The urban spatial structure reflexes the local particularities produced during the historical 25 development of a city. Currently high spatial resolution imagery and LiDAR data are used to 26 derive numerical attributes to characterize the intra-urban structure and morphology. The urban-27 block boundaries have been frequently used to define the units to extract metrics from the 28 remotely sensed data. In this paper, we propose to complement those metrics with a set of 29 descriptors of the streets surrounding the urban blocks that numerically characterize the 30 geometry, presence of vegetation, and relationship with buildings. To carry out this purpose we 31 also introduce a methodology to define the street area related with an urban block from which 32 derive the urban metrics referred to the street. The assessment of these metrics is fulfilled using 33 one-way ANOVA procedure and decision trees classifier. These results reveal that street 34 metrics, and particularly those describing the street geometry, are suitable to enhance the 35 2 discrimination of complex urban typologies. Thus, the overall classification accuracy increases 36 from 72.7% to 81.1% when adding the street descriptors. The results of this study demonstrate 37 the usefulness of the metrics describing the street properties to complement the information 38 derived from the urban blocks and to improve the characterization of urban areas. 39 40 Highlights 41We propose a set of urban metrics to describe the streets with remotely sensed data 42 A methodology to relate the street space to urban blocks is defined 43Results show that street metrics are useful to improve the characterization of cities 44 45

No abstract

Aim of study: To propose a methodology to establish motivations underlying wildland fire episodes by analyzing both the socioeconomics of the affected territory and the geographical distribution of the wildfire.Area of study: The wildfires occurred during 2006 in Galicia, in the NW of Spain, were analyzed and compared regard to the previous years.Material and methods: The proposed methodology in this study is divided into four steps: (a) definition of the forest context, (b) fire episode and socioeconomic data collection, (c) geospatial representation through map production, and (d) joint analysis and data interpretation. A combined analysis of the spatial and temporal coincidence of wildfire and the socioeconomic activities is performed.Main results: A combined analysis of the spatial and temporal coincidence of wildfire dynamics and the socioeconomic activitiesallow us to assess and to interpret wildfire causes and motivations of socioeconomic groups. In our area study, a broad analysis indicates that wildfire recurrence within this region is related to an accelerated rural flight process which exacerbates the conflict between rural and urban models.Research highlights: The socio-geographical analysis of a territory’s wildfire dynamics enables us to establish possible causes and motivations of their origins. Providing the specific contextual and socioeconomic information, this methodology has potential applicability across varied study locations.Key words: forest; wildfires’ causes; geographical distribution; socioeconomic analysisAbbreviations: FAA (Forest Affected Area); IFN (Inventario Forestal Nacional); GIS (Geographical Information Systems); IGE (Instituto Galego de Estadística); IGN (Instituto Nacional de Estadística); MVMC (Montes Vecinales en Mano Común)

World's human dynamics can be parameterized with metrics that explain the current model of economic growth and its sustainability. Changes in the world's human dynamics are crucial for understanding the current state of the world, which is faced with increasing challenges related to globalization. In this paper, we propose to analyze the shifting locations of centers of gravity of four basic global indicators (these are Gross Domestic Product, carbon dioxide emissions, population, and urban population) for the period 1960e2016. The spatial locations of the respective centers of gravity (one per year) draw some traces that explain, at least partially, relevant changes on different world's human dynamics at a global level. These traces and dynamics are further discussed. In addition, these traces are fundamental for predicting upcoming trends for the next few years. Results shown here may help political leaders and policymakers for solving upcoming and future global challenges related to the current economic system and its impact on the environment.

The point density is a preeminent parameter on airborne laser scanner surveys. It is not only related to accuracy but costs and savings. The lack of uniformity of the point density across the survey is wellknown in the scientific community. This paper analyzes the behaviour of the point density derived by an oscillating mirror laser scanner on different single strips on flat bare ground in order to estimate a meaningful mean density value. The variation of the point density at both extreme ends of the oscillating mirror scan is meaningful. It will be demonstrated that excluding the extreme sectors across the strip corresponding to 1/8 of the swath width (12.5% of the sampling area, half in each side) for the computation of the mean density value is enough to satisfy light detection and ranging (LiDAR) specifications for national level surveys.