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In coastal areas, the tourism sector contributes to the local economy, generating income, employment, investments and tax revenues but the rapid urban expansion creates great pressure on local resources and infrastructures, with negative repercussions on the residents’ quality of life, but also compromising the visitor’s experience. These areas face problems such as the formation of meteorological effects known as heat islands, due to the soil sealing, and increased energy demand in the peak season. To evaluate the impact of urban growth spatial pattern and change, three strategic sustainable challenges—urban form, urban energy, and urban outdoor comfort—were selected. The progress towards sustainability was measured and analyzed in a tourist city in the Algarve region, Portugal, for the period 2007–2018, using geographic information. A set of 2D and 3D indicators was derived for the building and block scales. Then, a change assessment based on cluster analysis was performed, and three different trends of sustainable development were identified and mapped. Results allow detecting the urban growth patterns that lead to more sustainable urban areas. The study revealed that a high sustainable development was observed in 12% of the changed blocks in the study area. All indicators suggest that the growth pattern of the coastal area is in line with the studied sustainability dimensions. However, most of the blocks that changed between 2007 and 2018 (82%) followed a low sustainable development. These blocks had the lowest variation in the built volume and density, and consequently the lowest variations in the roof areas with good solar exposition. The urban development also privileged more detached and less compact buildings. This analysis will support the integration of 2D and 3D information into the planning process, assisting smart cities to comply with the sustainable development goals.
Teresa Santos; Raquel Deus; Jorge Rocha; José António Tenedório. Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators. Energies 2021, 14, 5044 .
AMA StyleTeresa Santos, Raquel Deus, Jorge Rocha, José António Tenedório. Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators. Energies. 2021; 14 (16):5044.
Chicago/Turabian StyleTeresa Santos; Raquel Deus; Jorge Rocha; José António Tenedório. 2021. "Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators." Energies 14, no. 16: 5044.
Conservation and policy agendas, such as the European Biodiversity strategy, Aichi biodiversity (target 5) and Common Agriculture Policy (CAP), are overlooking the progress made in mountain grassland cover conservation by 2020, which has significant socio-ecological implications to Europe. However, because the existing data near 2020 is scarce, the shifting character of mountain grasslands remains poorly characterized, and even less is known about the conservation outcomes because of different governance regimes and map uncertainty. Our study used Landsat satellite imagery over a transboundary mountain region in the northwestern Iberian Peninsula (Peneda-Gerês) to shed light on these aspects. Supervised classifications with a multiple classifier ensemble approach (MCE) were performed, with post classification comparison of maps established and bias-corrected to identify the trajectory in grassland cover, including protected and unprotected governance regimes. By analysing class-allocation (Shannon entropy), creating 95% confidence intervals for the area estimates, and evaluating the class-allocation thematic accuracy relationship, we characterized uncertainty in the findings. The bias-corrected estimates suggest that the positive progress claimed internationally by 2020 was not achieved. Our null hypothesis to declare a positive progress (at least equality in the proportion of grassland cover of 2019 and 2002) was rejected (X2 = 1972.1, df = 1, p< 0.001). The majority of grassland cover remained stable (67.1 ± 10.1 relative to 2002), but loss (−32.8 ± 7.1% relative to 2002 grasslands cover) overcame gain areas (+11.4 ± 6.6%), indicating net loss as the prevailing pattern over the transboundary study area (−21.4%). This feature prevailed at all extents of analysis (lowlands, −22.9%; mountains, −17.9%; mountains protected, −14.4%; mountains unprotected, −19.7%). The results also evidenced that mountain protected governance regimes experienced a lower decline in grassland extent compared to unprotected. Shannon entropy values were also significantly lower in correctly classified validation sites (z = −5.69, p = 0.0001, n = 708) suggesting a relationship between the quality of pixel assignment and thematic accuracy. We therefore encourage a post-2020 conservation and policy action to safeguard mountain grasslands by enhancing the role of protected governance regimes. To reduce uncertainty, grassland gain mapping requires additional remote sensing research to find the most adequate spatial and temporal data resolution to retrieve this process.
Antonio Monteiro; Cláudia Carvalho-Santos; Richard Lucas; Jorge Rocha; Nuno Costa; Mariasilvia Giamberini; Eduarda Costa; Francesco Fava. Progress in Grassland Cover Conservation in Southern European Mountains by 2020: A Transboundary Assessment in the Iberian Peninsula with Satellite Observations (2002–2019). Remote Sensing 2021, 13, 3019 .
