Publicações 2017
Artigo de Pesquisa | Acesso aberto | 13 A new high‐resolution nationwide aboveground carbon map for Brazil

David Montenegro Lapola

Ano de publicação: 2017

Resumo:
Brazil is home to the largest tracts of tropical vegetation in the world, harbouring high levels of biodiversity and carbon. Several biomass maps have been produced for Brazil, using different approaches and methods, and for different purposes. These maps have been used to estimate historic, recent, and future carbon emissions from land use change (LUC). It can be difficult to determine which map to use for what purpose. The implications of using an unsuitable map can be significant, since the maps have large differences, both in terms of total carbon storage and its spatial distribution. This paper presents comparisons of Brazil's new ‘official’ carbon map; that is, the map used in the third national communication to the UNFCCC in 2016, with the former official map, and four carbon maps from the scientific literature. General strengths and weaknesses of the different maps are identified, including their suitability for different types of studies. No carbon map was found suitable for studies concerned with existing land use/cover (LULC) and LUC outside of existing forests, partly because they do not represent the current LULC sufficiently well, and partly because they generally overestimate carbon values for agricultural land. A new map of aboveground carbon is presented, which was created based on data from existing maps and an up‐to‐date LULC map. This new map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. We identify five ongoing climate policy initiatives in Brazil that can benefit from using this map.

Palavras chave:
Brazil; carbon map; GIS; aboveground biomass; land use policy

Link:
https://onlinelibrary.wiley.com/doi/abs/10.1002/geo2.45

Artigo de Pesquisa | Acesso aberto | 9 Impacts of climate change on drought: changes to drier conditions at the beginning of the crop growing season in southern Brazil

Ana Maria Heuminski de Avila, Gabriel Constantino Blain, Hilton Silveira Pinto, Regina Célia de Matos Pires, Vânia Rosa Pereira

Ano de publicação: 2017

Resumo:
The intensification of drought incidence is one of the most important threats of the 21st century with significant effects on food security. Accordingly, there is a need to improve the understanding of the regional impacts of climate change on this hazard. This study assessed long-term trends in probability-based drought indices (Standardized Precipitation Index and Standardized Evapotranspiration Index) in the State of São Paulo, Brazil. Owing to the multi-scalar nature of both indices, the analyses were performed at 1 to 12-month time scales. The indices were calculated by means of a relativist approach that allowed us to compare drought conditions from different periods. The years 1961-1990 were used as the referential period. To the authors’ best knowledge, this is the first time that such relativist approach is used in historical trend analysis. The results suggest that the evapotranspiration rates have intensified the regional drought conditions. The time scale used to calculate the indices significantly affected the outcomes of drought trend assessments. The reason behind this feature is that the significant changes in the monthly regional patterns are limited to a specific period of the year. More specifically, virtually all significant changes have been observed during the first trimester of the rainy season (October, November and December). Considering that this period corresponds to critical plant growth stages (flowering/regrowth/sprouting) of several major crops (e.g. Sugarcane and Citrus), we may conclude that these significant changes have increased the risk of crop yield reductions due to agricultural drought.

Palavras chave:
intensification of drought; drought Index; agricultural drought; crop yields

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052018000100201&lng=en&tlng=en

Artigo de Pesquisa | Acesso aberto | 4 Using the normality assumption to calculate probability‐based standardized drought indices: selection criteria with emphases on typical events

Ana Maria Heuminski de Avila, Gabriel Constantino Blain, Vânia Rosa Pereira

Ano de publicação: 2017

Resumo:
Enhancing the capability of both standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for quantifying wet and dry events under distinct climate conditions is of paramount importance. The different recommendations of recent studies regarding the best distribution to calculate the SPEI and the lack of studies addressing the effect of different parameters estimation methods on the SPI motivated us to apply and adapt distinct testing methodologies to select candidate models for calculating these standardized drought indices (SDI). The study is based on two data sets. The first represents a tropical–subtropical region of Brazil. The second comprises the same weather stations that were used for developing the original version of the SPEI. The study also emphasized the performance of the models within the range of typical SDI values [−2.0 : 2.0]. Along with goodness‐of‐fit tests, we calculated the mean absolute errors between the indices values estimated from the candidate distributions, and their corresponding theoretical values derived from the standard normal distribution. The two‐parameter gamma and the generalized extreme value distributions are, respectively, recommended for general use in SPI and SPEI algorithms (1–12‐month timescales). The unbiased probability weighted moments are recommended to estimate the distributions parameters. The study also described a trade‐off between choosing the best model for the central part and for the tails of the distributions. This trade‐off suggests that the methodologies used to select models for the SDI algorithms may have to decide which part of the distribution (central or tails) should be emphasized. The behaviour of the errors among different wet/dry categories showed that both indices were only capable of representing drought and floods in a similar probabilistic way within the range [−2.0 : 2.0]. This feature supports our decision to emphasize model performances within such range.

