Multi-dimensional assessment of watershed condition using a newly developed barometer of sustainability.

The present study was conducted to comprehensively evaluate watershed sustainability with the help of an initiative barometer developed based on different dimensions of social, economic, environmental, and policy. The newly developed barometer was then applied to assess the temporal variation of sustainability for the Shazand Watershed, Iran, for four-node years of 1986, 1998, 2008, and 2016. The appropriate criteria were then adapted to calculate the study dimensions. The effect sizes of selected criteria on each dimension were also determined. Consequently, the status of each dimension and integrated watershed sustainability status were mapped for four-node years. The results indicated that study dimensions were unevenly distributed over the Shazand Watershed. So that, the social dimension had high effectiveness across different sub-watersheds, and the policy dimension had a poor situation in all study years. In addition, the respective sustainability index of 0.32, 0.32, 0.35, and 0.35 for node years of 1986, 1998, 2008, and 2016 verified a slight improvement. Overall, the proposed barometer of sustainability facilitated understanding the dimensional sustainability and comprehensive watershed sustainability and provided references for policy formulations and watershed management. Besides, the developed barometer has a high potential for evaluating sustainability for other watersheds worldwide.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.