Pub Date : 2022-10-05DOI: 10.11137/1982-3908_2022_45_44825
Beatriz Da Silva Feitoza Santana, Felipe Gonçalves Amaral, C. B. M. Cruz
Goiás represents Brazil as one of the most important states in agricultural production. 97% of this territory is located in the Brazilian Cerrado, an area of fundamental importance for the understanding of agriculture. The relevance of soy is closely linked to its market value, being present since the 1970s and dominating Brazilian territory, becoming popular as the main export product. Sugar cane, on the other hand, reflects the mosaic of cultures and the recent economy of Goiás. This crop presents a progressive growth based on the interest for its derivatives (ethanol and sugar) and the expansion of the sugar-energy sector in the country. This paper intends to analyze the spatiotemporal behavior of soybean and sugarcane crops in the state of Goiás between the years 1988 to 2018, using geotechnologies. The two cultures present a favorable situation and confirmed the hypotheses brought throughout the work. The use of different forms of representation and analysis aided in the understanding the South of Goiás, a mesoregion that stands out for both crops. The two cultures dominate almost entirely the Goiás lands destined for agricultural production, however, the spatial-temporal dynamics of each one of them occurs in different ways and at different times.
{"title":"Spatial Analysis of Soybean and Sugarcane Monocultures in the Goiás Landscape","authors":"Beatriz Da Silva Feitoza Santana, Felipe Gonçalves Amaral, C. B. M. Cruz","doi":"10.11137/1982-3908_2022_45_44825","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_44825","url":null,"abstract":"Goiás represents Brazil as one of the most important states in agricultural production. 97% of this territory is located in the Brazilian Cerrado, an area of fundamental importance for the understanding of agriculture. The relevance of soy is closely linked to its market value, being present since the 1970s and dominating Brazilian territory, becoming popular as the main export product. Sugar cane, on the other hand, reflects the mosaic of cultures and the recent economy of Goiás. This crop presents a progressive growth based on the interest for its derivatives (ethanol and sugar) and the expansion of the sugar-energy sector in the country. This paper intends to analyze the spatiotemporal behavior of soybean and sugarcane crops in the state of Goiás between the years 1988 to 2018, using geotechnologies. The two cultures present a favorable situation and confirmed the hypotheses brought throughout the work. The use of different forms of representation and analysis aided in the understanding the South of Goiás, a mesoregion that stands out for both crops. The two cultures dominate almost entirely the Goiás lands destined for agricultural production, however, the spatial-temporal dynamics of each one of them occurs in different ways and at different times.","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43300793","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 : 2022-09-26DOI: 10.11137/1982-3908_2022_45_45982
U. Suhud, M. Allan
This study aims to measure the impact of travel motivation and destination image on stage of intention to visit a volcano site, particularly Anak Krakatau. "Anak" means "child". This mount is a new volcano created by the deadly eruption of the Krakatau volcano which killed 36,417 people in 1883 and had a wide-ranging impact on some of the world's ecosystems. This mountain is located on a small island between two large islands of Sumatra and Java, Indonesia. This destination is more popular among domestic tourists. Data were collected using an online questionnaire platform and participants were approached using a convenient sampling technique. Data were analysed using exploratory and confirmatory factor analyses, as well as structural equation model. Stage intention consisted of visit intention in the period of one, three, and five years and each of them were treated as individual variable unless for visit intention in a year due to insignificance. As a result, travel motivation had a significant impact on destination image and destination image significantly affects stage of intention.