Palavras chave:
drought; standardized precipitation index; standardized precipitation evapotranspiration index; trade-off; param-eter estimation

Link:
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.5381




Publicações 2016
Artigo de Pesquisa | Acesso aberto | 2 Amazon Forest Ecosystem Responses to Elevated Atmospheric CO2 and Alterations in Nutrient Availability: Filling the Gaps with Model-Experiment Integration

David Montenegro Lapola

Ano de publicação: 2016

Resumo:
The impacts of elevated atmospheric CO2 (eCO2) and alterations in nutrient availability on the carbon (C) storage capacity and resilience of the Amazon forest remain highly uncertain. Carbon dynamics are controlled by multiple eco-physiological processes responding to environmental change, but we lack solid experimental evidence, hampering theory development and thus representation in ecosystem models. Here, we present two ecosystem-scale manipulation experiments, to be carried out in the Amazon, that examine tropical ecosystem responses to eCO2 and alterations in nutrient availability and thus will elucidate the representation of crucial ecological processes by ecosystem models. We highlight current gaps in our understanding of tropical ecosystem responses to projected global changes in light of the eco-physiological assumptions considered by current ecosystem models. We conclude that a more detailed process-based representation of the spatial (e.g., soil type; plant functional type) and temporal (seasonal and inter-annual) variability of tropical forests is needed to enhance model predictions of ecosystem responses to projected global environmental change.

Palavras chave:
Amazon, carbon allocation, elevated CO2, free-air CO2 enrichment (FACE), nutrient addition, tropical forest

Link:
https://www.frontiersin.org/articles/10.3389/feart.2016.00019/full

Artigo de Pesquisa | Acesso aberto | 1 Model–data synthesis for the next generation of forest free‐air CO2 enrichment (FACE) experiment

David Montenegro Lapola

Ano de publicação: 2016

Resumo:
The first generation of forest free‐air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR‐FACE in a 150‐yr‐old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model–data interaction as an integral part of experimental design and to address a set of cross‐site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.

Palavras chave:
biodiversity; climate; elevated CO2;  forest; free‐air CO2 enrichment(FACE); model–data synthesis; nitrogen (N); phosphorus (P)

Link:
https://nph.onlinelibrary.wiley.com/doi/abs/10.1111/nph.13593

Artigo de Pesquisa | Acesso aberto Operationalizing payments for ecosystem services in Brazil

David Montenegro Lapola

Ano de publicação: 2016

Resumo:
In this paper the initial draft design of a payment for ecosystem services (PES) scheme in a municipality within the sugarcane belt of São Paulo state, Brazil (PES-RC), is compared with prevailing characteristics of successful PES cases in Latin America (PES-LA). This systematic comparison is performed by analyzing four major characteristics of PES: identity of traded ecosystem service (ES); spatial scale; type of transaction involved between ES providers and beneficiaries; and the involved actors. Information on the biophysical characteristics, institutional arrangement and financial options of PES-RC were assessed using participatory methods. We found that on the one hand there is an agreement between our case study and the prevailing successful cases of PES-LA regarding the traded ES (water) and the PES spatial scale (local). However, stakeholder opinions diverge from the success cases when it comes to the type of transaction (cash preferred in PES-RC; in-kind in successful PES-LA) and the involved actors. Our results raise the question whether stakeholder opinions or the characteristics of successful (or failure) cases should be prioritized when planning and operationalizing new PES schemes. We argue that stakeholder participation should be considered as an additional success criterion for the construction of public policies directed towards PES implementation.

Palavras chave:
Atlantic ForestBrazilian Forest CodeNature conservationPublic policiesRio Claro - SP municipalityParticipatory methods

Link:
https://www.sciencedirect.com/science/article/pii/S2212041616301176?via%3Dihub

Artigo de Pesquisa | Acesso aberto | 2 Socio-climatic hotspots in Brazil: how do changes driven by the new set of IPCC climatic projections affect their relevance for policy?

David Montenegro Lapola

Ano de publicação: 2016

Resumo:
This paper updates the SCVI (Socio-Climatic Vulnerability Index) maps developed by Torres et al. (2012) for Brazil, by using the new Coupled Model Intercomparison Project Phase 5 (CMIP5) projections and more recent 2010 social indicators data. The updated maps differ significantly from their earlier versions in two main ways. First, they show that heavily populated metropolitan areas – namely Belo Horizonte, Brasília, Salvador, Manaus, Rio de Janeiro and São Paulo – and a large swath of land across the states of São Paulo, Minas Gerais and Bahia now have the highest SCVI values, that is, their populations are the most vulnerable to climate change in the country. Second, SCVI values for Northeast Brazil are considerably lower compared to the previous index version. An analysis of the causes of such difference reveals that changes in climate projections between CMIP3 and CMIP5 are responsible for most of the change between the different SCVI values and spatial distribution, while changes in social indicators have less influence, despite recent countrywide improvements in social indicators as a result of aggressive anti-poverty programs. These results raise the hypothesis that social reform alone may not be enough to decrease people’s vulnerability to future climatic changes. Whereas the coarse spatial resolution and relatively simplistic formulation of the SCVI may limit how useful these maps are at informing decision-making at the local level, they can provide a valuable input for large-scale policies on climate change adaptation such as those of the Brazilian National Policy on Climate Change Adaptation.

