Spatial Distribution Of Settlements Research Articles

Defining priorities for wildfire mitigation actions at the local scale: insights from a novel risk analysis method applied in Portugal

IntroductionIn Portugal, the 2017 fire season was particularly extreme, leading to an unprecedented large number of fatalities, injured people, destruction of houses and infrastructures. These dramatic outcomes have contributed to raise awareness regarding the importance of ensuring the safety of people and assets from high intensity uncontrollable wildfires. It is crucial to identify the settlements at higher risk and the most suitable mitigation actions that can maximize the protection of people and assets.MethodsWe developed a simple methodology that combines exposure and vulnerability to estimate wildfire risk at the local level. Exposure was estimated using a fire spread simulation approach that was used to determine the probability of (i) a wildfire generating firebrands that could affect a settlement and (ii) a high intensity wildfire occurring adjacent to a settlement. Exposure was estimated using two fuel scenarios created to represent the current year of 2023 (short-term scenario) and 2030, assuming that no fuel management nor large fires occur in the meantime (medium-term worst-case scenario). Vulnerability was determined by the (i) Index of Total Dependence (IDT), and (ii) evacuation difficulty. Exposure and vulnerability metrics were normalized in percentiles, distributed into quadrants and combined to provide six levels of wildfire risk. For each vulnerability\exposure combination, we proposed a set of priority mitigation actions. The methodology was applied to three areas in Portugal where the risk estimates were analyzed and compared with the implementation rate of two risk mitigation programs already in place.ResultsResults showed that 8.7% of the settlements had “very high” wildfire risk and about 19.5% had “high” wildfire risk, potentially affecting 8,403 and 34,762 inhabitants, respectively. The spatial distribution of settlements at higher risk was very heterogeneous across the study areas and the total fraction ranged between 14% in Coimbra to 36% in Barlavento Algarvio. The overall implementation of mitigation programs in the study areas is very low, with only around 1% of the settlements in “very high” risk having any of the mitigation programs implemented. Conversely, our results also suggest that the implementation rate in settlements classified in lower risk classes is disproportionately high.DiscussionThe application of this risk analysis methodology can be used to assess the implementation status of mitigation actions, and contribute to tailor the actions that maximize the protection of people and assets according to the specific conditions found in each targeted area.

Research on Spatial Distribution of Settlements in the Upper Reaches of the Minjiang River

Research on Spatial Distribution of Settlements in the Upper Reaches of the Minjiang River

[Spatial differentiation characteristics and influencing factors of urban and rural settlements in Tibet, China].

Located in the hinterland of the Qinghai-Tibet Plateau, Tibet has very limited space sui-table for human living. The spatial distribution of settlements in Tibet is restricted by multiple factors. To reveal the spatial distribution characteristics and explore the main influencing factors of settlements in Tibet, we extracted patch data from the high-resolution images of urban and rural settlements in Tibet based on visual interpretation. Methods such as the kernel density analysis, space hotspot detection, Geodetector and others were applied to analyze the spatial differentiation characteristics and influencing factors, with the aim to provide reference for future settlements selection and formulation of relevant policies on regional economic development in the plateau region. The results showed that urban and rural settlements in Tibet had a clustering pattern, with different overall density distribution. Lhasa was a high-density core, and Ngari Prefecture, Qamdo, and Nyingchi were the "core-edge" structures with low-density edges. The settlement density of Lhasa was as high as 220 ind·km-2, while that of Ngari Prefecture, Qamdo and Nyingchi was only 5.7 ind·km-2. The gap between the two regions was more than 43 times. The clustering of high and low value clusters in urban and rural settlements was remarkable. The number of high-value of large plaques was rare, and the number of low-values of small plaques was dominant. The area of high-value cluster accounted for only 3.7%, concentrated in Lhasa and Lhoka. The proportion of low value cluster area reached 67.2%, mainly distributed in Ngari Prefecture and Nagqu on the Qiangtang Plateau. There were six types of urban and rural settlements in Tibet, which formed two circle structures in the "One River and Two Streams" basin and the "Three Rivers" basin. From the inside to the outside, the large plaque-dominated type, medium-density and cluster-like type, high-density and point-scattered type, low-density and point-scattered type and high-altitude and uninhabited type was successively distributed. Lhasa was dominated by medium-density and cluster-like type, accounting for 31%. Lhoka was dominated by low-density and point-scattered type, accounting for 38%. Qamdo was mainly low-density and point-scattered type, accounting for 51%. The Ngari Prefecture, Nagqu and Shigatse were dominated by high-altitude and uninhabited type, and the proportion of the Ngari Prefecture was as high as 64%. The effects of different factors on the spatial distribution of urban and rural settlements in Tibet were distinctly different. The population and GDP were highly decisive for the distribution of urban and rural settlements. In addition, urban settlements showed strong road orientation, while rural settlements were more characterized by river orientation.

