An Inquiry of Changes in Environmental Governance by Community-driven Process

Urban environmental depletion has been a critical problem among industrialized-transformed societies, especially at the local level where administrative authorities’ capacity lags behind changes. Derived from governance concept, the idea of civil society inclusion is highlighted. Focusing on an agglomerated case study, Bang Plee Community in Thailand, this research investigates on a non-state sector, 201-Community organization, as an agent for changes to improve urban environments on solid waste collection. Two roles are contested: as an agent for neighborhood internal change and as an intermediary toward governance changes in state-civil society interaction. By employing longitudinal analysis via a project intervention as research experiment, the outcomes of both roles are detected portrayed in three spheres: state, state-civil society interaction, and civil society sphere. It discovers in the research regarding agglomerated context that as an internal changes for environmental betterment, 201-Community organization operation brings on waste reduction at the minimal level. Community-based organization as an agent for changes – despite capacity input it still limited in efficiency and effectiveness – can mobilize fruitfully only at the individual and network level of civil society sectors, while fails managing at the organizational level. The positive outcomes result by economic waste incentive associated with a limited-bonded group rather than the rise of awareness at large. As an intermediary agent for shared governance, the community-based organization cannot bring on mutual dialogue with state as much as cannot change the state’s operation arena of solid waste management. The findings confine the shared governance concept that it does not applicable in agglomerated locality as an effective outcome, both in terms of being instrumental toward civil society inclusion and being provocative of internal change. Shared environmental governance as summarized in this research can last merely a community development action. It distances significantly from civil society inclusion and empowerment. However, the research proposes that community-based environmental management and shared governance toward civil society inclusion in urban environmental improvement are still an expectable option and reachable if their factors and conditions of key success and failure are intersected with a particular context. Further studies demand more precise on scale, scope, and theses factors of environmental management operation operated by civil society sectors.

Digital image analysis as a tool to estimate legume contributions in legume-grass swards

Summary: Productivity and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. For these objectives the botanical composition of the swards is of particular importance, especially, the content of legumes due to their ability to fix airborne nitrogen. As it can vary considerably within a field, a non-destructive detection method while doing other tasks would facilitate a more targeted sward management and could predict the nitrogen supply of the soil for the subsequent crop. This study was undertaken to explore the potential of digital image analysis (DIA) for a non destructive prediction of legume dry matter (DM) contribution of legume-grass mixtures. For this purpose an experiment was conducted in a greenhouse, comprising a sample size of 64 experimental swards such as pure swards of red clover (Trifolium pratense L.), white clover (Trifolium repens L.) and lucerne (Medicago sativa L.) as well as binary mixtures of each legume with perennial ryegrass (Lolium perenne L.). Growth stages ranged from tillering to heading and the proportion of legumes from 0 to 80 %. Based on digital sward images three steps were considered in order to estimate the legume contribution (% of DM): i) The development of a digital image analysis (DIA) procedure in order to estimate legume coverage (% of area). ii) The description of the relationship between legume coverage (% area) and legume contribution (% of DM) derived from digital analysis of legume coverage related to the green area in a digital image. iii) The estimation of the legume DM contribution with the findings of i) and ii). i) In order to evaluate the most suitable approach for the estimation of legume coverage by means of DIA different tools were tested. Morphological operators such as erode and dilate support the differentiation of objects of different shape by shrinking and dilating objects (Soille, 1999). When applied to digital images of legume-grass mixtures thin grass leaves were removed whereas rounder clover leaves were left. After this process legume leaves were identified by threshold segmentation. The segmentation of greyscale images turned out to be not applicable since the segmentation between legumes and bare soil failed. The advanced procedure comprising morphological operators and HSL colour information could determine bare soil areas in young and open swards very accurately. Also legume specific HSL thresholds allowed for precise estimations of legume coverage across a wide range from 11.8 - 72.4 %. Based on this legume specific DIA procedure estimated legume coverage showed good correlations with the measured values across the whole range of sward ages (R2 0.96, SE 4.7 %). A wide range of form parameters (i.e. size, breadth, rectangularity, and circularity of areas) was tested across all sward types, but none did improve prediction accuracy of legume coverage significantly. ii) Using measured reference data of legume coverage and contribution, in a first approach a common relationship based on all three legumes and sward ages of 35, 49 and 63 days was found with R2 0.90. This relationship was improved by a legume-specific approach of only 49- and 63-d old swards (R2 0.94, 0.96 and 0.97 for red clover, white clover, and lucerne, respectively) since differing structural attributes of the legume species influence the relationship between these two parameters. In a second approach biomass was included in the model in order to allow for different structures of swards of different ages. Hence, a model was developed, providing a close look on the relationship between legume coverage in binary legume-ryegrass communities and the legume contribution: At the same level of legume coverage, legume contribution decreased with increased total biomass. This phenomenon may be caused by more non-leguminous biomass covered by legume leaves at high levels of total biomass. Additionally, values of legume contribution and coverage were transformed to the logit-scale in order to avoid problems with heteroscedasticity and negative predictions. The resulting relationships between the measured legume contribution and the calculated legume contribution indicated a high model accuracy for all legume species (R2 0.93, 0.97, 0.98 with SE 4.81, 3.22, 3.07 % of DM for red clover, white clover, and lucerne swards, respectively). The validation of the model by using digital images collected over field grown swards with biomass ranges considering the scope of the model shows, that the model is able to predict legume contribution for most common legume-grass swards (Frame, 1992; Ledgard and Steele, 1992; Loges, 1998). iii) An advanced procedure for the determination of legume DM contribution by DIA is suggested, which comprises the inclusion of morphological operators and HSL colour information in the analysis of images and which applies an advanced function to predict legume DM contribution from legume coverage by considering total sward biomass. Low residuals between measured and calculated values of legume dry matter contribution were found for the separate legume species (R2 0.90, 0.94, 0.93 with SE 5.89, 4.31, 5.52 % of DM for red clover, white clover, and lucerne swards, respectively). The introduced DIA procedure provides a rapid and precise estimation of legume DM contribution for different legume species across a wide range of sward ages. Further research is needed in order to adapt the procedure to field scale, dealing with differing light effects and potentially higher swards. The integration of total biomass into the model for determining legume contribution does not necessarily reduce its applicability in practice as a combined estimation of total biomass and legume coverage by field spectroscopy (Biewer et al. 2009) and DIA, respectively, may allow for an accurate prediction of the legume contribution in legume-grass mixtures.