Palavras chave:
Adaptive Capacity Social Indicator Climate Change Adaptation Climate Projection Social Vulnerability 

Link:
https://link.springer.com/article/10.1007%2Fs10584-016-1635-z




Publicações 2015
Artigo de Pesquisa | Acesso aberto | 6 Changes in soil carbon, nitrogen, and phosphorus due to land-use changes in Brazil

Hilton Silveira Pinto

Ano de publicação: 2015

Resumo:
In this paper, soil carbon, nitrogen and phosphorus concentrations and stocks were investigated in agricultural and natural areas in 17 plot-level paired sites and in a regional survey encompassing more than 100 pasture soils In the paired sites, elemental soil concentrations and stocks were determined in native vegetation (forests and savannas), pastures and crop–livestock systems (CPSs). Nutrient stocks were calculated for the soil depth intervals 0–10, 0–30, and 0–60 cm for the paired sites and 0–10, and 0–30 cm for the pasture regional survey by sum stocks obtained in each sampling intervals (0–5, 5–10, 10–20, 20–30, 30–40, 40–60 cm). Overall, there were significant differences in soil element concentrations and ratios between different land uses, especially in the surface soil layers.

Palavras chave:
soil carbon; nitrogen; phosphorus

Link:
https://www.biogeosciences.net/12/4765/2015/bg-12-4765-2015.pdf

Artigo de Pesquisa | Acesso aberto | 1 Empirical models to predict LAI and aboveground biomass of Coffea arabica under full sun and shaded plantation: a case study of South of Minas Gerais, Brazil

Priscila Pereira Coltri, Hilton Silveira Pinto, Jurandir Zullo Junior

Ano de publicação: 2015

Resumo:
Leaf area index (LAI) and above ground biomass (AGB) are two parameters that are difficult to measure but very useful. In this paper we investigated the relationship between coffee biophysical properties and LAI and AGB in two coffee production systems: full sun (FS) and shaded with macadamia nuts (SH). The paper proposes an empirical relationship for calculating coffee AGB and coffee LAI which avoids destructive methods, using simple field measurements and agrometeorological data. Here, we reported that LAI is related to canopy structure but subject to strong seasonal variations, which can be identified using water requirements satisfaction index (WRSI). Coffee LAI answers to the decreased WRSI with 1 month lag (WRSI-1) and LAI values decreases more for FS systems than for SH systems during dry periods. The best empirical model to predict LAI for FS coffee production system was based on canopy height (ch) and WRSI-1 value. For SH systems, the best model used ch, WRSI-1 and the height of the first pair of branches. Coffee AGB values were measured using destructive analyses and an empirical equation was developed. Both coffee production systems stocked carbon, whereas the SH system stocked an increased carbon amount provided by the macadamia trees that contributed with 15 % of the total carbon above ground. Both systems can be considered mitigation techniques since they are able to remove atmospheric carbon and stock it in the biomass, which has been largely proposed as a compensation mechanism for greenhouse gas emissions.

Palavras chave:
Carbon stock; Coffee shaded system; Empirical equations; Seasonal LAI variation 

Link:
https://link.springer.com/article/10.1007%2Fs10457-015-9799-5




Publicações 2014
Artigo de Pesquisa | Acesso aberto | 2 Annual maximum daily rainfall trends in the Midwest, southeast and southern Brazil in the last 71 years

Eduardo Delgado Assad, Hilton Silveira Pinto

Ano de publicação: 2014

Resumo:
The aim of this study was to model, based on the overall distribution of extreme values, the probability of occurrence of a particular level of annual maximum daily rainfall in three Brazilian regions (Midwest, Southeast and South) and study their behavior over the past 71 years. The parameters of the general distribution of extreme values were estimated by the maximum likelihood method. The Mann–Kendall test showed that there is a positive trend in the annual maximum daily rainfall data series. The non-stationarity was rejected by the augmented Dickey–Fuller test supporting the use of the density function of extreme value distribution to describe the values of the occurrence of annual maximum daily rainfall. The Kolmogorov–Smirnov/Lilliefors goodness-of-fit test showed the good fit of the studied variable to the probability distribution function. The Midwest region has a return period of more frequent annual maximum daily rainfall below 300 mm in comparison with other regions. There is a clear change in the behavior of this extreme event in the Southern region. According to the literature, in past decades annual maximum daily rainfall of 248 mm has been estimated for a return period of 100 years for the state of Santa Catarina-South region, while the results found with the current series, annual maximum daily rainfall of 250 mm was estimated for a return period of 10 years. Extreme annual maximum daily rainfalls for return periods smaller were also found in other regions.

Palavras chave:
Climate changeClimate periodRainfall variability

Link:
https://www.sciencedirect.com/science/article/pii/S2212094714000802?via%3Dihub

Artigo de Pesquisa | Acesso aberto | 3 Collaborative Innovation in Agrometeorology: Coordination Strategies to Develop a Monitoring IT System for Brazil

Martha Delphino Bambini, Andre Tosi Furtado, Jurandir Zullo Junior, Priscila Pereira Coltri

Ano de publicação: 2014

Resumo:
This case-study article presents the results from a morphology analysis of a knowledge and information network, focusing on the coordination mechanisms employed to generate a convergent arrangement. Agritempo was the first information system to offer (in 2003) free access to a broad range of agrometeorological data comprising all the Brazilian territory, representing an important technological innovation to the agricultural sector. To study this phenomenon an analytical framework of the Techno-Economic Network (TEN) and concepts from the Innovation Sociology field was employed. Results indicate that the durability of this arrangement - from 2003 to 2014 - can be explained by the effectiveness of the coordination strategies established in the network such as: trust based relationships; institutional and individual leadership actions; contracting; software applications and shared common working procedures.

Palavras chave:
techno-economics networks; innovation; agrometeorology; information and communication technology.

