Rubens Augusto Camargo Lamparelli

A relevance feedback method based on genetic programming for classification of remote sensing images

This paper presents an interactive technique for remote sensing image classification. In our proposal, users are able to interact with the classification system, indicating regions of interest (and those which are not). This feedback information is employed by a genetic programming approach to learning user preferences and combining image region descriptors that encode spectral and texture properties. Experiments demonstrate that the proposed method is effective for image classification tasks and outperforms the traditional MaxVer method.

Spectral variables, growth analysis and yield of sugarcane

Spectral information is well related with agronomic variables and can be used in crop monitoring and yield forecasting. This paper describes a multitemporal research with the sugarcane variety SP80-1842, studying its spectral behavior using field spectroscopy and its relationship with agronomic parameters such as leaf area index (LAI), number of stalks per meter (NPM), yield (TSS) and total biomass (BMT). A commercial sugarcane field in Araras/SP/Brazil was monitored for two seasons. Radiometric data and agronomic characterization were gathered in 9 field campaigns. Spectral vegetation indices had similar patterns in both seasons and adjusted to agronomic parameters. Band 4 (B4), Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI) increased their values until the end of the vegetative stage, around 240 days after harvest (DAC). After that stage, B4 reflectance and NDVI values began to stabilize and decrease because the crop reached ripening and senescence stages. Band 3 (B3) and RVI presented decreased values since the beginning of the cycle, followed by a stabilization stage. Later these values had a slight increase caused by the lower amount of green vegetation. Spectral variables B3, RVI, NDVI, and SAVI were highly correlated (above 0.79) with LAI, TSS, and BMT, and about 0.50 with NPM. The best regression models were verified for RVI, LAI, and NPM, which explained 0.97 of TSS variation and 0.99 of BMT variation.

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

O objetivo deste trabalho foi estimar e mapear as areas com as culturas de soja e milho, no Parana, com uso de imagens multitemporais EVI/Modis. Foram avaliados os anos‑safra de 2004/2005 a 2007/2008. Em razao da alta dinâmica temporal e da heterogeneidade de datas de semeadura das culturas no estado, foram utilizadas cenas que contemplavam as fases de pre‑plantio e de desenvolvimento inicial das culturas, para gerar a imagem de minimo EVI (IMIE), e cenas que consideravam o pico vegetativo das culturas, para gerar a imagem de maximo EVI (IMAE). Estas imagens foram utilizadas para gerar a composicao colorida RGB (R, IMAE; GB, IMIE), o que permitiu a confeccao de mascara das areas com soja e milho. As estimativas das areas de mascara por municipio foram comparadas com dados oficiais de producao agricola municipal, tendo-se observado bons ajustes (R²>0,84, d>0,95, c>0,85) entre os dados. Para a avaliacao da exatidao espacial das mascaras, imagens Landsat‑5/TM e AWiFS/IRS foram usadas como referencia para construcao da matriz de erros. Os resultados obtidos sao indicativos de que a metodologia proposta e altamente eficiente e pode ser utilizada para mapeamento dessas culturas.

Growth indices ans productivity in sugarcane

O conhecimento do desenvolvimento temporal de variaveis agronomicas da cultura da cana-de-acucar e um aspecto preponderante, e ainda pouco explorado, para o desenvolvimento de modelos de entendimento e predicao da producao em estudos de sensoriamento remoto. O presente descreve a analise da evolucao temporal de variaveis agronomicas da cana-de-acucar como a biomassa total (BMT), produtividade (TCH), indice de area foliar (IAF) e numero de plantas por metro (NPM). Durante duas safras um talhao comercial em Araras/SP cultivado com a variedade SP80-1842 no 4o e 5o cortes foi acompanhado em oito campanhas de campo para a coleta de dados. O IAF, o NPM, a TCH e a BMT foram coletados em 18 amostras de 2 m em tres linhas de cana-de-acucar. Analise de regressao linear e multipla foram usadas para a analise do crescimento da cultura e para o estudo da correlacao e ajuste de modelos entre as variaveis agronomicas e a BMT e a TCH. O modelo Gompertz, de curva sigmoidal, foi o modelo que melhor se ajustou para a curva de BMT e para a TCH com r2 = 0,8987 e r2 = 0,9682, respectivamente. A BMT e o IAF tiveram melhores ajustes com curvas exponencial cubica e exponencial quadratica, respectivamente. A BMT e a TCH foram bem relacionadas com o IAF nas duas primeiras fases do ciclo, ajustando-se regressoes lineares. Para a fase de maturacao, a BMT e a TCH foram mais relacionadas com o NPM que com o IAF e as curvas obtiveram valores menores de que r2 que as demais fases do ciclo.

Mapping and discrimination of soya bean and corn crops using spectro-temporal profiles of vegetation indices

The use of remote-sensing technology has been studied as a way to make the monitoring of agricultural crops more efficient, dynamic, and reliable. The use of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has proved to be an interesting tool regarding the mapping of large areas, however, some challenges still need to be addressed. One of these is the identification of specific types of crops, especially when they have similar phenologies. The purpose of this study was to perform discrimination and mapping of soya bean and corn crops in the state of Paraná, Brazil, for the 2010/2011 and 2011/2012 crop years. A methodology using spectro-temporal profile information of the crops derived from vegetation indices (VIs), the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and the wide dynamic range vegetation index (WDRVI) based on MODIS data was appraised. This method generated a series of maps of the respective crops that were later qualitatively or quantitatively appraised. Some of the maps drawn showed a global accuracy rate above 80% and a kappa coefficient (κ) of over 0.7. The data areas showed an average difference of 6% for the cultivation of soya beans, and 11% for corn when compared to official data. The WDRVI and EVI were similar and showed better performance when compared to the NDVI in the assessments made. The results demonstrate that the soya bean crop was better mapped compared to corn, particularly in terms of the size of the crop area. The use of spectro-temporal profiles of the VIs assisted in obtaining important information, enabling better identification of crops from regional scale mapping using the MODIS data.

