941 resultados para land use mapping


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Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

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Crop monitoring and more generally land use change detection are of primary importance in order to analyze spatio-temporal dynamics and its impacts on environment. This aspect is especially true in such a region as the State of Mato Grosso (south of the Brazilian Amazon Basin) which hosts an intensive pioneer front. Deforestation in this region as often been explained by soybean expansion in the last three decades. Remote sensing techniques may now represent an efficient and objective manner to quantify how crops expansion really represents a factor of deforestation through crop mapping studies. Due to the special characteristics of the soybean productions' farms in Mato Grosso (area varying between 1000 hectares and 40000 hectares and individual fields often bigger than 100 hectares), the Moderate Resolution Imaging Spectroradiometer (MODIS) data with a near daily temporal resolution and 250 m spatial resolution can be considered as adequate resources to crop mapping. Especially, multitemporal vegetation indices (VI) studies have been currently used to realize this task [1] [2]. In this study, 16-days compositions of EVI (MODQ13 product) data are used. However, although these data are already processed, multitemporal VI profiles still remain noisy due to cloudiness (which is extremely frequent in a tropical region such as south Amazon Basin), sensor problems, errors in atmospheric corrections or BRDF effect. Thus, many works tried to develop algorithms that could smooth the multitemporal VI profiles in order to improve further classification. The goal of this study is to compare and test different smoothing algorithms in order to select the one which satisfies better to the demand which is classifying crop classes. Those classes correspond to 6 different agricultural managements observed in Mato Grosso through an intensive field work which resulted in mapping more than 1000 individual fields. The agricultural managements above mentioned are based on combination of soy, cotton, corn, millet and sorghum crops sowed in single or double crop systems. Due to the difficulty in separating certain classes because of too similar agricultural calendars, the classification will be reduced to 3 classes : Cotton (single crop), Soy and cotton (double crop), soy (single or double crop with corn, millet or sorghum). The classification will use training data obtained in the 2005-2006 harvest and then be tested on the 2006-2007 harvest. In a first step, four smoothing techniques are presented and criticized. Those techniques are Best Index Slope Extraction (BISE) [3], Mean Value Iteration (MVI) [4], Weighted Least Squares (WLS) [5] and Savitzky-Golay Filter (SG) [6] [7]. These techniques are then implemented and visually compared on a few individual pixels so that it allows doing a first selection between the five studied techniques. The WLS and SG techniques are selected according to criteria proposed by [8]. Those criteria are: ability in eliminating frequent noises, conserving the upper values of the VI profiles and keeping the temporality of the profiles. Those selected algorithms are then programmed and applied to the MODIS/TERRA EVI data (16-days composition periods). Tests of separability are realized based on the Jeffries-Matusita distance in order to see if the algorithms managed in improving the potential of differentiation between the classes. Those tests are realized on the overall profile (comprising 23 MODIS images) as well as on each MODIS sub-period of the profile [1]. This last test is a double interest process because it allows comparing the smoothing techniques and also enables to select a set of images which carries more information on the separability between the classes. Those selected dates can then be used to realize a supervised classification. Here three different classifiers are tested to evaluate if the smoothing techniques as a particular effect on the classification depending on the classifiers used. Those classifiers are Maximum Likelihood classifier, Spectral Angle Mapper (SAM) classifier and CHAID Improved Decision tree. It appears through the separability tests on the overall process that the smoothed profiles don't improve efficiently the potential of discrimination between classes when compared with the original data. However, the same tests realized on the MODIS sub-periods show better results obtained with the smoothed algorithms. The results of the classification confirm this first analyze. The Kappa coefficients are always better with the smoothing techniques and the results obtained with the WLS and SG smoothed profiles are nearly equal. However, the results are different depending on the classifier used. The impact of the smoothing algorithms is much better while using the decision tree model. Indeed, it allows a gain of 0.1 in the Kappa coefficient. While using the Maximum Likelihood end SAM models, the gain remains positive but is much lower (Kappa improved of 0.02 only). Thus, this work's aim is to prove the utility in smoothing the VI profiles in order to improve the final results. However, the choice of the smoothing algorithm has to be made considering the original data used and the classifier models used. In that case the Savitzky-Golay filter gave the better results.

