981 resultados para LANDSAT THEMATIC MAPPER
Resumo:
Pós-graduação em Agronomia (Energia na Agricultura) - FCA
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
The best irrigation management depends on accurate estimation of reference evapotranspiration (ET0) and then selection of the appropriate crop coefficient for each phenological stage. However, the evaluation of water productivity on a large scale can be done by using actual evapotranspiration (ETa), determined by coupling agrometeorological and remote sensing data. This paper describes methodologies used for estimating ETa for 20 centerpivots using three different approaches: the traditional FAO crop coefficient (K-c) method and two remote sensing algorithms, one called SEBAL and other named TEIXEIRA. The methods were applied to one Landsat 5 Thematic Mapper image acquired in July 2010 over the Northwest portion of the Sao Paulo State, Brazil. The corn, bean and sugar cane crops are grown under center pivot sprinkler irrigation. ET0 was calculated by the Penman-Monteith method with data from one automated weather station close to the study site. The results showed that for the crops at effective full cover, SEBAL and TEIXEIRA's methods agreed well comparing with the traditional method. However, both remote sensing methods overestimated ETa according to the degree of exposed soil, with the TEIXEIRA method presenting closer ETa values with those resulted from the traditional FAO K-c method. This study showed that remote sensing algorithms can be useful tools for monitoring and establishing realistic K-c values to further determine ETa on a large scale. However, several images during the growing seasons must be used to establish the necessary adjustments to the traditional FAO crop coefficient method.
Resumo:
Pós-graduação em Agronomia (Energia na Agricultura) - FCA
Resumo:
The structure of Brazilian savannah, named locally as “cerrado”, tends to change if the human pressures, such as pasture and intensive fire, are suppressed showing a densification of the physiognomies throughout the time. Vegetation Index acquired from remotely sensed data has been a proper way to study and monitoring large areas, and the Normalized Difference Vegetation Index (NDVI) is one of the most used for this purpose. The aim of this study was to assess the dynamic of structural changes in protected and non-protected areas of cerrado vegetation using NDVI. For this purpose, three cerrado fragments in the state of São Paulo, Brazil, were evaluated for a 26 year time span from 1985 and 2011, being two of them protected against anthropogenic interference. Landsat 5 –Thematic Mapper images were used and processed in ArcGIS. In the protected areas NDVI indicated that the vegetation followed the expected trend of changes for cerrado, with more open physiognomies tending to be denser throughout this period of 26 years, whereas in the non-protected fragment the NDVI evidences human pressure, showing lower phytomass in 2011. NDVI showed to be efficient in detecting and monitoring changes in cerrado vegetation structure, and can be useful to study both, the natural dynamics of cerrado vegetation and the anthropogenic interference in protected areas.
Resumo:
This study aimed to evaluate a period of 38 years, the use and soil occupation of the Paradise River watershed, inserted in the citys of São Manuel and Areiópolis-SP using aerial photographs for the year 1972 and TM image (Thematic Mapper) obtained by the Landsat-5 satellite, in 2010, using geoprocessing techniques. The watershed in question is very important for the city of São Manuel-SP, because its urban area is inserted in its divisors which part of it belongs to the Environmental Protection Area (APA) Perimeter Botucatu-SP, considered a recharge area of the aquifer Guarani. Today, the development of agriculture faces challenges, which is to produce more food without impacting the environment. Allied to this concern, research institutions have sought new technologies that allow the detection and quantification of human actions, enabling interventions in order to minimize possible damage to the environment. Among these technologies can be cited Geographic Information Systems (GIS), which a large volume of data and information stored in a region at different times can be evaluated in the same time, suggesting different approaches to the planning of land use. The results of the mapping of areas of use and soil occupation result nine classes in 1972, and the coffee culture showed the biggest occupation (37.94%) of the total area. The 2010 mapping formulated twelve classes of use, which demonstrated the predominance of sugar cane (37.94%), on the areas occupied by coffee and pasture before. The land use maps of 1972 and 2010 showed results that show intense human activity in the modification of natural landscape.
