969 resultados para Remote-sensing Data
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.
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Aquaculture of filter-feeding bivalve mollusks involves the fruitful conversion of marine particulate organic matter into premium protein of high nutritive value. Culture performance of bivalves is largely dependent on hydrological conditions and directly affected by e. g. temperature and chlorophyll levels. Accordingly, these parameters may be related with seasonality but also with oceanographic features combined with climate events. Yields of Pacific cupped oyster (Crassostrea gigas) reared at commercial procedures in suspended structures (long-lines) in a sheltered bay in Southern Brazil (Santa Catarina State, 27S 43'; 48 W 30') were evaluated in relation to local environmental conditions: sea surface temperature, chlorophyll a concentration, and associate effects of cold fronts events and El Nino and La Nina periods. Outputs from four consecutive commercial crop years were analyzed (2005/06, 2006/07, 2007/08, 2008/09) in terms of oyster survival and development time during the following grow-out phases of the culture cycle: seed to juvenile, juvenile to adult, adult to marketable. Since culture management and genetics were standardized significant differences verified among crop performance could be mostly related to environmental effects. Time series of temperature and chlorophyll a (remote sensing data) from crop periods displayed significant seasonal and interannual variation. As expected, performance during initial grow-out stages (seed to juvenile) was critical for final crop yield. Temperature was the main factor affecting survival in these initial stages with a trend of negative correlation, though not statistically significant. On the other hand, oyster development rate was significantly and positively affected by chlorophyll a concentration. Chlorophyll a values could be increased by upwelled cold nutrient-rich South Atlantic Central Water (SACW, related to predominant Northern winds) though further dependent on occurrence of Southern winds (cold fronts) to assist seawater penetration into the sheltered farming area. Lower salinity nutrient-rich northward drifted waters from La Plata River discharge may also result in chlorophyll a rise in the farming area. The El Nino period (July 2006 to February 2007) coincided with lower chlorophyll a levels in the farming site that may be related to both decreased number of cold fronts as well as predominance of Northern winds that retain northward spreading of La Plata River discharge waters. In contrast, the La Nina period (August 2007 to June 2008) corresponded to higher chlorophyll a values in the farming area by both upwelling of SACW and penetration of La Plata River discharge water assisted by increased occurrence of Southern winds and cold fronts. The recognition of the potentially changing climate and effects upon the environment will be an important step in planning future development of bivalve aquaculture.
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Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.
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ZUSAMMENFASSUNG Langzeitbeobachtungsstudien zur Landschaftsdynamik inSahelländern stehen generell einem defizitären Angebot anquantitativen Rauminformationen gegenüber. Der in Malivorgefundene lokal- bis regionalräumliche Datenmangelführte zu einer methodologischen Studie, die die Entwicklungvon Verfahren zur multi-temporalen Erfassung und Analyse vonLandschaftsveränderungsdaten beinhaltet. Für den RaumWestafrika existiert in großer Flächenüberdeckunghistorisches Fernerkundungsmaterial in Form hochauflösenderLuftbilder ab den 50er Jahren und erste erdbeobachtendeSatellitendaten von Landsat-MSS ab den 70er Jahren.Multitemporale Langzeitanalysen verlangen zur digitalenReproduzierbarkeit, zur Datenvergleich- undObjekterfaßbarkeit die a priori-Betrachtung derDatenbeschaffenheit und -qualität. Zwei, ohne verfügbare, noch rekonstruierbareBodenkontrolldaten entwickelte Methodenansätze zeigen nichtnur die Möglichkeiten, sondern auch die Grenzen eindeutigerradiometrischer und morphometrischerBildinformationsgewinnung. Innerhalb desÜberschwemmungsgunstraums des Nigerbinnendeltas im ZentrumMalis stellen sich zwei Teilstudien zur Extraktion vonquantitativen Sahelvegetationsdaten den radiometrischen undatmosphärischen Problemen:1. Präprozessierende Homogenisierung von multitemporalenMSS-Archivdaten mit Simulationen zur Wirksamkeitatmosphärischer und sensorbedingter Effekte2. Entwicklung einer Methode zur semi-automatischenErfassung und Quantifizierung der Dynamik derGehölzbedeckungsdichte auf panchromatischenArchiv-Luftbildern Die erste Teilstudie stellt historischeLandsat-MSS-Satellitenbilddaten für multi-temporale Analysender Landschaftsdynamik als unbrauchbar heraus. In derzweiten Teilstudie wird der eigens, mittelsmorphomathematischer Filteroperationen für die automatischeMusterkennung und Quantifizierung von Sahelgehölzobjektenentwickelte Methodenansatz präsentiert. Abschließend wird die Forderung nach kosten- undzeiteffizienten Methodenstandards hinsichtlich ihrerRepräsentativität für die Langzeitbeobachtung desRessourceninventars semi-arider Räume sowie deroperationellen Transferierbarkeit auf Datenmaterial modernerFernerkundungssensoren diskutiert.
