Journal of Hyperspectral Remote Sensing最新文献

Mudanças climáticas e aquíferos rasos: relações presentes no Nordeste brasileiro 气候变化与浅层含水层：巴西东北部的关系

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.5.p752-762

Laís Bezerra Alves, Luciana Mayla de Aquino França, Josiclêda Domiciano Galvincio

引用次数: 0

Potential of Irrigated Agricultural Production of Corn (Zea mays L.) in Semi-Arid Region using Geoprocessing 半干旱地区玉米（Zea mays L.）灌溉农业生产的地理处理潜力

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.5.p716-726

Paulo Roberto Megna Francisco, Viviane Farias Silva, Djail Santos, George do Nascimento Ribeiro, Gypson Dutra Junqueira Ayres, Raimundo Calixto Martins Rodrigues

{"title":"Potential of Irrigated Agricultural Production of Corn (Zea mays L.) in Semi-Arid Region using Geoprocessing","authors":"Paulo Roberto Megna Francisco, Viviane Farias Silva, Djail Santos, George do Nascimento Ribeiro, Gypson Dutra Junqueira Ayres, Raimundo Calixto Martins Rodrigues","doi":"10.29150/jhrs.v13.5.p716-726","DOIUrl":"https://doi.org/10.29150/jhrs.v13.5.p716-726","url":null,"abstract":"This work aimed to evaluate and map the potential of irrigated agricultural production for corn for the watershed of the region of the middle course of the Paraíba River. Using SPRING, a map of soil irrigation potential and soil retention capacity was prepared and a partial map was generated through matrix crossing. Using average annual rainfall data, the climate condition map was prepared. After using LEGAL, the agricultural production potential map was generated through the matrix crossing between the partial map and the climate scenario. For maize, a Full climatic condition (C1) was identified in 2.02% of the basin's total; the full climatic condition with prolonged rainy season (C2) and the climatic condition moderated by excess water (C3) were not identified; the climatic condition Moderate by water deficiency (C4) in 0.86%; the unfit condition due to severe water deficit (C5) in 97.12% of the basin. The potential of irrigated agricultural production for maize did not show Very High (MA), High (A), Medium (M) and Low (B) potential, only the Very Low (MB) potential in 100% of the basin.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":"1112 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139820415","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}

引用次数: 0

Avaliação da cobertura vegetal em bacia hidrográfica do rio Sucuru-PB utilizando o Google Earth Engine 利用谷歌地球引擎评估苏库鲁-PB 河流域的植被覆盖情况

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.5.p705-715

José Hugo Simplicio de Sousa, George do Nascimento Ribeiro, Jarlean Lopes Nóbrega, Paulo Roberto Megna Francisco, G. D. S. Silvino

引用次数: 0

Análise comparativa entre o NDVI obtido por imagens multiespectrais e visíveis (RGB) em câmera acoplada em drone em área de videira 葡萄园地区无人机耦合相机从多光谱和可见光（RGB）图像中获取的 NDVI 比较分析

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.6.p741-751

Larissa Silva Barbosa de Souza, Ícaro Cardoso Maia, Daniel Dos Santos Costa, Cloves Vilas Boas dos Santos, Ayala De Souza Reis Carneiro, Magna Soelma Beserra de Moura

{"title":"Análise comparativa entre o NDVI obtido por imagens multiespectrais e visíveis (RGB) em câmera acoplada em drone em área de videira","authors":"Larissa Silva Barbosa de Souza, Ícaro Cardoso Maia, Daniel Dos Santos Costa, Cloves Vilas Boas dos Santos, Ayala De Souza Reis Carneiro, Magna Soelma Beserra de Moura","doi":"10.29150/jhrs.v13.6.p741-751","DOIUrl":"https://doi.org/10.29150/jhrs.v13.6.p741-751","url":null,"abstract":"O uso das tecnologias em estudos que envolvem o sensoriamento remoto tem avançado em função do aprimoramento dos sistemas de sensores e dos equipamentos que os transportam. Os avanços tecnológicos também têm possibilitado a realização de análises da superfície em diferentes escalas espaço-temporais por meio do uso de sensores acoplados em veículos aéreos não tripulados (VANT’s). Seu uso na ciência agrícola tem possibilitado o cômputo de índices de vegetação que permitem diversas análises dos plantios. O Índice de Vegetação por Diferença Normalizada (NDVI) é um dos mais utilizados em sensoriamento remoto, no entanto, para seu cálculo é necessário a banda do infravermelho próximo (NIR). Diante disso, o objetivo desse trabalho foi calcular e avaliar índices que estimam o NDVI a partir das bandas RGB e comparar com o NDVI calculado a partir de câmera multiespectral, visando a aquisição deste índice por câmeras de custo mais acessível. O estudo foi realizado em uma área de cultivo de uva, localizada em Petrolina-PE. O imageamento aéreo ocorreu em diferentes fases fenológicas da videira, no ano de 2022. Após o processamento das imagens, foram calculados três índices: NDVI, vNDVI e NDVI_Arai. Observou-se que o NDVI_Arai superestimou o NDVI observado em todas as fases fenológicas avaliadas, enquanto o vNDVI superestimou apenas na fase inicial de crescimento vegetativo. As correlações entre os índices foram fortes (R2 ~ 1), e o NDVI estimado mostrou ser eficiente para a representação do NDVI, sendo uma boa alternativa quando houver a ausência de câmeras multiespectrais ou hiperespectrais para a avaliação do desenvolvimento da videira.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":"7 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139685847","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}