Evolutionäre Optimierung von Mensch-Maschine-Schnittstellen

Vorgestellt wird eine weltweit neue Methode, Schnittstellen zwischen Menschen und Maschinen für individuelle Bediener anzupassen. Durch Anwenden von Abstraktionen evolutionärer Mechanismen wie Selektion, Rekombination und Mutation in der EOGUI-Methodik (Evolutionary Optimization of Graphical User Interfaces) kann eine rechnergestützte Umsetzung der Methode für Graphische Bedienoberflächen, insbesondere für industrielle Prozesse, bereitgestellt werden. In die Evolutionäre Optimierung fließen sowohl die objektiven, d.h. messbaren Größen wie Auswahlhäufigkeiten und -zeiten, mit ein, als auch das anhand von Online-Fragebögen erfasste subjektive Empfinden der Bediener. Auf diese Weise wird die Visualisierung von Systemen den Bedürfnissen und Präferenzen einzelner Bedienern angepasst. Im Rahmen dieser Arbeit kann der Bediener aus vier Bedienoberflächen unterschiedlicher Abstraktionsgrade für den Beispielprozess MIPS ( MIschungsProzess-Simulation) die Objekte auswählen, die ihn bei der Prozessführung am besten unterstützen. Über den EOGUI-Algorithmus werden diese Objekte ausgewählt, ggf. verändert und in einer neuen, dem Bediener angepassten graphischen Bedienoberfläche zusammengefasst. Unter Verwendung des MIPS-Prozesses wurden Experimente mit der EOGUI-Methodik durchgeführt, um die Anwendbarkeit, Akzeptanz und Wirksamkeit der Methode für die Führung industrieller Prozesse zu überprüfen. Anhand der Untersuchungen kann zu großen Teilen gezeigt werden, dass die entwickelte Methodik zur Evolutionären Optimierung von Mensch-Maschine-Schnittstellen industrielle Prozessvisualisierungen tatsächlich an den einzelnen Bediener anpaßt und die Prozessführung verbessert.