Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

IDENTIFICATION OF SUITABLE AREAS FOR IRRIGATED RICE CROPPING USING MODIS IMAGES AND HAND MODEL

ABSTRACT One of the most relevant activities of Brazilian economy is agriculture. Among the main crops in Brazil, rice is one of high relevance. The state of Rio Grande do Sul, in Southern Brazil, is responsible for 68.7% of domestic production (IBGE, 2013). The goal of this study was to develop a low-cost methodology with a regional scope to identify suitable areas for irrigated rice cropping in this state, using spectro-temporal behavior of vegetation index by means of MODIS images and HAND model. The rice-cropped area of this study was the southern half of the State. Using the HAND model, flood areas were mapped to identify irrigated rice cultivation. We used multi-temporal images of vegetation index from MODIS sensor, covering the period from August 2001 to May 2012. To assess the results, we used data collected in the fields and cropped area information from IBGE. The results showed that the proposed methodology was satisfactory, with Kappa 0.92 and global accuracy of 98.18%. As result, MODIS sensor data and flood areas delineation by means of HAND model generated the estimate irrigated rice area for the area of study.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

The combined use of reflectance, emissivity and elevation Aster/Terra data for tropical soil studies

Reflectance, emissivity and elevation data of the sensor ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer)/Terra were used to characterize soil composition variations according to the toposequence position. Normalized data of SWIR (shortwave infrared) reflectance and TIR (thermal infrared) emissivity, coupled to a soil-fraction image from a spectral mixture model, were evaluated to separate bare soils from nonphotosynthetic vegetation. Regression relationships of some soil properties with reflectance and emissivity data were then applied on the exposed soil pixels. The resulting estimated values were plotted on the ASTER-derived digital elevation model. Results showed that the SWIR bands 5 and 6 and the TIR bands 10 and 14 measured the clay mineral absorption band and the quartz emissivity feature, respectively. These bands improved also the discrimination between nonphotosynthetic vegetation and soils. Despite the differences in pixel size and field sampling size, some soil properties were correlated with reflectance (R² of 0.65 for Al2O3 in band 6; 0.61 for Fe2O3 in band 3) and emissivity (R² of 0.65 for total sand fraction in the 10/14 band ratio). The combined use of reflectance, emissivity and elevation data revealed variations in soil composition with topography in specific parts of the landscape. From higher to lower slope positions, a general decrease in Al2O3 and increase in total sand fraction was observed, due to the prevalence of Rhodic Acrustox at the top and its gradual transition to Typic Acrustox at the bottom.

Sugarcane response to nitrogen rates, measured by a canopy reflectance sensor

Abstract:The objective of this work was to evaluate whether a canopy sensor is capable of estimating sugarcane response to N, as well as to propose strategies for handling the data generated by this device during the decision-making process for crop N fertilization. Four N rate-response experiments were carried out, with N rates varying from 0 to 240 kg ha-1. Two evaluations with the canopy sensor were performed when the plants reached average stalk height of 0.3 and 0.5 m. Only two experiments showed stalk yield response to N rates. The canopy sensor was able to identify the crop response to different N rates and the relationship of the nutrient with sugarcane yield. The response index values obtained from the canopy sensor readings were useful in assessing sugarcane response to the applied N rate. Canopy reflectance sensors can help to identify areas responsive to N fertilization and, therefore, improve sugarcane fertilizer management.

Potencialidades do dióxido de chumbo eletrodepositado como sensor potenciométrico

This paper proposes an experiment to be performed in both instrumental analysis and experimental physical-chemistry curricular disciplines in order to open options to develop challenging basic research activities. Thus the experimental procedures and the results obtained in the preparation of electrodeposited lead dioxide onto graphite and its evaluation as potentiometric sensor for H3O+ and Pb2+ ions, are presented. The data obtained in acid-base titrations were compared with those of the traditional combination glass electrode at the same conditions. Although a linear sub-Nernstian response to free hydrogen ions was observed for the electrodeposited PbO2 electrode, a good agreement was obtained between them. Working as lead(II) sensing electrode, the PbO2 showed a linear sub-Nernstian behavior at total Pb2+ concentrations ranging from 3,5 x 10-4 to 3,0 x 10-2 mol/L in nitrate media. For the redox couple PbO2/Pb(II) the operational slope converges to the theoretical one, as the acidity of the working solution increases.