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Für die Zukunft wird eine Zunahme an Verkehr prognostiziert, gleichzeitig herrscht ein Mangel an Raum und finanziellen Mitteln, um weitere Straßen zu bauen. Daher müssen die vorhandenen Kapazitäten durch eine bessere Verkehrssteuerung sinnvoller genutzt werden, z.B. durch Verkehrsleitsysteme. Dafür werden räumlich aufgelöste, d.h. den Verkehr in seiner flächenhaften Verteilung wiedergebende Daten benötigt, die jedoch fehlen. Bisher konnten Verkehrsdaten nur dort erhoben werden, wo sich örtlich feste Meßeinrichtungen befinden, jedoch können damit die fehlenden Daten nicht erhoben werden. Mit Fernerkundungssystemen ergibt sich die Möglichkeit, diese Daten flächendeckend mit einem Blick von oben zu erfassen. Nach jahrzehntelangen Erfahrungen mit Fernerkundungsmethoden zur Erfassung und Untersuchung der verschiedensten Phänomene auf der Erdoberfläche wird nun diese Methodik im Rahmen eines Pilotprojektes auf den Themenbereich Verkehr angewendet. Seit Ende der 1990er Jahre wurde mit flugzeuggetragenen optischen und Infrarot-Aufnahmesystemen Verkehr beobachtet. Doch bei schlechten Wetterbedingungen und insbesondere bei Bewölkung, sind keine brauchbaren Aufnahmen möglich. Mit einem abbildenden Radarverfahren werden Daten unabhängig von Wetter- und Tageslichtbedingungen oder Bewölkung erhoben. Im Rahmen dieser Arbeit wird untersucht, inwieweit mit Hilfe von flugzeuggetragenem synthetischem Apertur Radar (SAR) Verkehrsdaten aufgenommen, verarbeitet und sinnvoll angewendet werden können. Nicht nur wird die neue Technik der Along-Track Interferometrie (ATI) und die Prozessierung und Verarbeitung der aufgenommenen Verkehrsdaten ausführlich dargelegt, es wird darüberhinaus ein mit dieser Methodik erstellter Datensatz mit einer Verkehrssimulation verglichen und bewertet. Abschließend wird ein Ausblick auf zukünftige Entwicklungen der Radarfernerkundung zur Verkehrsdatenerfassung gegeben.
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This study investigates four decades of socio-economic and environmental change in a shifting cultivation landscape in the northern uplands of Laos. Historical changes in land cover and land use were analyzed using a chronological series of remote sensing data. Impacts of landscape change on local livelihoods were investigated in seven villages through interviews with various stakeholders. The study reveals that the complex mosaics of agriculture and forest patches observed in the study area have long constituted key assets for the resilience of local livelihood systems in the face of environmental and socio-economic risks. However, over the past 20 years, a process of segregating agricultural and forest spaces has increased the vulnerability of local land users. This process is a direct outcome of policies aimed at increasing national forest cover, eradicating shifting cultivation and fostering the emergence of more intensive and commercial agricultural practices. We argue that agriculture-forest segregation should be buffered in such a way that a diversity of livelihood opportunities and economic development pathways can be maintained.
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One of two active volcanoes in the western branch of the East African Rift, Nyamuragira (1.408ºS, 29.20ºE; 3058 m) is located in the D.R. Congo. Nyamuragira emits large amounts of SO2 (up to ~1 Mt/day) and erupts low-silica, alkalic lavas, which achieve flow rates of up to ~20 km/hr. The source of the large SO2 emissions and pre-eruptive magma conditions were unknown prior to this study, and 1994-2010 lava volumes were only recently mapped via satellite imagery, mainly due to the region’s political instability. In this study, new olivine-hosted melt inclusion volatile (H2O, CO2, S, Cl, F) and major element data from five historic Nyamuragira eruptions (1912, 1938, 1948, 1986, 2006) are presented. Melt compositions derived from the 1986 and 2006 tephra samples best represent pre-eruptive volatile compositions because these samples contain naturally glassy inclusions that underwent less post-entrapment modification than crystallized inclusions. The total amount of SO2 released from the 1986 (0.04 Mt) and 2006 (0.06 Mt) eruptions are derived using the petrologic method, whereby S contents in melt inclusions are scaled to erupted lava volumes. These amounts are significantly less than satellite-based SO2 emissions for the same eruptions (1986 = ~1 Mt; 2006 = ~2 Mt). Potential explanations for this observation are: 1) accumulation of a vapor phase within the magmatic system that is only released during eruptions, and/or 2) syn-eruptive gas release from unerupted magma. Post-1994 Nyamuragira lava volumes were not available at the beginning of this study. These flows (along with others since 1967) are mapped with Landsat MSS, TM, and ETM+, Hyperion, and ALI satellite data and combined with published flow thicknesses to derive volumes. Satellite remote sensing data was also used to evaluate Nyamuragira SO2 emissions. These results show that the most recent Nyamuragira eruptions injected SO2 into the atmosphere between 15 km (2006 eruption) and 5 km (2010 eruption). This suggests that past effusive basaltic eruptions (e.g., Laki 1783) are capable of similar plume heights that reached the upper troposphere or tropopause, allowing SO2 and resultant aerosols to remain longer in the atmosphere, travel farther around the globe, and affect global climates.