Link:
https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-27242014000100010&lng=en&nrm=iso&tlng=en

Artigo de Pesquisa | Acesso aberto QuMinS: Fast and scalable querying, mining and summarizing multi-modal databases

Luciana Alvim Santos Romani, Priscila Pereira Coltri

Ano de publicação: 2014

Resumo:
Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top- outlier images, and the  images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

Palavras chave:
Low-labor labelingSummarizationOutlier detectionQuery by exampleClusteringSatellite imagery

Link:
https://www.sciencedirect.com/science/article/pii/S0020025513008001?via%3Dihub




Publicações 2013
Artigo de Pesquisa | Acesso aberto | 1 A New Time Series Mining Approach Applied to Multitemporal Remote Sensing Imagery

Luciana Alvim Santos Romani, Ana Maria Heuminski de Avila, Jurandir Zullo Junior

Ano de publicação: 2013

Resumo:
In this paper, we present a novel unsupervised algorithm, called CLimate and rEmote sensing Association patteRns Miner, for mining association patterns on heterogeneous time series from climate and remote sensing data integrated in a remote sensing information system developed to improve the monitoring of sugar cane fields. The system, called RemoteAgri, consists of a large database of climate data and low-resolution remote sensing images, an image preprocessing module, a time series extraction module, and time series mining methods. The preprocessing module was projected to perform accurate geometric correction, what is a requirement particularly for land and agriculture applications of satellite images. The time series extraction is accomplished through a graphical interface that allows easy interaction and high flexibility to users. The time series mining method transforms series to symbolic representation in order to identify patterns in a multitemporal satellite images and associate them with patterns in other series within a temporal sliding window. The validation process was achieved with agroclimatic data and NOAA-AVHRR images of sugar cane fields. Results show a correlation between agroclimatic time series and vegetation index images. Rules generated by our new algorithm show the association patterns in different periods of time in each time series, pointing to a time delay between the occurrences of patterns in the series analyzed, corroborating what specialists usually forecast without having the burden of dealing with many data charts

Palavras chave:
Time series analysis, Data mining, Remote sensing, Meteorology, Indexes, Satellites, Agriculture

Link:
http://ieeexplore.ieee.org/document/6215038/

Artigo de Pesquisa | Acesso aberto Changes in soil carbon stocks in Brazil due to land use: paired site comparisons and a regional pasture soil survey

Eduardo Delgado Assad, Hilton Silveira Pinto

Ano de publicação: 2013

Resumo:
In this paper we calculated soil carbon stocks in Brazil studying 17 paired sites where soil stocks were determined in native vegetation, pastures and crop-livestock systems (CPS), and in other regional samplings encompassing more than 100 pasture soils, from 6.58 to 31.53° S, involving three major Brazilian biomes: Cerrado, Atlantic Forest, and the Pampa. The average native vegetation soil carbon stocks at 10, 30 and 60 cm soil depth were equal to approximately 29, 64, and 92 Mg ha−1, respectively. In the paired sites, carbon losses of 7.5 Mg ha−1 and 11.6 Mg ha−1 in CPS systems were observed at 10 cm and 30 cm soil depths, respectively. In pasture soils, carbon losses were similar and equal to 7.5 Mg ha−1 and 11.0 Mg ha−1 at 10 cm and 30 cm soil depths, respectively. Differences at 60 cm soil depth were not significantly different between land uses. The average soil δ13C under native vegetation at 10 and 30 cm depth were equal to −25.4‰ and −24.0‰, increasing to −19.6‰ and −17.7‰ in CPS, and to −18.9‰, and −18.3‰ in pasture soils, respectively; indicating an increasing contribution of C4 carbon in these agrosystems. In the regional survey of pasture soils, the soil carbon stock at 30 cm was equal to approximately 51 Mg ha−1, with an average δ13C value of −19.67‰. Key controllers of soil carbon stock in pasture sites were sand content and mean annual temperature. Collectively, both could explain approximately half of the variance of soil carbon stocks. When pasture soil carbon stocks were compared with the average soil carbon stocks of native vegetation estimated for Brazilian biomes and soil types by Bernoux et al. (2002) there was a carbon gain of 6.7 Mg ha−1, which is equivalent to a carbon gain of 15% compared to the carbon soil stock of the native vegetation. The findings of this study are consistent with differences found between regional comparisons like our pasture sites and plot-level paired study sites in estimating soil carbon stocks changes due to land use changes.

Palavras chave:
carbon stocks

Link:
https://www.biogeosciences.net/10/6141/2013/

Artigo de Pesquisa | Acesso aberto | 1 Coffee Crop's Biomass and Carbon Stock Estimation With Usage of High Resolution Satellites Images

Priscila Pereira Coltri, Hilton Silveira Pinto, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Renata Ribeiro do Valle Gonçalves

Ano de publicação: 2013

Resumo:
Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee's biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created.