AMA StyleAntonio Monteiro, Cláudia Carvalho-Santos, Richard Lucas, Jorge Rocha, Nuno Costa, Mariasilvia Giamberini, Eduarda Costa, Francesco Fava. Progress in Grassland Cover Conservation in Southern European Mountains by 2020: A Transboundary Assessment in the Iberian Peninsula with Satellite Observations (2002–2019). Remote Sensing. 2021; 13 (15):3019.
Chicago/Turabian StyleAntonio Monteiro; Cláudia Carvalho-Santos; Richard Lucas; Jorge Rocha; Nuno Costa; Mariasilvia Giamberini; Eduarda Costa; Francesco Fava. 2021. "Progress in Grassland Cover Conservation in Southern European Mountains by 2020: A Transboundary Assessment in the Iberian Peninsula with Satellite Observations (2002–2019)." Remote Sensing 13, no. 15: 3019.
Agricultural statistical data enable the detection and interpretation of the development of agriculture and the food supply situation over time, which is essential for food security evaluation in any country. Based on the historical agricultural statistics, this study produces a long spatial time-series with annual production values of three cereals relevant to global food security—wheat, maize, and rice, aiming to provide geographical and historical perspectives. Therefore, we reconstructed past and current production patterns and trends at the district level over 169 years, which supported a space–time cross-reading of the general characteristics of the regional agricultural production value distributions and relative densities in Portugal. Particularly, the production trends of wheat, maize, and rice showed three different situations: growth (maize), stability (rice), and decline (wheat). For decades, maize and wheat production alternated, depending on agricultural years and political aspects, such as the Wheat Campaign (1929–1938). The changes over time presented a pattern that, in the case of these three cereals, enabled a clear division of the country into major regions according to cereal production. Overall, maize and rice, both grown on irrigated croplands, presented a similar pattern in some regions of Portugal, mainly the central region. In this study, a preliminary analysis was presented and related to successive public policies; however, notably, there are more lessons to be learned from this long spatial time-series.
Cláudia Viana; Dulce Freire; Patrícia Abrantes; Jorge Rocha. Evolution of Agricultural Production in Portugal during 1850–2018: A Geographical and Historical Perspective. Land 2021, 10, 776 .
AMA StyleCláudia Viana, Dulce Freire, Patrícia Abrantes, Jorge Rocha. Evolution of Agricultural Production in Portugal during 1850–2018: A Geographical and Historical Perspective. Land. 2021; 10 (8):776.
Chicago/Turabian StyleCláudia Viana; Dulce Freire; Patrícia Abrantes; Jorge Rocha. 2021. "Evolution of Agricultural Production in Portugal during 1850–2018: A Geographical and Historical Perspective." Land 10, no. 8: 776.
Risk assessment and modeling are crucial to understand wildfire drivers and impacts. Methods and tools used to model key components of wildfire risk are described. Recent approaches and challenges in wildfire modeling are indicated.
Sandra Oliveira; Jorge Rocha; Ana Sá. Wildfire risk modeling. Current Opinion in Environmental Science & Health 2021, 23, 100274 .
AMA StyleSandra Oliveira, Jorge Rocha, Ana Sá. Wildfire risk modeling. Current Opinion in Environmental Science & Health. 2021; 23 ():100274.
Chicago/Turabian StyleSandra Oliveira; Jorge Rocha; Ana Sá. 2021. "Wildfire risk modeling." Current Opinion in Environmental Science & Health 23, no. : 100274.
La situación de proximidad de muchos espacios naturales protegidos respecto a áreas urbanas dinámicas puede desencadenar intensos procesos de cambio que pongan en riesgo el mantenimiento de los valores naturales y patrimoniales propios de estos espacios. El Parque Natural da Arrábida está situado en el Área Metropolitana de Lisboa y se encuentra a sólo 40 kilómetros de la capital de Portugal. El presente artículo analiza los cambios en los usos y coberturas del suelo en el periodo más reciente (1995-2015) para identificar los principales procesos de transformación del paisaje en este espacio protegido. Además se lleva a cabo un análisis, a partir de indicadores demográficos y económicos, de su área de influencia (los municipios de Setúbal, Sesimbra y Palmela). Estos indicadores sirven al propósito de vincular la evolución del paisaje del área protegida con la del modelo socioeconómico de su entorno más próximo.
