Cultural heritage constantly evolves, contributes fundamentally to human development, and increases collective life’s quality. Cultural assets are considered a treasure that must be protected accordingly and passed on to future generations. Among tourism resources, material and immaterial assets belonging to famous people are essential for this industry and for promoting Romanian cultural values. In this framework, the purpose of the study is to identify criteria for selecting Romanian personalities of genius whose valuable works and achievements may augment the country’s cultural tourist heritage. The research method is based on the survey, which targeted the Romanian Academy members (RAMs) and the resident population (RP). Data analysis has been performed through qualitative-quantitative methods. The results show that identified definitions, criteria and nominalizations of Romanian genius personalities by the two groups of respondents have many similarities. For a specific tourism product built on the core of the Romanian personalities of genius, the study reveals four clusters: highly recognized people; averagely known people of genius, which includes contemporaries; remarkable people with landmarks developed in the last two centuries; and another, internationally visible, and known by specialists in a domain. These identified personalities may be reconsidered to expand the cultural heritage for tourism strategy, to develop a tourist package dedicated to the Romanian geniuses based on the capitalization of their achievements.
{"title":"Criteria for Romanian geniuses’ selection as source for a new heritage tourism product","authors":"D. Nicolaie, Elena Matei, G. Manea","doi":"10.5719/hgeo.2022.162.6","DOIUrl":"https://doi.org/10.5719/hgeo.2022.162.6","url":null,"abstract":"Cultural heritage constantly evolves, contributes fundamentally to human development, and increases collective life’s quality. Cultural assets are considered a treasure that must be protected accordingly and passed on to future generations. Among tourism resources, material and immaterial assets belonging to famous people are essential for this industry and for promoting Romanian cultural values. In this framework, the purpose of the study is to identify criteria for selecting Romanian personalities of genius whose valuable works and achievements may augment the country’s cultural tourist heritage. The research method is based on the survey, which targeted the Romanian Academy members (RAMs) and the resident population (RP). Data analysis has been performed through qualitative-quantitative methods. The results show that identified definitions, criteria and nominalizations of Romanian genius personalities by the two groups of respondents have many similarities. For a specific tourism product built on the core of the Romanian personalities of genius, the study reveals four clusters: highly recognized people; averagely known people of genius, which includes contemporaries; remarkable people with landmarks developed in the last two centuries; and another, internationally visible, and known by specialists in a domain. These identified personalities may be reconsidered to expand the cultural heritage for tourism strategy, to develop a tourist package dedicated to the Romanian geniuses based on the capitalization of their achievements.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77785679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-28DOI: 10.3390/geographies2040045
Abhilasha Singh, M. Niranjannaik, S. V. N. Santhosh Kumar, Kumar Gaurav
We evaluate the penetration depth of synthetic aperture radar (SAR) signals into the ground surface at different frequencies. We applied dielectric models (Dobson empirical, Hallikainen, and Dobson semi-empirical) on the ground surface composed of different soil types (sandy, loamy, and clayey). These models result in different penetration depths for the same set of sensors and soil properties. The Dobson semi-empirical model is more sensitive to the soil properties, followed by the Hallikainen and Dobson empirical models. We used the Dobson semi-empirical model to study the penetration depth of the upcoming NASA-ISRO synthetic aperture radar (NISAR) mission operated at the L-band (1.25 GHz) and the S-band (3.22 GHz) into the ground. We observed that depending upon the soil types, the penetration depth of the SAR signals ranges between 0 to 10 cm for the S-band and 0 to 25 cm for the L-band.
