Taiwan's government will focus on investment in cultural and creative industries as one of the industries, developed one of the main directions of its development is the development of creative cultural park in this policy, the central and local governments are beginning to operate Cultural and Creative Industry. In Kaohsiung, Kaohsiung City Government Department of Cultural Affairs to use the second channel connecting the third ship of the old quayside warehouse to build the Pier 2 Art Center. Opened nearly a decade, now Pier 2 Art District has become an increasingly diverse field. Pier 2 Art Center from actual observations, the researchers believe that quantitative indicators of the shape the impression is only the creative culture of a small part of the park should take a more open mind, diversity of point of view and to observe the creative and cultural in addition to the economy outside of the park for the inherent meaning and value.

Kelp forests are highly productive three-dimensional marine ecosystems that provide valuable ecosystem services globally. Along the coast of British Columbia, Macrocystis pyrifera and Nereocystis luetkeana are two key species that form surface-canopies that are vulnerable to both biotic and abiotic drivers; making it imperative to monitor and understand whether these ecosystems are changing in the face of climate change. The monitoring of kelp forests is commonly enhanced by use of remote sensing, which allows researchers to survey large portions of the coast where it would otherwise be difficult to collect data, and to use archived imagery for comparisons of historic and contemporary kelp forest trends. Generally, the remote sensing of kelp surface-canopy relies on differences in the high near-infrared (NIR; 700-1000 nm) signal of kelp and the low NIR signal of water. However, kelp surface-canopy reflectance signals can be affected by submergence under water, caused by oceanographic features like tides and currents, or simply due to differences in the morphology and buoyancy of kelp canopy structures. This submersion may cause uncertainties when estimating the surface-canopy area of kelp beds in remote sensing imagery. This research aims to understand the effects of submersion on the remote sensing of kelp surface-canopy. To address our goal, (i) Nereocystis canopy structures (bulb and blade) were submerged while collecting above-water hyperspectral measurements. The hyperspectral data into the bandwidths of high-resolution multispectral aerial and space-borne sensors and vegetation indices were calculated to understand the kelp detection limits when using shorter red-edge wavelengths (RE; 690-750 nm) instead of the longer NIR wavelengths. The results showed that submerged kelp can be detected deeper in the water column using shorter RE wavelengths compared to the more commonly used NIR wavelengths. Further, (ii) in situ hyperspectral data were also collected for the different surface-canopy structures and compared with UAV imagery, which showed that the buoyancy of the kelp canopy structures at the surface affected the relative magnitude of reflectance in both the RE and NIR and supported the findings of the submersion experiment. The total surface-canopy area derived from classification with both RE and NIR vegetation indices were compared in the UAV imagery, and the RE index detected roughly 18% more kelp than the NIR index, with no differences seen between Macrocystis and Nereocystis, or between high and low tide in beds larger than 150m2. Finally, (iii) to understand how submersion by tides and currents affect the ability to estimate surface-canopy area for both Macrocystis and Nereocystis, surface-canopy area was derived from multispectral unoccupied aerial vehicle (UAV) imagery and compared with in situ tide and current data, which showed that surface-canopy area had a strong negative linear relationship with tidal height at all sites regardless of species. Macrocystis occupied sites where currents were low (<10cm/s) and did not affect the surface-canopy. Therefore, the extent of all Macrocystis beds decreased at a similar rate over their tidal range (22.7 + 2.8%/m). Nereocystis beds occupied a wider range of current speeds (0.0 - 19.0 cm/s), and at sites with high current speeds (> 10 cm/s) increasing current and tidal height decreased surface-canopy area simultaneously, resulting in both a higher and more variable rate of decrease (30.5 + 9.1%/m) with increasing tidal height than Macrocystis. Together, this thesis addressed critical questions related to the effects of kelp submersion on the remote sensing of surface-canopy forming kelps, and we provide recommendation for remote sensors who wish to minimize errors when using remote sensing to map kelp forests. / Graduate