Registrador portátil de odorantes basado en la modulación de temperatura de un sensor mos comercial

A simple, portable and low-cost system for odor detection was developed using a single MOS commercial sensor and a microcontroller. The temperature modulation technique was implemented applying a DC signal pulse to the sensor heater by a bipolar transistor. Two odorant profiles, ethanol and acetic acid vapors, were obtained and distinguished based on their amplitude versus time responses. Response for acetic acid was not reported by the sensor manufacturer. An ethanol vapor calibration curve was also obtained. Experimental data showed a potential behavior according to the theoretical equation of the MOS sensors. Values of logK=0.457 and α=-0.213 for a 95% confidence level were obtained.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

Development of capacitive sensor for measuring soil water content

The irrigation management based on the monitoring of the soil water content allows for the minimization of the amount of water applied, making its use more efficient. Taking into account these aspects, in this work, a sensor for measuring the soil water content was developed to allow real time automation of irrigation systems. This way, problems affecting crop yielding such as irregularities in the time to turn on or turn off the pump, and excess or deficit of water can be solved. To develop the sensors were used stainless steel rods, resin, and insulating varnish. The sensors measuring circuit was based on a microcontroller, which gives its output signal in the digital format. The sensors were calibrated using soil of the type “Quartzarenic Neosoil”. A third order polynomial model was fitted to the experimental data between the values of water content corresponding to the field capacity and the wilting point to correlate the soil water content obtained by the oven standard method with those measured by the electronic circuit, with a coefficient of determination of 93.17%, and an accuracy in the measures of ±0.010 kg kg-1. Based on the results, it was concluded that the sensor and its implemented measuring circuit can be used in the automation process of irrigation systems.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Experimental evaluation of the performance of a wireless sensor network in agricultural environments

The aim of this study was to perform an experimental study to evaluate the proper operation distance between the nodes of a wireless sensor network available on the market for different agricultural crops (maize, physic nut, eucalyptus). The experimental data of the network performance offers to farmers and researchers information that might be useful to the sizing and project of the wireless sensor networks in similar situations to those studied. The evaluation showed that the separation of the nodes depends on the type of culture and it is a critical factor to ensure the feasibility of using WSN. In the configuration used, sending packets every 2 seconds, the battery life was about four days. Therefore, the autonomy may be increased with a longer interval of time between sending packets.

Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop

The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.

Low-cost automatic activity data recording system

We describe a low-cost, high quality device capable of monitoring indirect activity by detecting touch-release events on a conducting surface, i.e., the animal's cage cover. In addition to the detecting sensor itself, the system includes an IBM PC interface for prompt data storage. The hardware/software design, while serving for other purposes, is used to record the circadian activity rhythm pattern of rats with time in an automated computerized fashion using minimal cost computer equipment (IBM PC XT). Once the sensor detects a touch-release action of the rat in the upper portion of the cage, the interface sends a command to the PC which records the time (hours-minutes-seconds) when the activity occurred. As a result, the computer builds up several files (one per detector/sensor) containing a time list of all recorded events. Data can be visualized in terms of actograms, indicating the number of detections per hour, and analyzed by mathematical tools such as Fast Fourier Transform (FFT) or cosinor. In order to demonstrate method validation, an experiment was conducted on 8 Wistar rats under 12/12-h light/dark cycle conditions (lights on at 7:00 a.m.). Results show a biological validation of the method since it detected the presence of circadian activity rhythm patterns in the behavior of the rats

Viral membrane fusion: is glycoprotein G of rhabdoviruses a representative of a new class of viral fusion proteins?

Enveloped viruses always gain entry into the cytoplasm by fusion of their lipid envelope with a cell membrane. Some enveloped viruses fuse directly with the host cell plasma membrane after virus binding to the cell receptor. Other enveloped viruses enter the cells by the endocytic pathway, and fusion depends on the acidification of the endosomal compartment. In both cases, virus-induced membrane fusion is triggered by conformational changes in viral envelope glycoproteins. Two different classes of viral fusion proteins have been described on the basis of their molecular architecture. Several structural data permitted the elucidation of the mechanisms of membrane fusion mediated by class I and class II fusion proteins. In this article, we review a number of results obtained by our laboratory and by others that suggest that the mechanisms involved in rhabdovirus fusion are different from those used by the two well-studied classes of viral glycoproteins. We focus our discussion on the electrostatic nature of virus binding and interaction with membranes, especially through phosphatidylserine, and on the reversibility of the conformational changes of the rhabdovirus glycoprotein involved in fusion. Taken together, these data suggest the existence of a third class of fusion proteins and support the idea that new insights should emerge from studies of membrane fusion mediated by the G protein of rhabdoviruses. In particular, the elucidation of the three-dimensional structure of the G protein or even of the fusion peptide at different pH's might provide valuable information for understanding the fusion mechanism of this new class of fusion proteins.