Municipal Scale Research Articles

Coastal Scenic Beauty and Sensitivity at the Balearic Islands, Spain: Implication of Natural and Human Factors

Coastal areas globally are facing a significant range of environmental stresses, enhanced by climate change-related processes and a continuous increase of human activities. The economic benefits of tourism are well-known for coastal regions, but, very often, conflicts arise between short-term benefits and long-term conservation goals. Among beach user preferences, five parameters of greater importance stand out from the rest, i.e., safety, facilities, water quality, litter and scenery; the latter is the main concern of this study. A coastal scenic evaluation was carried out in the Balearic Islands and focused on two major issues: coastal scenic beauty together with sensitivity to natural processes and human pressure. The archipelago is renowned as a top international coastal tourist destination that receives more than 13.5 million visitors (2019). Impressive landscape diversity makes the Balearics Islands an ideal field for this research. In total, 52 sites, respectively located in Ibiza (11), Formentera (5), Mallorca (18) and Menorca (18), were field-tested. In a first step, coastal scenic beauty was quantified using the coastal scenic evaluation system (CSES) method, based on the evaluation of 26 physical and human parameters, and using weighting matrices parameters and fuzzy logic mathematics. An evaluation index (“D”) was obtained for each site, allowing one to classify them in one of the five scenic classes established by the method. Twenty-nine sites were included in class I, corresponding to extremely attractive sites (CSES), which were mainly observed in Menorca. Several sound measures were proposed to maintain and/or enhance sites’ scenic value. In a second step, scenic sensitivity was evaluated using a novel methodological approach that makes possible the assessment of three different coastal scenic sensitivity indexes (CSSI), i.e., the natural sensitivity index NSI, the human sensitivity index HSI and the total sensitivity index TSI. Future climate change trends and projection of tourism development, studied at municipality scale, were considered as correction factors. All the islands showed places highly sensitive to environmental processes, while sensitivity to human pressure was essentially observed at Ibiza and Mallorca. Thereafter, sites were categorized into one of three sensitive groups established by the methodology. Results obtained are useful in pointing out very sensitive sceneries as well as limiting, preventing and/or anticipating future scenic degradation linked to natural and human issues.

A LIFE-STAGE APPROACH FOR DECOMPOSING SPATIOTEMPORAL POPULATION CHANGES ALONG AN URBAN-RURAL GRADIENT: IMPLICATIONS FOR REGIONAL PLANNING

abstract The study of population changes across space and time of cohorts at different life stages is relevant for regional planning, but it is often not taken into account. We focus on a case study along the urban-rural gradient of continental Spain from 2002 to 2017 at a municipal scale. Making use of longitudinal data from the municipal registers, we studied changes in total population and three birth cohorts: the cohort joining the workforce, the cohort at a mature working age and the cohort reaching retirement during the study period. The results showed key spatiotemporal population variations. The absolute population increased in 36% of the municipalities, but at least one of the study cohorts showed an increase in 75% of the municipalities. While the cohort joining workforce tended to concentrate in urban and suburban areas, the retiring cohort tended to move to small suburban and rural municipalities. In the next decades the retirement of large birth cohorts in Spain will be a relevant issue for planning. This methodological approach allows us to understand life cycle residential movements across urban, suburban and rural areas and better enables spatial planning decisions. The method can be applied to other study areas at different spatial and temporal scales.

The County-Scale Economic Spatial Pattern and Influencing Factors of Seven Urban Agglomerations in the Yellow River Basin—A Study Based on the Integrated Nighttime Light Data

The integrated night light (NTL) datasets were used to represent the economic development level, and visual analysis was carried out on the evolution characteristics of the economic spatial pattern of various urban agglomerations in the Yellow River Basin (YRB), at a county-scale, in 1992, 2005, and 2018. The Global Moran’s I and the local Getis-Ord G methods were used to explore the overall spatial correlation and local cold–hot spot of economic development levels, respectively. The spatial heterogeneity of the influence of relevant factors on the economic development level at the municipal scale was analyzed by using the multi-scale geographically weighted regression (MGWR) model. The results show that the county-level economic spatial pattern of urban agglomeration in the YRB has an obvious “pyramid” characteristic. The hot spots are concentrated in the hinterland of the Guanzhong Plain, the Central Plains, and the Shandong Peninsula urban agglomeration. The cold spots are concentrated in the junction of urban agglomerations, and the characteristics of “cold in the west and hot in the east” are obvious. Labor input and import and exporthave a positive impact on the economic development level for each urban agglomeration, government force has a negative impact, and education shows both positive and negative polarization on economic development.

