Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and ...present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape complexity maps. As expected, both for the complexity patterns evaluated by CompPlex HeROI and the complexity maps generated by CompPlex Janus, the areas with vegetation located in a region of intermediate spatial heterogeneity had lower values for the He and He/Hmax measures and higher values for the LMC and SDL measurements. So, these landscape metrics were able to capture the behaviour of the patterns of different types of land use present in the study area, bringing together uses linked to vegetation with increased canopy coverage and differentiating them from urban areas and transition areas that mix different uses. Thus, the algorithms implemented in these scripts were demonstrated to be robust and capable of measuring the variability in information levels from the landscape, not only in terms of spatial datasets but also spectrally. The automation of measurement calculations, owing to informational entropy provided by these scripts, allows a quick assessment of the complexity of patterns present in a landscape, and thus, generates indicators of landscape integrity and resilience.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The objective of this work was to simulate the geographical distribution of the incubation period of coffee leaf rust in Coffea arabica, using data of two regional climate models, Eta-HadGEM2-ES and ...Eta-MIROC5. The scenario of high greenhouse gas emission (RCP 8.5 W m-2) was used for the states of Minas Gerais and São Paulo, Brazil, for current and future climate scenarios. The behavior of six different regression equations for incubation period (IP), available in the literature, was also analyzed as affected by data from the regional climate models. The results indicate the possibility of an increase in the affected area in the studied region, when the IP is less than 19 days, from 0.5% for Eta-MIROC5 to 14.2% for Eta-HadGEM2-ES. The severity of coffee leaf rust in future scenarios should increase in the hottest and wettest months of the year, extending to the driest and coldest months. The potential of rust infection is estimated differently by the studied equations. In higher temperature scenarios, the Kushalappa & Martins equation indicates a very high severity potential.
Resumo: O objetivo deste trabalho foi simular a distribuição geográfica do período de incubação da ferrugem do cafeeiro Coffea arabica, com uso de dados de dois modelos climáticos regionais, o Eta-HadGEM2-ES e o Eta-MIROC5. O cenário de alta emissão de gases de efeito estufa (RCP 8,5 W m-2) foi utilizado para os estados de Minas Gerais e São Paulo, para os cenários climáticos atual e futuro. O comportamento de seis diferentes equações de regressão do período de incubação (PI), disponíveis na literatura, também foi analisado em função dos dados dos modelos climáticos regionais. Os resultados indicam possibilidade de aumento de área afetada na região estudada, com PI inferior a 19 dias, de 0,5% para Eta-MIROC5 a 14,2% para Eta-HadGEM2-ES. A severidade da ferrugem do cafeeiro em cenários futuros deverá aumentar nos meses mais quentes e úmidos do ano, estendendo-se para os meses mais secos e frios. O potencial de infecção da ferrugem é estimado de forma diferente pelas equações estudadas. Em cenários de temperaturas mais elevadas, a equação de Kushalappa & Martins indica um potencial muito alto de severidade.
An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 ...Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.
The Brazilian sugar-energy sector (SES) is facing an increasing challenge due to the worldwide expansion of biofuel consumption as a strategy to reduce greenhouse gas emissions, making yield ...improvement and land and water availability key factors in addressing this situation. Consequently, our main aim here is to identify SES vulnerability under climate change conditions, based on the methodology used by the Agricultural Zoning of Climatic Risks (ZARC) program. We assessed changes of the sugarcane ZARC in light of the current and near-future climatic conditions given by eight general circulation models (GCM) of the 5th IPCC report and under the representative concentration pathway (RCP) 8.5. We identified a conversion of the current climatic risk levels in the Brazilian central-southern macro-region for sugarcane in future climate change scenarios, but the spatial distribution of these changes is heterogeneous. The current expansion areas located mainly in southern Goiás and northwest of São Paulo are marked by an increase in areas of low water availability in the future, while the traditional production areas, east of São Paulo, do not present this same vulnerability. Sugarcane cultivation in the south of Goiás is already occurring based on a complementary irrigation (of about 50 mm per month from April to September) to reach a yield similar to traditional areas located in São Paulo state. The development of drought-resistant cultivars based on genetic engineering and the efficiency of the irrigation systems used on a large spatial scale and also in the long term are two key points of concern in the Brazilian context of greenhouse gas emission mitigation. The challenges for the traditional production regions are related to the production system’s ability to regulate the capacity and idleness of sugarcane mills aiming to avoid current and future competition by same raw material.