Palavras chave:
Correlation, Biomass, Vegetation mapping, Carbon, Indexes, Remote sensing, Agriculture

Link:
http://ieeexplore.ieee.org/document/6520004/

Artigo de Pesquisa | Acesso aberto | 1 Estimation of dry spells in three Brazilian regions — Analysis of extremes

Eduardo Delgado Assad, Hilton Silveira Pinto

Ano de publicação: 2013

Resumo:
The aim of this study was to model the occurrence of extreme dry spells in the Midwest, Southeast and Southern regions of Brazil and estimate the return period of the phenomenon indicating the time when the occurrence is more severe. The generalized extreme value distribution was the best fit for a series of maximum dry spell number and the parameters estimated by the maximum likelihood method. The data series adherence to the probability distribution was verified by the Kolmogorov–Smirnov test and the percentile–percentile charts. The positive trend of dry spells was verified by the Mann–Kendall test and non-stationarity rejected by Dickey–Fuller and augmented Dickey–Fuller tests. The irregular distribution of rainfall in the growing season for the Midwest region has increased the number of dry spells. The increase of rainy days in the Southeast and the South resulted in a decrease of dry spells in these regions. Regarding the return period of one year, dry spells occurred from 5 to 25 days in the Midwest region meaning a loss of productivity for Brazilian agriculture if it happened between the flowering and grain filling phases, making it, therefore the region with the largest agricultural risk. When the intensity of the dry spells was analyzed for different return periods, the Southern region was the most vulnerable.

Palavras chave:
Dry spellsGeneralized extreme value distributionNumber of rainy daysReturn period

Link:
https://www.sciencedirect.com/science/article/pii/S016980951300118X?via%3Dihub

Artigo de Pesquisa | Acesso aberto Impacts of climate change on the agricultural zoning of climate risk for cotton cultivation in Brazil

Eduardo Delgado Assad, Hilton Silveira Pinto

Ano de publicação: 2013

Resumo:
The objective of this work was to evaluate the effect of the temperature increase forecasted by the Intergovernmental Panel on Climate Change (IPCC) on agricultural zoning of cotton production in Brazil. The Northeastern region showed the highest decrease in the low-risk area for cotton cultivation due to the projected temperature increase. This area in the Brazilian Northeast may decrease from 83 million ha in 2010 to approximately 71 million ha in 2040, which means 15% reduction in 30 years. Southeastern and Center-Western regions had small decrease in areas suitable for cotton production until 2040, while the Northern region showed no reduction in these areas. Temperature increase will not benefit cotton cultivation in Brazil because dimension of low-risk areas for economic cotton production may decrease.

Palavras chave:
Gossypium hirsutum, evapotranspiration, global warming

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2013000100001&lng=en&tlng=en




Publicações 2012
Artigo de Pesquisa | Acesso aberto Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Renata Ribeiro do Valle Gonçalves, Agma Juci Machado Traina, Cristina R. Nascimento, Jurandir Zullo Junior, Luciana Alvim Santos Romani

Ano de publicação: 2012

Resumo:
Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international marketplaces. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Palavras chave:
Sugarcane

Link:
https://www.tandfonline.com/doi/full/10.1080/01431161.2011.638334




Publicações 2011
Artigo de Pesquisa | Acesso aberto | 3 Análise comparativa do clima atual e futuro para avaliar a expansão da cana-de-açúcar em São Paulo

Renata Ribeiro do Valle Gonçalves, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Priscila Pereira Coltri

Ano de publicação: 2011

Resumo:
O Brasil, o maior produtor mundial de cana-de-açúcar, é responsável por 35% da produção mundial. A produção de cana-de-açúcar se concentra nas regiões Centro-Sul e Nordeste e ocupa cerca de 8 milhões de hectares. A cana-de-açúcar, por apresentar um ciclo semi-perene, é influenciada pela variação das condições meteorológicas durante um ano inteiro. O objetivo do trabalho foi analisar os dados climáticos obtidos pelo modelo Eta (2011 a 2090) e os dados do clima atual (1991 a 2010) verificando suas implicações em relação a expansão da cana-de-açúcar no estado de São Paulo. Foram utilizados dados de precipitação e temperatura média, de 1991 a 2010, de estações meteorológicas de seis municípios de São Paulo. Para representar o cenário futuro (2011 a 2090), foram utilizados dados de precipitação e temperatura média obtidos pelo modelo Eta. A partir do balanço hídrico foi possível calcular a deficiência hídrica e o excedente hídrico para os municípios selecionados com armazenamento de água disponível no solo de 100mm. O balanço hídrico mostrou que haverá um aumento na deficiência hídrica. Com o aumento do período seco e do aumento da temperatura média poderá ocorrer uma queda na produtividade de sacarose da cana-de-açúcar.

Palavras chave:
water balance, Eta model, mean temperature

Download
analise-comparativa-do-clima-atual-e-futuro-para-avaliar-a-expansao-da-cana-de-acucar-em-sao-paulo-02061715.pdf

Link:
http://www.cpa.unicamp.br/alcscens/docs/publicacoes/Analise%20comparativa%20do%20clima%20atual%20e%20futuro%20para%20avaliar%20a%20expansao%20da%20cana-de-acucar%20em%20Sao%20Paulo%20.pdf

Artigo de Pesquisa | Acesso aberto Análise dos dados de projeção climática do modelo Eta e suas implicações para a cultura do Café arábica

Priscila Pereira Coltri, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani, Renata Ribeiro do Valle Gonçalves

Ano de publicação: 2011

Resumo:
Extremos de temperatura durante a fase do florescimento do café arábica causam abortamento de flores e perda na produção. Estudos de projeção climática, normalmente baseados em modelos de baixa resolução, já demonstram perdas na produção de café como conseqüência das altas temperaturas. No entanto, esses estudos têm uma menor precisão nas respostas por causa da resolução dos modelos, e novos estudos baseados em modelos de melhor resolução se tornam necessários. Este trabalho apresenta uma análise das implicações dos extremos de temperatura e precipitação na aptidão climática em municípios tradicionalmente produtores de café em Minas Gerais e São Paulo, utilizando o modelo climático Eta (40km de resolução). Primeiramente, as respostas do modelo foram comparadas com os dados climáticos atuais (dados observados). As projeções do modelo Eta foram satisfatórias porque seguem o padrão do clima já existente. Os dados do modelo demonstram um deslocamento do maior déficit hídrico do ano para o mês de setembro. O modelo projeta cenários com aumento de temperaturas, principalmente nos meses de setembro e outubro, que é o florescimento do café, impactando a produção de café arábica.

