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IMAGE:  Map-based areal data summaries for accumulated deforestation and annual soybeans are shown. Pre-Soy Moratorium and post-Soy Moratorium deforest trend lines are also depicted, with respective regression slopes provided in red... view more LAWRENCE -- The Brazilian state of Mato Grosso produces enough soybeans to be the equivalent of Iowa and Illinois put together. But it also plays home to lush Amazon rain forest, one of the richest, and most vulnerable, ecological treasures on our planet. Using satellite imagery and unique ground-based information, the interface between highly mechanized agriculture and rainforest in Mato Grosso is shown with exceptionally granular detail in a new study led by Jude Kastens, research associate professor at the Kansas Applied Remote Sensing Program of the Kansas Biological Survey, and co-authored by J. Christopher Brown, professor of geography and atmospheric science and director of the Environmental Studies Program at the University of Kansas. Their paper appears today (April 28, 2017) in PLOS ONE. "Mato Grosso is a frontier in the sense that natural vegetation, both rainforest and savanna, known as cerrado, is being replaced with crop production and other agricultural uses," Kastens said. "Mechanized agriculture moved rapidly into the area in the 1990s, so there's a lot of opportunity for crop production and farm-related business development." Indeed, the researchers said agriculture in the area has a boom-town energy, generating billions of dollars annually that contribute to the state's economy. "There are cases of U.S. farmers selling everything in Iowa and moving to Mato Grosso in Brazil," Brown said. "That's a great indicator of being a frontier. There's opportunity. I've often boarded planes for Brazil in Houston and waited in line with lots of farmers headed on tours in Brazil to scope out moving operations there." However, agricultural expansion has come at the expense of the Amazon rainforest. Concerns over widespread deforestation in the area led to a 2006 agreement between environmental groups and large agricultural corporations called the "Soy Moratorium." Under the moratorium, major soy purchasers agreed to not buy soy produced on land deforested after July of that year. "This begs the question -- over such a large area, how are you going to know which deforested areas were replaced by soybeans after that date?" Brown said. "You need a really detailed land cover data set like we produced to know this." Kastens and Brown, along with KU colleague Christopher Bishop and Alexandre Coutinho and Júlio Esquerdo of the Brazilian Agricultural Research Corporation (Embrapa), relied in part on satellite datasets from the Moderate Resolution Imaging Spectroradiometer, or MODIS. By looking at images taken over 14 growing seasons, the researchers could examine changes in cropland location and production intensity across Mato Grosso. Most soy production in the Amazon Forest Biome occurs in this large state. "The satellite images capture reflectance values from the ground in various wavelengths -- the ones commonly used in vegetation studies are the red and near-infrared bands," Kastens said. "Red light reflectance goes down as photosynthesis increases, whereas near-infrared reflectance goes up with denser leaf canopies. These two bands are combined to form the Normalized Difference Vegetation Index. NDVI signals from healthy soy fields will look different from healthy cotton fields, which will look different from other cover types." To interpret the satellite data, co-authors from Embrapa, the Brazilian equivalent of the USDA, collected an unprecedented amount of ground reference data in Mato Grosso by interviewing farmers. In 2006, the KU and Brazilian researchers began working under a memorandum of understanding to share methods in ground data collection and land cover classification. Since then, the researchers have visited each other's labs and carried out field work together. "The wealth of ground reference data made this research possible," Brown said. "There hasn't been anything like this for such a large area outside the U.S. Our colleagues worked with farmers to trace field boundaries on printed satellite imagery and give cropping histories for various parcels of land." A major finding of the research suggests the 2006 Soy Moratorium had a larger effect in reducing deforestation in the Amazon than has been previously understood. "Based on our analysis, we found a much stronger deforestation decline coincident with the Soy Moratorium than other studies have reported," Kastens said. "The Soy Moratorium has been downplayed in some research as a factor in deforestation reduction. Our examination of essentially the same deforestation dataset used by others revealed a major decline in deforestation occurred immediately after the moratorium took effect. "Deforestation is still happening, but it has slowed, and less of this land is being used for soy production," Kastens said. The study incorporated deforestation data produced by the Brazilian Institute for Space Research (INPE). The team also found a sharp rise in production on existing cropland after the moratorium, dubbed "vertical intensification," while deforestation-driven cropland expansion, or "horizontal intensification," slowed substantially. "With vertical intensification, we see a dramatic increase in double cropping, where farmers plant a first crop of soybeans followed by a second commercial crop, typically corn, in the same growing season and field," Brown said. The researchers are making their land cover data freely available. They hope it will help guide land managers and policymakers looking to strike a balance between farming and conservation. "The rain forest helps regulate many climate-related factors in the Amazon basin and nearby regions, including temperatures and the hydrologic cycle," Kastens said. "It has obvious ecological value and is a biodiversity hotspot with many untapped natural resources." The Amazon is also home to many native populations. "Indigenous people in rain forest reserves are being completely surrounded by these soybean fields, many of which are upstream," Brown said. Kastens added, "Researchers can utilize our map data, with its detailed spatial and class resolutions, to examine market accessibility impacts and other agricultural frontier-related questions, as well as issues related to climate, ecology and human geography."

