Digital processing of a Landsat-TM time series for mapping and monitoring degraded areas caused by independent gold miners, Roraima State, Brazilian Amazon

Problems of digital processing of Poisson-distributed data time series from various counters of radiation particles, photons, slow neutrons etc. are relevant for experimental physics and measuring technology. A low-pass filtering method for normalized Poisson-distributed data time series is proposed. A digital quasi-Gaussian filter is designed, with a finite impulse response and non-negative weights. The quasi-Gaussian filter synthesis is implemented using the technology of stochastic global minimization and modification of the annealing simulation algorithm. The results of testing the filtering method and the quasi-Gaussian filter on model and experimental normalized Poisson data from the URAGAN muon hodoscope, that have confirmed their effectiveness, are presented.

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Comparison of Segment and Pixel-based Non-parametric Land Cover Classification in the Brazilian Amazon Using Multitemporal Landsat TM/ETM+ Imagery

Photogrammetric Engineering & Remote Sensing ◽

10.14358/pers.73.7.813 ◽

2007 ◽

Vol 73 (7) ◽

pp. 813-827 ◽

Cited By ~ 20

Author(s):

Katherine A. Budreski ◽

Randolph H. Wynne ◽

John O. Browder ◽

James B. Campbell

Keyword(s):

Land Cover ◽

Brazilian Amazon ◽

Land Cover Classification ◽

Landsat Tm ◽

Non Parametric

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Use of artificial neural networks and geographic objects for classifying remote sensing imagery

CERNE ◽

10.1590/01047760.201420021615 ◽

2014 ◽

Vol 20 (2) ◽

pp. 267-276 ◽

Cited By ~ 4

Author(s):

Pedro Resende Silva ◽

Fausto Weimar Acerbi Júnior ◽

Luis Marcelo Tavares de Carvalho ◽

José Roberto Soares Scolforo

Keyword(s):

Neural Networks ◽

Time Series ◽

Image Segmentation ◽

Artificial Neural Networks ◽

Forest Inventory ◽

Landsat Tm ◽

Inventory Data ◽

Forest Inventory Data ◽

Artificial Neural ◽

Test Use

The aim of this study was to develop a methodology for mapping land use and land cover in the northern region of Minas Gerais state, where, in addition to agricultural land, the landscape is dominated by native cerrado, deciduous forests, and extensive areas of vereda. Using forest inventory data, as well as RapidEye, Landsat TM and MODIS imagery, three specific objectives were defined: 1) to test use of image segmentation techniques for an object-based classification encompassing spectral, spatial and temporal information, 2) to test use of high spatial resolution RapidEye imagery combined with Landsat TM time series imagery for capturing the effects of seasonality, and 3) to classify data using Artificial Neural Networks. Using MODIS time series and forest inventory data, time signatures were extracted from the dominant vegetation formations, enabling selection of the best periods of the year to be represented in the classification process. Objects created with the segmentation of RapidEye images, along with the Landsat TM time series images, were classified by ten different Multilayer Perceptron network architectures. Results showed that the methodology in question meets both the purposes of this study and the characteristics of the local plant life. With excellent accuracy values for native classes, the study showed the importance of a well-structured database for classification and the importance of suitable image segmentation to meet specific purposes.

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Variação Espacial e Temporal de NDVI na Lagoa do Peixe, RS (Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v4i5.232706 ◽

2012 ◽

Vol 4 (5) ◽

pp. 897 ◽

Cited By ~ 1

Author(s):

Luana Portz ◽

Laurindo Antonio Guasselli ◽

Iran Carlos Stalliviere Corrêa

Keyword(s):

Time Series ◽

Temporal Variation ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Analysis Data ◽

Landsat Tm ◽

Spatial And Temporal Variation ◽

Rainfall Analysis ◽

Ndvi Time Series ◽

High Precipitation

Neste estudo foram analisadas as variações espaciais e temporais do Índice de Vegetação por Diferença Normalizada (NDVI) na lagoa do Peixe, no litoral do Rio Grande do Sul. Para alcançar o objetivo proposto foram utilizadas imagens de satélite Landsat TM5, entre os anos de 1986 e 2009, seguindo os procedimentos de elaboração de mosaico das cenas, verificação de campo, geração das imagens de NDVI, análise de dados de precipitação acumulada, geração dos mapas finais e análise qualitativa dos resultados obtidos. Os resultados obtidos com a geração de imagens de NDVI mostraram que a análise espaço-temporal associada aos dados de precipitação fornecem informações de valiosa importância sobre a dinâmica da lagoa do Peixe. A importância do NDVI neste estudo se destaca pelo contraste existente entre água e vegetação, realçando os diferentes níveis de água sobre os bancos vegetados presentes na borda oeste da lagoa. Estes bancos são um importante controlador da dinâmica de circulação lagunar, onde em períodos de seca ocorre a compartimentação da lagoa, enquanto que em épocas de grande precipitação e acumulação de água estes bancos ficam submersos. Palavras-chave: Landsat TM, série temporal, Parque Nacional. Spatial and Temporal Variation of NDVI in the Peixe Lagoon, RS ABSTRACTThis paper analyzed the spatial and temporal variation of Normalized Difference Vegetation Index (NDVI) in the Peixe lagoon. To reach the purpose, the NDVI time-series were collected from the study area between year 1986 and 2009 derived from Landsat TM5 satellite. The adopted methodology may be subdivided into the following steps: mosaic of scenes, fild verification, generation of NDVI time-series and qualitative analysis, in addition, it was complemented with rainfall analysis. The results obtained with the NDVI time-series associated with the rainfall analysis data provide valuable information about the environmental dynamics. The importance of NDVI in this work is given by the contrast between water and vegetation, highlighting the different levels of water over vegetated banks present on the western edge of the lagoon. These banks are an important driver circulation in the lagoon, where in periods of drought occurs the partitioning of the lagoo, while in periods of high precipitation and accumulation of water they are submerged. Keywords: Landsat TM, time-series, National Park.

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