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Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.
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Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.
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The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.
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An important share of paleoclimatic information is buried within the lowermost layers of deep ice cores. Because improving our records further back in time is one of the main challenges in the near future, it is essential to judge how deep these records remain unaltered, since the proximity of the bedrock is likely to interfere both with the recorded temporal sequence and the ice properties. In this paper, we present a multiparametric study (δD-δ18Oice, δ18Oatm, total air content, CO2, CH4, N2O, dust, high-resolution chemistry, ice texture) of the bottom 60 m of the EPICA (European Project for Ice Coring in Antarctica) Dome C ice core from central Antarctica. These bottom layers were subdivided into two distinct facies: the lower 12 m showing visible solid inclusions (basal dispersed ice facies) and the upper 48 m, which we will refer to as the "basal clean ice facies". Some of the data are consistent with a pristine paleoclimatic signal, others show clear anomalies. It is demonstrated that neither large-scale bottom refreezing of subglacial water, nor mixing (be it internal or with a local basal end term from a previous/initial ice sheet configuration) can explain the observed bottom-ice properties. We focus on the high-resolution chemical profiles and on the available remote sensing data on the subglacial topography of the site to propose a mechanism by which relative stretching of the bottom-ice sheet layers is made possible, due to the progressively confining effect of subglacial valley sides. This stress field change, combined with bottom-ice temperature close to the pressure melting point, induces accelerated migration recrystallization, which results in spatial chemical sorting of the impurities, depending on their state (dissolved vs. solid) and if they are involved or not in salt formation. This chemical sorting effect is responsible for the progressive build-up of the visible solid aggregates that therefore mainly originate "from within", and not from incorporation processes of debris from the ice sheet's substrate. We further discuss how the proposed mechanism is compatible with the other ice properties described. We conclude that the paleoclimatic signal is only marginally affected in terms of global ice properties at the bottom of EPICA Dome C, but that the timescale was considerably distorted by mechanical stretching of MIS20 due to the increasing influence of the subglacial topography, a process that might have started well above the bottom ice. A clear paleoclimatic signal can therefore not be inferred from the deeper part of the EPICA Dome C ice core. Our work suggests that the existence of a flat monotonic ice–bedrock interface, extending for several times the ice thickness, would be a crucial factor in choosing a future "oldest ice" drilling location in Antarctica.
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The north-eastern escarpment of Madagascar contains the island’s last remaining large-scale humid forest massifs surrounded by diverse small-scale agricultural mosaics. There is high deforestation mainly caused by shifting cultivation practiced by local land users to produce upland rice for subsistence. Today, large protected areas restrict land users’ access to forests to collect wood and other forest products. Moreover, they are no more able to expand their cultivated land, which leads to shorter shifting cultivation cycles and decreasing plot sizes for irrigated rice and cash crop cultivation. Cash crop production of clove and vanilla is exposed to risks such as extreme inter-annual price fluctuations, pests and cyclones. In the absence of work opportunities, agricultural extension services and micro-finance schemes people are stuck in a poverty trap. New development strategies are needed to mitigate the trade-offs between forest conservation and human well-being. As landscape composition and livelihood strategies vary across the region, these strategies need to be spatially differentiated to avoid implementing generic solutions, which do not fit the local context. However, up to date, little is known about the spatial patterns of shifting cultivation and other land use systems at the regional level. This is mainly due to the high spatial and temporal dynamics inherent to shifting cultivation, which makes it difficult to monitor the dynamics of this land use system with remote sensing methods. Furthermore, knowledge about land users’ livelihood strategies and the risks and opportunities they face stems from very few local case studies. To overcome this challenge, firstly, we used remote sensing data and a landscape mosaic approach to delineate the main landscape types at the regional level. Secondly, we developed a land user typology based on socio-ecological data from household surveys in 45 villages spread throughout the region. Combining the land user typology with the landscape mosaic map allowed us to reveal spatial patterns of the interaction between landscapes and people and to better understand the trade-offs between forest conservation and local wellbeing. While shifting cultivation systems are being transformed into more intensive permanent agricultural systems in many countries around the globe, Madagascar seems to be an exception to this trend. Linking land cover information to human-environmental interactions over large areas is crucial to designing policies and to inform decision making for a more sustainable development of this resource-rich but poverty-prone context.