{"title":"Comparison of Different Dielectric Models to Estimate Penetration Depth of L- and S-Band SAR Signals into the Ground Surface","authors":"Abhilasha Singh, M. Niranjannaik, S. V. N. Santhosh Kumar, Kumar Gaurav","doi":"10.3390/geographies2040045","DOIUrl":"https://doi.org/10.3390/geographies2040045","url":null,"abstract":"We evaluate the penetration depth of synthetic aperture radar (SAR) signals into the ground surface at different frequencies. We applied dielectric models (Dobson empirical, Hallikainen, and Dobson semi-empirical) on the ground surface composed of different soil types (sandy, loamy, and clayey). These models result in different penetration depths for the same set of sensors and soil properties. The Dobson semi-empirical model is more sensitive to the soil properties, followed by the Hallikainen and Dobson empirical models. We used the Dobson semi-empirical model to study the penetration depth of the upcoming NASA-ISRO synthetic aperture radar (NISAR) mission operated at the L-band (1.25 GHz) and the S-band (3.22 GHz) into the ground. We observed that depending upon the soil types, the penetration depth of the SAR signals ranges between 0 to 10 cm for the S-band and 0 to 25 cm for the L-band.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72952694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.3390/geographies2040044
O. D. de Moraes
This article analyses a near-centennial time series of daily precipitation in the Metropolitan Region of São Paulo, Brazil, in order to quantify the detectable increase in intensity and/or frequency of extreme events. This area is the most populated in the southern hemisphere, and heavy or extreme precipitation events, mainly those related with hydro-meteorological disasters, have important effects on its society. Indexes derived from daily precipitation data through a simple methodological approach are able to quantify changes at decadal and annual time scales. The analysis was carried out for five thresholds, i.e., daily precipitation higher than 50, 60, 70, 80, and 90 mm. The indexes exhibited statistically trends in both precipitation intensity and frequency for all thresholds, indicating significant changes in daily extreme events in the study period.
{"title":"Using a Simple Methodology to Assess the Acceleration in Daily Precipitation Extreme Events in the São Paulo Metropolitan Region","authors":"O. D. de Moraes","doi":"10.3390/geographies2040044","DOIUrl":"https://doi.org/10.3390/geographies2040044","url":null,"abstract":"This article analyses a near-centennial time series of daily precipitation in the Metropolitan Region of São Paulo, Brazil, in order to quantify the detectable increase in intensity and/or frequency of extreme events. This area is the most populated in the southern hemisphere, and heavy or extreme precipitation events, mainly those related with hydro-meteorological disasters, have important effects on its society. Indexes derived from daily precipitation data through a simple methodological approach are able to quantify changes at decadal and annual time scales. The analysis was carried out for five thresholds, i.e., daily precipitation higher than 50, 60, 70, 80, and 90 mm. The indexes exhibited statistically trends in both precipitation intensity and frequency for all thresholds, indicating significant changes in daily extreme events in the study period.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77069739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-11DOI: 10.3390/geographies2040042
Gurwinder Singh, Sartajvir Singh, G. Sethi, V. Sood
Continuous observation and management of agriculture are essential to estimate crop yield and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to monitor agriculture on a larger scale. With high-resolution satellite datasets, the monitoring and mapping of agricultural land are easier and more effective. Nowadays, the applicability of deep learning is continuously increasing in numerous scientific domains due to the availability of high-end computing facilities. In this study, deep learning (U-Net) has been implemented in the mapping of different agricultural land use types over a part of Punjab, India, using the Sentinel-2 data. As a comparative analysis, a well-known machine learning random forest (RF) has been tested. To assess the agricultural land, the major winter season crop types, i.e., wheat, berseem, mustard, and other vegetation have been considered. In the experimental outcomes, the U-Net deep learning and RF classifiers achieved 97.8% (kappa value: 0.9691) and 96.2% (Kappa value: 0.9469), respectively. Since little information exists on the vegetation cultivated by smallholders in the region, this study is particularly helpful in the assessment of the mustard (Brassica nigra), and berseem (Trifolium alexandrinum) acreage in the region. Deep learning on remote sensing data allows the object-level detection of the earth’s surface imagery.