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The First Cataract region (Egypt) has always played a crucial role as a border area and a crossroads for cultures and people living in adjacent landscapes. The region has its central point in the modern city of Aswan, but it extends up to the Kom Ombo Plain in the north and reaches the Bab el-Kalabsha in the south. Its eastern and western limits cannot be defined with the same precision, given that they are located in deserts. This research focused on the landscape analysis of the region intended as a complex entanglement of archaeological evidence in a geographical and natural environment whose changes impacted and, simultaneously, were influenced by human activities. Settlement patterns and land use can give interesting information on how these relationships worked from a diachronic perspective and how they shaped the region’s characteristics. To understand the links between the human presence and its evidence and the landscape of the First Cataract region, the integration of various datasets was needed, from historical and archaeological ones to the remote sensing observation of large areas. An area corresponding to ca. 18.000 km2 has been selected for this research. The chronological framework has been chosen to cover a considerable period, from the beginning of the 5th millennium BCE to the 7th century AD. Multi-temporality and multifunctionality appear as two essential aspects when the archaeological evidence of the First Cataract region is considered in its geographical and topographical setting as a general context for settlement patterns and resource exploitation analyses. A combination of remote sensing data and topographical materials has been integrated with archaeological evidence to obtain information about resource exploitation strategies and settlement adaptation from a diachronic perspective.

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Ozone and inhalable particulate matter are the major air pollutants in the Metropolitan Area of São Paulo, Brazil, a region that has more than 19 million inhabitants and approximately 7 million registered vehicles. Proximity of roadways, adjacent land use, and local circulation are just some of the factors that can affect the results of monitoring of pollutant concentrations. The so-called weekend effect (higher ozone concentrations on weekends than on weekdays) might be related to the fact that concentrations of ozone precursors, such as nitrogen oxides (NOx) and Non Methane-Hydrocarbon (NMHC), are relatively lower on weekends. This phenomenon has been reported in some areas of the United States since the 1970s. The differences between the concentrations of ozone in period of weekend and weekday, were obtained from analysis of data hourly average of CETESB for 2004, studied the precursors to the formation of troposphere ozone, the meteorological variables and traffic profile for RMSP. Because of the proximity to sources of emissions from the station Pinheiros showed higher concentrations of NO and NO² and greater variations to the periods weekend and weekday. With fewer vehicles circulating during the weekend, and consequently less emission of pollutants, it has cleaner air and less concentration of NO and NO², there is the ideal setting to the formation of troposphere ozone, despite the lower concentration of NO². The proximity with the source emissions, aided by the increased availability of solar radiation and the presence of ozone precursors, were factors conditions for the occurrence of weekend effect.

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Este estudo tem como objetivos caracterizar o perfil demográfico e socioeconômico de nove comunidades remanescentes de quilombos no vale do Ribeira, estado de São Paulo, e identificar os principais fatores responsáveis pelas mudanças recentes nos seus padrões de subsistência. Desde a formação das primeiras aglomerações de escravos libertos e foragidos no século XVIII, as relações estabelecidas entre estas populações com as cidades próximas e com o mercado regional têm vivenciado momentos de retração e de expansão, adaptando-se e ajustando-se a novas mudanças políticas e socioeconômicas. Nas últimas cinco décadas, o impacto de fatores externos na aceleração das mudanças nos padrões de subsistência locais parece ter tido um aumento significativo. Os resultados mostram que as restrições impostas pela legislação ambiental, os conflitos de terra, a construção de uma rodovia na região, a crescente inserção no mercado regional e a atuação de órgãos governamentais e não-governamentais de desenvolvimento são os principais fatores responsáveis pelas mudanças observadas no sistema agrícola de corte e queima e, conseqüentemente, na organização socioeconômica destas populações.