Palavras chave:
Aptidão climática, Café arábica, Eta

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analise-dos-dados-de-projecao-climatica-do-modelo-eta-e-suas-implicacoes-para-a-cultura-do-cafe-arabica-02061715.pdf
Artigo de Pesquisa | Acesso aberto | 2 Análise temporal de municípios produtores de cana-de-açúcar no estado de São Paulo por meio de agrupamento do NDVI (AVHRR/NOAA) e dados de produtividade e área

Renata Ribeiro do Valle Gonçalves, Agma Juci Machado Traina, Ana Maria Heuminski de Avila, Jurandir Zullo Junior, Luciana Alvim Santos Romani

Ano de publicação: 2011

Resumo:
O objetivo deste trabalho foi detectar municípios produtores de cana-de-açúcar no estado de São Paulo, similares, pelo método de agrupamento, analisando variáveis espectrais (NDVI), área plantada e produtividade no período de 2001 a 2009. O resultado dessa análise exploratória dos dados mostrou que a técnica é apropriada para a determinação de grupos de municípios com características semelhantes o que permite classificar as regiões automaticamente.

Palavras chave:
remote sensing, K-means biofuel

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analise-temporal-de-municipios-produtores-cana-de-acucar-no-estado-de-sao-paulo-02061715.pdf
Artigo de Pesquisa | Acesso aberto | 1 Incubation period of Hemileia vastatrix in coffee plants in Brazil simulated under climate change

Renata Ribeiro do Valle Gonçalves

Ano de publicação: 2011

Resumo:
Risk analysis of climate change on plant diseases has great importance for agriculture since it allows the evaluation of management strategies to minimize future damages. This work aimed to simulate future scenarios of coffee rust (Hemileia vastatrix) epidemics by elaborating geographic distribution maps using a model that estimates the pathogen incubation period and the output from three General Circulation Models (CSIRO-Mk3.0, INM-CM3.0, and MIROC3.2.medres). The climatological normal from 1961-1990 was compared with that of the decades 2020s, 2050s and 2080s using scenarios A2 and B1 from the IPCC. Maps were prepared with a spatial resolution of 0.5 × 0.5 degrees of latitude and longitude for ten producing states in Brazil. The climate variables used were maximum and minimum monthly temperatures. The maps obtained in scenario A2 showed a tendency towards a reduction in the incubation period when future scenarios are compared with the climatological normal from 1961-1990. A reduction in the period was also observed in scenario B1, although smaller than that in scenario A2.

Palavras chave:
Coffea arabica, coffee rust, future scenarios, global warming

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-54052011000200001&lng=en&tlng=en

Artigo de Pesquisa | Acesso aberto Potential for growing Arabica coffee in the extreme south of Brazil in a warmer world

Jurandir Zullo Junior, Ana Maria Heuminski de Avila, Eduardo Delgado Assad, Hilton Silveira Pinto

Ano de publicação: 2011

Resumo:
Agriculture appears to be one of the human activities most vulnerable to climatic changes due to its large dependence on environmental conditions. However, the diversity of Brazilian environmental conditions could be of great advantage to adapting this sector to new climatic conditions, which should be assessed as in this study on shifting Arabica coffee cultivation to the extreme south of the country. The methodology applied is the same the one used to define climatic risks in current productive regions of Brazil and their vulnerability to climatic change predicted by IPCC reports. The basic climatic parameters applied were frost probability and annual average temperature, since annual water deficit did not prove to be a restricting factor for Arabica coffee cultivation in the study area. The climatic conditions suitable for coffee production are: annual average temperature between 18°C and 22°C, annual water deficit less than 100 mm and frost probability (risk of lowest annual temperature less than 1°C) less than 25%. An area is said to have “low climatic risks” for coffee production when these three climatic conditions are met. Current climatic conditions were used and simulations of four temperature increases between 1°C and 4°C were also performed. The results indicated a substantial increase in the size of low climatic risks areas for the production of Arabica coffee in the extreme south of Brazil, mainly for mean temperature increases of 3°C in the study area in relation to present conditions. Increases of 2°C and 4°C were also favorable, but not as good as those obtained for 3°C. It should be underscored that areas with low climatic risks will be able to be found mainly in the extreme south of the study region, the border with Uruguay and North of Argentina.