Laura Porcel-Rodríguez; Yolanda Jiménez-Olivencia; Jorge Rocha. Evolución Reciente de las Áreas Protegidas en Portugal: El Caso del Parque Natural da Arrábida. Anuário do Instituto de Geociências 2021, 44, 1 .
AMA StyleLaura Porcel-Rodríguez, Yolanda Jiménez-Olivencia, Jorge Rocha. Evolución Reciente de las Áreas Protegidas en Portugal: El Caso del Parque Natural da Arrábida. Anuário do Instituto de Geociências. 2021; 44 ():1.
Chicago/Turabian StyleLaura Porcel-Rodríguez; Yolanda Jiménez-Olivencia; Jorge Rocha. 2021. "Evolución Reciente de las Áreas Protegidas en Portugal: El Caso del Parque Natural da Arrábida." Anuário do Instituto de Geociências 44, no. : 1.
This article provides an approach to the geographic and quantitative interpretation of tourism intensification, drawing on the concepts of fractals, and fractal dimension ( D). Exploring tourism intensification in Lisbon, we first present a geographic construct that represents the spatial layout of tourism based on crowd-contributed spatial signatures advocating a collective sense of the “tourist city.” Then, we assess the tourism-related intensification patterns, based on the estimation of D, for different years. Significant statistical associations can be found between D and tourism intensification across the urban space. Intensification on tourism cores is more homogeneously distributed, yet it evolves into a more compact form of spatial organization. On the other hand, there is a decline in the degree of homogeneity of tourism intensification from tourism cores to the periphery. This approach has also proved useful for exploring tourism intensification in destinations at different hierarchical levels, such as in Lisbon and Oporto metropolitan areas.
Luis Encalada-Abarca; Carlos Cardoso Ferreira; Jorge Rocha. Measuring Tourism Intensification in Urban Destinations: An Approach Based on Fractal Analysis. Journal of Travel Research 2021, 1 .
AMA StyleLuis Encalada-Abarca, Carlos Cardoso Ferreira, Jorge Rocha. Measuring Tourism Intensification in Urban Destinations: An Approach Based on Fractal Analysis. Journal of Travel Research. 2021; ():1.
Chicago/Turabian StyleLuis Encalada-Abarca; Carlos Cardoso Ferreira; Jorge Rocha. 2021. "Measuring Tourism Intensification in Urban Destinations: An Approach Based on Fractal Analysis." Journal of Travel Research , no. : 1.
In this chapter, a hybrid approach integrating cellular automata (CA), fuzzy logic, logistic regression, and Markov chains for modelling and prediction of land-use and land-cover (LULC) change at the local scale, using geographic information with fine spatial resolution is presented. A spatial logistic regression model was applied to determine the transition rules that were used by a conventional CA model. The overall dimension of LULC change was estimated using a Markov chain model. The proposed CA-based model (termed CAMLucc) in combination with physical variables and land-use planning data was applied to simulate LULC change in Portimão, Portugal between 1947 and 2010 and to predict its future spatial patterns for 2020 and 2025. The main results of this research show that Portimão has been facing massive growth in artificial surfaces, particularly near the main urban settlements and along the coastal area, and reveal an early and intensive urban sprawl over time.
Raquel Faria de Deus; José António Tenedório; Jorge Rocha. Modelling Land-Use and Land-Cover Changes. Interdisciplinary Approaches to Spatial Optimization Issues 2021, 57 -102.
AMA StyleRaquel Faria de Deus, José António Tenedório, Jorge Rocha. Modelling Land-Use and Land-Cover Changes. Interdisciplinary Approaches to Spatial Optimization Issues. 2021; ():57-102.
Chicago/Turabian StyleRaquel Faria de Deus; José António Tenedório; Jorge Rocha. 2021. "Modelling Land-Use and Land-Cover Changes." Interdisciplinary Approaches to Spatial Optimization Issues , no. : 57-102.
Jorge Rocha. Smart Tourism and Smart Destinations for a Sustainable Future. Encyclopedia of the UN Sustainable Development Goals 2020, 871 -880.
AMA StyleJorge Rocha. Smart Tourism and Smart Destinations for a Sustainable Future. Encyclopedia of the UN Sustainable Development Goals. 2020; ():871-880.