This thesis examines the &ldquo / unoccupied&rdquo / buildings in Ankara, which are not refunctioned due to the social, political, and economic reasons after 1980s. 1980s can be accepted as the breaking point in the social, economic and political history of Turkey. The significant policy of this period is the privatization of the governmental institutions, which includes the institutions of service, production and also finance. The building stock of privatized institutions is sold or assigned to the other institutions, or demolished. The object of the thesis is the unoccupied buildings in Ankara. The thesis particularly focuses on three of these buildings, which are Emlakbank, S&uuml / merbank and TEKEL Buildings in Ulus. The thesis aims to understand the common points how these buildings become unoccupied. The possessions of Emlakbank, S&uuml / merbank and TEKEL were transferred from the public sector (government) to the private sector (business) after 1980s. Their buildings, which were used as the central administration buildings are still unoccupied. Although they are physically present, their non-presence in terms of function can be considered to be creating &ldquo / voids&rdquo / of the city. For each building, related data is collected. The selected buildings and the institutions, they belonged to, are studied through their limited chronologies (their stories) by the help of the newspapers, interviews, laws, codes and regulations. The collected data helps to analyze the objects as a text, which provides evaluation of the total scene (i.e.the city of Ankara). By thoroughly investigating and discussing unoccupied buildings and their reasons of becoming unoccupied, this study makes an alternative reading of the transformation of Ankara.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-04-18T14:57:01Z No. of bitstreams: 1 pricillaaparecidaramosdasilva.pdf: 1357730 bytes, checksum: bec628f23697a75937d6745913a2d216 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-04-19T14:16:05Z (GMT) No. of bitstreams: 1 pricillaaparecidaramosdasilva.pdf: 1357730 bytes, checksum: bec628f23697a75937d6745913a2d216 (MD5) / Made available in DSpace on 2018-04-19T14:16:05Z (GMT). No. of bitstreams: 1 pricillaaparecidaramosdasilva.pdf: 1357730 bytes, checksum: bec628f23697a75937d6745913a2d216 (MD5) Previous issue date: 2017-08-30 / O objeto desse estudo são os moradores da periferia das cidades brasileiras que se organizam para criar alternativas para acessar os meios de vida, tais como renda e moradia, nesses tempos em que a crise estrutural do capital submete contingentes massivos ao desemprego, à desocupação. Nesse sentido, buscamos compreender o estágio atual da crise do capitalismo e os processos destrutivos do seu modo de produção movidos pela ideologia da modernidade. Observamos uma profunda transformação no mundo do trabalho como consequência do desenvolvimento das forças produtivas que expulsa o trabalho humano da produção. Assim, a crise do capital cria uma superpopulação de desempregados que, ao se exceder, já não exerce a função do exército industrial de reserva. Tornam-se desocupados, supérfluos, sujeitos ao descarte e destinados ao lixo nas periferias das cidades sem que o Estado lhes assegure proteção social. / The object of this study is the inhabitants of the periphery of Brazilian cities who organize themselves to create alternatives to access the means of life, such as income and housing, in those times when the structural crisis of capital submits massive contingents to unemployment. In this sense, we seek to understand the current stage of the crisis of capitalism and the destructive processes of its mode of production driven by the ideology of modernity. We see a profound transformation in the world of labor as a consequence of the development of the productive forces that drives out human labor from production. Thus, the crisis of capital creates a superpopulation of the unemployed who, when it exceeds, no longer exercises the function of the reserve industrial army. They become unoccupied, superfluous, subject to discarding as waste in the peripheries of cities without the state guaranteeing them social protection.

<div>Sea turtles are integral components of many marine ecosystems. Green turtles (Chelonia mydas) are generally herbivorous, feed primarily on seagrasses, and are endangered in the Caribbean. The species utilizes extensive marine habitats for foraging and migratory routes, and because of its broad distribution, it is difficult to conduct population assessments. Here, I assessed commonly used techniques for monitoring green turtles in the wild. Specifically: (1) biopsy sampling for molecular assays and (2) unoccupied aerial vehicles (UAVs) deployment and boat-based surveys for population monitoring.</div><div><br></div><div>Skin biopsies are collected from sea turtles for a variety of molecular analyses; however, very little information exists on the natural healing rates at the site of the biopsy in the wild. In Chapter 2, I monitored the healing rates of 17 juvenile green turtles in Eleuthera, The Bahamas, for up to 488 d after taking a 6mm biopsy tissue sample. Complete tissue repair and maturation was observed after a year and a half, and there was no evidence of infection at any point during the healing process. While scarring persisted for several months, biopsy sampling had minimal long-term impact.</div><div><br></div><div>UAVs are increasingly being used to monitor marine megafauna. In Chapter 3, I evaluated the efficacy of using UAVs to detect sea turtles when compared to boat-based surveys. During UAV surveys, the UAV was flown along preprogrammed routes in four creek systems. A boat survey was conducted simultaneously on the same path. I used regression analyses for each survey type to assess the effects of environmental variables on turtle detection rates My results indicate that there were no statistically significant difference between the numbers of turtle detected via boat or UAV surveys; however, there were clear differences in the time and potential cost associated with either method.</div>

