Quantification and reduction of erroneous differences between images in remote sensing

The reliability of image data, along with the difficulty of accurately comparing images acquired at different times or from different sensors, is a generic problem in remote sensing. Measurement repeatability errors occur frequently and can substantially reduce the system’s ability to reliably quantify real spectral and spatial change in a target. This paper outlines methodologies for quantifying and reducing erroneous differences between monochrome and multispectral or hyperspectral images. [Each of these image types is acquired by an instrument that collects light photons across a variable range of the electromagnetic spectrum (often referred to as an image band). The hyperspectral image is often referred to as a hyperspectral cube with XY spatial dimensions and many Z bands (spectral demotions)]. In this paper, we specifically discuss the Pixel Block Transform (PBT), the Spectral Averaging Transform (SAT), and the Wavelet Transform (WAVEL). We briefly address sensor fusion. Results indicate that the PBT is a powerful cross-noise and repeatability error reducing tool, applicable to monochrome, multispectral, and hyperspectral images. The SAT is as powerful as the PBT in reducing error but is suitable only for hyperspectral imagery. WAVEL can reduce some of the finer scale noise, but it is not as powerful in reducing cross-noise as PBT or SAT and it requires some trial and error for selecting the appropriate wavelet function. It is important that those involved in developing statistically sound relationships between remotely sensed imagery and other data sources understand the problems and their solutions to prevent wasting time or developing relationships that are statistically insignificant or unstable, or that lead to faulty conclusions.     

Incorporating Uncertainty into Management Models for Marine Mammals

Abstract: Good management models and good models for understanding biology differ in basic philosophy. Management models must facilitate management decisions despite large amounts of uncertainty about the managed populations. Such models must be based on parameters that can be estimated readily, must explicitly account for uncertainty, and should be simple to understand and implement. In contrast, biological models are designed to elucidate the workings of biology and should not be constrained by management concerns. We illustrate the need to incorporate uncertainty in management models by reviewing the inadequacy of using standard biological models to manage marine mammals in the United States. Past management was based on a simple model that, although it may have represented population dynamics adequately, failed as a management tool because the parameter that triggered management action was extremely difficult to estimate for the majority of populations. Uncertainty in parameter estimation resulted in few conservation actions. We describe a recently adopted management scheme that incorporates uncertainty and its resulting implementation. The approach used in this simple management scheme, which was tested by using simulation models, incorporates uncertainty and mandates monitoring abundance and human-caused mortality. Although the entire scheme may be suitable for application to some terrestrial and marine problems, two features are broadly applicable: the incorporation of uncertainty through simulations of management and the use of quantitative management criteria to translate verbal objectives into levels of acceptable risk.     

Building institutions based on information disclosure: lessons from GRI's sustainability reporting

Global Reporting Initiative (GRI) is the best-known framework for voluntary reporting of environmental and social performance by business worldwide. Using extensive empirical data, including interviews and documentary analysis, we examine GRI's organizational field and conclude that since its modest beginnings in 1999 GRI has been by several measures a successful institutionalization project. But the institutional logic of this new entity, as an instrument for corporate sustainability management, leaves out one of the central elements of the initial vision for GRI: as a mobilizing agent for many societal actors. This emergent logic reflects GRI's dominant constituency – large global companies and financial institutions and international business management consultancies – and not the less active civil society organizations and organized labor. We attribute these developments to factors such as building GRI within the existing institutional structures; the highly inclusive multistakeholder process; and the underdeveloped base of information users. From the institutional theory perspective, this case shows how the process of institutionalization is deeply affected by initial strategies of the founders, and how it reproduces existing power relations. From the governance perspective, this case leads us to question the power of commodified information to mobilize civil society and to strengthen governance based on partnerships.     

Shifts in Microbial Communities, Microbial Biomass and Organic Matter Mineralization for Three Mediterranean Soils Contaminated By Metals

Microbial communities (phospholipid fatty acid pattern, bacterial growing strategies, eco-physiological index (EPI) and total bacteria counts, as a number of heterotrophic cuhurable bacteria), substrate-induced respiration (SIR), and nitrogen mineralization were studied in three Mediterranean soils at three different depth levels (A, B and C). Soils were experimentally treated with a final concentration of 1000 ppm of trace metals (Cu²⁺, Zn²⁺, Al³⁺, Fe²⁺, Pb²⁺, Ni²⁺, Mn²⁺, Cr³⁺ and Cd²⁺). Soils were stored in 571 plastic containers for one year, and watered with 1001 during this period. Leachate was recovered through a bottom tap. Samples of the three depths were studied. Soil microbial communities showed different effects to other studies presented in the literature, but carried out on non-Mediterranean soils. Dramatic differences were found between treated soils and untreated ones, but not between soils or horizons. the treated soil displayed a decrease in CFUs, SIR N-mineralization and EPI together with a dominance of r-growing strategists. the relative moles percent of several PLFAs, especially 15:0, 16: 1ω7, cy17: 0, br18:0 and 18: 1ω7 decreased because of the pollution of soils, whereas 10Me16, 18:2ω6, cy19:0, i16:0 and br17:0 showed higher values than in untreated soils.