The Benefits and Limits of Urban Tree Planting for Environmental and Human Health

Many of the world’s major cities have implemented tree planting programs based on assumed environmental and social benefits of urban forests. Recent studies have increasingly tested these assumptions and provide empirical evidence for the contributions of tree planting programs, as well as their feasibility and limits, for solving or mitigating urban environmental and social issues. We propose that current evidence supports local cooling, stormwater absorption, and health benefits of urban trees for local residents. However, the potential for urban trees to appreciably mitigate greenhouse gas emissions and air pollution over a wide array of sites and environmental conditions is limited. Consequently, urban trees appear to be more promising for climate and pollutionadaptationstrategies than mitigation strategies. In large part, this is due to space constraints limiting the extent of urban tree canopies relative to the current magnitude of emissions. The most promising environmental and health impacts of urban trees are those that can be realized with well-stewarded tree planting and localized design interventions at site to municipal scales. Tree planting at these scales has documented benefits on local climate and health, which can be maximized through targeted site design followed by monitoring, adaptive management, and studies of long-term eco-evolutionary dynamics.

Power ramp rates and variability of individual and aggregate photovoltaic systems using measured production data at the municipal scale

Intermittency from photovoltaic systems can negatively impact electricity grid stability due to increased power ramp rates and temporal misalignment between generation and load. Distributed systems, especially rooftop residential systems, present a range of orientations and spatial separation that when aggregated introduce temporal diversity. If these features reduce negative impacts, they should be weighed against increased costs per delivered energy compared to larger commercial/industrial systems. We compare power production data from 60 distributed residential PV systems spread across a large municipality with medium and large commercial rooftop systems located centrally in the municipality. Power ramp rates and power output variability were calculated. The aggregated distributed residential system ramp rates never exceed 13% per 5 min, while the medium/large commercial systems experienced ramp rates up to 61% and 68% per 5 min. In aggregate the residential output variability is 3 times lower than the commercial sites. Consistent with previous literature the output variability decreases as the number of systems grows. There are however diminishing returns due to the limited geographic area, with a relative output variability for the municipality approaching 20% of the variability of a single system. Residential data was scaled up to represent 10% of electrical load and resulted in 10% more electricity grid ramp rates exceeding ±5 MW per 5 min compared to baseline. Finally, a comparison between pyranometer and photovoltaic system ramps rates shows the latter are less severe, likely because pyranometers are single points sources.

Quantitatively Assessing Ecological Stress of Urbanization on Natural Ecosystems by Using a Landscape-Adjacency Index

Urban spatial expansion poses a threat to regional ecosystems and biodiversity directly through altering the size, shape, and interconnectivity of natural landscapes. Monitoring urban spatial expansion using traditional area-based metrics from remote sensing provides a feasible way to quantify this regional ecological stress. However, variation in landscape-adjacency relationships (i.e., the adjacency between individual landscape classes) caused by urban expansion is often overlooked. In this study, a novel edge-based index (landscape-adjacency index, LAdI) was proposed based on the spatial-adjacency relationship between landscape patches to measure the regional ecological stress of urban expansion on natural landscapes. Taking the entire Yangtze River Delta Urban Agglomerations (YRD) as a study area, we applied the LAdI for individual landscape classes (Vi) and landscape level (LV) to quantitatively assess change over time in the ecological stress of YRD from 1990 to 2015 at two spatial scales: municipal scale and 5 km-grid scale. The results showed that the vulnerable zones (LV ≥ 0.6) were mainly distributed in the north of the YRD, and cultivated land was the most vulnerable natural landscape (Vi ≥ 0.6) at the 5 km-grid scale. The most vulnerable landscape at the municipal scale was cultivated land in 19 of 26 cities in each period, and that in the remaining 7 cities varied at distinct urbanization stages. We used scatter diagrams and Pearson correlation analysis to compare the edge-based LAdI with an area-based index (percent of built-up area, PB) and found that: LV and PB had a significant positive correlation at both the municipal scale and 5 km-grid scale. But there were multiple LVs with different values corresponding to one PB with the same value at the 5 km-grid scale. Both indexes could represent the degree of urban expansion; however, the edge-based metric better quantified ecological stress under different urban-sprawl patterns sharing the same percent of built-up area. As changes in land use affect both the size and edge effect among landscape patches, the area-based PB and the edge-based LAdI should be applied together when assessing the ecological stress caused by urbanization.

