Análise do potencial do sensor OLI (Operational Land Imager) a bordo do Landsat-8 em estimar a concentração de sólidos totais em suspensão no reservatório de Barra Bonita

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Télédétection du carbone organique des lacs boréaux

Une estimation des quantités de carbone organique dissous dans les millions de lacs boréaux est nécessaire pour améliorer notre connaissance du cycle global du carbone. Les teneurs en carbone organique dissous sont corrélées avec les quantités de matière organique dissoute colorée qui est visible depuis l’espace. Cependant, les capteurs actuels offrent une radiométrie et une résolution spatiale qui sont limitées par rapport à la taille et l’opacité des lacs boréaux. Landsat 8, lancé en février 2013, offrira une radiométrie et une résolution spatiale améliorées, et produira une couverture à grande échelle des régions boréales. Les limnologistes ont accumulé des années de campagnes de terrain dans les régions boréales pour lesquelles une image Landsat 8 sera disponible. Pourtant, la possibilité de combiner des données de terrain existantes avec une image satellite récente n'a pas encore été évaluée. En outre, les différentes stratégies envisageables pour sélectionner et combiner des mesures répétées au cours du temps, sur le terrain et depuis le satellite, n'ont pas été évaluées. Cette étude présente les possibilités et les limites d’utiliser des données de terrain existantes avec des images satellites récentes pour développer des modèles de prédiction du carbone organique dissous. Les méthodes se basent sur des données de terrain recueillies au Québec dans 53 lacs boréaux et 10 images satellites acquises par le capteur prototype de Landsat 8. Les délais entre les campagnes de terrain et les images satellites varient de 1 mois à 6 ans. Le modèle de prédiction obtenu se compare favorablement avec un modèle basé sur des campagnes de terrain synchronisées avec les images satellite. L’ajout de mesures répétées sur le terrain, sur le satellite, et les corrections atmosphériques des images, n’améliorent pas la qualité du modèle de prédiction. Deux images d’application montrent des distributions différentes de teneurs en carbone organique dissous et de volumes, mais les quantités de carbone organique dissous par surface de paysage restent de même ordre pour les deux sites. Des travaux additionnels pour intégrer les sédiments dans l’estimation sont nécessaires pour améliorer le bilan du carbone des régions boréales.

A Texture-based land cover classification for the delineation of a shifting cultivation landscape in the Lao PDR using landscape metrics

The delineation of shifting cultivation landscapes using remote sensing in mountainous regions is challenging. On the one hand, there are difficulties related to the distinction of forest and fallow forest classes as occurring in a shifting cultivation landscape in mountainous regions. On the other hand, the dynamic nature of the shifting cultivation system poses problems to the delineation of landscapes where shifting cultivation occurs. We present a two-step approach based on an object-oriented classification of Advanced Land Observing Satellite, Advanced Visible and Near-Infrared Spectrometer (ALOS AVNIR) and Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) data and landscape metrics. When including texture measures in the object-oriented classification, the accuracy of forest and fallow forest classes could be increased substantially. Based on such a classification, landscape metrics in the form of land cover class ratios enabled the identification of crop-fallow rotation characteristics of the shifting cultivation land use practice. By classifying and combining these landscape metrics, shifting cultivation landscapes could be delineated using a single land cover dataset.

Carbon sequestration associated to the land-use and land-cover changes in the forestry sector in Southern Brazil.

We studied the Paraíba do Sul river watershed , São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implication s to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. Th e region covers a n area of 1,395,975 ha . We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat - 8) to produce mappings , and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB) , we used an indirect method and applied literature - based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C . Considering the whole NF area (455,232 ha), the amount of C accumulated al ong the whole watershed was 3 5 .5 Tg , and the whole Eucalyptus crop (EU) area (113,600 ha) sequester ed 4. 4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 3 9 . 9 Tg of C or 1 45 . 6 Tg of CO 2 , and the NF areas were responsible for the large st C stock at the watershed (8 9 %). Therefore , the increase of the NF cover contribut es positively to the reduction of CO 2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD + ) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.

Análise do uso da terra nas áreas de preservação permanente dos corpos d’água da bacia do córrego espraiado como subsídio para pagamentos por serviços ambientais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of chlorophyll-a concentration and the trophic state of the Barra Bonita hydroelectric reservoir using oli/landsat-8 images

Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.