Schroeder W.,University of Maryland University College | Oliva P.,University of Maryland University College | Giglio L.,University of Maryland University College | Quayle B.,U.S. Department of Agriculture | And 2 more authors.
Remote Sensing of Environment | Year: 2015

The gradual increase in Landsat-class data availability creates new opportunities for fire science and management applications that require higher-fidelity information about biomass burning, improving upon existing coarser spatial resolution (≥. 1. km) satellite active fire data sets. Targeting those enhanced capabilities we describe an active fire detection algorithm for use with Landsat-8 Operational Land Imager (OLI) daytime and nighttime data. The approach builds on the fire-sensitive short-wave infrared channel 7 complemented by visible and near-infrared channel 1-6 data (daytime only), while also expanding on the use of multi-temporal analysis to improve pixel classification results. Despite frequent saturation of OLI's fire-affected pixels, which includes radiometric artifacts resulting from folding of digital numbers, our initial assessment based on visual image analysis indicated high algorithm fidelity across a wide range of biomass burning scenarios, gas flares and active volcanoes. Additional field data verification confirmed the sensor's and algorithm's ability to resolve fires of significantly small areas compared to current operational satellite fire products. Commission errors were greatly reduced with the addition of multi-temporal analysis tests applied to co-located pixels, averaging less than 0.2% globally. Because of its overall quality, Landsat-8/OLI active fire data could become part of a network of emerging earth observation systems providing enhanced spatial and temporal coverage of biomass burning at global scales. © 2015.

De Vasconcelos L.G.,Brazilian Institute for Space Research | Dos Santos R.D.C.,Brazilian Institute for Space Research | Baldochi L.A.,Federal University of Itajubá
Proceedings of the 13th International Conference WWW/Internet 2014, ICWI 2014 | Year: 2014

With the increasing use of the Internet, the Web has become the predominant means by which people obtain information. However, due to the fast growth of the amount and (sometimes competing) sources of resources available on the Web, users want to find information quickly and efficiently. Currently, web personalization has been explored in order to encourage user's feedback, improve usability and provide interesting content. In the literature, the most common approach is to analyze server logs, which contain information about what pages the user accesses during browsing. However, client logs contain more information about the user navigation. The amount of data of the client logs is significantly greater than the amount of server logs, and this is one factor that discourages analysis of client logs. In this paper, an approach is presented to classify the level of user's experience in real time, using indices of efficiency and effectiveness. The proposed approach, called RUX (Real-time User eXperience), contains an efficient algorithm for analyzing the user's behavior of web applications in real time using client logs. RUX focuses on the paths that a user goes through during the interaction, comparing them to previously defined tasks. RUX approach can be used by application developer to consume the classification of user's experience in real time, previously programming actions that can be taken. Experimental results show that the approach is efficient for aspects of data collection, latency and scalability.