Log removal values in membrane bioreactors: Correlation of surrogate monitoring and operational parameters

Log removal values (LRV) for a range of pathogens in membrane bioreactors (MBRs) were aggregated for 180 sampling events across 11 municipal scale installations. Important correlations were established between LRV for biological (LRVBio) and physical (LRVMem) inactivation with reactor conditions (pH, temperature, solid and hydraulic retention times (SRT, HRT), and mixed liquor suspended solids (MLSS)), membrane properties (pore size and flux), operational variables and filtrate quality. LRVBio correlated positively and significantly between all microorganism indicators and dissolved organic carbon (DOC), becoming a suitable monitoring technique for biological removal. LRVMem correlated positively for protozoa indicators and bacteria consistent with size exclusion as a predominant removal mechanism. Strong correlations between LRV for protozoa, virus and bacteria indicators were established at lower flux, TMP and MLSS, higher pH and temperature and longer solids and hydraulic retention time. The implications of this study provide important guidance for the validation of MBRs producing safe and consistent recycled water.

Running on renewables: Building local support for 100% net-renewable electricity resolutions at the municipal scale in the United States

In the absence of national leadership on climate policy in the United States, municipalities are adopting resolutions to reduce their carbon footprint and transition to clean energy. However, what leads to successful adoption of these ambitious resolutions needs further exploration. Using a qualitative, exploratory case study approach, this paper examines the resolutions adopted in Salt Lake City, Park City, and Moab, Utah to transition to 100% renewable electricity by 2030. We conducted in-depth document analyses and semi-structured interviews with government officials, city staff, and community members involved with the resolution process. We used time series and thematic analyses to determine causal events and identify fundamental themes within the data. The data that emerged from the interviews and document analyses were then cross compared to the social-ecological transformations framework and community coalition building theory to inform and organize our findings of how renewable electricity resolutions were developed and adopted in these communities. Our findings deliver a transferable five-step framework: 1) using trigger events for inspiration; 2) envisioning change; 3) identifying challenges and potential solutions; 4) building support; 5) taking it to a vote. The purpose of this framework is to assist other cities in adopting similar resolutions, furthering a national transition to renewable electricity.

Governance and groundwater modelling: Hints to boost the implementation of the EU Nitrate Directive. The Lombardy Plain case, N Italy

The EU Nitrate Directive has been ruling for almost 30 years, nevertheless nitrate concentration in the Lombardy Plain did not decrease. Together with failures of management implementation, a possible cause for such field observations is that management actions were taken without adequately considering the actual hydrogeological dynamics. To consider this aspect, the paper presents a groundwater flow and transport numerical model of a specific area of the Lombardy Plain. The aim of this model is to demonstrate how modelling, as a management tool, can be useful in the governance process.The groundwater model, using well-known MODFLOW-MT3D codes, is based on existing hydrogeological information, while a nitrogen mass balance has been performed at municipal scale to determine the agricultural N surplus to the subsurface. The model adequately reproduces head levels and nitrate concentrations in observation wells for a 10-year simulation period, showing that 4.5% of the N annual input remains stored in the system. The model indicates the efficiency of rivers and springs to export N out from the system at an estimated rate of 77.5% of the annual N inputs.Back to governance, the model shows that management data at municipal level (e.g. irrigation rates, groundwater withdrawal, N net recharge) provide a satisfactory scale for successfully reproducing nitrate evolution. Hence those variables that can be object of debate during a governance process can be treated as input data to the numerical model. Therefore, backcasting exercises can be conducted to check whether the model outcome fits with the expected results of specific management actions. The model highlights how the N mass balance evolves, providing clues on which factors can be managed to reduce nitrate concentrations and meet the Directive's requirements. Numerical groundwater models, as an option to address water management issues, ultimately contribute to solve the information and capacity governance gaps.