Chicago/Turabian StyleJorge Rocha. 2020. "Smart Tourism and Smart Destinations for a Sustainable Future." Encyclopedia of the UN Sustainable Development Goals , no. : 871-880.
Open access peer-reviewed chapter
Jorge Rocha; Sandra Oliveira; César Capinha. Introductory Chapter: Risk Management. Risk Management and Assessment 2020, 1 .
AMA StyleJorge Rocha, Sandra Oliveira, César Capinha. Introductory Chapter: Risk Management. Risk Management and Assessment. 2020; ():1.
Chicago/Turabian StyleJorge Rocha; Sandra Oliveira; César Capinha. 2020. "Introductory Chapter: Risk Management." Risk Management and Assessment , no. : 1.
Aedes albopictus is an invasive mosquito that has colonized several European countries as well as Portugal, where it was detected for the first time in 2017. To increase the knowledge of Ae. albopictus population dynamics, a survey was carried out in the municipality of Loulé, Algarve, a Southern temperate region of Portugal, throughout 2019, with Biogents Sentinel traps (BGS traps) and ovitraps. More than 19,000 eggs and 400 adults were identified from May 9 (week 19) and December 16 (week 50). A positive correlation between the number of females captured in the BGS traps and the number of eggs collected in ovitraps was found. The start of activity of A. albopictus in May corresponded to an average minimum temperature above 13.0 °C and an average maximum temperature of 26.2 °C. The abundance peak of this A. albopictus population was identified from September to November. The positive effect of temperature on the seasonal activity of the adult population observed highlight the importance of climate change in affecting the occurrence, abundance, and distribution patterns of this species. The continuously monitoring activities currently ongoing point to an established population of A. albopictus in Loulé, Algarve, in a dispersion process to other regions of Portugal and raises concern for future outbreaks of mosquito-borne diseases associated with this invasive mosquito species.
Hugo Osório; Jorge Rocha; Rita Roquette; Nélia Guerreiro; Líbia Zé-Zé; Fátima Amaro; Manuel Silva; Maria Alves. Seasonal Dynamics and Spatial Distribution of Aedes albopictus (Diptera: Culicidae) in a Temperate Region in Europe, Southern Portugal. International Journal of Environmental Research and Public Health 2020, 17, 7083 .
AMA StyleHugo Osório, Jorge Rocha, Rita Roquette, Nélia Guerreiro, Líbia Zé-Zé, Fátima Amaro, Manuel Silva, Maria Alves. Seasonal Dynamics and Spatial Distribution of Aedes albopictus (Diptera: Culicidae) in a Temperate Region in Europe, Southern Portugal. International Journal of Environmental Research and Public Health. 2020; 17 (19):7083.
Chicago/Turabian StyleHugo Osório; Jorge Rocha; Rita Roquette; Nélia Guerreiro; Líbia Zé-Zé; Fátima Amaro; Manuel Silva; Maria Alves. 2020. "Seasonal Dynamics and Spatial Distribution of Aedes albopictus (Diptera: Culicidae) in a Temperate Region in Europe, Southern Portugal." International Journal of Environmental Research and Public Health 17, no. 19: 7083.
The 2030 Agenda for Sustainable Development set 17 Sustainable Development Goals (SDGs). These include ensuring access to affordable, reliable, sustainable and modern energy for all (SGD7) and making cities and human settlements inclusive, safe, resilient and sustainable (SGD11). Thus, across the globe, major cities are moving in the smart city direction, by, for example, incorporating photovoltaics (PV), electric buses and sensors to improve public transportation. We study the concept of integrated PV bus stop shelters for the city of Lisbon. We identified the suitable locations for these, with respect to solar exposure, by using a Geographic Information System (GIS) solar radiation map. Then, using proxies to describe tourist and commuter demand, we determined that 54% of all current city bus stop shelters have the potential to receive PV-based solutions. Promoting innovative solutions such as this one will support smart mobility and urban sustainability while increasing quality of life, the ultimate goal of the Smart Cities movement.
Teresa Santos; Killian Lobato; Jorge Rocha; José Tenedório. Modeling Photovoltaic Potential for Bus Shelters on a City-Scale: A Case Study in Lisbon. Applied Sciences 2020, 10, 4801 .
AMA StyleTeresa Santos, Killian Lobato, Jorge Rocha, José Tenedório. Modeling Photovoltaic Potential for Bus Shelters on a City-Scale: A Case Study in Lisbon. Applied Sciences. 2020; 10 (14):4801.