Sander de Carvalho L.A.,Brazilian Institute for Space Research | Faria Barbosa C.C.,Brazilian Institute for Space Research | Leao de Moraes Novo E.M.,Brazilian Institute for Space Research | de Moraes Rudorff C.,Brazilian Institute for Space Research
Remote Sensing of Environment | Year: 2015

Amazon floodplain lakes range widely in concentrations of optically active constituents (OAC) driven by seasonality in hydrological and biogeochemical processes, but in general they are characterized by high turbidity (NTU from 90 to 1645) compared to coastal waters. In this work, instruments for measuring inherent optical properties (IOPs) of water bodies were evaluated for the first time in floodplain lakes in the lower Amazon River during the falling limb of the hydrograph. Water column profiles of total attenuation and absorption were measured using the Spectral Absorption and Attenuation Meter (AC-S-WETLabs), and of backscattering using Hydroscat. These measurements, however, are subject to uncertainties and require corrections for turbid waters. In this paper, we assessed the implications of scattering correction methods for the absorption tube, proposed by the AC-S manufacturer, in the simulation of the Remote Sensing Reflectance (Rrs). The closure experiment comparing Hydrolight (Mobley & Sundman, 2001) simulated Rrs and in situ Rrs demonstrated that neither of the corrections was able to thoroughly account for the scattering errors which were propagated to the absorption measurements with AC-S and backscattering with Hydroscat. The three scattering correction methods (Flat, Proportional and "Kirk") either under or overestimated the absorption coefficient that resulted in either under or overestimation of the simulated Rrs. Flat and Proportional Methods resulted in an underestimation of Rrs from 400 to 550nm and overestimation from 600 to 700nm, indicating that the assumption of zero (0) absorption in the near infrared does not apply to inland turbid water. The Rrs errors varied also according to water OAC composition. Overall, "Kirk" correction method provided the best results regarding the spectral shape of the Rrs, however, failed to account for magnitude. Based on the tuning tests, the errors in spectra magnitude seem to be sensitive to the constant fraction of scattering (CFS) used in the Kirk method. Tests carried out with CFS values varying from 0.18 to 0.38 indicated that magnitude error can be partially overcomed by tuning CFS according to water composition. Improvements in the scattering correction methods are required in order to obtain reliable IOPs in turbid inland Amazon lakes. © 2014 Elsevier Inc.

Alcantara E.H.,Brazilian Institute for Space Research | Stech J.L.,Brazilian Institute for Space Research | Lorenzzetti J.A.,Brazilian Institute for Space Research | Bonnet M.P.,CIRAD - Agricultural Research for Development | And 3 more authors.
Remote Sensing of Environment | Year: 2010

Water temperature plays an important role in ecological functioning and in controlling the biogeochemical processes of a water body. Conventional water quality monitoring is expensive and time consuming. It is particularly problematic if the water bodies to be examined are large. Conventional techniques also bring about a high probability of undersampling. Conversely, remote sensing is a powerful tool to assess aquatic systems. The objective of this study was to map the surface water temperature and improve understanding of spatiotemporal variations in a hydroelectric reservoir. In this work, MODIS land-surface temperature (LST) level 2, 1-km nominal resolution data (MOD11L2, version 5) were used. All available clear-sky MODIS/Terra images from 2003 to 2008 were used, resulting in a total of 786 daytime and 473 nighttime images. Descriptive statistics (mean, maximum and minimum) were computed for the historical images to build a time series of daytime and nighttime monthly mean temperatures. The thermal amplitude and anomaly were also computed. In-situ meteorological variables were used from 2003 to 2008 to help understand the spatiotemporal variability of the surface water temperature. The surface energy budget and the depth at which the wind can distribute the heat input of a given surface were also measured. A correlation between daytime and nighttime surface water temperatures and the computed heat fluxes were made. These relationships and the causes of the water surface temperature variability are discussed. © 2010 Elsevier Inc.

Alcantara E.,Brazilian Institute for Space Research | Novo E.,Brazilian Institute for Space Research | Stech J.,Brazilian Institute for Space Research | Assireu A.,Brazilian Institute for Space Research | And 3 more authors.
Journal of Hydrology | Year: 2010