{"title":"Deep Learning in the Mapping of Agricultural Land Use Using Sentinel-2 Satellite Data","authors":"Gurwinder Singh, Sartajvir Singh, G. Sethi, V. Sood","doi":"10.3390/geographies2040042","DOIUrl":"https://doi.org/10.3390/geographies2040042","url":null,"abstract":"Continuous observation and management of agriculture are essential to estimate crop yield and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to monitor agriculture on a larger scale. With high-resolution satellite datasets, the monitoring and mapping of agricultural land are easier and more effective. Nowadays, the applicability of deep learning is continuously increasing in numerous scientific domains due to the availability of high-end computing facilities. In this study, deep learning (U-Net) has been implemented in the mapping of different agricultural land use types over a part of Punjab, India, using the Sentinel-2 data. As a comparative analysis, a well-known machine learning random forest (RF) has been tested. To assess the agricultural land, the major winter season crop types, i.e., wheat, berseem, mustard, and other vegetation have been considered. In the experimental outcomes, the U-Net deep learning and RF classifiers achieved 97.8% (kappa value: 0.9691) and 96.2% (Kappa value: 0.9469), respectively. Since little information exists on the vegetation cultivated by smallholders in the region, this study is particularly helpful in the assessment of the mustard (Brassica nigra), and berseem (Trifolium alexandrinum) acreage in the region. Deep learning on remote sensing data allows the object-level detection of the earth’s surface imagery.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75912036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-11DOI: 10.3390/geographies2040043
S. K. Abdul Rahaman, S. Aruchamy
Nilgiri tea is a vital perennial beverage variety and is in high demand in global markets due to its quality and medicinal value. In recent years, the cultivation of tea plantations has decreased due to the extreme climate and prolonged practice of tea cultivation in the same area, decreasing its taste and quality. In this scenario, land suitability analysis is the best approach to evaluate the bio-physiochemical and ecological parameters of tea plantations. The present study aims to identify and delineate appropriate land best suited for the cultivation of tea within the Kallar watershed using the geographic information system (GIS) and multi-criteria evaluation (MCE) techniques. This study utilises various suitability criteria, such as soil (texture, hydrogen ion concentration, electrical conductivity, depth, base saturation, and drainability), climate (rainfall and temperature), topography (relief and slope), land use, and the normalised difference vegetation index (NDVI), to evaluate the suitability of the land for growing tea plantations based on the Food and Agricultural Organization (FAO) guidelines for rainfed agriculture. The resultant layers were classified into five suitability classes, including high (S1), moderate (S2), and marginal (S3) classes, which occupied 16.7%, 7.08%, and 16.3% of the land, whereas the currently and permanently not suitable (N1 and N2) classes covered about 18.52% and 29.06% of the total geographic area. This study provides sufficient insights to decision-makers and farmers to support them in making more practical and scientific decisions regarding the cultivation of tea plantations that will result in the increased production of quality tea, and prevent and protect human life from harmful diseases.
{"title":"Land Suitability Evaluation of Tea (Camellia sinensis L.) Plantation in Kallar Watershed of Nilgiri Bioreserve, India","authors":"S. K. Abdul Rahaman, S. Aruchamy","doi":"10.3390/geographies2040043","DOIUrl":"https://doi.org/10.3390/geographies2040043","url":null,"abstract":"Nilgiri tea is a vital perennial beverage variety and is in high demand in global markets due to its quality and medicinal value. In recent years, the cultivation of tea plantations has decreased due to the extreme climate and prolonged practice of tea cultivation in the same area, decreasing its taste and quality. In this scenario, land suitability analysis is the best approach to evaluate the bio-physiochemical and ecological parameters of tea plantations. The present study aims to identify and delineate appropriate land best suited for the cultivation of tea within the Kallar watershed using the geographic information system (GIS) and multi-criteria evaluation (MCE) techniques. This study utilises various suitability criteria, such as soil (texture, hydrogen ion concentration, electrical conductivity, depth, base saturation, and drainability), climate (rainfall and temperature), topography (relief and slope), land use, and the normalised difference vegetation index (NDVI), to evaluate the suitability of the land for growing tea plantations based on the Food and Agricultural Organization (FAO) guidelines for rainfed agriculture. The resultant layers were classified into five suitability classes, including high (S1), moderate (S2), and marginal (S3) classes, which occupied 16.7%, 7.08%, and 16.3% of the land, whereas the currently and permanently not suitable (N1 and N2) classes covered about 18.52% and 29.06% of the total geographic area. This study provides sufficient insights to decision-makers and farmers to support them in making more practical and scientific decisions regarding the cultivation of tea plantations that will result in the increased production of quality tea, and prevent and protect human life from harmful diseases.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85804548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-08DOI: 10.3390/geographies2040041
E. Mikhailova, Lili Lin, Zhenbang Hao, H. Zurqani, C. Post, M. Schlautman, Gregory C. Post, G. Shepherd
Conflicts of interest (COI) are an integral part of human society, including their influence on greenhouse gas (GHG) emissions and climate change. Individuals or entities often have multiple interests ranging from financial benefits to reducing climate change-related risks, where choosing one interest may negatively impact other interests and societal welfare. These types of COI require specific management strategies. This study examines COI from land-use decisions as an intersection of different perspectives on land use (e.g., land conservation versus land development), which can have various consequences regarding GHG emissions. This study uses the state of New Jersey (NJ) in the United States of America (USA) as a case study to demonstrate COI related to soil-based GHG emissions from land conversions between 2001 and 2016 which caused $722.2 M (where M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions. These emissions are currently not accounted for in NJ’s total carbon footprint (CF), which can negatively impact the state’s ability to reach its carbon reduction goals. The state of NJ Statutes Annotated 26:2C-37 (2007): Global Warming Response Act (GWRA) (updated in 2019) set a statewide goal of reducing GHG emissions to 80 percent below 2006 levels by 2050. Remote sensing and soil data analysis allow temporal and quantitative assessment of the contribution of land cover conversions to NJ’s CF by soil carbon type, soil type, land cover type, and administrative units (state, counties), which helps document past, and estimate future related GHG emissions using a land cover change scenario to calculate the amount of GHG emissions if an area of land was to be developed. Decisions related to future land conversions involve potential COI within and outside state administrative structures, which could be managed by a conflict-of-interest policy. The site and time-specific disclosures of GHG emissions from land conversions can help governments manage these COI to mitigate climate change impacts and costs by assigning financial responsibility for specific CF contributions. Projected sea-level rise will impact 16 out of 21 NJ’s counties and it will likely reach coastal areas with densely populated urban areas throughout NJ. Low proportion of available public land limits opportunities for relocation. Increased climate-change-related damages in NJ and elsewhere will increase the number of climate litigation cases to alleviate costs associated with climate change. This litigation will further highlight the importance and intensity of different COI.