Cultural landscap’s changes of Solyna commune

The main aim of the present work was to analyze the dynamics of settlements from the 2nd half of the 18th century to 2nd half of 20th century in Solyna commune (in polish Solina), in Lesko district, Podkarpackie voivodeship in Eastern Poland. There was analyzed the Solyna commune in terms of the changes of settlements and applied maps together with published historical data for the analysis of changes in its structure. The first was the historical map, in other words the tactical map of «WIG- Military Institute of Geography». Next maps from the «WMS-Web Map Service, Geoportal» were analyzed. Changes in the number of villages and households population dynamics for Greek-catholics, «Latynnykys» and Jews for the year 1785 were evaluated applying ArcGIS 10.3 program. Ukrainian ones were evaluated using ArcGIS program in comparison with the number of Poles and Jews for the year 1939. Ethnic and religious composition from the 2nd half of the 18th century to 2nd half of 20th century and the character of settlements distribution in Solyna commune was evaluated based on the study of spatial distribution of settlements with the use of Spatial Statistics (Spatial Autocorrelation Global Moran's test, Standard Deviational Ellipse and Mean Centre). In 1785 there were 80,55% of Greek-catholics and in 1939 there were 89,82% of Ukrainians in Solyna commune. There was confirmed a similar configuration of Standard Deviation Ellipse and Mean Center for Greek-catholic for the year 1785 and Ukrainians for the year 1939 in Solyna commune. The scale and results of such changes are essential for future research, mainly in terms of the change of traditional village system infrastructure and culture.

Network and Geography: Dependence and Disparity Between Human Settlement Pattern and Socioeconomic Network in Chengui, China

AbstractThe spatial distribution of settlements in a heterogeneous landscape matrix influences the capacity of people to form and maintain relationships. Although such a perspective has gained seve...

Urban Influence on Settlement Patterns: A Study of Ahmedabad Metropolitan Region

The evolution of the settlement pattern of any area is governed by a number of forces which vary from one region to another and hence, we get varying patterns in the spatial distribution of settlements. The conventional visual judgment of the settlement pattern as sparse, dispersed, agglomerated or dens has been replaced by more scientific characterization with the help of the nearest neighbour index. Nearest neighbour analysis (NND) helps in distinguishing three kinds of basic distribution of points, namely uniform (even), random and clustered. The problem of nearest neighbour distance analysis is that of finding a single index for any given pattern, running on a continuous scale, i.e. from extreme when all the points are clustered to the other extreme a situation in which all the points are distributed uniformly. In this paper an attempt has been made to discover whether statistically settlements have clustered, random or even distribution in Ahmedabad metropolitan region. The results obtained are then compared with the settlements pattern in Delhi Metropolitan region. The comparison between two regions highlights whether the distribution of settlements in the region under study is general or unique in nature or not. Number of Pages in PDF File: 13

Analysis of spatial pattern of settlements in the federal capital territory of Nigeria using vector-based GIS data

Human settlements are important, seemingly static but dynamic, features of the cultural landscape that have attracted several studies due to the important role they play in human life. This paper examined the spatial distribution of settlements in the Federal Capital Territory (FCT) of Nigeria. The analysis uses vector based GIS data derived from the 1989 political map of the FCT. Map composition was done with ArcView 3.2a software and the nearest neighbour statistics was computed using the pattern analysis function of Ilwis 3.0 software. The result of the quadrat count analysis yielded a variance mean ratio of 1.34 to show that the settlements of the FCT were clustered in space as opposed to the subjective findings of some authors, which suggested that the settlements were evenly spread. Analysis of the degree of clustering reveals that 51 per cent of all settlement pair has a separation of less than four kilometres, 63 per cent has a separation of less than five kilometres, 79 per cent has less than six kilometres while 97 per cent has a separation of less then nine kilometres. It was thus found out that, for 80 per cent of all settlements in the point map, one nearest neighbour can be found within a radius of 2 kilometres. Also, for 68 per cent of the settlements, three nearest neighbours can be found while for 60 per cent of the settlements, six nearest neighbours can be found within a radius of 2 kilometres. Analysis of the distance at which neighbours could be found revealed that the probability of finding six neighbours becomes 1 at a distance of one kilometre. This indicates that, we are 100 per cent sure of finding 6 nearest neighbours within a distance of one kilometre radius on the map.

Some factors affecting marital distances in the Outer Hebrides.

Some factors affecting marital distances have been studied in two Outer Hebridean islands, Harris (843 marriages) and Barra (444 marriages), over the period 1855-1990. In each island marital distances fell before 1900, but then rose to their greatest values after the 1950s. Fisherman generally married at the shortest distances and men in land-based occupations at the longest. The depression in the fishing industry during the 1880s and early 1890s was associated with reductions in marital distances, especially among fisherman. In the different regions of Harris, marital distances were least in the south-east, where settlement was most dense, and greatest in the south-west where it was most sparse. When the association between marital frequencies and inter-settlement distances was studied, it was found that for Harris there was, overall, a trend to endogamous and short-distance marriage. However, this trend was only slight during 1955-90. For Barra a similar trend was found before 1955, but thereafter there appeared to be virtually no connection between marital frequency and inter-settlement distance. Thus the only constraint on marriage was the spatial distribution of settlements. In this situation the chances of random mating with respect to distance are maximised. Application of 'Central Place' theory suggested that only since 1946 can any tendency be detected to regard Tarbert in Harris or Castlebay in Barra as Central Places, at least as far as marriage is concerned. In each island the tendency appears to be limited to the settlements closest to the Central Place.