Chicago/Turabian StyleTeresa Santos; Killian Lobato; Jorge Rocha; José Tenedório. 2020. "Modeling Photovoltaic Potential for Bus Shelters on a City-Scale: A Case Study in Lisbon." Applied Sciences 10, no. 14: 4801.
Jorge Rocha. Smart Tourism and Smart Destinations for a Sustainable Future. Encyclopedia of the UN Sustainable Development Goals 2020, 1 -10.
AMA StyleJorge Rocha. Smart Tourism and Smart Destinations for a Sustainable Future. Encyclopedia of the UN Sustainable Development Goals. 2020; ():1-10.
Chicago/Turabian StyleJorge Rocha. 2020. "Smart Tourism and Smart Destinations for a Sustainable Future." Encyclopedia of the UN Sustainable Development Goals , no. : 1-10.
The present study used the official Portuguese land use/land cover (LULC) maps (Carta de Uso e Ocupação do Solo, COS) from 1995, 2007, 2010, 2015, and 2018 to quantify, visualize, and predict the spatiotemporal LULC transitions in the Beja district, a rural region in the southeast of Portugal, which is experiencing marked landscape changes. Here, we computed the conventional transition matrices for in-depth statistical analysis of the LULC changes that have occurred from 1995 to 2018, providing supplementary statistics regarding the vulnerability of inter-class transitions by focusing on the dominant signals of change. We also investigated how the LULC is going to move in the future (2040) based on matrices of current states using the Discrete-Time Markov Chain (DTMC) model. The results revealed that, between 1995 and 2018, about 28% of the Beja district landscape changed. Particularly, croplands remain the predominant LULC class in more than half of the Beja district (in 2018 about 64%). However, the behavior of the inter-class transitions was significantly different between periods, and explicitly revealed that arable land, pastures, and forest were the most dynamic LULC classes. Few dominant (systematic) signals of change during the 1995–2018 period were observed, highlighting the transition of arable land to permanent crops (5%) and to pastures (2.9%), and the transition of pastures to forest (3.5%) and to arable land (2.7%). Simulation results showed that about 25% of the territory is predicted to experience major LULC changes from arable land (−3.81%), permanent crops (+2.93%), and forests (+2.60%) by 2040.
Cláudia M. Viana; Jorge Rocha. Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method. Sustainability 2020, 12, 4332 .
AMA StyleCláudia M. Viana, Jorge Rocha. Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method. Sustainability. 2020; 12 (10):4332.
Chicago/Turabian StyleCláudia M. Viana; Jorge Rocha. 2020. "Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method." Sustainability 12, no. 10: 4332.
Future land use/cover change (LUCC) analysis has been increasingly applied to spatial planning instruments in the last few years. Nevertheless, stakeholder participation in the land use modelling process and analysis is still low. This paper describes a methodology engaging stakeholders (from the land use planning, agriculture, and forest sectors) in the building and assessment of future LUCC scenarios. We selected as case study the Torres Vedras Municipality (Portugal), a peri-urban region near Lisbon. Our analysis encompasses a participatory workshop to analyse LUCC model outcomes, based on farmer LUCC intentions, for the following scenarios: A0 - current social and economic trend (Business as Usual); A1 - regional food security; A2 - climate change; and B0 - farming under urban pressure. This analysis allowed local stakeholders to develop and discuss their own views on the most plausible future LUCC for the following land use classes: artificial surfaces, non-irrigated arable land, permanently irrigated land, permanent crops and heterogeneous agricultural land, pastures, forest and semi-natural areas, and water bodies and wetlands. Subsequently, we spatialized these LUCC views into a hybrid model (Cellular Automata - Geographic Information Systems), identifying the most suitable land conversion areas. We refer to this model, implemented in NetLogo, as the stakeholder-LUCC model. The results presented in this paper model where, when, why, and what conversions may occur in the future in regard to stakeholders' points of view. These outcomes can better enable decision-makers to perform land use planning more efficiently and develop measures to prevent undesirable futures, particularly in extreme events such as scenarios of food security, climate change, and/or farming under pressure.
Eduardo Gomes; Arnaud Banos; Patrícia Abrantes; Jorge Rocha; Markus Schläpfer. Future land use changes in a peri-urban context: Local stakeholder views. Science of The Total Environment 2020, 718, 137381 .