(Table 1) Accumulation and ice discharge of West Antarctic glaciers draining into the Amundsen Sea between 1974 and 2007

The Advanced Land Observation System (ALOS) Phased-Array Synthetic-Aperture Radar (PALSAR) is an L-band frequency (1.27 GHz) radar capable of continental-scale interferometric observations of ice sheet motion. Here, we show that PALSAR data yield excellent measurements of ice motion compared to C-band (5.6 GHz) radar data because of greater temporal coherence over snow and firn. We compare PALSAR velocities from year 2006 in Pine Island Bay, West Antarctica with those spanning years 1974 to 2007. Between 1996 and 2007, Pine Island Glacier sped up 42% and ungrounded over most of its ice plain. Smith Glacier accelerated 83% and ungrounded as well. Their largest speed up are recorded in 2007. Thwaites Glacier is not accelerating but widening with time and its eastern ice shelf doubled its speed. Total ice discharge from these glaciers increased 30% in 12 yr and the net mass loss increased 170% from 39 ± 15 Gt/yr to 105 ± 27 Gt/yr. Longer-term velocity changes suggest only a moderate loss in the 1970s. As the glaciers unground into the deeper, smoother beds inland, the mass loss from this region will grow considerably larger in years to come.

Diurnal cycle of land surface temperature in a desert encroachment zone as observed from satellites

Climate variability in the African Soudano-Sahel savanna zone has attracted much attention because of the persistence of anomalously low rainfall. Past efforts to monitor the climate of this region have focused on rainfall and vegetation conditions, while land surface temperature (LST) has received less attention. Remote sensing of LST is feasible and possible at global scale. Most remotely sensed estimates of LST are based on the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) that are limited in their ability to capture the full diurnal cycle. Although more frequent observations are available from past geostationary satellites, their spatial resolution is coarser than that of polar orbiting satellites. In this study, the improved capabilities of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the METEOSAT Second Generation (MSG) instrument are used to remotely sense the LST in the African Soudano-Sahel savanna zone at a resolution of 3 km and 15 minutes. In support of the Radiative Atmospheric Divergence using the ARM Mobile Facility (AMF), GERB and AMMA Stations (RADAGAST) project, African Monsoon Multidisciplinary Analyses (AMMA) project and the Department of Energy's Atmospheric Radiation Measurement (ARM) program, the ARM Mobile Facility was deployed during 2006 in this climatically sensitive region, thereby providing a unique opportunity to evaluate remotely sensed algorithms for deriving LST.

Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer

We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

Twenty-year advanced DInSAR analysis of severe land subsidence: The Alto Guadalentín Basin (Spain) case study

A twenty-year period of severe land subsidence evolution in the Alto Guadalentín Basin (southeast Spain) is monitored using multi-sensor SAR images, processed by advanced differential interferometric synthetic aperture radar (DInSAR) techniques. The SAR images used in this study consist of four datasets acquired by ERS-1/2, ENVISAT, ALOS and COSMO-SkyMed satellites between 1992 and 2012. The integration of ground surface displacement maps retrieved for different time periods allows us to quantify up to 2.50 m of cumulated displacements that occurred between 1992 and 2012 in the Alto Guadalentín Basin. DInSAR results were locally compared with global positioning system (GPS) data available for two continuous stations located in the study area, demonstrating the high consistency of local vertical motion measurements between the two different surveying techniques. An average absolute error of 4.6 ± 4 mm for the ALOS data and of 4.8 ± 3.5 mm for the COSMO-SkyMed data confirmed the reliability of the analysis. The spatial analysis of DInSAR ground surface displacement reveals a direct correlation with the thickness of the compressible alluvial deposits. Detected ground subsidence in the past 20 years is most likely a consequence of a 100–200 m groundwater level drop that has persisted since the 1970s due to the overexploitation of the Alto Guadalentín aquifer system. The negative gradient of the pore pressure is responsible for the extremely slow consolidation of a very thick (> 100 m) layer of fine-grained silt and clay layers with low vertical hydraulic permeability (approximately 50 mm/h) wherein the maximum settlement has still not been reached.

Application of multi-sensor advanced DInSAR analysis to severe land subsidence recognition: Alto Guadalentín Basin (Spain)

Multi-sensor advanced DInSAR analyses have been performed and compared with two GPS station measurements, in order to evaluate the land subsidence evolution in a 20-year period, in the Alto Guadalentín Basin where the highest rate of man-induced subsidence (> 10 cm yr−1) of Europe had been detected. The control mechanisms have been examined comparing the advanced DInSAR data with conditioning and triggering factors (i.e. isobaths of Plio-Quaternary deposits, soft soil thickness and piezometric level).

