Legal Challenges and Market Rewards to the Use and Acceptance of Remote Sensing and Digital Information as Evidence

Bakgrund I den nutida forskningen är det essentiellt att företag tar hänsyn till medarbetarnas motivation så att de gynnas av det arbetssätt som tillämpas. En arbetsmetod som blivit allt vanligare är konceptet Lean som ursprungligen kommer från den japanska bilindustrin. Lean har idag utvecklats till ett allmängiltigt koncept som tillämpas i flertalet branscher världen över. Trots att konceptet innebär flertalet positiva aspekter har det fått utstå stark kritik när det kommer till de mänskliga aspekterna och forskare har ställt sig frågan om Lean är "Mean". Kritiken härleds främst till medarbetares arbetsmiljö i form av stress och brist på variation, självbestämmande, hälsa och välmående. Få empiriska studier har däremot genomförts som undersöker konsekvenserna som Lean får på medarbetares upplevda motivation. Syfte Vårt syfte är att undersöka och öka förståelsen för medarbetares upplevelser av motivationen i företag som tillämpar Lean. Vidare har studien för avsikt att utreda om det föreligger en paradox mellan Lean och vad som motiverar medarbetare på en arbetsplats. Metod Studien har utgått från en kvalitativ metod via intervjuer. För att göra en djupare undersökning och analysera hur vårt fenomen, motivation, upplevs i en kontext med Lean tillämpade vi Små-N-studier. Vi har även haft en iterativ forskningsansats som förenat den deduktiva och induktiva ansatsen där studien pendlat mellan teorier och empiriska observationer fram tills det slutgiltiga resultatet. Slutsatser Utefter medarbetarnas upplevelser har vi identifierat att det inte föreligger någon paradox mellan Lean och motivation eftersom övervägande antal medarbetare upplevde att de är motiverade även om företaget tillämpar Lean. Dock har studien kunnat urskilja både stödjande och motverkande faktorer när det kommer till medarbetarnas upplevda arbetsförhållanden som i sin tur inverkar på motivationen. De motverkande faktorerna menar vi främst beror på att arbetsförhållandena i somliga fall innehåller höga prestationskrav, målstyrning samt standardiseringar. Vidare upplevs motivationen överlag som mer positiv när företagen använder en mjukare form av Lean där samtliga medlemmars intressen beaktas.Background In modern research, it is essential that companies consider employees’ motivation so that they benefit from the applied practices. A working method that has become increasingly common is the concept Lean, which has its origin in the Japanese automotive industry. Today, Lean has evolved into a universal concept that is applied in many industries worldwide. Although the concept involves numerous positive aspects it has endured strong criticism when it comes to the human aspects and researchers have raised the question if Lean is "Mean". Criticism is derived primarily to employees’ working conditions in terms of stress and lack, variation, autonomy, health and wellbeing. However, few empirical studies have been carried out that examines the impact that Lean has on employees’ experienced motivation. Aim The aim is to increase the understanding of employees’ experienced motivation in companies that practice Lean. Further on the study has the intention to investigate if there is a paradox between Lean and what motivates employees on work. Methodology The study has been conducted through a qualitative method by interviews and to be able to do a deeper examination and analyze how our phenomenon, motivation, is experienced in a Lean context we applied small-N-studies. Our strategy has been iterative, combining both a deductive and inductive approach, where the study has varied between theories and empirical observations until the final result. Conclusions We have identified that there is no paradox between Lean and motivation since the majority of employees’ experienced that they are motivated even though the company practice Lean. Nevertheless the study shows that there are both supportive and counteractive factors when it comes to the employees’ experienced working conditions. The counteractive factors consists foremost of high performance standards, goal steering and standardizations, and have in some cases a negative influence on the working conditions. Furthermore the experienced motivation is more positive overall when the companies use a softer form of Lean where all the members’ interests are taken into account

An object-based classification approach for mapping "migrant housing" in the mega-urban area of the Pearl River Delta (China)

Urban areas develop on formal and informal levels. Informal development is often highly dynamic, leading to a lag of spatial information about urban structure types. In this work, an object-based remote sensing approach will be presented to map the migrant housing urban structure type in the Pearl River Delta, China. SPOT5 data were utilized for the classification (auxiliary data, particularly up-to-date cadastral data, were not available). A hierarchically structured classification process was used to create (spectral) independence from single satellite scenes and to arrive at a transferrable classification process. Using the presented classification approach, an overall classification accuracy of migrant housing of 68.0% is attained

Impervious surface estimation using remote sensing images and gis : how accurate is the estimate at subdivision level?