Palavras chave:
Global Warming; Climatic Risk; Coffee Production; Current Climatic Condition; Arabica Coffee 

Link:
https://link.springer.com/article/10.1007%2Fs10584-011-0058-0




Publicações 2010
Artigo de Pesquisa | Acesso aberto | 1 Estimativa de ocorrência de precipitação em áreas agrícolas utilizando floresta de caminhos ótimos

Greice Martins de Freitas, Alexandre Xavier Falcão, Ana Maria Heuminski de Avila, Hilton Silveira Pinto, João Paulo Papa

Ano de publicação: 2010

Resumo:
As condições meteorológicas são determinantes para a produção agrícola; a precipitação, em particular, pode ser citada como a mais influente por sua relação direta com o balanço hídrico. Neste sentido, modelos agrometeorológicos, os quais se baseiam nas respostas das culturas às condições meteorológicas, vêm sendo cada vez mais utilizados para a estimativa de rendimentos agrícolas. Devido às dificuldades de obtenção de dados para abastecer tais modelos, métodos de estimativa de precipitação utilizando imagens dos canais espectrais dos satélites meteorológicos têm sido empregados para esta finalidade. O presente trabalho tem por objetivo utilizar o classificador de padrões "floresta de caminhos ótimos" para correlacionar informações disponíveis no canal espectral infravermelho do satélite meteorológico GOES-12 com a refletividade obtida pelo radar do IPMET/UNESP localizado no município de Bauru, visando o desenvolvimento de um modelo para a detecção de ocorrência de precipitação. Nos experimentos foram comparados quatro algoritmos de classificação: redes neurais artificiais (ANN), k-vizinhos mais próximos (k-NN), máquinas de vetores de suporte (SVM) e floresta de caminhos ótimos (OPF). Este último obteve melhor resultado, tanto em eficiência quanto em precisão.

Palavras chave:
Classificadores Supervisionados, Floresta de Caminhos Ótimos, GOES, Estimativa de Ocorrência de Precipitação

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862010000100002&lng=pt&tlng=pt

Artigo de Pesquisa | Acesso aberto | 1 Extended time weather forecasts contributes to agricultural productivity estimates

Andrea de Oliveira Cardoso, Ana Maria Heuminski de Avila, Hilton Silveira Pinto, Pedro Leite da Silva Dias

Ano de publicação: 2010

Resumo:
Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Paraná, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

Palavras chave:
Weather Forecast; Productivity Estimate; Ensemble Forecast; Forecast Period; Crop Cycle 

Link:
https://link.springer.com/article/10.1007%2Fs00704-010-0264-0

Artigo de Pesquisa | Acesso aberto Impacto da correção atmosférica de imagens AVHRR/NOAA-17 no cálculo do índice de vegetação NDVI

Cristina Rodrigues Nascimento, Jurandir Zullo Junior

Ano de publicação: 2010

Resumo:
Para obter a refletância real da superfície, nas bandas 1 e 2 do sensor AVHRR, foi realizada a correção atmosférica, baseada na entrada dos parâmetros atmosféricos fornecidos pelo sensor MODIS/Terra. A utilização de dados do MODIS está diretamente relacionada à obtenção das informações, necessárias para a correção atmosférica, considerando-se a variabilidade dos parâmetros no tempo e no espaço. Utilizando-se o aplicativo SCORADIS, baseado no modelo de transferência radiativa 5S, foi proposta uma adaptação que possibilitasse a entrada das imagens correspondentes aos planos atmosféricos, através da utilização de metodologias distintas de correção atmosférica. As análises indicaram que as correções apresentaram resultados coerentes com eliminação dos efeitos de espalhamento e de absorção atmosférica. Foi avaliada a magnitude desses efeitos sobre o índice de vegetação NDVI, muito utilizado em estudos agrometeorológicos. A diferença percentual entre as imagens com e sem correção chegou a ser de aproximadamente 60 a 80% para as datas analisadas, ressaltando a importância da correção atmosférica dessas imagens.

Palavras chave:
efeitos atmosféricos, SCORADIS, MODIS

Link:
http://www.agraria.pro.br/ojs-2.4.6/index.php?journal=agraria&page=article&op=view&path%5B%5D=agraria_v5i2a530




Publicações 2009
Artigo de Pesquisa | Acesso aberto Robust Pruning of Training Patterns for Optimum-Path Forest Classification Applied to Satellite-Based Rainfall Occurrence Estimation

João Paulo Papa, Alexandre Xavier Falcão, Ana Maria Heuminski de Avila, Greice Martins de Freitas

Ano de publicação: 2009

Resumo:
The decision correctness in expert systems strongly depends on the accuracy of a pattern classifier, whose learning is performed from labeled training samples. Some systems, however, have to manage, store, and process a large amount of data, making also the computational efficiency of the classifier an important requirement. Examples are expert systems based on image analysis for medical diagnosis and weather forecasting. The learning time of any pattern classifier increases with the training set size, and this might be necessary to improve accuracy. However, the problem is more critical for some popular methods, such as artificial neural networks and support vector machines (SVM), than for a recently proposed approach, the optimum-path forest (OPF) classifier. In this letter, we go beyond by presenting a robust approach to reduce the training set size and still preserve good accuracy in OPF classification. We validate the method using some data sets and for rainfall occurrence estimation based on satellite image analysis. The experiments use SVM and OPF without pruning of training patterns as baselines.

