Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Spatial statistics applied to soybean production data from Paraná State for 2003-04 to 2009-10 crop-years

In the current study, we performed a soybean production spatial distribution analysis in Paraná State. Seven crop-year data, from 2003-04 to 2009-10, obtained from the Paraná Department of Agriculture and Supply (SEAB) were used to develop a Boxmap for each crop-year, show soybean production throughout this time interval. Moran's index was used to measure spatial autocorrelation among municipalities at an aggregate level, while LISA index local correlation. For each index, different contiguity matrix and order were used and there was a significance level study. As a result, we have showed spatial relationship among cities regarding the production, which allowed the indication of high and low production clusters. Finally, identifying main soybean-producing cities, what may provide supply chain members with information to strengthen the crop production in Paraná.

Spatial influence of physical and chemical parameters on management zone definition in apple orchards

ABSTRACT Precision agriculture adoption in Brazilian apple orchards is still incipient. This study aimed at evaluating the spatial variability of certain soil properties as soil density, soil penetration resistance, electrical conductivity, yield, and fruit quality in an apple orchard through digital mapping, as well as assessing the correlation between these factors by means of geostatistics, establishing management zones. Forty representative points were set within 2.5 hectares of apple orchard, wherein soil samples were collected and analyzed, besides measurements of fruit quality (Brix degree, size or diameter, pulp firmness and color) to generate an overall index quality. We concluded that the fruit quality indexes, when isolated, did not show strong spatial dependence, unlike the index of fruit quality (FQI), derived from a combination of these parameters, allowing orchard planning according to management zones based on quality.

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

ABSTRACT The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.

Spatial multicriteria decision analysis for the siting of on-shore wind power in Kemiönsaari

Wind power is a low-carbon energy production form that reduces the dependence of society on fossil fuels. Finland has adopted wind energy production into its climate change mitigation policy, and that has lead to changes in legislation, guidelines, regional wind power areas allocation and establishing a feed-in tariff. Wind power production has indeed boosted in Finland after two decades of relatively slow growth, for instance from 2010 to 2011 wind energy production increased with 64 %, but there is still a long way to the national goal of 6 TWh by 2020. This thesis introduces a GIS-based decision-support methodology for the preliminary identification of suitable areas for wind energy production including estimation of their level of risk. The goal of this study was to define the least risky places for wind energy development within Kemiönsaari municipality in Southwest Finland. Spatial multicriteria decision analysis (SMCDA) has been used for searching suitable wind power areas along with many other location-allocation problems. SMCDA scrutinizes complex ill-structured decision problems in GIS environment using constraints and evaluation criteria, which are aggregated using weighted linear combination (WLC). Weights for the evaluation criteria were acquired using analytic hierarchy process (AHP) with nine expert interviews. Subsequently, feasible alternatives were ranked in order to provide a recommendation and finally, a sensitivity analysis was conducted for the determination of recommendation robustness. The first study aim was to scrutinize the suitability and necessity of existing data for this SMCDA study. Most of the available data sets were of sufficient resolution and quality. Input data necessity was evaluated qualitatively for each data set based on e.g. constraint coverage and attribute weights. Attribute quality was estimated mainly qualitatively by attribute comprehensiveness, operationality, measurability, completeness, decomposability, minimality and redundancy. The most significant quality issue was redundancy as interdependencies are not tolerated by WLC and AHP does not include measures to detect them. The third aim was to define the least risky areas for wind power development within the study area. The two highest ranking areas were Nordanå-Lövböle and Påvalsby followed by Helgeboda, Degerdal, Pungböle, Björkboda, and Östanå-Labböle. The fourth aim was to assess the recommendation reliability, and the top-ranking two areas proved robust whereas the other ones were more sensitive.

GIS assessing traditional and modern agricultural land use/land cover change. A case study 1959-2005: Rekijoki, Somero, SW-Finland