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Land cover change constitutes one of main way of alteration of soil organic matter in both quantitative and qualitative terms. The goal of this study was to compare the carbon stock and the isotopic signature of the organic matter in the soil of areas with different land use,covered with forest and grass (pasture). The study area is located at Sorocaba, SP, Brazil. Using un-deformed soil samples, we measured the carbon content and bulk density. The isotopic signature of soil carbon was determined through the analysis of isotopic ratio (12)C/(13)C. The pasture soil stocks 48% less carbon than the soil covered by natural forest. The isotopic signature indicated that 42.2% of organic matter of the soil covered by pasture is originated from grasses. This characterizes a highly degradation of organic matter in the environment, both quantitatively and qualitatively. Hence, some guidelines of recuperation are described in order to restore the soil organic matter, structure and porosity.

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Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region`s predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.

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Tropical ecosystems play a large and complex role in the global carbon cycle. Clearing of natural ecosystems for agriculture leads to large pulses of CO(2) to the atmosphere from terrestrial biomass. Concurrently, the remaining intact ecosystems, especially tropical forests, may be sequestering a large amount of carbon from the atmosphere in response to global environmental changes including climate changes and an increase in atmospheric CO(2). Here we use an approach that integrates census-based historical land use reconstructions, remote-sensing-based contemporary land use change analyses, and simulation modeling of terrestrial biogeochemistry to estimate the net carbon balance over the period 1901-2006 for the state of Mato Grosso, Brazil, which is one of the most rapidly changing agricultural frontiers in the world. By the end of this period, we estimate that of the state`s 925 225 km(2), 221 092 km(2) have been converted to pastures and 89 533 km(2) have been converted to croplands, with forest-to-pasture conversions being the dominant land use trajectory but with recent transitions to croplands increasing rapidly in the last decade. These conversions have led to a cumulative release of 4.8 Pg C to the atmosphere, with similar to 80% from forest clearing and 20% from the clearing of cerrado. Over the same period, we estimate that the residual undisturbed ecosystems accumulated 0.3 Pg C in response to CO2 fertilization. Therefore, the net emissions of carbon from Mato Grosso over this period were 4.5 Pg C. Net carbon emissions from Mato Grosso since 2000 averaged 146 Tg C/yr, on the order of Brazil`s fossil fuel emissions during this period. These emissions were associated with the expansion of croplands to grow soybeans. While alternative management regimes in croplands, including tillage, fertilization, and cropping patterns promote carbon storage in ecosystems, they remain a small portion of the net carbon balance for the region. This detailed accounting of a region`s carbon balance is the type of foundation analysis needed by the new United Nations Collaborative Programmme for Reducing Emissions from Deforestation and Forest Degradation (REDD).

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The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

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No-tillage mulch-based (NTM) cropping systems have been widely adopted by farmers in the Brazilian savanna region (Cerrado biome). We hypothesized that this new type of management should have a profound impact on soil organic carbon (SOC) at regional scale and consequently on climate change mitigation. The objective of this study was thus to quantify the SOC storage potential of NTM in the oxisols of the Cerrado using a synchronic approach that is based on a chronosequence of fields of different years under NTM. The study consisted of three phases: (1) a farm/cropping system survey to identify the main types of NTM systems to be chosen for the chronosequence; (2) a field survey to identify a homogeneous set of situations for the chronosequence and (3) the characterization of the chronosequence to assess the SOC storage potential. The main NTM system practiced by farmers is an annual succession of soybean (Glycine max)or maize (Zea mays) with another cereal crop. This cropping system covers 54% of the total cultivated area in the region. At the regional level, soil organic C concentrations from NTM fields were closely correlated with clay + silt content of the soil (r(2) = 0.64). No significant correlation was observed (r(2) = 0.07), however, between these two variables when we only considered the fields with a clay + silt content in the 500-700 g kg(-1) range. The final chronosequence of NTM fields was therefore based on a subsample of eight fields, within this textural range. The SOC stocks in the 0-30 cm topsoil layer of these selected fields varied between 4.2 and 6.7 kg C m(-2) and increased on average (r(2) = 0.97) with 0.19 kg C m(-2) year(-1). After 12 years of NTM management, SOC stocks were no longer significantly different from the stocks under natural Cerrado vegetation (p < 0.05), whereas a 23-year-old conventionally tilled and cropped field showed SOC stocks that were about 30% below this level. Confirming our hypotheses, this study clearly illustrated the high potential of NTM systems in increasing SOC storage under tropical conditions, and how a synchronic approach may be used to assess efficiently such modification on farmers` fields, identifying and excluding non desirable sources of heterogeneity (management, soils and climate). (C) 2010 Elsevier B.V. All rights reserved.

