Análise da intensificação da agricultura no Mato Grosso à partir de dados TRMM 3B42 e de series temporais MODIS/EVI.

The Brazilian state of Mato Grosso (southern Amazonia) is one of the main national producer of agricultural products such as soybean, cotton and corn. After having based its development on the expansion of arable lands through deforestation for thrity years, the agricultural sector is now increasing its productive potential through the adoption of new agricultural management practices such as double cropping systems. Remote sensing tehcniques such as classification of MODIS/TERRA EVI times series are efficient tools for monitoring this phenomena. It appears that double cropping systems with wo comercial crops (soybean and corn or soybean and cotton) improved from 6% to 26% of the total cultivated area in Mato Grosso between 2000- 2001 and 2006-2007 harvests. However, when studying at a county level, those rates vary from 1 to more than 50%, attesting that it exists a strong spatial variability concerning the application of this agricultural management practice. It is argued that this rate is in part drove by the importance of total agricultural areas in a place and by pluviometric conditions. This hypothesis is confirmed by crossing MODIS data with rainfall data. These data are issue from the TRMM 3B42 products, which are computed into parameters such as duration, onset, end of the rain season and total annual rainfalls. Those parameters are found to explain 42% of the spatial variability of the application of double cropping systems in Mato Grosso. O objetivo deste artigo é de mapear as áreas cultivadas com duas safras e de estimar se o grau de intensificação encontrado em uma área pode ser relacionado às condições pluviométricas

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data

A spatial statistics approach to land use cover change modeling.

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Recurrence of multiple meiotic abnormalities in maize genotypes from the same origin and their influence on productivity.

The frequency of meiotic abnormalities among single-, double- and three-way cross experimental hybrids and their parental inbred lines is studied. Among the sixteen inbred lines examined, fifteen originated from populations developed at the National Center of Research in Maize and Sorghum (CNPMS/Embrapa) and one from a population developed at ESALQ (Faculty of Agriculture Luiz de Queiroz of the University of São Paulo). Previous analyses of homozygous and heterozygous maize genotypes from CNPMS populations demonstrated high meiotic instability. The present investigation aims at analyzing the meiotic behavior of different inbred lines obtained from CNPMS populations by another breeding enterprise to verify the presence of the same abnormalities and determine whether the abnormalities might compromise productivity. Analyses showed the presence of some abnormalities described previously, albeit at a lower frequency. The most common abnormalities in homozygous and heterozygous genotypes from CNPMS populations were related to irregular chromosome segregation and to chromosome stickiness. An inbred line from the ESALQ population showed only abnormalities related to irregular chromosome segregation caused by the presence of univalent chromosomes. The Pearson correlation procedure indicated high negative correlation between meiotic abnormalities and productivity

Recurrence of multiple meiotic abnormalities in maize genotypes from the same origin and their influence on productivity.

The frequency of meiotic abnormalities among single-, double- and three-way cross experimental hybrids and their parental inbred lines is studied. Among the sixteen inbred lines examined, fifteen originated from populations developed at the National Center of Research in Maize and Sorghum (CNPMS/Embrapa) and one from a population developed at ESALQ (Faculty of Agriculture Luiz de Queiroz of the University of São Paulo). Previous analyses of homozygous and heterozygous maize genotypes from CNPMS populations demonstrated high meiotic instability. The present investigation aims at analyzing the meiotic behavior of different inbred lines obtained from CNPMS populations by another breeding enterprise to verify the presence of the same abnormalities and determine whether the abnormalities might compromise productivity. Analyses showed the presence of some abnormalities described previously, albeit at a lower frequency. The most common abnormalities in homozygous and heterozygous genotypes from CNPMS populations were related to irregular chromosome segregation and to chromosome stickiness. An inbred line from the ESALQ population showed only abnormalities related to irregular chromosome segregation caused by the presence of univalent chromosomes. The Pearson correlation procedure indicated high negative correlation between meiotic abnormalities and productivity