Finland’s rural landscape has gone through remarkable changes from the 1950’s, due to agricultural developments. Changed farming practices have influenced especially traditional landscape management, and modifications in the arable land structure and grasslands transitions are notable. The review of the previous studies reveal the importance of the rural landscape composition and structure to species and landscape diversity, whereas including the relevance in presence of the open ditches, size of the field and meadow patches, topology of the natural and agricultural landscape. This land-change study includes applying remote sensed data from two time series and empirical geospatial analysis in Geographic Information Systems (GIS). The aims of this retrospective research is to detect agricultural landscape use and land cover change (LULCC) dynamics and discuss the consequences of agricultural intensification to landscape structure covering from the aspects of landscape ecology. Measurements of LULC are derived directly from pre-processed aerial images by a variety of analytical procedures, including statistical methods and image interpretation. The methodological challenges are confronted in the process of landscape classification and combining change detection approaches with landscape indices. Particular importance is paid on detecting agricultural landscape features at a small scale, demanding comprehensive understanding of such agroecosystems. Topological properties of the classified arable land and valley are determined in order to provide insight and emphasize the aspect the field edges in the agricultural landscape as important habitat. Change detection dynamics are presented with change matrix and additional calculations of gain, loss, swap, net change, change rate and tendencies are made. Transition’s possibility is computed following Markov’s probability model and presented with matrix, as well. Thesis’s spatial aspect is revealed with illustrative maps providing knowledge of location of the classified landscape categories and location of the dynamics of the changes occurred. It was assured that in Rekijoki valley’s landscape, remarkable changes in landscape has occurred. Landscape diversity has been strongly influenced by modern agricultural landscape change, as NP of open ditches has decreased and the MPS of the arable plot has decreased. Overall change in the diversity of the landscape is determined with the decrease of SHDI. Valley landscape considered as traditional land use area has experienced major transitional changes, as meadows class has lost almost one third of the area due to afforestation. Also, remarkable transitions have occurred from forest to meadow and arable land to built area. Boundaries measurement between modern and traditional landscape has indicated noticeable proportional increase in arable land-forest edge type and decrease in arable land-meadow edge type. Probability calculations predict higher future changes for traditional landscape, but also for arable land turning into built area.

Self-deposit, discovery, and delivery of scientific GIS datasets using GeoHydra

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

GIS in Digital Repositories

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Temporal and spatial variations in the structure of macroalgal communities associated with mangrove trees of Ilha do Cardoso, São Paulo state, Brazil

Temporal and spatial variations in species composition and vertical distribution of macroalgal communities growing on mangrove trees were analyzed bimonthly in the Ilha do Cardoso State Park, São Paulo state (25°03'S and 47°55'W), Southeastern Brazil. The macroalgal communities from mangroves of Perequê and Sítio Grande rivers comprised 10 and 18 taxa respectively. Bostrychia radicans (Mont.) Mont. and B. calliptera (Mont.) Mont. were the predominant taxa, present almost throughout the year and in all the sites studied. The species composition of macroalgal communities from both mangroves presented temporal and spatial variations related to environmental factors. The highest number of taxa was observed during colder, drier months, coinciding with the highest means of high water neap and short periods of continuous emersion (April to August). Some mangrove algae such as B. calliptera, Rhizoclonium spp., Caloglossa spp., and Boodleopsis pusilla (Collins) W. Taylor, Joly et Bernatowicz showed a high degree of tolerance to desiccation, being able to tolerate continuous emersion up to six days. The spatial variations in species composition were related to light, as observed in Catenella caespitosa (Withering) L. Irvine, which occurred in well-lit sites. No pattern of vertical zonation was observed, since Rhizoclonium spp., B. radicans, and B. calliptera occur over the entire vertical range. Variations in the range of vertical distribution of macroalgae of Perequê mangrove were mainly related to the variations in the tidal levels (mean high water neap and/or mean high water spring) while those observed in Sítio Grande mangrove were related to salinity variations, except for B. calliptera and Caloglossa spp. related to tidal levels and high irradiance, respectively.

Forest spatial heterogeneity and palm richness, abundance and community composition in Terra Firme forest, Central Amazon

The mechanisms that maintain tree diversity in tropical rain forests are still in debate. Variations in forest structural components produce forest microenvironmental heterogeneity, which in turn may affect plant performance and have been scarcely analyzed in the Amazon. Palms are widespread in the Neotropical rainforests and have relatively well known taxonomy, apart from being ecologically and economically important. The understanding of how palms respond to variation in the forest structural components may help to explain their abundance and richness in a given area. In this study, we describe a palm community and analyze how it is affected by forest microenvironmental heterogeneity. In a pristine "Terra Firme" forest at Reserva Ducke, Manaus, we recorded all adult palm trees in twenty 100 × 10 m plots. In the same plots we recorded the variation in canopy openness, the leaflitter thickness and counted all non-palm forest trees. A total of 713 individuals in 29 palm species were found. The three most abundant species were Astrocaryum sciophilum (Miq.) Pulle, A. gynacanthum Mart. and Attalea attaleoides (Barb. Rodr.) Wess. Boer. The most locally abundant species were also very frequent or occurred in a larger number of plots. There were no significant effects of litter depth, forest canopy openness and forest tree abundance on palm richness. However, in areas where leaf litter was thicker a significant lower number of palm trees occurred. In microsites where proportionally more incident light was reaching the forest understory, due to higher canopy opening, significantly more palm trees were present.