{"title":"Travel Motivation, Destination Image, and Stage of Intention to Visit Anak Krakatau Mount: a Study of Volcano Tourism in Indonesia","authors":"U. Suhud, M. Allan","doi":"10.11137/1982-3908_2022_45_45982","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_45982","url":null,"abstract":"This study aims to measure the impact of travel motivation and destination image on stage of intention to visit a volcano site, particularly Anak Krakatau. \"Anak\" means \"child\". This mount is a new volcano created by the deadly eruption of the Krakatau volcano which killed 36,417 people in 1883 and had a wide-ranging impact on some of the world's ecosystems. This mountain is located on a small island between two large islands of Sumatra and Java, Indonesia. This destination is more popular among domestic tourists. Data were collected using an online questionnaire platform and participants were approached using a convenient sampling technique. Data were analysed using exploratory and confirmatory factor analyses, as well as structural equation model. Stage intention consisted of visit intention in the period of one, three, and five years and each of them were treated as individual variable unless for visit intention in a year due to insignificance. As a result, travel motivation had a significant impact on destination image and destination image significantly affects stage of intention.","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45266218","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 : 2022-09-20DOI: 10.11137/1982-3908_2022_45_40758
Elisiane Alba, Marta Laura de Souza Alexandre, Juliana Marchesan, Luciana Sandra Bastos De Souza, A. C. Bezerra, Emanuelle Silva Araújo
{"title":"Comparação entre Algoritmos de Aprendizado de Máquina para a Identificação de Floresta Tropical Sazonalmente Seca","authors":"Elisiane Alba, Marta Laura de Souza Alexandre, Juliana Marchesan, Luciana Sandra Bastos De Souza, A. C. Bezerra, Emanuelle Silva Araújo","doi":"10.11137/1982-3908_2022_45_40758","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_40758","url":null,"abstract":"","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46368512","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 : 2022-09-16DOI: 10.11137/1982-3908_2022_45_41356
Lígia Albuquerque de Alcântara Ferreira, R. M. Gonçalves, J. Cabral
{"title":"Entendendo a Complexidade dos Requisitos Necessários para Subsidiar a Implementação de SIGWEB para Comitês de Bacias Hidrográficas a partir da Avaliação de Sistemas Existentes no Brasil","authors":"Lígia Albuquerque de Alcântara Ferreira, R. M. Gonçalves, J. Cabral","doi":"10.11137/1982-3908_2022_45_41356","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_41356","url":null,"abstract":"","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47405227","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 : 2022-09-15DOI: 10.11137/1982-3908_2022_45_40011
I. Bezerra, T. Silva
{"title":"Influência da Evolução do Uso e Ocupação do Solo do Município de Lucena- PB no Armazenamento de Carbono: Projeções para os anos de 2030 e 2040","authors":"I. Bezerra, T. Silva","doi":"10.11137/1982-3908_2022_45_40011","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_40011","url":null,"abstract":"","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44861968","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 : 2022-09-15DOI: 10.11137/1982-3908_2022_45_46456
I. Indarto, E. Hidayah, Farid Lukman Hakim
This study aims to analyse land use, and land cover (LULC) changes in East Java province in Indonesia. The changes are analysed by comparing two maps (the national digital map and the map interpreted from Landsat-8). Supervised classification of Landsat image using maximum likelihood algorithm done an overall and kappa accuracy of 96.62% and 96.02 %, respectively. The classification produces nine (9) classes, i.e.: (1) the pavement or urban area, (2) heterogeneous agricultural land, (3) paddy field, (4) open water, (5) dense vegetation (forest), (6) sparse vegetation (plantation), (7) shrubland, (8) Wetlands, and (9) Sandy-clay-rock. Furthermore, three subsets areas are explored to study the LULC changes caused by the development of the transportation infrastructure; industrial sites; the agricultural sector; tourism; urbanisation and sub-urbanisation. The LULC change is more marked in the most urbanised areas (in and around the big cities), followed by LULC change in and around medium cities and rural areas. Regional development during the last two decades has increased built-up and plantation areas. Conversely, the development has reduced paddy fields, rural areas, and water bodies. The LULC changes have significantly changed the natural to a human-dominated landscape.
{"title":"Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia","authors":"I. Indarto, E. Hidayah, Farid Lukman Hakim","doi":"10.11137/1982-3908_2022_45_46456","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_46456","url":null,"abstract":"This study aims to analyse land use, and land cover (LULC) changes in East Java province in Indonesia. The changes are analysed by comparing two maps (the national digital map and the map interpreted from Landsat-8). Supervised classification of Landsat image using maximum likelihood algorithm done an overall and kappa accuracy of 96.62% and 96.02 %, respectively. The classification produces nine (9) classes, i.e.: (1) the pavement or urban area, (2) heterogeneous agricultural land, (3) paddy field, (4) open water, (5) dense vegetation (forest), (6) sparse vegetation (plantation), (7) shrubland, (8) Wetlands, and (9) Sandy-clay-rock. Furthermore, three subsets areas are explored to study the LULC changes caused by the development of the transportation infrastructure; industrial sites; the agricultural sector; tourism; urbanisation and sub-urbanisation. The LULC change is more marked in the most urbanised areas (in and around the big cities), followed by LULC change in and around medium cities and rural areas. Regional development during the last two decades has increased built-up and plantation areas. Conversely, the development has reduced paddy fields, rural areas, and water bodies. The LULC changes have significantly changed the natural to a human-dominated landscape. ","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46857440","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 : 2022-08-31DOI: 10.11137/1982-3908_2022_45_42913
Fidel Martínez-García
Within the framework of the “site effect” study and the spatial impact of local geographic features on seismic waves, the maximum accelerations of 45 interplate and intraslab seismic events with magnitudes (Mw) in the range of 5.6 to 8.2 that occurred from 1985 to 2018 were spatially analyzed and processed. Averages and maximum acceleration values of 172 accelerographs distributed among the territories boundaries located in the most seismic region of Mexico, are replaced the data of the scale of seismic moment magnitude (Mw) in each of the epicenters of the 45 events studied. The differential seismic impact of the topography that four Significant Epicentral Zones (SEZ) identified exert in two important cities, two tourist poles and two commercial seaports is identified. Correspondingly, the predominant orientation, direction, spatial tendency at the lithosphere level, which follow seismic waves as a result of interaction with topography within each SEZ were identified.
