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| Registros recuperados: 11 | |
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| Leonardi, Fernando; Silva, Erivaldo Antônio da. |
| Brazil presents great deficiency in cartographic updating area. Many products are outdated around in 30 years in the several scales. A country that has the continental dimensions as Brazil needs have a solid cartographic base to take important decisions about urban planning and consequenting to administration of the territory. One way of updating the cartographic products is the combined use of remote sensing products and techniques of Digital Processing Images (DPI). Among many DPI tools, the Mathematical Morphology allied to the remote sensing data, is one alternative method used to minimize this problem. For the development of this work three images taken with the Landsat sensor was used, having draining net, as the interest features. In this paper was... |
| Tipo: Article |
Palavras-chave: Sensoriamento Remoto; Remote Sensing; PDI; Detecção de Feições; Morfologia Matemática; Mathematical Morphology; Features of detection. |
| Ano: 2007 |
URL: http://hdl.handle.net/2315/97 |
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| Sarmiento,Christiany M.; Coltri,Priscila P.; Alves,Marcelo de C.; Carvalho,Luiz G. de. |
| ABSTRACT This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Geographic Information System; Mathematical Modeling; Remote Sensing; Agrometeorology; Crop Monitoring. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000300405 |
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| Xu, Qiu-xiao. |
| The three-period (1995, 1998 and 2003) remote sensing images in Jinan City, China are selected. And the information of green land, construction land, woodland and water body is extracted by using the image processing module of remote-sensing software and computerized interpretation module. Both the change table and transfer matrix table of land use area are analyzed by modeling module of remote-sensing software. Then, the Geo-information Tupu is obtained; and the temporal and spatial variation of land use in Jinan City is monitored and analyzed by Geo-information Tupu and transfer matrix. Result shows that land use structure change of Jinan City in the years 1995-1998 shows a transformation from green land to construction land. Area of green land... |
| Tipo: Journal Article |
Palavras-chave: Remote Sensing; Geo-information tupu; Dynamic change of the green land; Jinan; China; Agribusiness. |
| Ano: 2011 |
URL: http://purl.umn.edu/108419 |
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| Demattê,José A. M.; Alves,Marcelo Rodrigo; Gallo,Bruna Cristina; Fongaro,Caio T.; Souza,Arnaldo Barros e; Romero,Danilo Jefferson; Sato,Marcus Vinicius. |
| Minimizing environmental impacts and increasing crop productivity depend mainly on the knowledge of chemical, physical and mineralogical characteristics of the soil attributes. However, traditional methods are timeconsuming and costly. The objective of this study was to determine and validate a method to quantify soil attributes using UV-Vis-NIR Spectroscopy as an alternative to conventional methods of soil analyses. The work comprised two main phases: (1) creation and calibration of statistical models to determine the soil attributes derived from spectral data extracted from soil samples collected in area 1, (2) validation of statistical models in area 2 and correlations between the estimated and observed values (conventional method) for each soil... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Reflectance; Soil analysis; Remote Sensing. |
| Ano: 2015 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000200223 |
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| ALMEIDA,Cláudio Aparecido de; COUTINHO,Alexandre Camargo; ESQUERDO,Júlio César Dalla Mora; ADAMI,Marcos; VENTURIERI,Adriano; DINIZ,Cesar Guerreiro; DESSAY,Nadine; DURIEUX,Laurent; GOMES,Alessandra Rodrigues. |
| ABSTRACT Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Remote Sensing; Tropical Deforestation; TerraClass; Image Processing. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000300291 |
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| SILVA,CARLOS ALBERTO; KLAUBERG,CARINE; HUDAK,ANDREW T.; VIERLING,LEE A.; LIESENBERG,VERALDO; BERNETT,LUIZ G.; SCHERAIBER,CLEWERSON F.; SCHOENINGER,EMERSON R.. |
| ABSTRACT Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Forest inventory; LiDAR metrics; K-NN Imputation; Remote Sensing. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100295 |
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| Registros recuperados: 11 | |
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