引用次数: 0

Avaliação da cobertura vegetal em bacia hidrográfica do rio Sucuru-PB utilizando o Google Earth Engine 利用谷歌地球引擎评估苏库鲁-PB 河流域的植被覆盖情况

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.5.p705-715

José Hugo Simplicio de Sousa, George do Nascimento Ribeiro, Jarlean Lopes Nóbrega, Paulo Roberto Megna Francisco, G. D. S. Silvino

引用次数: 0

Potential of Irrigated Agricultural Production of Corn (Zea mays L.) in Semi-Arid Region using Geoprocessing 半干旱地区玉米（Zea mays L.）灌溉农业生产的地理处理潜力

Journal of Hyperspectral Remote Sensing Pub Date : 2024-02-01 DOI: 10.29150/jhrs.v13.5.p716-726

Paulo Roberto Megna Francisco, Viviane Farias Silva, Djail Santos, George do Nascimento Ribeiro, Gypson Dutra Junqueira Ayres, Raimundo Calixto Martins Rodrigues

{"title":"Potential of Irrigated Agricultural Production of Corn (Zea mays L.) in Semi-Arid Region using Geoprocessing","authors":"Paulo Roberto Megna Francisco, Viviane Farias Silva, Djail Santos, George do Nascimento Ribeiro, Gypson Dutra Junqueira Ayres, Raimundo Calixto Martins Rodrigues","doi":"10.29150/jhrs.v13.5.p716-726","DOIUrl":"https://doi.org/10.29150/jhrs.v13.5.p716-726","url":null,"abstract":"This work aimed to evaluate and map the potential of irrigated agricultural production for corn for the watershed of the region of the middle course of the Paraíba River. Using SPRING, a map of soil irrigation potential and soil retention capacity was prepared and a partial map was generated through matrix crossing. Using average annual rainfall data, the climate condition map was prepared. After using LEGAL, the agricultural production potential map was generated through the matrix crossing between the partial map and the climate scenario. For maize, a Full climatic condition (C1) was identified in 2.02% of the basin's total; the full climatic condition with prolonged rainy season (C2) and the climatic condition moderated by excess water (C3) were not identified; the climatic condition Moderate by water deficiency (C4) in 0.86%; the unfit condition due to severe water deficit (C5) in 97.12% of the basin. The potential of irrigated agricultural production for maize did not show Very High (MA), High (A), Medium (M) and Low (B) potential, only the Very Low (MB) potential in 100% of the basin.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":"14 3-4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139880372","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}

引用次数: 0

Evaluation of EnMAP hyperspectral satellite data for epithermal alteration mapping at Cuprite-Goldfield, southwestern Nevada, USA 评估 EnMAP 高光谱卫星数据用于绘制美国内华达州西南部 Cuprite-Goldfield 的热液蚀变图

Journal of Hyperspectral Remote Sensing Pub Date : 2023-12-19 DOI: 10.29150/jhrs.v13.2.p262-269

E. Bedini

{"title":"Evaluation of EnMAP hyperspectral satellite data for epithermal alteration mapping at Cuprite-Goldfield, southwestern Nevada, USA","authors":"E. Bedini","doi":"10.29150/jhrs.v13.2.p262-269","DOIUrl":"https://doi.org/10.29150/jhrs.v13.2.p262-269","url":null,"abstract":"The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission launched into orbit on April 1, 2022. The EnMAP records 246 hyperspectral channels in the 0.42-2.45 μm wavelength range, with a spatial resolution of 30 m. This wavelength range is useful for environmental and geological mapping. This study evaluates the application of the EnMAP data to the mapping of epithermal alteration systems at Cuprite and Goldfield in southwestern Nevada, USA. The Cuprite has served since 1980s as a test site of the U.S. National Aeronautics and Space Administration (NASA) for the evaluation of airborne and satellite remote sensing sensors. The surface reflectance Cuprite-Goldfield EnMAP scene analyzed in this study was recorded on April 9, 2023. The EnMAP data were analyzed using the spectral mixture analysis technique. The results obtained from the EnMAP moderate spatial resolution satellite hyperspectral data show accurate detection of the alteration zones in the Cuprite-Goldfield study area. The study indicates the potential of the EnMAP data for various geological and environmental applications.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962910","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}