Using demographic data to understand the distribution of H1N1 and COVID-19 pandemics cases among federal entities and municipalities of Mexico.

BackgroundThe novel coronavirus disease (COVID-19) pandemic is the second global health emergency the world has faced in less than two decades, after the H1N1 Influenza pandemic in 2009–2010. Spread of pandemics is frequently associated with increased population size and population density. The geographical scales (national, regional or local scale) are key elements in determining the correlation between demographic factors and the spread of outbreaks. The aims of this study were: (a) to collect the Mexican data related to the two pandemics; (b) to create thematic maps using federal and municipal geographic scales; (c) to investigate the correlations between the pandemics indicators (numbers of contagious and deaths) and demographic patterns (population size and density).MethodsThe demographic patterns of all Mexican Federal Entities and all municipalities were taken from the database of “Instituto Nacional de Estadística y Geografía” (INEGI). The data of “Centro Nacional de Programas Preventivos y Control de Enfermedades” (CENAPRECE) and the geoportal of Mexico Government were also used in our analysis. The results are presented by means of tables, graphs and thematic maps. A Spearman correlation was used to assess the associations between the pandemics indicators and the demographic patterns. Correlations with a p value < 0.05 were considered significant.ResultsThe confirmed cases (ccH1N1) and deaths (dH1N1) registered during the H1N1 Influenza pandemic were 72.4 thousand and 1.2 thousand respectively. Mexico City (CDMX) was the most affected area by the pandemic with 8,502 ccH1N1 and 152 dH1N1. The ccH1N1 and dH1N1 were positively correlated to demographic patterns; p-values higher than the level of marginal significance were found analyzing the % ccH1N1 and the % dH1N1 vs the population density. The COVID-19 pandemic data indicated 75.0 million confirmed cases (ccCOVID-19) and 1.6 million deaths (dCOVID-19) worldwide, as of date. The CDMX, where 264,330 infections were recorded, is the national epicenter of the pandemic. The federal scale did not allow to observe the correlation between demographic data and pandemic indicators; hence the next step was to choose a more detailed geographical scale (municipal basis). The ccCOVID-19 and dCOVID-19 (municipal basis) were highly correlated with demographic patterns; also the % ccCOVID-19 and % dCOVID-19 were moderately correlated with demographic patterns.ConclusionThe magnitude of COVID-19 pandemic is much greater than the H1N1 Influenza pandemic. The CDMX was the national epicenter in both pandemics. The federal scale did not allow to evaluate the correlation between exanimated demographic variables and the spread of infections, but the municipal basis allowed the identification of local variations and “red zones” such as the delegation of Iztapalapa and Gustavo A. Madero in CDMX.

Are Cities Truly Dispersed? A Long-Term Analysis of Vertical Profile of Settlements in Athens’ Metropolitan Region

Using nonparametric, exploratory statistics, the spatial structure of the city’s vertical profile was investigated at the municipal scale in Athens’ metropolitan region (Greece), evaluating changes over a sufficiently long time interval (1983–2019) that encompasses different phases of the urban cycle in Greece. Assuming the vertical profile of cities as an honest indicator of urban form, the study was aimed to test the intensity and spatial direction of the (supposed) change in settlement models toward sprawl. Transitioning slowly from a dense to a more dispersed settlement structure, Athens’ dynamics revealed a quite representative model for cities expanding significantly but remaining substantially compact and dense, while responding similarly to different (external) economic stimuli. Nonparametric correlation between the average (vertical) profile of each municipality and the distance from downtown Athens revealed a substantially stable mono-centric structure over time, with small changes over time still responding to factors dependent on the urban gradient. The inherent shift towards “horizontal” urban expansion was relatively modest and characteristic of few periurban contexts. The empirical results of this study can be envisaged as a practical tool of regional planning, allowing continuous monitoring of urban sprawl and land take in complex systems under rapid socioeconomic changes.