{"title":"Landforms Spatial Interference with Seismic Waves in the Area of Influence of the Cocos Plate, Mexico","authors":"Fidel Martínez-García","doi":"10.11137/1982-3908_2022_45_42913","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_42913","url":null,"abstract":"Within the framework of the “site effect” study and the spatial impact of local geographic features on seismic waves, the maximum accelerations of 45 interplate and intraslab seismic events with magnitudes (Mw) in the range of 5.6 to 8.2 that occurred from 1985 to 2018 were spatially analyzed and processed. Averages and maximum acceleration values of 172 accelerographs distributed among the territories boundaries located in the most seismic region of Mexico, are replaced the data of the scale of seismic moment magnitude (Mw) in each of the epicenters of the 45 events studied. The differential seismic impact of the topography that four Significant Epicentral Zones (SEZ) identified exert in two important cities, two tourist poles and two commercial seaports is identified. Correspondingly, the predominant orientation, direction, spatial tendency at the lithosphere level, which follow seismic waves as a result of interaction with topography within each SEZ were identified.","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42757620","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 : 2022-08-12DOI: 10.11137/1982-3908_2022_45_47481
A. M. Santos, Nadyelle Curcino do Carmo, Fabrizia Gioppo Nunes, Larissa Andrade de Aguiar, Carlos Fabricio Assunção da Silva
In the classification of images for land cover and land use mapping, several methods can be applied, however, they can present different results in relation to field truth. Therefore, the objective of this work was to test techniques for classifying high spatial digital images obtained from the Google Earth Pro® platform. The images refer to a section of the Federal University of Goias, campus Samambaia Goiania - GO, Brazil. Classification tests were performed on the images obtained, using two classifiers per region and two classifiers per pixel, both available free of charge, in the Spring software of the National Institute for Space Research (INPE / Brazil). For the analysis of the quality of the classifications, the results were compared to a survey by direct method, in this case the topographic one, seeking to identify which classifier came closest to the field truth. The classification that presented the best performance and class separability was the Bhattacharya, with Global Accuracy of 0.85. Bhattacharya was also the classifier that came closest in terms of measured areas, by the topographic survey, with the areas of the “zinc roofing” use class, analyzed and calculated.
{"title":"Digital Image Classification: a Comparison of Classic Methods for Land Cover and Land Use Mapping","authors":"A. M. Santos, Nadyelle Curcino do Carmo, Fabrizia Gioppo Nunes, Larissa Andrade de Aguiar, Carlos Fabricio Assunção da Silva","doi":"10.11137/1982-3908_2022_45_47481","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_47481","url":null,"abstract":"In the classification of images for land cover and land use mapping, several methods can be applied, however, they can present different results in relation to field truth. Therefore, the objective of this work was to test techniques for classifying high spatial digital images obtained from the Google Earth Pro® platform. The images refer to a section of the Federal University of Goias, campus Samambaia Goiania - GO, Brazil. Classification tests were performed on the images obtained, using two classifiers per region and two classifiers per pixel, both available free of charge, in the Spring software of the National Institute for Space Research (INPE / Brazil). For the analysis of the quality of the classifications, the results were compared to a survey by direct method, in this case the topographic one, seeking to identify which classifier came closest to the field truth. The classification that presented the best performance and class separability was the Bhattacharya, with Global Accuracy of 0.85. Bhattacharya was also the classifier that came closest in terms of measured areas, by the topographic survey, with the areas of the “zinc roofing” use class, analyzed and calculated.","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42147751","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 : 2022-07-26DOI: 10.11137/1982-3908_2022_45_45732
Renan Evangelista Vieira, L. C. da Cunha, Luana Keiroz Pinho, Alexandre Macedo Fernandes, Raquel Da Conceicao Dos Santos, Ricardo Keim, Carlos Musetti De Assis, T. Franklin, Jessica da Silva Nogueira