This paper proposes a fast and inexpensive method for estimating the bathymetry of hydroelectric reservoirs. Brazil has more than 30 large hydroelectric reservoirs with a combined volume exceeding one billion cubic meters. The hydroelectric sector is responsible for 97% of the energy production in Brazil and is the largest hydroelectric park in the world. Among the variables affecting the environmental impacts of reservoirs, depth plays a major role because it influences the aquatic system hydrodynamics. Reservoir depth distribution (i.e., the bathymetry) is also a fundamental factor controlling the physical-chemical and biological properties of the system. However, the acquisition of bathymetric information for the large reservoirs in Brazil is not a simple task because: (1) most of the topographic maps available in the area of the lake have a very small scale (1:100,000 and smaller), (2) larger charts are the property of the hydropower companies and are classified, and (3) the size of the reservoirs prevent the use of bathymetric surveys. The proposed method of integrating historical and Shuttle Radar Topography Mission (SRTM) topographic data allowed for the estimation of the bathymetry of the Itumbiara reservoir with R2=0.98 (n=100, ρ=0.00) and RMSE=3.78m. For researchers who need a rapid and simple method to develop bathymetric maps of hydroelectric reservoirs, the proposed method can provide a simple and fast alternative to more data intensive methods. © 2010 Elsevier B.V.

Ricci M.C.,Brazilian Institute for Space Research
World Academy of Science, Engineering and Technology | Year: 2010

An alternative iterative computational procedure is proposed for internal normal ball loads calculation in statically loaded single-row, angular-contact ball bearings, subjected to a known thrust load, which is applied in the inner ring at the geometric bearing center line. An accurate method for curvature radii at contacts with inner and outer raceways in the direction of the motion is used. Numerical aspects of the iterative procedure are discussed. Numerical examples results for a 218 angular-contact ball bearing have been compared with those from the literature. Twenty figures are presented showing the geometrical features, the behavior of the convergence variables and the following parameters as functions of the thrust load: normal ball loads, contact angle, distance between curvature centers, and normal ball and axial deflections.

Ricci M.C.,Brazilian Institute for Space Research
World Academy of Science, Engineering and Technology | Year: 2010

A known iterative computational procedure is used for internal normal ball loads calculation in statically loaded single-row, angular-contact ball bearings, subjected to a known thrust load, which is applied in the inner ring at the geometric bearing center line. Numerical aspects of the iterative procedure are discussed. Numerical examples results for a 218 angular-contact ball bearing have been compared with those from the literature. Twenty figures are presented showing the geometrical features, the behavior of the convergence variables and the following parameters as functions of the thrust load: normal ball loads, contact angle, distance between curvature centers, and normal ball and axial deflections between the raceways.

Gomes V.,Brazilian Institute for Space Research | Velho H.C.,Brazilian Institute for Space Research | Charao A.,Federal University of Santa Maria
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

This paper presents the design and implementation of a fast Poisson solver on a reconfigurable hybrid system. Our hybrid solver integrates a FPGA-based FFT coprocessor to collaborate in the solution of a numerical meteorological model involving one-dimensional shallow water equations. The Poisson equation is solved using a singular value decomposition associated with the Moore-Penrose inverse. The hybrid fast Poisson solver is evaluated under different amount of data entry and shows performance gains compared to the reference application. © 2013 Springer-Verlag.

Alcantara E.,Brazilian Institute for Space Research | Novo E.,Brazilian Institute for Space Research | Stech J.,Brazilian Institute for Space Research | Lorenzzetti J.,Brazilian Institute for Space Research | And 3 more authors.
Hydrology and Earth System Sciences | Year: 2010

Observations of turbidity provide quantitative information about water quality. However, the number of available in situ measurements for water quality determination is usually limited in time and space. Here, we present an analysis of the temporal and spatial variability of the turbidity of an Amazon floodplain lake using two approaches: (1) wavelet analysis of a turbidity time series measured by an automatic monitoring system, which should be improved/simplified, and (2) turbidity samples measured in different locations and then interpolated using an ordinary Kriging algorithm. The spatial and temporal variability of turbidity are clearly related to the Amazon River flood pulses in the floodplain. When the water level in the floodplain is rising or receding, the exchange between the Amazon River and the floodplain is the major driving force in turbidity variability. At high-water levels, turbidity variability is controlled by Lake Bathymetry. When the water level is low, wind action and Lake Morphometry are the main causes of turbidity variability. The combined use of temporal and spatial data shows a good potential for better understanding of the turbidity behaviour in a complex aquatic system such as the Amazon floodplain.

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