Landslide risk index map at the municipal scale for Costa Rica

Landslides are a common natural hazard worldwide with greater socioeconomic impacts in developing and tropical countries. In Central America and Costa Rica, this phenomenon is mainly triggered by seismicity and extraordinary rainfall. In order to portray the damaging landslides, that caused human and material losses in Costa Rica, DesInventar disaster database was used to analyze damaging landslides reports from 1970 to 2018. Moreover, different generalized linear models (GLM) were performed to analyze the landslide hazard, vulnerability and risk in all the municipalities of the country. An Akaike Information Criterion (AIC) backward selection was used to contrast and determine the best hazard and vulnerability models. From a total of ten variables, terrain ruggedness index, 5 year intensity-duration-frequency precipitation curves and earthquakes distribution determined the landslide hazard. Otherwise, population, municipality area and Social Development Index are the most suitable variables to explain the landslide vulnerability. Subsequently, the multiplication between alternative landslide hazard and vulnerability indexes produced the risk index. Consequently, the highest risk values were obtained for large and rural municipalities (Pérez Zeledón, San Carlos, and Turrialba) as well as for densely populated and urban units (Alajuela, Desamparados, and Cartago. Results are critical for disaster risk reduction public institutions and academic stakeholders. Therefore, this methodology could be an interesting opportunity for different tropical and developing countries to achieve national or regional analyses of the most important risk component in each municipality and implement risk reduction strategies adapted for each municipality characteristics.

Distribution of birds in Colombia.

Background1. Colombia with 1941 known recorded bird species is one of the most species rich countries in the world. Efforts are necessary to conserve, study and promote sustainable use of this important taxonomic group throughout Colombia’s vast territory.2. In an ideal world, informed decisions that are based on sound scientific information should be likelier to have successful outcomes. Nevertheless, there are barriers that make it difficult to access and use information in a timely fashion. Those same barriers impede the study, conservation and sustainable use of bird species in Colombia. On the other hand, given that there is good documentation about the ecology of a large number of species, information about the distribution of birds can be easily incorporated into decision-making processes, once this information becomes readily available in a consumable format using Geographic Information Sciences tools.3. In this context, the main objective of this paper is to present the first compilation of the current distribution of 1889 (97%) species of birds in Colombia, using expert criteria. The shapefiles were used to show the distribution and diversity of bird species in Colombia under both geopolitical and conservation geographic units.4. The information provided in this paper can be used as a baseline for a huge number of initiatives that aim to strengthen conservation efforts and improve knowledge about one the most unique taxonomic groups in the country. These range from land use planning strategies at the municipal or department scale to sustainable use of bird species - such as those initiatives related to bird watching - in Colombia.New informationThis study has considered three key aspects: 1) the importance of birds for Colombia’s ecosystems, 2) the privileged place of Colombia in bird species richness and 3) the importance of data mobilisation in formats easily consumable by Geographic Information Systems (GIS) to facilitate the processes of informed decision-making. We present the first compilation - in shapefile format - for 1889 of the 1941 bird species recorded from Colombia. Using this novel collection, we showed the species richness of birds in Colombia’s 33 Departments plus its Captial District (DPs), 1122 Municipalities (MNs), 58 protected areas (PAs), 39 Regional Autonomous Corporations (the authorities responsible within their respective jurisdictions for regulating the environment and renewable natural resources in Colombia; CARs) and 916 Collectively Titled Territories (including both indigenous reservations and afro-descendant communities; CTTs). In addition, we provide a list of known bird species richness for the above geographic units found in the available literature. The information provided here can be used as a baseline for a huge number of initiatives concerning the study, conservation and sustainable use of bird species present in Colombia, providing access to key features of bird distribution that should facilitate decision-making.

Traits of a bloom: a nationwide survey of U.S. urban tree planting initiatives (TPIs)

Municipal leaders worldwide are showing substantial interest in urban greening. This encompasses incentives, policies, and programs to vegetate urban landscapes, and it often includes urban tree planting initiatives (TPIs). Over the past decade there has been a seven-fold increase in scholarly use of terms denoting TPIs, and roughly two-thirds of associated studies address TPIs in the United States (U.S.). This reflects a bloom of scholarly interest in TPIs. Yet, there has been limited research on contemporary TPIs as historically situated cultural phenomena, and there has to the best of our knowledge been no nationwide survey of TPIs across municipal scales. Addressing these gaps, this article presents findings from a survey of 41 TPIs in the United States. We report on typical traits of U.S. TPIs across six themes: background, dates and goals, public awareness, funding and governance, planting, and stewardship. Respondents identified over 115 traits that distinguish TPIs from typical urban tree planting activity, suggesting that TPIs are a discrete form of urban forestry. Over two-thirds of TPIs are funded separate from traditional urban forestry, and lack of institutionalization raises questions about long-term viability. TPIs mobilize political and financial resources for program launch, tree purchasing, and planting, but there may be a need for greater investment in stewardship activities and the social infrastructure that undergirds green infrastructure. Large shade trees for ecosystem services and native trees are the principal factors informing TPI species lists. Beautification and regulating ecosystem functions are, in turn, the principal potential benefits animating tree planting goals, yet few TPIs have conducted research to assess the fulfillment of associated outcomes. This study provides a foundation for future interdisciplinary scholarship on TPIs across the humanities, natural sciences, and social sciences.

