Tomohisa Yano

Analysis of four change detection algorithms in bi-temporal space with a case study

Although change detection algorithms for temporal remote sensing images have been compared using various datasets, there is no general agreement on their performance for separating change and no-change. This study compared image differencing, image ratioing, image regression, and principal component analysis (PCA) from a mathematical perspective. Error analysis showed that no-change pixels with errors are expected to be located within an error zone in bi-temporal space. Bi-temporal space consists of two temporal axes of target pixel values observed successively. All algorithms confine a no-change area to a zone delineating change and no-change pixels in the space. Image ratioing defines a fan-like sector as a no-change area, generally unsuitable for change detection. The other algorithms confine a no-change area to a strip-like zone. Image differencing defines a no-change zone with a fixed slope, leading to its inability to specify flexibly the error zone that varies with different conditions. In the examined case, image regression and standardized PCA (SPCA) achieved the best performance for change detection, followed by PCA, image differencing, and image ratioing.

The response of low and high swelling smectites to sodic conditions

Swelling and dispersion of clays are the primary processes responsible for the degradation of soil hydraulic properties in the presence of exchangeable Na. The relative importance of these processes was evaluated by studying the response of low and high swelling smectites to sodic conditions. Smectite from Ariake bay sediments in Japan represented the low swelling smectite, and clay from the Kamenose landslide in Japan represented the high swelling smectite. Changes in hydraulic conductivity (HC) and clay dispersivity of sediment-sand mixtures (10, 20, and 30 g of sediment mixed with 90, 80, and 70 g of sand, respectively) as a function of total electrolyte concentration (TEC) (0.05 and 0.01 M Cl - and distilled water, (DW)) and sodium adsorption ratio ((SAR) of 0,10, and 20) of the percolating solutions were measured. In the low swelling smectite, no changes in HC were measured in the electrolyte solutions (TEC ≥ 0.01 M Cl - ) at the three SAR values. When the low swelling smectites were leached with DW, the HC of the Ca-smectite increased, whereas the HC of the SAR 10 and 20 treatments decreased. Clay dispersion and migration out of the 10% soil column was substantial. The increase in HC in Ca-mixture of low swelling smectite leached with dilute solutions was attributable to the collapse of the open microstructure that prevails in electrolyte solutions. In low swelling smectite, clay dispersion was the main process responsible for HC deterioration under sodic conditions, and smectite dispersion was prevented when TEC exceeded the flocculation value of the clay. Clay dispersion increased with an increase in exchangeable sodium percentage (ESP), and it affected the HC of the porous media only when the pores were fine and the dispersed clay plugged the conducting pores. In the high swelling smectite mixtures, a gradual decrease in the HC was measured as the TEC decreased and the SAR increased. In these mixtures, swelling was the main process responsible for HC deterioration in electrolyte solutions with TEC ≥ 0.01M Cl - . Swelling increased with an increase in clay percentage, ESP, and decreasing TEC.

Radiometric correction for linear change-detection techniques: analysis in bi-temporal space

Radiometric corrections can remove or reduce inconsistencies induced by temporal factors in multi‐temporal images, but their effectiveness for change detection is still unclear. This study applied a physics‐based model to pseudo‐invariant features (PIFs) and showed that absolute correction is in principle equivalent to relative correction in change‐detection studies if the spatial heterogeneity of the atmosphere is not rigorously considered. Bi‐temporal space analysis revealed that the performance of a linear change‐detection algorithm depends on whether the determined slope of the no‐change zone coincides with that of the PIF line, offering insight into the effectiveness of radiometric correction. A case examination showed that either absolute or relative correction adjusted the paired image bands to a common standard. However, the corrections did not necessarily reduce the bias in the zone slope determined by the change‐detection algorithm, illustrating the futility of performing either absolute or relative corrections for linear change‐detection techniques, except for image differencing.