It is widely accepted that fish farms (FF) have important contribution to input of nutrients into water, however fundamental knowledge regarding the influence of land use and land cover (LULC) on the ...water quality of fish farms is still lacking. The aim of this study was to assess the linkages between the LULC types and the water quality parameters in FFs. Three specific objectives were set: (1) to characterize the current water quality standards in four FFs (FF1, FF2, FF3, FF4) installed in the Ilha Solteira reservoir; (2) to delineate and analyze the LULC changes in sub-basins of tributaries where FFs are installed; (3) to elucidate the interactions between LULC and water quality in FFs. Results indicated signs of eutrophication in FF2 in both the dry and wet seasons. The mainly LULC was decrease of pasture and increase of sugarcane crops were observed in the four FFs' sub-basins between 2005 and 2018. Sugarcane land uses showed a significant positive correlation with SO4, Mg and K (r > 0.95, p < 0.005). The most likely source of these highlighted parameters may come from mineral fertilization, decomposition of the plinth in sugarcane and the application of vinasse to irrigate and fertilize crops. Concentrations of SO4, Mg and K observed in this present study do not cause direct toxic effects to Nile tilapia in fish farms. However, indirect impacts to water quality should be expected due to enhance primary production and promotes water eutrophication, as observed in FF2. Based on our results, we suggest that the criteria “basin characteristics”, including future sugarcane expansions, should be adopted to gather information in identifying areas more suitable for aquaculture parks that the Brazilian government intends to install in the large reservoirs.
•We investigated the effects of LULC on FFs.•Pastureland to sugarcane field conversion reduced the water quality.•LULC should be analyzed to identifying areas suitable for aquaculture in reservoirs
The aim of this study is to present APOIA-Aquaculture, an indicator system for assessing Best Management Practices (BMPs) in tilapia cage farming. Two specific objectives were set: (1) to detail the ...construction and operation of APOIA-Aquaculture; and (2) to attest to its analytical feasibility for BMP assessment in six fish farms selected as contrasting ventures at the Furnas and the Ilha Solteira reservoirs, important production sites in Southeastern Brazil. The proposed APOIA-Aquaculture comprises 68 integrated indicators, grouped into a set of four managerial dimensions: Spatial Organization (22 indicators), Management and Nutrition (23), Water Quality (14), and Quality of Sediment (9). The indicators were devised as to express fish farm compliance to predefined environmental standards, selected legislation requirements, and BMP effectiveness. Results of farm assessments indicate common deficiencies in the indicators of the Spatial Organization dimension, such as those related to the lack of equipment for water quality monitoring, fish cage positioning, improper storage of feed and supplements, inadequate control of fish disease symptoms, lack of appropriate records of the use of therapeutic and prophylactic products, and conflicts related to multiple water uses. In the Management and Nutrition dimension, indicators stressed the absence of biometric checks, inadequate procedures for residue disposal, and deficient control and records of fish losses (escapes). Overall, interactions were observed among indicators of the Management and Nutrition dimension and signs of deterioration in Water and Sediment Quality, as a consequence of inadequate feeding practices. Based on our results, we demonstrate the efficacy of APOIA-Aquaculture as an analytical tool for assessment of BMPs in tilapia cage farming. Aggregate information from indicators facilitates the adoption of measures to promote specific local infrastructure and monitoring needs according to proposed BMPs, towards improving the sustainability of the fish farms.
•An assessment system for aquaculture best management practices is presented.•Management performances were assessed in fish cage farms with different typologies, in contrasting contexts of large hydroelectric reservoirs.•Specific deficiencies in performance indices are related to environmental impairment and implied management recommendations.•Improved management practices can be properly reported to farmers based on the integrated assessment of indicators.
In this research, we combine data analyses with hotspots method to identify the spatio-temporal trend of São Paulo’s coffee cultivation area. Our hypothesis is that coffee cultivation area has been ...changing significantly in the study area since 1990. Therefore, the main goal of this research was to map the spatial pattern of coffee land use change. For coffee land use diagnostics, official data of cultivated area, hotspot analyses and growth rate were used. The results demonstrated that coffee cultivation area decreased and concentrated in smaller areas, which are traditionally recognized as “coffee quality regions”. The producer size analyses evidenced that, not only the localization, but also the producer profile changes as well. Smallholders increased but medium and large producers decreased significantly in the studied period. The coffee abandonment analyses demonstrated that, over the study period, 51.46% of the coffee area cultivated in the study region was abandoned.