Comparing vulnerability and institutional capacities in three Latin American coastal localities in response to extreme rainfall events

A multidisciplinary approach is used to evaluate the vulnerability resulting from extreme rainfall events (EREs) and to examine how institutional capacities related to prevention and response, assist small coastal locations in Latin America in coping with ERE, currently intensified by climate change. The analysis was carried out in Brazil, Dominican Republic and Mexico, at municipality and local scale, based on socio-economic and environmental indicators. Institutional capacity was assessed mainly based on semi-structured interviews, with key actors of selected study sites to obtain empirical information on the level of coordination and cooperation among them (social networks), to examine the effectiveness of the legal framework and the mechanisms for citizen participation in the decision-making process on the local scale. Present findings indicate that vulnerability by site is not directly related to local institutional capacity. The key actors’ networks and legal frameworks by country seemed to be sufficient to cope with ERE impacts, but citizen participation must be reinforced. In addition, public spaces are required for sharing, discussing and exchanging information to take action regarding the prevention, response and adaptation to future ERE impacts.

Public-cooperative policy mechanisms for housing commons

Cooperative housing is experiencing a resurgence of interest worldwide. As a more democratic and affordable alternative to dominant housing provision, it is often heralded as a blueprint for ‘housing commons’. Despite its long history, however, cooperative housing has rarely gone beyond a ‘niche’ in the housing market. Recent critical housing scholarship is beginning to address this marginalisation and understand how a more widespread development of the sector can be supported. In times and places where cooperative housing has expanded beyond a ‘niche’ solution, the role of the state, through policy making at national, regional and municipal scale, stands out as an important enabling factor. Drawing on ten international cases, this study presents a framework for a rigorous and politically meaningful comparative approach to public-cooperative policy mechanisms for ‘housing commons’. Three key phases in the housing process (production, access and management, and maintenance of the model in time) are identified and discussed through concrete examples of policy areas and mechanisms. The article contributes to scholarship on cooperative housing policy making and ‘housing commons’ and argues for a shift in attention to questions of accessibility over time, and the thorny issue of permanent decommodification.

A new small area estimation algorithm to balance between statistical precision and scale

Combining national forest inventory (NFI) data with auxiliary information allows downscaling and improving the precision of NFI estimates for small domains, where normally too few field plots are available to produce reliable estimates. In most situations, small domains represent administrative units that could greatly vary in size and forested area. In small and poorly sampled domains, the precision of estimates often drop below expected standards.To tackle this issue, we introduce a downscaling algorithm generating the smallest possible groups of domains satisfying prescribed sampling density and estimation error. The binary space partitioning algorithm recursively divides the population of domains in two groups while the prescribed precision conditions are fulfilled.The algorithm was tested on two major forest attributes (i.e. growing stock and basal area) in an area of 7,500 km2 dominated by hardwood forests in the centre of France. The estimation domains consisted in 157 municipalities. The field data included 819 NFI plots surveyed during a 5 years period. The auxiliary data consisted in 48 metrics derived from a forest map, photogrammetric models and Landsat images. A model-assisted framework was used for estimation. For each forest attribute, the best model was selected using a best-subset approach using a Bayesian Information Criteria. The retained models explained 58% and 41% of the observed variance for the growing stocks and basal areas respectively. The performance of the algorithm was evaluated using a minimum of 3 NFI points per domain and estimation errors varying from 10 to 50%.For a target estimation error set to 10%, the algorithm led to a limited number of estimation domains (<23 for both attributes) of large size (~15,000 ha) having an average estimation error lower than 7.7% for both attributes. Relaxing the targeted error threshold to 50% led to a larger amount of smaller domains (80 domains of 4,176 ha in average) for both attributes, and maximum estimation errors reaching 42.8%. Among those domains 65% consisted in single municipalities. For the sake of comparison, the estimation was also conducted at the scale of municipalities. Out of the 157 municipalities studied, only 93 were sampled with at least 3 NFI points and therefore estimated. Missing values were generated for the remaining 64 municipalities. Average errors of 15.9% and 15.6% were obtained for growing stock and basal area respectively, but estimation errors greater than 50% were obtained for some municipalities.The algorithm provides a flexible estimation framework for small area estimation. The key advantages of the approach are relying on its capacity to produce estimations based on a preselected precision threshold and to produce results over the whole area of interest, avoiding areas without any estimates. The algorithm could also be used on any kind of polygon layers (not only administrative ones), provided that the field sampling design enable estimation. This makes the proposed algorithm a convenient tool notably for decision makers and forest managers.

