Hyperspectral Satellite Data in Mapping Salt-Affected Soils Using Linear Spectral Unmixing Analysis

Abstract

Development of salt-affected soils in the irrigated lands of arid and semi-arid region is major cause of land degradation. Hyperion hyperspectral remote sensing data (EO-1) was used in the present study for characterization and mapping of salt-affected soils in a part of irrigation command area of IndoGangetic alluvial plains. Linear spectral mixture analysis approach was used to map various categories of salt affected soils represented by spectral endmembers of slightly, moderately and highly salt-affected soils. These endmembers were related to surface expression of various categories of salt-affected soils in the area. The endmembers were selected by performing minimum noise fraction (MNF) transformation and pixel purity index (PPI) on Hyperion (EO-1) data with reference to high resolution LISS IV data and field data. The results showed that various severity classes of salt-affected soils could be reliably mapped using linear spectral unmixing analysis. A low RMSE value (0.0193) over the image was obtained that revealed a good fit of the model in identification and classification of endmembers of various severities of salt affected soils. The overall classification accuracies for slight, moderate and highly salt-affected soils were estimated of 78.57, 79.81 and 84.43% respectively.

Analyses of Recent Sediment Surface Dynamic of a Namibian Kalahari Salt Pan Based on Multitemporal Landsat and Hyperspectral Hyperion Data

“…The RMSE image shows that the overall pan surface is well explained with the linear mixture of the four selected endmembers except for higher RMSE areas at: (1) the northeast corner and western pan border associated with heavy cattle disturbances; (2) the mainly diagonal SW-NE lines crossing the pan, which are used as driving shortcuts across the pan during the dry season as well as cattle path ways; and (3) the parallel, vertical stripes (~11 • ), associated with remaining sensor noise that were not removed through the pre-processing procedure. In general the performance of the unmixing model is very good with an overall mean RMSE of~1% comparable to equivalent studies, e.g., [105] achieved an mean RMSE of~2% using linear unmixing on Hyperion data to map salt effect soils or [106] getting the same accuracy range for the abundances of vegetation, soil and limestone bedrock. The SMA mapping shows that more than half of the pan surface is dominated by halite crust in variable amounts (Figure 5a).…”

Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS)

“…Several studies have shown the visible, near infrared, or short-wave infrared spectral bands from the optical sensors to be promising for the detection of surface soil salinity [11][12][13][14][15]. In addition, hyperspectral data have been successfully used in several studies on soil salinity, enabling quantitative assessment of salt-affected soils [16][17][18][19][20][21][22]. However, practical limitations associated with hyperspectral imagery, including the availability of orbital data and the limited spatial coverage of the existing satellite sensors, still limit its potential for regional monitoring of salt-affected soils [23].…”

Spectral identification and quantification of salts in the Atacama Desert

“…Mining interests have been investigated with Magendran and Sanjeevi 11 classifying iron ore and Hosseinjani Zadeh et al 12 mapping a porphyry copper belt. Ghosh et al 13 utilised Hyperion imagery to characterise and map salinated soil in the Indo-Gangetic plains in India. Minimum Noise Fraction (MNF) transformations and Pixel Purity Index (PPI) analysis techniques were combined with linear spectral unmixing to quantify the severity of the salination in the regions examined.…”