AMA StyleEduardo Gomes, Arnaud Banos, Patrícia Abrantes, Jorge Rocha, Markus Schläpfer. Future land use changes in a peri-urban context: Local stakeholder views. Science of The Total Environment. 2020; 718 ():137381.
Chicago/Turabian StyleEduardo Gomes; Arnaud Banos; Patrícia Abrantes; Jorge Rocha; Markus Schläpfer. 2020. "Future land use changes in a peri-urban context: Local stakeholder views." Science of The Total Environment 718, no. : 137381.
Cláudia M. Viana; Patrícia Abrantes; Jorge Rocha. Introductory Chapter: Geographic Information Systems and Science. Geographic Information Systems and Science 2019, 1 .
AMA StyleCláudia M. Viana, Patrícia Abrantes, Jorge Rocha. Introductory Chapter: Geographic Information Systems and Science. Geographic Information Systems and Science. 2019; ():1.
Chicago/Turabian StyleCláudia M. Viana; Patrícia Abrantes; Jorge Rocha. 2019. "Introductory Chapter: Geographic Information Systems and Science." Geographic Information Systems and Science , no. : 1.
Jorge Rocha. Simulation and Sustainability. Encyclopedia of Sustainability in Higher Education 2019, 1466 -1473.
AMA StyleJorge Rocha. Simulation and Sustainability. Encyclopedia of Sustainability in Higher Education. 2019; ():1466-1473.
Chicago/Turabian StyleJorge Rocha. 2019. "Simulation and Sustainability." Encyclopedia of Sustainability in Higher Education , no. : 1466-1473.
This research is focused on the susceptibility assessment of shallow slides by modeling the failure and run-out areas separately. The shallow slides failure is evaluated using a statistical method (logistic regression) and for the run-out assessment, a simple cellular automata model is proposed. The existence of shallow slides inventories occurred in distinct time periods allowed the separation of data into two independent groups (modeling and validation) and the adoption of the temporal criterion for the independent validation. The logistic regression model showed a very good predictive capacity (area under the receiver operating characteristic curve of 0.90), although it may be overestimated, as well as the susceptibility scores obtained. The run-out modeling, using a simple cellular automata model developed for this study, provided good results, with an overlap between the simulation and the real cases of 77%. Lastly, a final shallow slide susceptibility map was constructed including both failure and run-out areas. This work accomplished a combination of low-cost methodology with limited input data that allowed a good performance of the landslide susceptibility assessment and can be easily applied to other regions.
Raquel Melo; José L. Zêzere; Jorge Rocha; Sérgio C. Oliveira. Combining data-driven models to assess susceptibility of shallow slides failure and run-out. Landslides 2019, 16, 2259 -2276.
AMA StyleRaquel Melo, José L. Zêzere, Jorge Rocha, Sérgio C. Oliveira. Combining data-driven models to assess susceptibility of shallow slides failure and run-out. Landslides. 2019; 16 (11):2259-2276.
Chicago/Turabian StyleRaquel Melo; José L. Zêzere; Jorge Rocha; Sérgio C. Oliveira. 2019. "Combining data-driven models to assess susceptibility of shallow slides failure and run-out." Landslides 16, no. 11: 2259-2276.
En este artículo se utilizaron las fotos georreferenciadas, compartidas por usuarios de la red “Panoramio” entre 2007 y 2014, como un proxy para analizar la distribución espacial y temporal de los visitantes, en la ciudad de Lisboa. El conjunto total de datos (> 75.000 fotografías) fue segmentado en turistas y locales, con base en las marcas temporales, resultando una muestra de 17.604 fotos tomadas por > 5.000 usuarios. La evidencia empírica sugiere que la distribución espacial de los visitantes no es homogénea. Además, exploramos la relación espacial entre el patrón observado (la aglomeración geográfica de visitantes) y un conjunto de 24 variables asociadas a la oferta turística de la ciudad. A través del análisis de regresión lineal múltiple, se verificó que son los “monumentos de interés público”, los elementos que presentan mayor atractivo, considerando los factores explicativos seleccionados, y que existen áreas del centro histórico cuyo potencial turístico está subestimado.
Luis Encalada; Jorge Rocha; Carlos Ferreira. Análise exploratória da pegada digital dos turistas para a identificação de padrões espaciais e temporais em destinos urbanos. Revista Cartográfica 2019, 17 -35.