A multi‐scale approach to rural depopulation in Mexico

AbstractThis paper aims to sketch rural population decline in Mexico. A comprehensive multi‐scale documentation of Mexico's urban and rural fabric and its depopulation dynamics is undertaken. This paper does not identify the causes and effects of rural depopulation, but aims to detect its geographical presence in a manner which other approaches are unable to do. The granularity of rural depopulation is identified as manifested at four different scales: national, state, municipal, and local village scale. We use census data for the period 2000–2010. We relate rural depopulation to spatio‐geographical features found in the literature; the relationship of depopulating territories with urban ones and the altitude range in which they are located. We find that proximity to and remoteness from urban areas as well as that of altitude do not follow the typical patterns often observed elsewhere. Unlike that shown in other countries, in Mexico, rural depopulation is manifested mostly in lower‐lying areas and despite the fact that most of the country is at altitude. Rural depopulation and disappearance occur mainly in the areas of plains below 1,000 metres above sea level, regardless of the population density of the territories where they were located. Also, our multi‐scaling approach has allowed us to identify not just at what scale the phenomenon of rural depopulation is observed, but also, to identify the areas in which the phenomenon is manifested regionally or locally. As we see, much of the phenomenon is concentrated in different areas to what national narratives suggest.

Determining Key Parameters in Riots Using Lexicographic Directional Differentiation

This article investigates parametric sensitivities of rioting activity, based on a model of the 2005 French riots. Previously validated against a comprehensive data set, the aforementioned modeling efforts were multiscale in nature and applied at the provincial scale for all of France and the municipal scale in the Île-de-France region around Paris. The governing dynamics at the municipal scale include a bandwagon effect, observed in rioting activity wherein an outburst of activity occurs once a “tipping point” threshold is reached in the people engaging in the activity. This tipping point mechanism is modeled using a nonsmooth function, yielding a framework of nonsmooth ODEs, which makes conventional theory and methods unsuitable. In this article, we perform a sensitivity analysis of the municipal-scale model by adopting a recently developed tool in nonsmooth analysis called the lexicographic directional derivative. Numerical solutions are provided from which we can conclude the relative importance of different parameters in the model, in order to discover the underlying mechanisms that play a crucial role in driving the riot activities. It is shown that the exit/removal rate from rioting activity and geographic proximity have the greatest impact on the dynamics of the social contagion. On the other hand, the initial rioting activity and the tipping point seem less influential.

Evaluación de la Vulnerabilidad Social en la Provincial de Málaga, España: Comparación de Técnicas de Estandarización de Indicadores

Hazards are any sort of extreme events that occurred by natural causes, human activities or sometimes both reasons are responsible. Social vulnerability exposes people’s condition in hazards. To prevent the loss and damages by hazards, it is necessary to identify vulnerable population of a region by constructing social vulnerability maps of that region. Here in this work, study region is Malaga province, located in southern part of Spain, under the autonomous community of Andalusia. 23 key indicators have been adopted to understand the vulnerability of people in Malaga province at a municipality scale. Three different standardization methodologies (maximum value transformation, z score transformation and min–max rescaling transformation) have been used to build five vulnerable zones. There exists strong to very strong relationship between the results obtained by using three methodologies. The final result shows that most socio-economically vulnerable municipalities are located mainly in western part of the Malaga province.