The effects of organic versus conventional crop management practices (crop rotation, crop protection, and fertility management strategies) on wheat yields and grain metal (Al, Cd, Cu, Ni, Pb, and Zn) concentrations were investigated in a long-term field trial. The interactions between crop management practices and the season that the crop was grown were investigated using univariate and redundancy analysis approaches. Grain yields were highest where conventional fertility management and crop protection practices were used, but growing wheat after a previous crop of grass/clover was shown to partially compensate for yield reductions due to the use of organic fertility management. All metals except for Pb were significantly affected by crop management practices and the year that the wheat was grown. Grain Cd and Cu levels were higher on average when conventional fertility management practices were used. Al and Cu were higher on average when conventional crop protection practices were used. The results demonstrate that there is potential to manage metal concentrations in the diet by adopting specific crop management practices shown to affect crop uptake of metals.

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms.Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

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