Long-term Prospects For The Environmental Profile Of Advanced Sugar Cane Ethanol.

This work assessed the environmental impacts of the production and use of 1 MJ of hydrous ethanol (E100) in Brazil in prospective scenarios (2020-2030), considering the deployment of technologies currently under development and better agricultural practices. The life cycle assessment technique was employed using the CML method for the life cycle impact assessment and the Monte Carlo method for the uncertainty analysis. Abiotic depletion, global warming, human toxicity, ecotoxicity, photochemical oxidation, acidification, and eutrophication were the environmental impacts categories analyzed. Results indicate that the proposed improvements (especially no-til farming-scenarios s2 and s4) would lead to environmental benefits in prospective scenarios compared to the current ethanol production (scenario s0). Combined first and second generation ethanol production (scenarios s3 and s4) would require less agricultural land but would not perform better than the projected first generation ethanol, although the uncertainties are relatively high. The best use of 1 ha of sugar cane was also assessed, considering the displacement of the conventional products by ethanol and electricity. No-til practices combined with the production of first generation ethanol and electricity (scenario s2) would lead to the largest mitigation effects for global warming and abiotic depletion. For the remaining categories, emissions would not be mitigated with the utilization of the sugar cane products. However, this conclusion is sensitive to the displaced electricity sources.

Advanced orbital pipe welding

Since the introduction of automatic orbital welding in pipeline application in 1961, significant improvements have been obtained in orbital pipe welding systems. Requirement of more productive welding systems for pipeline application forces manufacturers to innovate new advanced systems and welding processes for orbital welding method. Various methods have been used to make welding process adaptive, such as visual sensing, passive visual sensing, real-time intelligent control, scan welding technique, multi laser vision sensor, thermal scanning, adaptive image processing, neural network model, machine vision, and optical sensing. Numerous studies are reviewed and discussed in this Master’s thesis and based on a wide range of experiments which already have been accomplished by different researches the vision sensor are reported to be the best choice for adaptive orbital pipe welding system. Also, in this study the most welding processes as well as the most pipe variations welded by orbital welding systems mainly for oil and gas pipeline applications are explained. The welding results show that Gas Metal Arc Welding (GMAW) and its variants like Surface Tension Transfer (STT) and modified short circuit are the most preferred processes in the welding of root pass and can be replaced to the Gas Tungsten Arc Welding (GTAW) in many applications. Furthermore, dual-tandem gas metal arc welding technique is currently considered the most efficient method in the welding of fill pass. Orbital GTAW process mostly is applied for applications ranging from single run welding of thin walled stainless tubes to multi run welding of thick walled pipes. Flux cored arc welding process is faster process with higher deposition rate and recently this process is getting more popular in pipe welding applications. Also, combination of gas metal arc welding and Nd:YAG laser has shown acceptable results in girth welding of land pipelines for oil and gas industry. This Master’s thesis can be implemented as a guideline in welding of pipes and tubes to achieve higher quality and efficiency. Also, this research can be used as a base material for future investigations to supplement present finding.

European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset

Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuous European vegetation phenology dataset of a 10-day temporal and 0.1° spatial resolution; additionally, land surface parameters for use in biosphere–atmosphere modelling are derived. The analysis of time-series from this dataset reveals, for the years 1982–2001, strong seasonal and interannual variability in European land surface vegetation state. Phenological metrics indicate a late and short growing season for the years 1985–1987, in addition to early and prolonged activity in the years 1989, 1990, 1994 and 1995. These variations are in close agreement with findings from phenological measurements at the surface; spring phenology is also shown to correlate particularly well with anomalies in winter temperature and winter North Atlantic Oscillation (NAO) index. Nevertheless, phenological metrics, which display considerable regional differences, could only be determined for vegetation with a seasonal behaviour. Trends in the phenological phases reveal a general shift to earlier (−0.54 days year−1) and prolonged (0.96 days year−1) growing periods which are statistically significant, especially for central Europe.

Generalized Bayesian cloud detection for satellite imagery. part 1: technique and validation for night-time imagery over land and sea

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud-masks. Here, this is done over both land and ocean using night-time (infrared) imagery. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 87% and 48% for ocean and land, respectively using the Bayesian technique, compared to 74% and 39%, respectively for the threshold-based techniques associated with the validation dataset.