Consulta: subjectFacets:"Hyperspectral remote sensing"
Registros recuperados: 4
Data/hora: 12/06/2024 14:54:24

Sensoriamento Remoto para a Caracterização do Aporte de Sedimentos e Compostos Orgânicos da Represa de Paraibuna, São Paulo.
Provedor de dados: 25
Autores: Dias, Nelson Wellausen; Batista, Getulio; Targa, Marcelo dos Santos; Novo, Evlyn Marcia Leão Moraes; Barbosa, Claudio Clemente.
As águas do rio Paraíba do Sul apresentam um alto nível de degradação ambiental em função do despejo direto de efluentes domésticos sem tratamento e de contaminações de origem difusa (sedimentos, nutrientes e matéria orgânica) provenientes do carreamento de solo erodido, fertilizantes, pesticidas, herbicidas e dejetos de animais para os canais de drenagem. Comparativamente, a água do reservatório de Paraibuna possui qualidade de água significativamente superior aos demais trechos do Rio Paraíba do Sul devido ao fato de estar a montante dos principais centros urbanos do Vale do Paraíba. Entretanto as águas que abastecem esta represa são provenientes de duas bacias (Paraibuna e Paraitinga) com características de cobertura e uso do solo bastante distintas que...
Tipo: Article
Palavras-chave: Represas; Sedimentação; Sensoriamento remoto hiperespectral; Hyperspectral remote sensing; Reservoirs; Sedimentation.
Ano: 2006
URL: http://hdl.handle.net/2315/41

Assessing biophysical variable parameters of bean crop with hyperspectral measurements
Provedor de dados: 63
Autores: Monteiro,Priscylla Ferraz Câmara; Angulo Filho,Rubens; Xavier,Alexandre Cândido; Monteiro,Rodrigo Otávio Câmara.
Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Hyperspectral remote sensing; Spectroradiometry; Vegetation indices.
Ano: 2012
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000200001

Narrow band spectral indexes for chlorophyll determination in soybean canopies [Glycine max (L.) Merril]
Provedor de dados: 61
Autores: Ferri,Clotilde Pinheiro; Formaggio,Antonio Roberto; Schiavinato,Marlene Aparecida.
Photosynthetic pigments are essential for plant development. Quantifying these pigments in great extensions of agricultural crops is an important objective in remote sensing for agricultural purposes. This information can be used to produce a more accurate estimation of the physiological state of the vegetation, for species discrimination and productivity estimation. The aim of the present study was to (a) evaluate the potential for estimating chlorophyll content of crop canopies, using narrow band spectral indexes, and (b) in this respect compare the performances of NDVI (a multispectral wide band index) and two narrow band vegetation indexes (R750/700 and R750/550). Experiments were carried out under greenhouse conditions whereby soybean [Glycine max...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Canopy chemistry; Hyperspectral remote sensing; Remote sensing in agriculture; Spectroradiometry.
Ano: 2004
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1677-04202004000300002

Measurement of nitrogen content in rice by inversion of hyperspectral reflectance data from an unmanned aerial vehicle
Provedor de dados: 65
Autores: Wen,Du; Tongyu,Xu; Fenghua,Yu; Chunling,Chen.
ABSTRACT: The Nitrogen content of rice leaves has a significant effect on growth quality and crop yield. We proposed and demonstrated a non-invasive method for the quantitative inversion of rice nitrogen content based on hyperspectral remote sensing data collected by an unmanned aerial vehicle (UAV). Rice canopy albedo images were acquired by a hyperspectral imager onboard an M600-UAV platform. The radiation calibration method was then used to process these data and the reflectance of canopy leaves was acquired. Experimental validation was conducted using the rice field of Shenyang Agricultural University, which was classified into 4 fertilizer levels: zero nitrogen, low nitrogen, normal nitrogen, and high nitrogen. Gaussian process regression (GPR) was...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: UAV; Hyperspectral remote sensing; Machine learning; Nitrogen content.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000600352