{"title":"Conflicts of Interest and Emissions from Land Conversions: State of New Jersey as a Case Study","authors":"E. Mikhailova, Lili Lin, Zhenbang Hao, H. Zurqani, C. Post, M. Schlautman, Gregory C. Post, G. Shepherd","doi":"10.3390/geographies2040041","DOIUrl":"https://doi.org/10.3390/geographies2040041","url":null,"abstract":"Conflicts of interest (COI) are an integral part of human society, including their influence on greenhouse gas (GHG) emissions and climate change. Individuals or entities often have multiple interests ranging from financial benefits to reducing climate change-related risks, where choosing one interest may negatively impact other interests and societal welfare. These types of COI require specific management strategies. This study examines COI from land-use decisions as an intersection of different perspectives on land use (e.g., land conservation versus land development), which can have various consequences regarding GHG emissions. This study uses the state of New Jersey (NJ) in the United States of America (USA) as a case study to demonstrate COI related to soil-based GHG emissions from land conversions between 2001 and 2016 which caused $722.2 M (where M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions. These emissions are currently not accounted for in NJ’s total carbon footprint (CF), which can negatively impact the state’s ability to reach its carbon reduction goals. The state of NJ Statutes Annotated 26:2C-37 (2007): Global Warming Response Act (GWRA) (updated in 2019) set a statewide goal of reducing GHG emissions to 80 percent below 2006 levels by 2050. Remote sensing and soil data analysis allow temporal and quantitative assessment of the contribution of land cover conversions to NJ’s CF by soil carbon type, soil type, land cover type, and administrative units (state, counties), which helps document past, and estimate future related GHG emissions using a land cover change scenario to calculate the amount of GHG emissions if an area of land was to be developed. Decisions related to future land conversions involve potential COI within and outside state administrative structures, which could be managed by a conflict-of-interest policy. The site and time-specific disclosures of GHG emissions from land conversions can help governments manage these COI to mitigate climate change impacts and costs by assigning financial responsibility for specific CF contributions. Projected sea-level rise will impact 16 out of 21 NJ’s counties and it will likely reach coastal areas with densely populated urban areas throughout NJ. Low proportion of available public land limits opportunities for relocation. Increased climate-change-related damages in NJ and elsewhere will increase the number of climate litigation cases to alleviate costs associated with climate change. This litigation will further highlight the importance and intensity of different COI.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82101558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-24DOI: 10.3390/geographies2040040
J. Knight
Sand grains are ubiquitous in the Earth’s system, and are found in different environmental settings globally, but sand itself as a physical object has multiple conflicting meanings with respect to both its agglomeration into landforms such as sand dunes and beaches, and how sand and its dynamics have cultural significance and meaning. This study takes a transdisciplinary approach towards examining the multiple meanings of sand, focusing on sand as a spatiotemporal pheneomenon that exists in different contexts within the Earth system. The nature and spatiotemporalities of sand are framed in this study through the concepts of presence, absence and transience, which are key interpretive approaches that lie at the interface of how the physical and phenomenological worlds interact with each other. This is a new and innovative approach to understanding people–environment relationships. These concepts are then discussed using the examples of the dynamics of and values ascribed to desert dune and sandy beach landscapes, drawn from locations globally. These examples show that the dynamic geomorphic changes taking place in sand landscapes (sandscapes) by erosion and deposition (determining the presence and absence of sand in such landscapes) pose challenges for the ways in which people make sense of, locate, interact with and value these landscapes. This uncertainty that arises from constant change (the transience of sandscapes) highlights the multiple meanings that sandscapes can hold, and this represents the comforting yet also unsettling nature of sand, as a vivid symbol of human–Earth relationships.