Patterns of spatial distribution in macroalgal communities from tropical lotic ecosystems

Three sampling sites were analysed in each of the following tropical regions: 1) northwestern São Paulo State, representing a disturbed region; 2) Bonito, Mato Grosso do Sul State, representing a hard water region; and 3) Ubatuba, northern costal region of São Paulo State, a well preserved tropical rainforest region. The hard water region had the highest mean values for macroalgal species richness (6.3) and diversity index (H' = 0.62). Northwest and rainforest regions had the highest percent cover values (22.5% and 17.0%, respectively). All sites in the northwest region had one or two dominant species (percent cover significantly higher than the remaining species), characterizing the niche pre-emption distribution pattern. The same pattern was found in two sites of the Atlantic rainforest. The hard water region had dominance of one species in two out of the three sites, but differently from the northwest region, niche overlap values were lower, evidencing a patch distribution. Competition for space was one of the main factors to explain spatial distribution. Overall, sites characterized by niche pre-emption had lower species richness, higher values for niche width and overlap, dominance index and percent cover of dominant species. In contrast, sites characterized by patch distribution had higher species richness and lower values for niche overlap and width, dominance index and percent cover.

Spatial variation in the structure and floristic composition of "restinga" vegetation in southeastern Brazil

We examined large-scale spatial variation of structural parameters and floristic composition in open Clusia scrub, a vegetation type of the Brazilian "restingas" (sandy coastal plain vegetation). This vegetation is organized in islands separated by sandy stretches with sparse herbaceous vegetation. We located 12 sample areas on three consecutive beach ridges, lying parallel to the coastline and at different distances from the ocean, in close proximity to two lagoons (Cabiúnas and Comprida). Each sample area was divided into three strips. We used the line intercept method to sample all woody plants ³ 50 cm tall. We used nested ANOVA to verify structural variation between different sampling scales. TWINSPAN analysis was performed to examine the variation in floristic composition between areas. The overall diversity index was 3.07. Six species are repeatedly dominant throughout the entire sampling area. There was homogeneity in relation to diversity and species richness between beach ridges but not within beach ridges. Floristic composition and structural parameters did not vary in relation to distance from the sea but floristic composition did vary as a function of proximity to Cabiúnas or Comprida lagoon. Differences in plant cover between sample areas may be related to the paleoformation of this sandy coastal plain.

Biomass and chemical composition of Nitella furcata subsp. mucronata var. mucronata f. oligospira (A. Braun) R. D. Wood (Chlorophyta, Characeae) in the littoral region of Ninféias Pond, São Paulo, Southeast Brazil

Temporal variation of Nitella furcata (Roxburgh ex Bruzelius) C. Agardh emend. R. D. Wood subsp. mucronata (A. Braun) R. D. Wood var. mucronata f. oligospira (A. Braun) R. D. Wood biomass and chemical composition were studied at the Ninféias Pond (23°38'18.9" S, 46°37'16.3" W), a mesotrophic reservoir located in the Parque Estadual das Fontes do Ipiranga Biological Reserve, Municipality of São Paulo, Southeast Brazil. Plants were collected monthly from October 1996 to October 1997 at three fixed stations of reservoir's littoral region. Charophyte biomass spatial distribution pattern did not vary significantly throughout the study period at all sampling stations. As to seasonal variation, the highest average values of the total alga biomass (98.35-266.06 g m-2 DW) were registered during the rainy season, whereas lowest values (48.86-170.56 g m-2 DW) were in the dry season. P values varied from 23.8 to 225.2 mg m-2 and C from 139 to 353 mg m-2. During the rainy season, greatest air and water temperature, rain precipitation, turbidity and dissolved inorganic nitrogen values were measured, constituting the best conditions for charophyte growth. Water temperature and nutrient availability in the reservoir played a decisive role towards growth and accumulation of algal biomass.

The modulation of simple reaction time by the spatial probability of a visual stimulus

Simple reaction time (SRT) in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming). The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14) investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12) examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.