A New Approach for the Analysis of Hyperspectral Data: Theory and Sensitivity Analysis of the Moment Distance Method

Abstract

Abstract:We present the Moment Distance (MD) method to advance spectral analysis in vegetation studies. It was developed to take advantage of the information latent in the shape of the reflectance curve that is not available from other spectral indices. Being mathematically simple but powerful, the approach does not require any curve transformation, such as smoothing or derivatives. Here, we show the formulation of the MD index (MDI) and demonstrate its potential for vegetation studies. We simulated leaf and canopy reflectance samples derived from the combination of the PROSPECT and SAIL models to understand the sensitivity of the new method to leaf and canopy parameters. We observed reasonable agreements between vegetation parameters and the MDI when using the 600 to 750 nm wavelength range, and we saw stronger agreements in the narrow red-edge region 720 to 730 nm. Results suggest that the MDI is more sensitive to the Chl content, especially at higher amounts (Chl > 40 μg/cm 2 ) compared to other indices such as NDVI, EVI, and WDRVI. Finally, we found an indirect relationship of MDI against the changes of the magnitude of the reflectance around the red trough with differing values of LAI.

Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs

“…Capturing additional information from the Landsat bands added value in studying the spectral behaviors of the classes that may not be possible for other indices. The advantage of the MDI against other metrics (e.g., [37,38]) is threefold. First, there is no requirement in the MDI to select the best bands in its equation as it utilizes the available bands of the Landsat product.…”

“…Unlike broadband sensors such as the Landsat that have few bands, both spaceborne sensors have many spectral channels that span from the visible to NIR-regions considered as essential for vegetation studies. As stated by Salas and Henebry [38], MDI is applicable for the full spectrum or subsets of it. Future work will include analyzing wavelength subsets from hyperspectral datasets and how these band subsets could classify plant species.…”

“…The index is specifically sensitive in the VIS to NIR regions where there is a strong difference in the reflectances. Also, there is not a significant effect of soil reflectance on the MDI at the strip of curve in the red-edge region, a region between the red and NIR [38].…”

“…The processed DEM was sourced from NASA's Shuttle Radar Topography Mission (SRTM) digital elevation dataset that is available for download through the USGS website [63]. NDVI [57] exploits the strong differences in the red and NIR reflectances where contrast between vegetation and soil is maximal [38]. Sensitive to pixel-level changes in greenness, NDVI is calculated as the difference between the spectral reflectance measurements of the NIR and red bands divided by the sum of the same measurements.…”

Object-Based Greenhouse Mapping Using Very High Resolution Satellite Data and Landsat 8 Time Series

“…In addition to the object-based features containing spectral information (mean and standard deviation values of all pixels within an object) and several spectral and vegetation indices, the capabilities of the spectral metric Moment Distance Index (MDI) [37,44,45] was explored in this study as one of the predictor variables for greenhouse mapping. To the best knowledge of the authors, it is the first time that this index is tested in plastic covering mapping.…”