Citizen participation, quality of life and territorial trans-regional justice: A social basis for common good

For globalized local worlds undergoing transformation, territorial interventions are increasingly producing larger social and environmental impacts. Macro-interventions profoundly alter the functioning of ecosystems and human habitats or communities, becoming inclusive in extreme situations of exploitation or extraction, risking their very existence. Therefore it is necessary to develop a system or Social Baseline that clearly establishes the philosophical bases, restrictions and criteria that regulate and curb the negative impacts of such interventions. This implies defining methods for citizen participation. This article focuses on defining a basic framework with criteria and indicators that regulate the impact of macro-interventions - of different natures - on human territories and communities

Tabacaleros al grito de guerra: The Mexican tobacco industry and the U.S.-Mexico War

This study analyzes the role of the Mexican tobacco industry during the chaotic years from 1845 to 1847. In nineteenth-century Mexico the tobacco industry was an important financial contributor to Mexican government’s efforts to sustain the war against the United States. Without any significant success, the Mexican government tried to confront and solve the problems limiting the amount of revenues that was expected from the tobacco industry. Regional interests, political factionalism, administrative negligence, and tobacco contraband limited the amount of money the tobacco industry contributed. In spite of all the problems the tobacco industry experienced between 1845 and 1847, the federal government still received significant financial assistance from that industry and the people involved

Latino Immigrant Narratives from Maryland

Despite the intensive work conducted by scholars to capture and preserve the memories of Latino immigrants in the Los Angeles, New York, Miami, and Chicago metro areas, relatively little is known about the history and experiences of this immigrant group living in the Washington metro area, home to twelve of the top sixty Latino communities in the nation.62 Currently, there are 906,000 Latinos living in the region.63 This paper showcases some of the perspectives of Latino immigrants through oral history interviews conducted by students in two undergraduate history courses offer at Montgomery College (MC)64 : “History of Latinos in the US” and “Latin American History.” Students in these classes are required to identify immigrant community members and to request their cooperation for being interviewed. The process of collecting, creating, and preserving the life stories of these immigrants stimulates a keen interest in how both place of origin and historical experience inform the lives of immigrants. It gives the students too the opportunity to understand the impact of the past on immigrant experience and to gain an understanding of immigrants’ aspirations, hopes, and fears as well as their positive contributions to American society and culture. During the course of a semester, students conduct, transcribe, and construct oral histories and compose brief, one-page reflections on their interviews. Specifically, students document how their assumptions about the historical immigrant experience have changed as a result of their participation in this oral history project. The transcripts generated by these students represent original and relevant primary sources contributing an understanding of how the past is prologue for American immigrants going forward and foster an appreciation of the immigrant presence among us

Morphological Segmentation of Building Façade Images

ISBN : 978-1-4244-5653-6International audienceIn this paper, we describe an automatic method for segmentation of building façade images. First, individual façades are isolated from general city block images. This step is based on accumulation of directional color gradients, assuming that façade structures are aligned. Then sky region is detected based on segmentation approach and color marker extraction. Finally, the images are split in floors using directional color gradient accumulation, as well. Our approach introduces several morphological filters to augment the robustness to problems such as: textured balconies, some specular reflections of the bright windows and small obstacles in images. The experimental results show the performance of our approach

Segmentation et Interprétation de Nuages de Points pour la Modélisation d'Environnements Urbains

National audienceIn this article, we present a method for detection and classification of artifacts at the street level, in order to filter cloud point, facilitating the urban modeling process. Our approach exploits 3D information by using range image, a projection of 3D points onto an image plane where the pixel intensity is a function of the measured distance between 3D points and the plane. By assuming that the artifacts are on the ground, they are detected using a Top-Hat of the hole filling algorithm of range images. Then, several features are extracted from the detected connected components and a stepwise forward variable/model selection by using the Wilk's Lambda criterion is performed. Afterward, CCs are classified in four categories (lampposts, pedestrians, cars and others) by using a supervised machine learning method. The proposed method was tested on cloud points of Paris, and have shown satisfactory results on the whole dataset.Dans cet article, nous présentons une méthode pour la détection et la classification d'artefacts au niveau du sol, comme phase de filtrage préalable à la modélisation d'environnements urbains. La méthode de détection est réalisée sur l'image profondeur, une projection de nuage de points sur un plan image où la valeur du pixel correspond à la distance du point au plan. En faisant l'hypothèse que les artefacts sont situés au sol, ils sont détectés par une transformation de chapeau haut de forme par remplissage de trous sur l'image de profondeur. Les composantes connexes ainsi obtenues, sont ensuite caractérisées et une analyse des variables est utilisée pour la sélection des caractéristiques les plus discriminantes. Les composantes connexes sont donc classifiées en quatre catégories (lampadaires, piétons, voitures et "Reste") à l'aide d'un algorithme d'apprentissage supervisé. La méthode a été testée sur des nuages de points de la ville de Paris, en montrant de bons résultats de détection et de classification dans l'ensemble de données

Filtering of Artifacts and Pavement Segmentation from Mobile LiDAR Data

International audienceThis paper presents an automatic method for filtering and segmenting 3D point clouds acquired from mobile LIDAR systems. Our approach exploits 3D information by using range images and several morphological operators. Firstly, a detection of artifacts is carried out in order to filter point clouds. The artifact detection is based on a Top-Hat of hole filling algorithm. Secondly, ground segmentation extracts the contour between pavements and roads. The method uses a quasi-flat zone algorithm and a region adjacency graph representation. Edges are evaluated with the local height difference along the corresponding boundary. Finally, edges with a value compatible with the pavement/road difference (about 14[ cm ] ) are selected. Preliminary results demonstrate the ability of this approach to automatically filter artifacts and segment pavements from 3D data