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Lignin phenols were measured in the sediments of Sepitiba Bay, Rio de Janeiro, Brazil and in bedload sediments and suspended sediments of the four major fluvial inputs to the bay: Sao Francisco and Guandu Channels and the Guarda and Cacao Rivers. Fluvial suspended lignin yields (Sigma 8 3.5-14.6 mgC 10 g dw(-1)) vary little between the wet and dry seasons and are poorly correlated with fluvial chlorophyll concentrations (0.8-50.2 mu gC L(-1)). Despite current land use practices that favor grassland agriculture or industrial uses, fluvial lignin compositions are dominated by a degraded leaf-sourced material. The exception is the Guarda River, which has a slight influence from grasses. The Lignin Phenol Vegetation Index, coupled with acid/aldehyde and 3.5 Db/V ratios, indicate that degraded leaf-derived phenols are also the primary preserved lignin component in the bay. The presence of fringe Typha sp. and Spartina sp. grass beds surrounding portions of the Bay are not reflected in the lignin signature. Instead, lignin entering the bay appears to reflect the erosion of soils containing a degraded signature from the former Atlantic rain forest that once dominated the watershed, instead of containing a significant signature derived from current agricultural uses. A three-component mixing model using the LPVI, atomic N:C ratios, and stable carbon isotopes (which range between -26.8 and -21.8 parts per thousand) supports the hypothesis that fluvial inputs to the bay are dominated by planktonic matter (78% of the input), with lignin dominated by leaf (14% of the input) over grass (6%). Sediments are composed of a roughly 50-50 mixture of autochthonous material and terrigenous material, with lignin being primarily sourced from leaf. (C) 2010 Elsevier Ltd. All rights reserved.

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The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.

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Estimates of greenhouse-gas emissions from deforestation are highly uncertain because of high variability in key parameters and because of the limited number of studies providing field measurements of these parameters. One such parameter is burning efficiency, which determines how much of the original forest`s aboveground carbon stock will be released in the burn, as well as how much will later be released by decay and how much will remain as charcoal. In this paper we examined the fate of biomass from a semideciduous tropical forest in the ""arc of deforestation,"" where clearing activity is concentrated along the southern edge of the Amazon forest. We estimated carbon content, charcoal formation and burning efficiency by direct measurements (cutting and weighing) and by line-intersect sampling (LIS) done along the axis of each plot before and after burning of felled vegetation. The total aboveground dry biomass found here (219.3 Mg ha(-1)) is lower than the values found in studies that have been done in other parts of the Amazon region. Values for burning efficiency (65%) and charcoal formation (6.0%, or 5.98 Mg C ha(-1)) were much higher than those found in past studies in tropical areas. The percentage of trunk biomass lost in burning (49%) was substantially higher than has been found in previous studies. This difference may be explained by the concentration of more stems in the smaller diameter classes and the low humidity of the fuel (the dry season was unusually long in 2007, the year of the burn). This study provides the first measurements of forest burning parameters for a group of forest types that is now undergoing rapid deforestation. The burning parameters estimated here indicate substantially higher burning efficiency than has been found in other Amazonian forest types. Quantification of burning efficiency is critical to estimates of trace-gas emissions from deforestation. (C) 2009 Elsevier B.V. All rights reserved.