Caracter��sticas espectrais da soja ao longo do ciclo vegetativo com imagens landsat 5/TM em ��rea agr��cola no oeste do Paran��

The objective of this study was to analyze changes in the spectral behavior of the soybean crop through spectral profiles of the vegetation indexes NDVI and GVI, expressed by different physical values such as apparent bi-directional reflectance factor (BRF), surface BRF, and normalized BRF derived from images of the Landsat 5/TM. A soybean area located in Cascavel, Paran��, was monitored by using five images of Landsat 5/TM during the 2004/2005 harvesting season. The images were submitted to radiometric transformation, atmospheric correction and normalization, determining physical values of apparent BRF, surface BRF and normalized BRF. NDVI and GVI images were generated in order to distinguish the soybean biomass spectral response. The treatments showed different results for apparent, surface and normalized BRF. Through the profiles of average NDVI and GVI, it was possible to monitor the entire soybean cycle, characterizing its development. It was also observed that the data from normalized BRF negatively affected the spectral curve of soybean crop, mainly, during the phase of vegetative growth, in the 12-9-2004 image.

Albedo �� superf��cie a partir de imagens Landsat 5 em ��reas de cana-de-a����car e cerrado

Prop��s-se, neste trabalho, estimar dados de albedo �� superf��cie terrestre usando-se o sensor Thematic Mapper (TM) do sat��lite LANDSAT 5 e compar��-lo com dados de duas esta����es agrometeorol��gicas localizadas em regi��o de Cerrado e a outra em cultivo da cana-de-a����car. A regi��o de estudo est�� localizada no munic��pio de Santa Rita do Passa Quatro, SP, Brasil. Para a realiza����o do estudo obtiveram-se seis imagens orbitais do sat��lite Landsat 5 sensores TM, na ��rbita 220 e ponto 75, nas datas de 22/02, 11/04, 29/05, 01/08, 17/08 e 21/11, todas do ano de 2005, a que correspondem os dias juliano de 53, 101, 149, 213, 229 e 325, respectivamente. As corre����es geom��tricas para as imagens foram realizadas e geradas as cartas de albedo. O algoritmo SEBAL estimou satisfatoriamente os valores de albedo de superf��cies sobre ��reas de cerrado e de cana-de-a����car, na regi��o de Santa Rita do Passa Quatro, SP, consistentes com observa����es realizadas do albedo �� superf��cie.

Using indicators of deforestation and land-use dynamics to support conservation strategies: A case study of central Rondonia, Brazil

In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.

Interpreta����o tect��nica de um conjunto de lineamentos WNW-ESE observados em imagens landsat da margem oeste ib��rica

The existence of satellite images ofthe West Iberian Margin allowed comparative study of images as a tool applied to structural geology. Interpretation of LANDSAT images of the Lusitanian Basin domain showed the existence of a not previously described WNW-ESE trending set oflineaments. These lineaments are persistent and only observable on small scale images (e.g. approx. 11200000 and 11500 000) with various radiometric characteristics. They are approximately 20 km long, trend l200��15�� and cross cut any other families oflineaments. The fact that these lineaments are perpendicular to the Quaternary thrusts of the Lower Tagus Valley and also because they show no off-set across them, suggests that they resulted from intersection oflarge tensile fractures on the earth's surface. It is proposed in this work that these lineaments formed on a crustal flexure of tens ofkm long, associated with the Quaternary WNW-ESE oriented maximum compressive stress on the West Iberian Margin. The maximum compressive stress rotated anticlockwise from a NW -SE orientation to approximately WNW-ESE, from Late Miocene to Quaternary times (RIBEIRO et aI., 1996). Field inspection of the lineaments revealed zones of norm~1.J. faulting and cataclasis, which are coincident with the lineaments and affect sediments of upper Miocene up to Quaternary age. These deformation structures show localized extension perpendicular to the lineaments, i.e. perpendicular to the maximum compressive direction, after recent stress data along the West Portuguese Margin (CABRAL & RIBEIRO, 1989; RIBEIRO et at., 1996). Also, on a first approach, the geographical distribution of these lineaments correlates well with earthquake epicenters and areas of largest Quaternary Vertical Movements within the inverted Lusitanian Basin (CABRAL, 1995).

Detecting and evaluating land cover change in the eastern half of East Timor (1972-2011)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Analysis of urban land use and land cover changes: a case of study in Bahir Dar, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region���s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth���s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal���s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia���s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Avaliação de técnicas de segmentação e classificação automática de imagens landsat-tm no mapeamento do uso do solo na Amazônia1

O mapeamento do uso da terra é fundamental para o entendimento dos processos de mudanças globais, especialmente em regiões como a Amazônia que estão sofrendo grande pressão de desenvolvimento. Tradicionalmente estes mapeamentos têm sido feitos utilizando técnicas de interpretação visual de imagens de satélites, que, embora de resultados satisfatórios, demandam muito tempo e alto custo. Neste trabalho é proposta uma técnica de segmentação da imagens com base em um algoritmo de crescimento de regiões, seguida de uma classificação não-supervisionada por regiões. Desta forma, a classificação temática se refere a um conjunto de elementos (pixels da imagem), beneficiando-se portanto da informação contextual e minimizando as limitações das técnicas de processamento digital baseadas em análise pontual (pixel-a-pixel). Esta técnica foi avaliada numa área típica da Amazônia, situada ao norte de Manaus, AM, utilizando imagens do sensor "Thematic Mapper" - TM do satélite Landsat, tanto na sua forma original quanto decomposta em elementos puros como vegetação verde, vegetação seca (madeira), sombra e solo, aqui denominada imagem misturas. Os resultados foram validados por um mapa de referência gerado a partir de técnicas consagradas de interpretação visual, com verificação de campo, e indicaram que a classificação automática é viável para o mapeamento de uso da terra na Amazônia. Testes estatísticos indicaram que houve concordância significativa entre as classificações automáticas digitais e o mapa de referência (em tomo de 95% de confiança).