Conservation of elasmobranch populations is often inhibited by a lack of data, particularly in understudied regions like the Red Sea. Survey efforts in this region have been infrequent and often highly localized. Establishing a broad baseline for elasmobranch diversity and abundance along the Saudi Arabian Red Sea coast could inform both conservation efforts and a nascent ecotourism industry. In this thesis, I describe a pilot study comparing biodiversity data from baited remote underwater video stations (BRUVS), unoccupied aerial vehicle surveys (UAVs), and eDNA sequencing at five islands in the Farasan Banks region of the Saudi Arabian Red Sea. Estimates of relative abundance were also compared between the BRUVS and UAVs. Each method identified species missed by the other two, but all three techniques exhibited clear habitat- and taxa-specific biases. I was able to identify key concerns for each approach that need to be addressed before large-scale implementation. If carefully planned and executed well, a full assessment of the Saudi Arabian coastline could establish a true baseline for shallow water elasmobranchs in the eastern Red Sea. Informing best conservation practices and identifying potential ecological attractions in accordance the environmental and economic goals of Saudi Arabia’s Vision 2030.

Inverse photoemission spectroscopy (IPES) is utilized for determining the unoccupied electron states of materials. It is a complementary technique to the widely used photoemission spectroscopy (PES) as it analyzes what PES cannot, the states above the Fermi energy. This method is essential to investigating the structure of a solid and its states. IPES has a broad range of uses and is only recently being utilized. This thesis describes the setup, calibration and operation of an IPES experiment. The IPES setup consists of an electron gun which emits electrons towards a sample, where photons are released, which are measured in isochromat mode via a photon detector of a set energy bandwidth. By varying the electron energy at the source, a spectrum of the unoccupied density of states can be obtained. Since IPES is not commonly commercially available the design consists of many custom made components. The photon detector operates as a bandpass filter with a mixture of acetone/argon and a CaF2 window setting the cutoff energies. The counter electronics consist of a pre-amplifier, amplifier and analyzer to detect the count rate at each energy level above the Fermi energy. Along with designing the hardware components, a Labview program was written to capture and log the data for further analysis. The software features several operating modes including automated scanning which allows the user to enter the desired scan parameters and the program will scan the sample accordingly. Also implemented in the program is the control of various external components such as the electron gun and high voltage power supply. The new setup was tested for different gas mixtures and an optimum ratio was determined. Subsequently, IPES scans of several sample materials were performed for testing and optimization. A scan of Au was utilized for the determination of the Fermi edge energy and for comparison to literature spectra. The Fermi edge energy was then used in a measurement of indium tin oxide (ITO) determining the conduction band onset. This allowed the determination of the "transfer gap" of ITO. Future experiments will allow further application of IPES on materials and interfaces where characterization of their electronic structure is desired.

La télédétection des forêts est devenue de plus en plus accessible grâce à l'utilisation de véhicules aériens inoccupés (UAV) et à l'apprentissage profond, ce qui permet d'obtenir des images répétées à haute résolution et d’observer les changements phénologiques à des échelles spatiales et temporelles plus importantes. Dans les forêts tempérées, à l'automne, la sénescence des feuilles se produit lorsque les feuilles changent de couleur et tombent. Cependant, l'influence de la sénescence foliaire sur la segmentation des espèces d'arbres à l'aide d'un réseau neuronal convolutif (CNN) n'a pas encore été évaluée. Nous avons acquis de l’imagerie haute résolution par UAV au-dessus d’une forêt tempérée au Québec à sept reprises entre mai et octobre 2021. Nous avons segmenté et identifié 23 000 couronnes d'arbres de 14 classes différentes pour entraîner et valider un CNN pour chaque acquisition d'imagerie. La meilleure segmentation (F1-score le plus élevé) était au début de la coloration des feuilles (début septembre) et le F1-score le plus bas au pic de la coloration automnale (début octobre). La chronologie de la sénescence varie considérablement d’une espèce à l’autre et au sein d’une même espèce, ce qui entraîne une grande variabilité du signal télédétecté. Les espèces d'arbres à feuilles caduques et à feuilles persistantes qui présentaient des traits distinctifs et moins variables dans le temps entre les individus ont été mieux classées. Bien que la segmentation des arbres dans une forêt hétérogène demeure un défi, l'imagerie UAV et l'apprentissage profond démontrent un grand potentiel pour la cartographie des espèces d'arbres. Les résultats obtenus dans une forêt tempérée où la couleur des feuilles change fortement pendant la sénescence automnale montrent que la meilleure performance pour la segmentation des espèces d'arbres se produit au début de ce changement de couleur. / Remote sensing of forests has become increasingly accessible with the use of unoccupied aerial vehicles (UAV), along with deep learning, allowing for repeated high-resolution imagery and the capturing of phenological changes at larger spatial and temporal scales. In temperate forests during autumn, leaf senescence occurs when leaves change colour and drop. However, the influence of leaf senescence in temperate forests on tree species segmentation using a Convolutional Neural Network (CNN) has not yet been evaluated. Here, we acquired high-resolution UAV imagery over a temperate forest in Quebec, Canada on seven occasions between May and October 2021. We segmented and labelled 23,000 tree crowns from 14 different classes to train and validate a CNN for each imagery acquisition. The CNN-based segmentation showed the highest F1-score (0.72) at the start of leaf colouring in early September and the lowest F1-score (0.61) at peak fall colouring in early October. The timing of the events occurring during senescence, such as leaf colouring and leaf fall, varied substantially between and within species and according to environmental conditions, leading to higher variability in the remotely sensed signal. Deciduous and evergreen tree species that presented distinctive and less temporally-variable traits between individuals were better classified. While tree segmentation in a heterogenous forest remains challenging, UAV imagery and deep learning show high potential in mapping tree species. Our results from a temperate forest with strong leaf colour changes during autumn senescence show that the best performance for tree species segmentation occurs at the onset of this colour change.