Water masses are commonly identified according to their conservative parameters. However, there are also studies that use non-conservative parameters, together with the conservative ones, to refine the water masses identification. The aim of this study was to analyze the chemical properties of the water masses in the western tropical Atlantic Ocean (WTAO) according to their inorganic nutrient concentration: nitrate-NO3–, phosphate-PO43–, and silicic acid-Si(OH)4, to set a regional descriptive framework of the water column in view of future comparative studies. We collected full-depth water column samples from 18 oceanographic stations from a latitudinal transect along 38°W, from 02°S to 15°N during the PIRATA-BR XVII and XVIII campaigns, in November 2017 and 2018. We have also used the regional data available from GLODAPv.2 data product to improve the water masses characterization. Six water masses were identified in the region based on their values of potential temperature, salinity, potential density, and neutral density observed in the study area according to the CTD-O2 data: Tropical Surface Water (TSW); South and North Atlantic Central Water (SACW and NACW, respectively); Antarctic Intermediate Water (AAIW); North Atlantic Deep Water (NADW); and Antarctic Bottom Water (AABW). Regarding the nutrient content within each water mass, our results showed that TSW corresponds to a surface oligotrophic water; NACW and SACW have intermediate nutrient concentration values between TSW and AAIW; AAIW showed the highest concentration of phosphate-PO43– (~ 1.35 µmol kg–1) and nitrate-NO3– (~30 µmol kg–1); AABW, on the other hand, was the water mass with the highest silicic acid-Si(OH)4 concentration (~ 80 µmol kg–1), as well as high nitrate-NO3– (~ 25 µmol kg–1) and phosphate-PO43– (~ 1.80 µmol kg–1) concentrations. Additionally, the water column between 300 and 650 m displays an increase in phosphate-PO43– concentrations north of 5oN, associated to a low dissolved oxygen area coupled to the North Equatorial Under Current (NEUC). Long-term, sustained hydrographic and ocean biogeochemistry observations are key to understand how climate change is affecting the ocean, and this study is a contribution to that.
{"title":"Biogeochemical Characteristics of Western Tropical Atlantic Ocean Water Masses","authors":"Renan Evangelista Vieira, L. C. da Cunha, Luana Keiroz Pinho, Alexandre Macedo Fernandes, Raquel Da Conceicao Dos Santos, Ricardo Keim, Carlos Musetti De Assis, T. Franklin, Jessica da Silva Nogueira","doi":"10.11137/1982-3908_2022_45_45732","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_45732","url":null,"abstract":"Water masses are commonly identified according to their conservative parameters. However, there are also studies that use non-conservative parameters, together with the conservative ones, to refine the water masses identification. The aim of this study was to analyze the chemical properties of the water masses in the western tropical Atlantic Ocean (WTAO) according to their inorganic nutrient concentration: nitrate-NO3–, phosphate-PO43–, and silicic acid-Si(OH)4, to set a regional descriptive framework of the water column in view of future comparative studies. We collected full-depth water column samples from 18 oceanographic stations from a latitudinal transect along 38°W, from 02°S to 15°N during the PIRATA-BR XVII and XVIII campaigns, in November 2017 and 2018. We have also used the regional data available from GLODAPv.2 data product to improve the water masses characterization. Six water masses were identified in the region based on their values of potential temperature, salinity, potential density, and neutral density observed in the study area according to the CTD-O2 data: Tropical Surface Water (TSW); South and North Atlantic Central Water (SACW and NACW, respectively); Antarctic Intermediate Water (AAIW); North Atlantic Deep Water (NADW); and Antarctic Bottom Water (AABW). Regarding the nutrient content within each water mass, our results showed that TSW corresponds to a surface oligotrophic water; NACW and SACW have intermediate nutrient concentration values between TSW and AAIW; AAIW showed the highest concentration of phosphate-PO43– (~ 1.35 µmol kg–1) and nitrate-NO3– (~30 µmol kg–1); AABW, on the other hand, was the water mass with the highest silicic acid-Si(OH)4 concentration (~ 80 µmol kg–1), as well as high nitrate-NO3– (~ 25 µmol kg–1) and phosphate-PO43– (~ 1.80 µmol kg–1) concentrations. Additionally, the water column between 300 and 650 m displays an increase in phosphate-PO43– concentrations north of 5oN, associated to a low dissolved oxygen area coupled to the North Equatorial Under Current (NEUC). Long-term, sustained hydrographic and ocean biogeochemistry observations are key to understand how climate change is affecting the ocean, and this study is a contribution to that.","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47558436","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 : 2022-07-26DOI: 10.11137/1982-3908_2022_45_40761
Bruno César Capucin, Michelle Simões Reboita, Vinícius Lucyrio, Gustavo Carlos Juan Escobar
{"title":"Onda de Frio Histórica no Brasil: um Estudo de Caso de Junho de 1985","authors":"Bruno César Capucin, Michelle Simões Reboita, Vinícius Lucyrio, Gustavo Carlos Juan Escobar","doi":"10.11137/1982-3908_2022_45_40761","DOIUrl":"https://doi.org/10.11137/1982-3908_2022_45_40761","url":null,"abstract":"","PeriodicalId":39973,"journal":{"name":"Anuario do Instituto de Geociencias","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41944378","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：