{"title":"Presence, Absence, Transience: The Spatiotemporalities of Sand","authors":"J. Knight","doi":"10.3390/geographies2040040","DOIUrl":"https://doi.org/10.3390/geographies2040040","url":null,"abstract":"Sand grains are ubiquitous in the Earth’s system, and are found in different environmental settings globally, but sand itself as a physical object has multiple conflicting meanings with respect to both its agglomeration into landforms such as sand dunes and beaches, and how sand and its dynamics have cultural significance and meaning. This study takes a transdisciplinary approach towards examining the multiple meanings of sand, focusing on sand as a spatiotemporal pheneomenon that exists in different contexts within the Earth system. The nature and spatiotemporalities of sand are framed in this study through the concepts of presence, absence and transience, which are key interpretive approaches that lie at the interface of how the physical and phenomenological worlds interact with each other. This is a new and innovative approach to understanding people–environment relationships. These concepts are then discussed using the examples of the dynamics of and values ascribed to desert dune and sandy beach landscapes, drawn from locations globally. These examples show that the dynamic geomorphic changes taking place in sand landscapes (sandscapes) by erosion and deposition (determining the presence and absence of sand in such landscapes) pose challenges for the ways in which people make sense of, locate, interact with and value these landscapes. This uncertainty that arises from constant change (the transience of sandscapes) highlights the multiple meanings that sandscapes can hold, and this represents the comforting yet also unsettling nature of sand, as a vivid symbol of human–Earth relationships.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76569535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-21DOI: 10.3390/geographies2040039
L. Valderrama-Landeros, F. Flores-Verdugo, F. Flores-de-Santiago
Tropical sandy beaches provide essential ecosystem services and support many local economies. In recent times, however, there has been a massive infrastructure expansion in popular tourist destinations worldwide. To investigate the shoreline variability at a popular tourist destination in Mexico, we used the novel semi-automatic CoastSat program (1980 to 2020) and the climate dataset ERA5 (wave energy and direction). We also measured the beach cross-shore distance and the foredune height with topographic surveys. The results indicate that the section of real estate seafront infrastructure in the study site presents a considerable shoreline erosion due to the fragmentation between the foredune ridge and the beach berm, based on the in situ transects. Moreover, foredune corridors with cross-shore distances of up to 70 to 90 m and dune heights of 8 m, can be seen in the short unobstructed passages between buildings. In the south section we found the coastline in a much more stable condition because this area has not had coastal infrastructures, as of yet. For the most part, the remote sensing analysis indicates constant erosion since 1990 in the real estate section (mainly seafront hotels) and an overall accretion pattern at the unobstructed beach-dune locations. This study demonstrates the catastrophic consequences of beach fragmentation due to unplanned real estate developments, by combining in situ surveys and a freely available big-data approach (CoastSat).