The world population is increasing and so is the housing shortage. 62 percent of Sweden's municipalities report a housing shortage. At the same time about 280 000 buildings in Sweden are abandoned. The purpose of this study is to investigate how municipalities can work to create better conditions to repopulate the abandoned houses in rural areas. This study is based on Uppvidinge municipality, but could also be applied in other municipalities in Sweden. To achieve a good result, both a semi-structured interview study, a literature review and a field study were conducted. The methods were chosen to provide a deeper understanding of the work other municipalities already have done regarding deserted houses. The research resulted in a strategy plan that describes how municipalities can work to identify abandoned houses and make them habitable again. The results showed that the inventory of abandoned houses should focus on communication rather than technical inventory work. In order for municipalities to succeed in the work of repopulating abandoned houses, they need financial support from politics, good communication and cooperation with other actors in the society, but also a passion for rural development.

Combiner les drones et l’intelligence artificielle afin de cartographier la végétation représente une nouvelle approche prometteuse susceptible d’améliorer la détection des espèces végétales exotiques envahissantes (EVEE). La résolution au sol élevée atteignable avec les drones et les innovations récentes en vision par ordinateur, notamment avec les réseaux neuronaux convolutifs, laissent penser qu'une détection précoce des EVEE serait possible, favorisant ainsi leur gestion. Dans cette étude, nous avons évalué la pertinence de cette approche pour cartographier l’emplacement du roseau commun (Phragmites australis subsp. australis) à l’intérieur d'un parc national situé dans le sud du Québec, Canada. Nous avons collecté des données à six dates distinctes durant la saison de croissance, couvrant des environnements présentant différents niveaux d'envahissement par le roseau. De façon générale, la performance du modèle était élevée pour les différentes dates et zones, surtout au niveau du rappel (moyenne globale de 0.89). Les résultats ont montré une augmentation de la performance pour atteindre un sommet à la suite de l’apparition de l’inflorescence en septembre (F1-score le plus haut à 0.98). De plus, une diminution de la résolution spatiale affectait négativement le rappel (diminution de 18% entre une résolution au sol de 0,15 cm pixel-1 et 1,50 cm pixel-1), mais n’avait pas un impact important sur la précision (diminution de 2%). Malgré des défis associés à la cartographie du roseau commun dans un contexte de gestion post-traitement, l'utilisation de drones et de l'apprentissage profond montre un grand potentiel pour la détection des EVEE lorsque appuyé par un jeu de données adapté. Nos résultats montrent que, d'un point de vue opérationnel, cette approche pourrait être un outil efficace pour accélérer le travail des biologistes sur le terrain et assurer une meilleure gestion des EVEE. / The combination of unoccupied aerial vehicles (UAVs) and artificial intelligence to map vegetation represents a promising new approach to improve the detection of invasive alien plant species (IAPS). The high spatial resolution achievable with UAVs and recent innovations in computer vision, especially with convolutional neural networks, suggest that early detection of IAPS could be possible, thus facilitating their management. In this study, we evaluated the suitability of this approach for mapping the location of common reed (Phragmites australis subsp. australis) within a national park located in southern Quebec, Canada. We collected data on six distinct dates during the growing season, covering environments with different levels of reed invasion. Overall, model performance was high for the different dates and zones, especially for recall (mean of 0.89). The results showed an increase in performance, reaching a peak following the appearance of the inflorescence in September (highest F1-score at 0.98). Furthermore, a decrease in spatial resolution negatively affected recall (18% decrease between a spatial resolution of 0.15 cm pixel-1 and 1.50 cm pixel-1) but did not have a strong impact on precision (2% decrease). Despite challenges associated with common reed mapping in a post-treatment monitoring context, the use of UAVs and deep learning shows great potential for IAPS detection when supported by a suitable dataset. Our results show that, from an operational point of view, this approach could be an effective tool for speeding up the work of biologists in the field and ensuring better management of IAPS.