorldView Water Index (WV-WI)
This index uses WorldView-2 bands to highlight areas of standing water greater than one pixel in size.
Reference: Wolf, A. Using WorldView 2 Vis-NIR MSI Imagery to Support Land Mapping and Feature Extraction Using Normalized Difference Index Ratios. Unpublished report, Longmont, CO: DigitalGlobe (2010).
See Also
Spectral Indices