Impervious surface has long been accepted as a key environmental indicator linking development to its impacts on water. Many have suggested that there is a direct correlation between degree of imperviousness and both quantity and quality of water. Quantifying the amount of impervious surface, however, remains difficult and tedious especially in urban areas. Lately more efforts have been focused on the application of remote sensing and GIS technologies in assessing the amount of impervious surface and many have reported promising results at various pixel levels. This paper discusses an attempt at estimating the amount of impervious surface at subdivision level using remote sensing images and GIS techniques. Using Landsat ETM+ images and GIS techniques, a regression tree model is first developed for estimating pixel imperviousness. GIS zonal functions are then used to estimate the amount of impervious surface for a sample of subdivisions. The accuracy of the model is evaluated by comparing the model-predicted imperviousness to digitized imperviousness at the subdivision level. The paper then concludes with a discussion on the convenience and accuracy of using the method to estimate imperviousness for large areas

TaLAM: Mapping Land Cover in Lowlands and Uplands with Satellite Imagery

End-of-Project ReportThe Towards Land Cover Accounting and Monitoring (TaLAM) project is part of Ireland’s response to creating a national land cover mapping programme. Its aims are to demonstrate how the new digital map of Ireland, Prime2, from Ordnance Survey Ireland (OSI), can be combined with satellite imagery to produce land cover maps

Riparian Corridors Encroachment and Flood Risk Assessment in Ile-Ife: A GIS Perspective

The Publisher's final version can be found by following the DOI link.Recent development and expansion of paved surfaces as a result of urban growth has resulted in encroachment of riparian corridors, the immediate effect of which poses flood risk to affected areas. Geographic Information System (GIS) method was employed in this study to determine the level of encroachment as well as areas susceptible/at risk to flood and flooding. Results from the study indicated that urban and agricultural land uses had encroached significantly on the riparian corridor and had disrupted the ecosystem services of the corridor. Results also indicated that major parts of the watershed had low flood risk but serious encroachment exists therein. Buildings as many as 1129 had already encroached into the 30 metres minimum setback standard which are mainly riparian corridor and the buildings which had encroached into the corridor fall within the high flood risk zone of the watershed

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

Using high resolution optical imagery to detect earthquake-induced liquefaction: the 2011 Christchurch earthquake

Using automated supervised methods with satellite and aerial imageries for liquefaction mapping is a promising step in providing detailed and region-scale maps of liquefaction extent immediately after an earthquake. The accuracy of these methods depends on the quantity and quality of training samples and the number of available spectral bands. Digitizing a large number of high-quality training samples from an event may not be feasible in the desired timeframe for rapid response as the training pixels for each class should be typical and accurately represent the spectral diversity of that specific class. To perform automated classification for liquefaction detection, we need to understand how to build the optimal and accurate training dataset. Using multispectral optical imagery from the 22 February, 2011 Christchurch earthquake, we investigate the effects of quantity of high-quality training pixel samples as well as the number of spectral bands on the performance of a pixel-based parametric supervised maximum likelihood classifier for liquefaction detection. We find that the liquefaction surface effects are bimodal in terms of spectral signature and therefore, should be classified as either wet liquefaction or dry liquefaction. This is due to the difference in water content between these two modes. Using 5-fold cross-validation method, we evaluate performance of the classifier on datasets with different pixel sizes of 50, 100, 500, 2000, and 4000. Also, the effect of adding spectral information was investigated by adding once only the near infrared (NIR) band to the visible red, green, and blue (RGB) bands and the other time using all available 8 spectral bands of the World-View 2 satellite imagery. We find that the classifier has high accuracies (75%–95%) when using the 2000 pixels-size dataset that includes the RGB+NIR spectral bands and therefore, increasing to 4000 pixels-size dataset and/or eight spectral bands may not be worth the required time and cost. We also investigate accuracies of the classifier when using aerial imagery with same number of training pixels and either RGB or RGB+NIR bands and find that the classifier accuracies are higher when using satellite imagery with same number of training pixels and spectral information. The classifier identifies dry liquefaction with higher user accuracy than wet liquefaction across all evaluated scenarios. To improve classification performance for wet liquefaction detection, we also investigate adding geospatial information of building footprints to improve classification performance. We find that using a building footprint mask to remove them from the classification process, increases wet liquefaction user accuracy by roughly 10%.Published versio