{"title":"Assessing the Coastal Vulnerability by Combining Field Surveys and the Analytical Potential of CoastSat in a Highly Impacted Tourist Destination","authors":"L. Valderrama-Landeros, F. Flores-Verdugo, F. Flores-de-Santiago","doi":"10.3390/geographies2040039","DOIUrl":"https://doi.org/10.3390/geographies2040039","url":null,"abstract":"Tropical sandy beaches provide essential ecosystem services and support many local economies. In recent times, however, there has been a massive infrastructure expansion in popular tourist destinations worldwide. To investigate the shoreline variability at a popular tourist destination in Mexico, we used the novel semi-automatic CoastSat program (1980 to 2020) and the climate dataset ERA5 (wave energy and direction). We also measured the beach cross-shore distance and the foredune height with topographic surveys. The results indicate that the section of real estate seafront infrastructure in the study site presents a considerable shoreline erosion due to the fragmentation between the foredune ridge and the beach berm, based on the in situ transects. Moreover, foredune corridors with cross-shore distances of up to 70 to 90 m and dune heights of 8 m, can be seen in the short unobstructed passages between buildings. In the south section we found the coastline in a much more stable condition because this area has not had coastal infrastructures, as of yet. For the most part, the remote sensing analysis indicates constant erosion since 1990 in the real estate section (mainly seafront hotels) and an overall accretion pattern at the unobstructed beach-dune locations. This study demonstrates the catastrophic consequences of beach fragmentation due to unplanned real estate developments, by combining in situ surveys and a freely available big-data approach (CoastSat).","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77772548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-19DOI: 10.3390/geographies2040038
P. R. Giongo, Ana Paula Aparecida de Oliveira Assis, M. Silva, A. Montenegro, J. Taveira, Adriana R Costa, P. C. Silva, A. M. M. Giongo, Héliton Pandorfi, Alessandro José Marques Santos, C. Backes, Maria Beatriz Ferreira, J. L. B. D. Silva
The Brazilian Cerrado biome provides relevant ecosystem services for Brazil and South America, being strategic for the planning and management of water resources as well as for agribusiness. The objective was to evaluate the water quality along the course of the Córrego da Formiga in a virgin portion of the Brazilian Cerrado, the relationship of land use with physical-chemical and biological parameters of the water, and the inflow of the tributary. Five water collection points were defined (between the source and mouth) and observed on a quarterly scale in 2015, water samples were collected and analyzed for physical-chemical and biological parameters in the laboratory, and flow measurements were performed at the same point and day of water collection. To identify and quantify land use and land cover (LULC) in the watershed, an image from the Landsat8-OLI satellite was obtained, and other geomorphological data from hypsometry (Topodata-INPE) were obtained to generate the slope, basin delimitation, and contribution area for each water collection point. The LULC percentages for each area of contribution to the water collection points were correlated with the physical-chemical and biological parameters of the water and submitted to multivariate analysis (PLS-DA) for analysis and grouping among the five analyzed points. Changes in water-quality patterns were more pronounced concerning the time when the first and last sampling was performed (rainy period) and may be influenced by the increase in the volume of water in these periods. The stream flow is highly variable over time and between points, with the lowest recorded flow being 0.1 L s−1 (P1) and the highest being 947.80 L s−1 (P5). Córrego da Formiga has class III water quality (CONAMA resolution 357), which characterizes small restrictions on the use of water for multiple uses. The soil cover with native vegetation is just over 12%, while the predominance was of the classes of sugar cane (62.42%) and pasture (19.33%). The PLS-DA analysis allowed separating the water analysis points between P1, P2, P3, and P5, while P4 was superimposed on others. It was also possible to verify that the parameters that weighed the most for this separation of water quality were pH, alkalinity_T, alkalinity_h, calcium, and hardness, all with a tendency to increase concentration from the source (P1) to the mouth (P5). As for water quality, it was also possible to verify that points P2 and P5 presented better water-quality conditions.
巴西塞拉多生物群落为巴西和南美洲提供了相关的生态系统服务，对水资源的规划和管理以及农业综合企业具有战略意义。目的是评价巴西塞拉多(Cerrado)未开发地区Córrego da Formiga河沿岸的水质、土地利用与水的物理化学和生物参数的关系以及支流的流入情况。2015年确定了5个取水点(在水源和河口之间)，并按季度进行观测，在实验室采集水样并分析其物理化学和生物参数，并在取水的同一点和当天进行流量测量。为了识别和量化流域的土地利用和土地覆盖(LULC)，利用Landsat8-OLI卫星图像和其他地貌数据(Topodata-INPE)生成每个集水点的坡度、流域划界和贡献面积。各集水点贡献区域的LULC百分比与水的物理化学和生物参数相关，并提交多变量分析(PLS-DA)对五个分析点进行分析和分组。在进行第一次和最后一次采样的时间(雨季)，水质模式的变化更为明显，并可能受到这些时期水量增加的影响。水流随时间和点间变化很大，最低记录流量为0.1 L s−1 (P1)，最高记录流量为947.80 L s−1 (P5)。Córrego da Formiga的水质为III级(CONAMA决议357)，其特点是对多种用途的用水限制很小。原生植被覆盖面积略高于12%，以甘蔗类(62.42%)和牧草类(19.33%)为主。PLS-DA分析允许在P1、P2、P3和P5之间分离水分析点，而P4则叠加在其他点上。还可以验证，对这种水质分离最重要的参数是pH、碱度t、碱度h、钙和硬度，它们都有从源头(P1)到口(P5)浓度增加的趋势。在水质方面，也可以验证P2点和P5点的水质条件较好。
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