AMA StyleLuis Encalada, Jorge Rocha, Carlos Ferreira. Análise exploratória da pegada digital dos turistas para a identificação de padrões espaciais e temporais em destinos urbanos. Revista Cartográfica. 2019; (97):17-35.
Chicago/Turabian StyleLuis Encalada; Jorge Rocha; Carlos Ferreira. 2019. "Análise exploratória da pegada digital dos turistas para a identificação de padrões espaciais e temporais em destinos urbanos." Revista Cartográfica , no. 97: 17-35.
The increasing availability and volume of remote sensing data, such as Landsat satellite images, have allowed the multidimensional analysis of land use/land cover (LULC) changes. However, the performance of image classification is highly dependent on the quality and quantity of the training set and its temporal continuity, which may affect the accuracy of the classification and bias the analysis of the LULC changes. In this study, we intended to apply a long-term LULC analysis in a rural region based on a Landsat time series of 21 years (1995 to 2015). Here, we investigated the use of open LULC source data to provide training samples and the application of the K-means clustering technique to refine the broad range of spectral signatures for each LULC class. Experiments were conducted on a predominantly rural region characterized by a mixed agro-silvo-pastoral environment. The open source data of the official Portuguese LULC map (Carta de Uso e Ocupação do Solo, COS) from 1995, 2007, 2010, and 2015 were integrated to generate the training samples for the entire period of analysis. The time series was computed from Landsat data based on the normalized difference vegetation index and normalized difference water index, using 221 Landsat images. The Time-Weighted Dynamic Time Warping (TWDTW) classifier was used, since it accounts for LULC-type seasonality and has already achieved promising overall accuracy values for classifications based on time series. The results revealed that the proposed method was efficient in classifying a long-term satellite time-series with an overall accuracy of 76%, providing insights into the main LULC changes that occurred over 21 years.
Cláudia M. Viana; Inês Girão; Jorge Rocha. Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region. Remote Sensing 2019, 11, 1104 .
AMA StyleCláudia M. Viana, Inês Girão, Jorge Rocha. Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region. Remote Sensing. 2019; 11 (9):1104.
Chicago/Turabian StyleCláudia M. Viana; Inês Girão; Jorge Rocha. 2019. "Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region." Remote Sensing 11, no. 9: 1104.
Different mechanisms drive land use and land cover changes (LUCC). This paper presents an exploratory analysis aimed at understanding the complex dynamics of LUCC based on farmers’ intentions when they are faced with four scenarios with the time horizon of 2025: (1) A0 – current social and economic trend; (2) A1 – intensified agricultural production; (3) A2 – reduced agricultural production; and (4) B0 - increasing demand for urban development. LUCC models are applied to a Torres Vedras (Portugal) case study. This territory is located in a peri-urban area near Lisbon dominated by forest and agricultural land, which has been suffering considerable urban pressure in the last decades. Farmers — major agents of agricultural land use change — were interviewed to obtain their LUCC intentions according to the scenarios studied. To model LUCC a Cellular automata-Markov chain approach was applied. Our results suggest that significant LUCC will occur depending on their intentions in the different scenarios. The highlights are: (1) the highest growth in permanently irrigated land in the A1 scenario; (2) the biggest drop in non-irrigated arable land, and the highest growth in forest in the A2 scenario; and (3) the greatest urban growth was recognized in the B0 scenario. To verify if the fitting simulations performed well, techniques to measure agreement and quantity-allocation disagreements were applied.These outcomes could provide decision-makers with the capacity to observe different possible futures in ‘what if’ scenarios, allowing them to anticipate future uncertainties, and consequently allowing them the possibility to choose the more desirable future.
Eduardo Gomes; Patrícia Abrantes; Arnaud Banos; Jorge Rocha. Modelling future land use scenarios based on farmers’ intentions and a cellular automata approach. Land Use Policy 2019, 85, 142 -154.
AMA StyleEduardo Gomes, Patrícia Abrantes, Arnaud Banos, Jorge Rocha. Modelling future land use scenarios based on farmers’ intentions and a cellular automata approach. Land Use Policy. 2019; 85 ():142-154.
Chicago/Turabian StyleEduardo Gomes; Patrícia Abrantes; Arnaud Banos; Jorge Rocha. 2019. "Modelling future land use scenarios based on farmers’ intentions and a cellular automata approach." Land Use Policy 85, no. : 142-154.