引用次数: 0

A estatística aplicada à Geografia: Análise de calorias em algumas capitais brasileiras 应用于地理学的统计学：分析巴西一些首都的卡路里含量

Journal of Hyperspectral Remote Sensing Pub Date : 2023-12-19 DOI: 10.29150/jhrs.v13.2.p234-253

Kawhan Oliveira Da Silva, J. Galvíncio

引用次数: 0

Avaliação de recursos para o mapeamento de cobertura do solo em sub-bacia do rio Capibaribe-PE usando imagem Kompsat-2 利用 Kompsat-2 图像评估伯南布哥州卡皮巴里贝河分流域的土地覆被绘图资源

Journal of Hyperspectral Remote Sensing Pub Date : 2023-11-29 DOI: 10.29150/jhrs.v13.2.p270-280

Juarez Antônio da Silva Júnior, Admilson Da Penha Pacheco

{"title":"Avaliação de recursos para o mapeamento de cobertura do solo em sub-bacia do rio Capibaribe-PE usando imagem Kompsat-2","authors":"Juarez Antônio da Silva Júnior, Admilson Da Penha Pacheco","doi":"10.29150/jhrs.v13.2.p270-280","DOIUrl":"https://doi.org/10.29150/jhrs.v13.2.p270-280","url":null,"abstract":"Land use and land cover mapping is an important factor in geospatial analysis in watershed management. The integration of remote sensing images and Machine Learning classification techniques enable the identification and environmental monitoring of landscape elements. The MSC (MultiSpectral Camara) sensor on the Kompsat-2 satellite captures images of high spatial resolution, which allows the identification of terrestrial resources on a local scale. Six data models were developed for classifying land use and land cover by Random Forest in a Capibaribe River sub-basin. These models were created based on spectral indices and ranking of variable importance. The evaluation of the results was done through spatial quantification and accuracy analysis. Products based on bands and spectral indices showed global accuracy ranging between 94 and 98%, where the classes of Arboreal and Shrubby Vegetation stood out with estimates of accuracy of the producer and user above 80%. Products with the lowest data resources showed poor accuracy performance with overall accuracy values clustered below 60%. This study is the first to use adaptations of Kompsat-2 spectral data and computer learning methods to demonstrate the application of high-performance land cover mapping. Thus, this article contributed to the monitoring of the soil surface in urban sub-basins that need precise spatial information about the state of environmental conversation.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139210527","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}

引用次数: 0

Rio Tejipió: Cota de Inundação em constraste com as residências em áreas de risco Tejipió 河：洪水位与危险地区住宅的对比

Journal of Hyperspectral Remote Sensing Pub Date : 2023-11-29 DOI: 10.29150/jhrs.v13.2.p202-212

João Lucas Marques Presbítero, Daniel Pereira da Silva Filho, Joélia Natália Bezerra da Silva

{"title":"Rio Tejipió: Cota de Inundação em constraste com as residências em áreas de risco","authors":"João Lucas Marques Presbítero, Daniel Pereira da Silva Filho, Joélia Natália Bezerra da Silva","doi":"10.29150/jhrs.v13.2.p202-212","DOIUrl":"https://doi.org/10.29150/jhrs.v13.2.p202-212","url":null,"abstract":"Segundo o IPCC, o aquecimento global agravado pela atividade antrópica é um dos fatores que contribuem para a ocorrência de eventos extremos que tendem a piorar nos próximos anos. Entre os ecossistemas mais vulneráveis aos impactos das variações climáticas encontram-se as zonas adjuntas aos cursos d'água e corpos hídricos. Tal fato se torna particularmente preocupante, uma vez que essas regiões, no âmbito global, tendem a ser densamente habitadas e focadas nas especificidades das consequências. Dessa forma, o presente trabalho buscou fazer simulações de inundação usando o modelo HEC-RAS 5.0.7 (Hydrologic Engineering Center - RiverAnalysis System) na Bacia do Rio Tejipió localizada nos municípios de Recife e Jaboatão. Os resultados da análise hidrológica revelaram um cenário de grande importância em relação à área de inundação do Rio Tejipió, conforme os dados, em um período de retorno de 200 anos, uma área de inundação abrange aproximadamente 912 hectares, afetando cerca de 2.600 residências. Diante do contexto apresentado anteriormente, emerge claramente a imprescindibilidade de um planejamento urbano estrategicamente orientado para enfrentar os desafios das mudanças climáticas. Palavras-chave: Simulação, HEC-RAS, enchentes, Hidrografia.","PeriodicalId":332244,"journal":{"name":"Journal of Hyperspectral Remote Sensing","volume":"153 12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211392","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}

引用次数: 0