Palavras chave:
Robustness, Management training, Support vector machines, Support vector machine classification, Image analysis, Expert systems, Computational efficiency, Medical expert systems, Diagnostic expert systems, Medical diagnosis

Link:
http://ieeexplore.ieee.org/document/5357415/




Publicações 2008
Artigo de Pesquisa | Acesso aberto Análise de risco das mudanças climáticas globais sobre a sigatoka-negra da bananeira no Brasil

Raquel Ghini, Emília Hamada, José Clério R. Pereira, Luadir Gasparotto, Renata Ribeiro do Valle Gonçalves

Ano de publicação: 2008

Resumo:
O conhecimento dos prováveis impactos das mudanças climáticas globais sobre a ocorrência de doenças de plantas é de grande importância para o setor agrícola, pois permite a elaboração de estratégias de controle. O presente trabalho teve por finalidade estudar os possíveis impactos das mudanças climáticas sobre a sigatoka-negra da bananeira, por meio da elaboração de mapas de distribuição da doença confeccionados a partir dos cenários disponibilizados pelo IPCC. Os mapas mostraram que haverá redução da área favorável à doença no país. Tal redução será gradativa para as décadas de 2020, 2050 e 2080 e de forma mais acentuada no cenário A2 que no B2. Apesar disso, extensas áreas ainda continuarão favoráveis à ocorrência da doença, especialmente no período de novembro a abril.

Palavras chave:
Mycosphaerella fijiensis, Musa spp., banana, plátano

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-41582007000300003&lng=pt&tlng=pt

Artigo de Pesquisa | Acesso aberto Relação entre a resposta espectral da cana-de-açúcar, registrada em série temporal de imagens do satélite AVHRR/NOAA, e condições agroclimáticas descritas pelo índice ISNA

Renata Ribeiro do Valle Gonçalves, Jurandir Zullo Junior

Ano de publicação: 2008

Resumo:
O Brasil é o maior produtor mundial de cana-de-açúcar e conta com uma posição privilegiada para atender as necessidades mundiais de açúcar e álcool combustível. O país possui várias regiões produtoras, com safras alternadas, que podem garantir a presença do seu produto no mercado mundial, sendo o Estado de São Paulo a maior delas. Para tanto, é necessário estimar a produção da cana-de-açúcar com a maior precisão e antecipação possíveis, sendo que o sensoriamento remoto pode ser de grande utilidade nesse caso, devido à maior disponibilidade atual de dados e ao conhecimento já existente na utilização deles na área ambiental. Sendo o clima um dos principais fatores determinantes da produção agrícola, o conhecimento da sua infl uência na resposta espectral da vegetação pode ser de grande utilidade no apoio ao desenvolvimento de sistemas operacionais de monitoramento e previsão de safras da cana-de-açúcar. Sendo assim, este trabalho teve o objetivo principal de avaliar o grau de correlação existente entre a resposta espectral de plantios de cana-de-açúcar, expressa através de uma série temporal de valores do Índice de Vegetação da Diferença Normalizada (NDVI), determinada a partir de imagens do satélite AVHRR/NOAA, com dados agroclimáticos, em dez municípios localizados no Estado de São Paulo, no período de 2001 a 2007. Avaliou-se a série temporal de imagens como um todo, além de cada ano-safra, em particular, considerando a maior disponibilidade atual de dados de sensoriamento remoto orbital e a variabilidade climática existente ao longo dos seis anos-safra utilizados. Os perfi s temporais do índice NDVI foram obtidos através do processamento automático das imagens disponíveis que consistiu nas correções radiométrica e geométrica e no cálculo de imagens compostas, contendo os valores máximos mensais do NDVI. Dados agroclimáticos, ao longo do período de análise, foram descritos pelo índice ISNA (Índice de Satisfação das Necessidades de Água). Para determiná-lo, fez-se o balanço hídrico e calcularam-se as evapotranspirações real e máxima nas escalas decendial, quinzenal e mensal. As análises estatísticas realizadas apresentaram correlações signifi cativas entre os dados agroclimáticos (representado pelo ISNA) e a resposta espectral da cana-de-açúcar (representada pelos valores do NDVI), sendo que os melhores resultados foram obtidos na avaliação da série temporal como um todo. Esses resultados são de grande utilidade, por exemplo, na determinação de equações de estimativa do NDVI em relação ao ISNA, e vice-versa, a serem empregadas no apoio à estimativa da produção da cana-de-açúcar no país.

Palavras chave:
Sensoriamento remoto, Series temporais, Cana-de-açucar, Agricultura, Climatologia agricola, Processamento de imagens

Link:
http://www.sbagro.org.br/rbagro/ojs/index.php/rbagro/article/view/103

Artigo de Pesquisa | Acesso aberto Risk analysis of climate change on coffee nematodes and leaf miner in Brazil

Raquel Ghini, Emília Hamada, Mário José Pedro Júnior, Renata Ribeiro do Valle Gonçalves

Ano de publicação: 2008

Resumo:
The objective of this work was to assess the potential impact of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using a Geographic Information System. Assessment of the impacts of climate change on pest infestations and disease epidemics in crops is needed as a basis for revising management practices to minimize crop losses as climatic conditions shift. Future scenarios focused on the decades of the 2020's, 2050's, and 2080's (scenarios A2 and B2) were obtained from five General Circulation Models available on Data Distribution Centre from Intergovernmental Panel on Climate Change. Geographic distribution maps were prepared using models to predict the number of generations of the nematodes and leaf miner. Maps obtained in scenario A2 allowed prediction of an increased infestation of the nematode and of the pest, due to greater number of generations per month, than occurred under the climatological normal from 1961–1990. The number of generations also increased in the B2 scenario, but was lower than in the A2 scenario for both organisms.

Palavras chave:
Coffea arabica, Leucoptera coffeella, Meloidogyne incognita, global warming, pest zoning.

Link:
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2008000200005&lng=en&tlng=en




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