Resumo:
This study aimed to map the classes of use and occupation and their conflicts in Areas of Permanent Preservation (APPs) in the basin of Ribeirão São Pedro - Botucatu (SP) with the use of remote sensing techniques - image obtained by satellite 2011 - and the use of GIS. For this, we used the GIS techniques, and the integration of information held in the Geographic Information System (GIS) - IDRISI, coupled with the use of digital maps, published by the Brazilian Institute of Geography and Statistics - IBGE, scale 1: 50,000 and satellite images LANDSAT - 5 (2011) sensor TM (Thematic Mapper) with spatial resolution of 30 x 30 meters, provided by the National Institute for Space Research (INPE) .The Geographic Information System (GIS) was used IDRISI Selva and software, CartaLinx. This work had as legal support environmental legislation, specifically, the Federal Law 12.651 / 12. Thus, the study of the watershed becomes an important tool to understand its dynamics in relation to the use and occupation of their area and to characterize their environmental problems and taking as legal counsel to the preservation and conservation of the land to support environmental legislation.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
The objective of this study is to gain a quantitative understanding of land use and land cover change (LULCC) that have occurred in a rural Nicaraguan municipality by analyzing Landsat 5 Thematic Mapper (TM) images. By comparing the potential extent of tropical dry forest (TDF) with Landsat 5 TM images, this study analyzes the loss of this forest type on a local level for the municipality of San Juan de Cinco Pinos (63.5 km2) in the Department of Chinandega. Change detection analysis shows where and how land use has changed from 1985 to the present. From 1985 to 2011, nearly 15% of the TDF in San Juan de Cinco Pinos was converted to other land uses. Of the 1434.2 ha of TDF that was present in 1985, 1223.64 ha remained in 2011. The deforestation is primarily a result of agricultural expansion and fuelwood extraction. If current rates of TDF deforestation continue, the municipality faces the prospect of losing its forest cover within the next few decades.
Resumo:
Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.
Resumo:
Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs. (c) 2004 Elsevier Ltd. All rights reserved.
Resumo:
The urban heat island effect is often associated with large metropolises. However, in the Netherlands even small cities will be affected by the phenomenon in the future (Hove et al., 2011), due to the dispersed or mosaic urbanisation patterns in particularly the southern part of the country: the province of North Brabant. This study analyses the average night time land surface temperature (LST) of 21 North-Brabant urban areas through 22 satellite images retrieved by Modis 11A1 during the 2006 heat wave and uses Landsat 5 Thematic Mapper to map albedo and normalized difference temperature index (NDVI) values. Albedo, NDVI and imperviousness are found to play the most relevant role in the increase of nighttime LST. The surface cover cluster analysis of these three parameters reveals that the 12 “urban living environment” categories used in the region of North Brabant can actually be reduced to 7 categories, which simplifies the design guidelines to improve the surface thermal behaviour of the different neighbourhoods thus reducing the Urban Heat Island (UHI) effect in existing medium size cities and future developments adjacent to those cities.
Resumo:
En el presente artículo se describe el procedimiento utilizado para actualizar el mapa de uso y cobertura de la tierra de Costa Rica para el año 1992. En el proceso se integró la cartografía análoga existente para 1985 a escala 1:200.000 e imágenes digitales del Mapeador Temático de LANDSAT para los años 1991 y 1993. Para comprobar la exactitud de la clasificación se usaron 1.372 puntos obtenidos de fotos aéreas de 1992 y trabajo de campo empleando un Sistema de Posicionamiento Global (SPG). Los resultados obtenidos indican que existe un 46.6% del país bajo pastos, un 32,9 bajo bosques y un 8,5% bajo uso agrícola. Un 7,8% del área se incluyó en una categoría denominada <<no clasificada, usos mezclados, deforestada>>. La exactitud global de la clasificación fue de un 74%; con una confusión entre pasto y bosque de un 19%. SUMMARY The objective of this paper is to describe the process used by the authors to update the preliminary 1985 land use-land cover map of Costa Rica. Paper maps of 1985 at scale 1:200.000 we digitized, rasterized and use to label the output of a nonsupervised classification carried out using 1991-93 digital data from LANDSAT 5 (Thematic Mapper). Aerial photography and field work aided by a Global Positional System (GPS) was used to gather ground-truth data. A total of 1372 stratified points were used to test the accuracy of the final map. Our results showed that 46,6% of the country is under pasture, 32,9% under forest and 8.5% under agriculture. The nonclassified areas were lumped into one category that accounted for 7,8% of the country. Global accuracy of the classification was 74% with the confusion between forest and pasture accounting for 19% of this error.
Resumo:
The Montreal Process indicators are intended to provide a common framework for assessing and reviewing progress toward sustainable forest management. The potential of a combined geometrical-optical/spectral mixture analysis model was assessed for mapping the Montreal Process age class and successional age indicators at a regional scale using Landsat Thematic data. The project location is an area of eucalyptus forest in Emu Creek State Forest, Southeast Queensland, Australia. A quantitative model relating the spectral reflectance of a forest to the illumination geometry, slope, and aspect of the terrain surface and the size, shape, and density, and canopy size. Inversion of this model necessitated the use of spectral mixture analysis to recover subpixel information on the fractional extent of ground scene elements (such as sunlit canopy, shaded canopy, sunlit background, and shaded background). Results obtained fron a sensitivity analysis allowed improved allocation of resources to maximize the predictive accuracy of the model. It was found that modeled estimates of crown cover projection, canopy size, and tree densities had significant agreement with field and air photo-interpreted estimates. However, the accuracy of the successional stage classification was limited. The results obtained highlight the potential for future integration of high and moderate spatial resolution-imaging sensors for monitoring forest structure and condition. (C) Elsevier Science Inc., 2000.
Resumo:
High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.