In-flight absolute calibration of the Landsat-5 TM on the test site Salar de Uyuni

In Brazil, the increase of the application of quantitative approaches in the natural resources studies using remote sensing technology has required knowledge about the radiometric conditions of remote sensors as the Thematic Mapper (TM) and the Enhanced TM Plus, for instance. The establishment of a correlation between radiometric data and biophysical and geophysical ones has become a frequent need in the Brazilian remote sensing community, and it has increased the demand of calibration coefficients in order to transform digital numbers to physical values like radiance and reflectance. Since the China-Brazil Environmental Remote Sensing Satellite became a reality, the necessity to perform calibration campaigns increased significantly. Following Price and other researchers suggestions, an in-flight absolute calibration of the Landsat-5 data was carried out in the Salar de Uyuni, Bolivia. It was only possible to determine calibration coefficients for bands TM2, TM3, and TM4 due to the saturation of band TM1 and surface moisture conditions that impacted the TM5 and TM7. The methodology applied here seemed to be sufficient to determine valid calibration coefficients for orbital sensors.

Orbital spectral variables, growth analysis and sugarcane yield

Temporal analysis of crop development in commercial fields requires tools for large area monitoring, such as remote sensing. This paper describes the temporal evolution of sugar cane biophysical parameters such as total biomass (BMT), yield (TSS), leaf area index (LAI), and number of plants per linear meter (NPM) correlated to Landsat data. During the 2000 and 2001 cropping seasons, a commercial sugarcane field in Araras, Sao Paulo state, Brazil, planted with the SP80-1842 sugarcane variety in the 4th and 5th cuts, was monitored using nine Landsat images. Spectral data were correlated with agronomic data, obtained simultaneously to the imagery acquisition. Two methodologies were used to collect spectral data from the images: four pixels (2 × 2) window and average of total pixels in the field. Linear and multiple regression analysis was used to study the spectral behavior of the plants and to correlate with agronomic variables (days after harvest-DAC, LAI, NPM, BMT and TSS). No difference was observed between the methodologies to collect spectral data. The best models to describe the spectral crop development in relation to DAC were the quadratic and cubic models. Ratio vegetation index and normalized difference vegetation index demonstrated correlation with DAC, band 3 (B3) was correlated with LAI, and NDVI was well correlated with TSS and BMT. The best fit curves to estimate TSS and BMT presented r2 between 0.68 and 0.97, suggesting good potential in using orbital spectral data to monitor sugarcane fields.

Characterization of the Salar de Uyuni for in-orbit satellite calibration

Field work was carried out on June 8 and 9, 1999 to evaluate the use of the Salar de Uyuni as a test site for in-orbit satellite calibration. A dataset of ten Thematic Mapper (TM) images, from 1988-1997, was used to select three test points based on the analysis of the temporal stability of the reflectance of Salars surface. Bidirectional reflectance factor (BRF) values of Salars surface within the precision suitable for vicarious calibration procedures were obtained using a CE313-2/CIMEL radiometer. In spite of seeming visually homogeneous, the BRF values of one test point have presented significative statistical differences with the two others. Atmospheric characterization was possible with a sunphotometer CE317/CIMEL showing the low importance of the atmospheric effects in the image acquisition. The results confirm that the Salar de Uyuni has the characteristics pointed out by many authors as suitable for a vicarious calibration site, specially from April to November because of the reduced rainfall occurrence. The main disadvantages are the difficult access and the critical period for data collecting in the rainy season from November to March. An angular reflectance variation study is recommended in order to evaluate its Lambertian properties.

Mapeamento de culturas de verão no Estado do Paraná por meio de composições decendiais de NDVI do sensor spot vegetation

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmotts concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.A busca por menor subjetividade em estimativas de area tem aumentado a utilizacao do sensoriamento remoto para monitoramento agricola e previsao de safras, pois proporciona maior agilidade na aquisicao de dados e menor custo em relacao a metodos tradicionais de censos e pesquisas. Imagens de satelite de baixa resolucao espacial e alta periodicidade sao adequadas para o mapeamento, acompanhamento e desenvolvimento de culturas em areas extensas. O objetivo deste trabalho foi mapear culturas de verao no Estado do Parana por meio de composicoes decendiais de imagens NDVI do satelite SPOT Vegetation para safras de 2005/2006, 2006/2007 e 2007/2008. Para isso, foi utilizado um metodo de classificacao digital supervisionada com algoritmo Paralelepipedo em composicoes RGB multitemporais das imagens, de forma a gerar mascaras das culturas de verao para cada composicao decendial. A verificacao da acuracia das mascaras foi realizada utilizando indice Kappa, exatidao global e indice de concordância de Willmott, resultando em bons indices de acerto. Essa metodologia possibilitou realizar, com dados gratuitos e de baixa resolucao espacial, o mapeamento de culturas de verao em nivel estadual.

A Genetic Programming approach for coffee crop recognition

This work presents a new approach for automatic recognition of coffee crops in RSIs. The method applies an approach based on Genetic Programming (GP) to combine texture and spectral information encoded by image descriptors. Experiments show that the proposed method yields slightly better results than the traditional MaxVer approach.