An��lise da composi����o flor��stica e fitossociol��gica da floresta nacional do Tapaj��s com o apoio geogr��fico de imagens de sat��lites

O objetivo desse trabalho foi analisar a distribui����o da cobertura vegetal de diversas por����es da Floresta Nacional (FLONA) do Tapaj��s (FNT), no Par��, atrav��s de atributos flor��sticos e fitossociol��gicos apoiados por imagens de sat��lites, em ��reas de floresta prim��ria (FP) e floresta secund��ria (FS). Para isso foram amostrados 35 transectos de 10 m ' 250 m em ��reas de FP de alto e baixo plat��, incluindo tamb��m as ��reas alteradas por de corte florestal seletivo de madeira e 29 transectos de 10 m ' 100 m em ��reas de FS em v��rios est��gios regenerativos. Em cada um desses transectos foram levantadas informa����es dendrom��tricas como DAP (Di��metro �� Altura do Peito), altura total (AT) e altura comercial (AC), al��m de localiza����o dos indiv��duos arb��reos dentro das amostras. Os di��metros de inclus��o para as ��reas de floresta prim��ria e secund��ria foram de 10 cm e 3 cm, respectivamente. Foram inventariados 7666 indiv��duos (6607 ��rvores ou arbustos e 1059 palmeiras) em uma ��rea amostral de 11,65 ha, distribu��dos em diferentes regi��es da FNT. Foram identificadas em ��reas de FP e FS 190 esp��cies de ��rvores, arbustos e palmeiras distribu��das entre 153 g��neros e 46 fam��lias. Nas FP e FS foi encontrado um ��ndice de diversidade de Shannon-Wiener (H') de 4,44 e 4,09 nits.indiv��duos-1, respectivamente, indicando uma alta diversidade biol��gica para essas duas fitofisionomias. Atrav��s de an��lises multivariadas foi poss��vel concluir que existe uma diferen��a flor��stica e quantitativa na por����o norte, centro e sul da FLONA. As ��reas de FS apresentaram uma grande heterogeneidade ambiental, dificultando o processo de agrupamento das suas fases sucessionais. Atrav��s desse trabalho foi poss��vel concluir que o apoio das imagens ETM+/Landsat e RADARSAT-1 otimizou o processo de amostragem da FNT e possibilitou a an��lise espacial das regi��es com maior diferencia����o flor��stica e fitossociol��gica da Floresta Nacional.

Mapeamento da antiga cobertura vegetal de v��rzea do Baixo Amazonas a partir de imagens hist��ricas (1975-1981) do Sensor MSS-Landsat

Este estudo apresenta um mapa da cobertura vegetal da plan��cie de inunda����o do Rio Amazonas entre as cidades de Parintins (AM) e Almeirim (PA), com base em imagens Landsat-MSS adquiridas entre 1975 e 1981. O processamento digital dessas imagens envolveu a transforma����o para imagens-fra����o de vegeta����o, solo e ��gua escura (sombra), seguido da aplica����o de t��cnicas de segmenta����o e classifica����o por regi��o. O mapa resultante da classifica����o foi organizado em quatro classes de cobertura do solo: floresta de v��rzea, vegeta����o n��o-florestal de v��rzea, solo exposto e ��gua aberta. A precis��o do mapa foi estimada a partir de dois tipos de informa����es coletadas em campo: 1) pontos de descri����o: para valida����o das classes de cobertura n��o sujeitas a grandes altera����es, como �� o caso dos corpos d'��gua permanentes, e identifica����o de indicadores dos tipos de cobertura original presentes na paisagem na ocasi��o da obten����o das imagens (72 pontos); 2) entrevistas com moradores antigos para a recupera����o da mem��ria sobre a cobertura vegetal existente h�� 30 anos (44 question��rios). Ao todo foram coletadas informa����es em 116 pontos distribu��dos ao longo da ��rea de estudo. Esses pontos foram utilizados para calcular o ��ndice Kappa de concord��ncia entre os dados de campo e o mapa resultante da classifica����o autom��tica, cujo valor (0,78) indica a boa qualidade do mapa de cobertura vegetal da v��rzea. Os resultados mostram que a regi��o possu��a uma cobertura florestal de v��rzea de aproximadamente 8.650 km2 no per��odo de aquisi����o das imagens.

Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm

ABSTRACTThe Amazon v��rzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in v��rzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.

An��lise de ��reas com diferentes classes de declividade atrav��s de imagens TM/LANDSAT

�� feita a an��lise de ��reas com diferentes classes de declividade (A = 0-3%, B = 3-8%, C = 8-16% e D = 16-30%) sscom a fina1idade de se verificar a potencialidade de imagens TM/LANDSAT, na escala 1:100.000, para planejamento agr��cola. Devido �� aus��ncia de vis��o tridimensional, o trabalho baseia-se nas rela����es quantitativas entre ��ndices dedrenagem (freq����ncia de rios e densidade de drenagem) determinados a partir das imagens, e express��o do relevo (declividade m��dia) extra��da de cartas planialtim��tricas, na escala 1:50.000. Fotografias a��reas na escala 1:35.000 s��o utilizadas para fins comparativos. Conclui-se que o uso dessas imagens para mapear classes de declividade atrav��s do padr��o de drenagem �� vi��vel, embora as caracter��sticas regionais o tenham limitado para diferenciar mais facilmente ��reas com declividades A e B de ��reas com declividades C e D.