Quantification of soil organic carbon (SOC) is a low-cost and necessary practice to meet increasing agricultural demands. Studies show that remote sensing (RS) is important for SOC prediction and its ...use has become crucial in agricultural management. In this study, a Multiple Linear Regression (MLR) model was constructed to predict SOC in a site in Piracicaba, São Paulo, Brazil. As predictor variables, we used the optical-satellite data of OLI/Landsat-8 sensor (bands 5 and 7, specifically), clay concentration, and the Normalized Difference Vegetation Index (NDVI). We collected 218 samples at the sampling points in the field to quantify clay and SOC in the laboratory as a calibration procedure. An Exposed Soil Mask (ESM) was created using the method GEOS3 technology, which showed pixels with greater variability of bare soil. The pixels were evaluated with their respective surface reflectance values obtained by the satellite sensor and their respective NDVI index values. We evaluated the model predictive performance based on the adjusted coefficient of determination (R2), the Root Mean-Squared Error (RMSE), and the Ratio of Performance to Interquartile Range (RPIQ) obtained in data validation. The MLR model presented R2 values 0.79 and 0.81 for calibration and validation, respectively. We obtained important RMSE and RPIQ values, 0.14 and 2.32, respectively. The high RPIQ indicated significative sampling distribution around the trendline. After construction, the model was applied to the C spatial distribution using the predictive variables as layers, predominant concentrations of 0.65 to 0.79 g. Kg−1 in 51 (23.4%) soil samples. The analysis presented here offer possibilities for SOC prediction using Geographic Information Systems (GIS) tools.
•Landsat bands, clay content, and NDVI showed great accuracy in estimating the soil organic carbon (SOC).•Multiple Linear Regression (MLR) model was constructed to predict SOC.•SOC spatial distribution (g. Kg −1) was observed in the study site.
After the deregulation of the sugar and alcohol sector, the decision on the location and scale of processing units was transferred to the private sector. Given the competition, the search for raw ...materials increased substantially and became the key variable in determining the viability of plants. The neoclassical microeconomics indicates that the increase in capacity is the result of a decision to maximize the outcome of firms, especially considering the industrial economies of scale. However, the theory of industrial organization, raises the possibility of the decision on the installed capacity be affected by the competitive strategy of the firm, leading to raise barriers to entry. Thus, plants located in regions with greater competition for sugarcane would work with higher levels of idle capacity, as deterrent to entry of new units. Using techniques of geo-referencing, the research shows that in the traditional sugarcane areas, the installed capacity in recent years far exceeds the availability of raw material. Thus, it is unlikely that plants installed in these regions are operating in an ìoptimalî level grinding. Gains force the hypothesis that excess capacity has the role to impose barriers to entry despite the reduced efficiency of the plants
Orientador: Luci Hidalgo Nunes
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Geociencias
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Previous issue date: 2005
Resumo: Os eventos extremos de precipitação fazem parte do ritmo climático de um lugar. Portanto, o conhecimento do comportamento das chuvas intensas é de fundamental importância para o planejamento do uso e ocupação da terra de forma a prevenir os impactos associados a esses episódios. Este trabalho teve como foco o estudo da variabilidade da precipitação na Região Metropolitana de Campinas (RMC), com ênfase nas chuvas extremas, que trazem maiores impactos para a sociedade e para os processos físicos do local. Dados de precipitação da série temporal de 1959/60 a 1998/99 foram analisados nos níveis decadal, anual, mensal e diário, para 11 postos distribuídos heterogeneamente na RMC. Através de informações pesquisadas em órgãos de imprensa, três episódios com montantes extremos e registrados em décadas distintas foram relacionados aos problemas decorrentes. A década de 1980 configurou-se como a mais chuvosa no período analisado, destacando-se o ano de 1982/83 como o ano com maiores totais, fato relacionado à atuação do El Niño. Também nas décadas mais recentes, 1980 e 1990, houve elevação no volume de chuvas intensas (a partir de 50mm/24h.) em relação às décadas anteriores. Observou-se que os impactos deflagrados pelos eventos extremos de precipitação na RMC são causados, principalmente, pelo uso e ocupação inadequados da terra oriundos do rápido crescimento verificado na região associado à falta de planejamento urbano
Abstract: The extreme rainfall events are part of the climatic rhythm of a place. Therefore, the knowledge on how intense rains work is fundamental for planning the use and occupation of the land, so as to prevent the impacts associated to such episodes. This dissertation focuses on the study of rainfall variability in the Metropolitan Area of Campinas, emphasizing the extreme rains, which cause broader impacts in the society and in the physical processes of the place. Rainfall data of the temporal series from the year 1959 60 to 1998 99 were analyzed in the levels of decade, year, month and day, considering the 11 stations distributed heterogeneously in the Metropolitan Area of Campinas. By analyzing the information extracted from press agencies, three episodes with extreme amounts, registered in distinct decades, were related to the deriving problems. In the analyzed period, the decade of 1980 is the most rainy, mainly the year of 1982 83, with the larger amounts, which are related to the performance of El Niño. Yet in the recent decades, 1980 and 1990, there has been elevation in the intense rains volume (from 50,0mm 24h) in relation to the two previous decades. It was observed that the impacts occasioned by the extreme rainfall events in the Metropolitan Area of Campinas are caused, mainly, by the inadequate use and occupation of land, due to both the fast growing verified in the area and the lack of urban planning
Mestrado
Análise Ambiental e Dinâmica Territorial
Geografia
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