Mauricio Alves Moreira

Studies on the rapid expansion of sugarcane for ethanol production in São Paulo State (Brazil) using Landsat data.

Abstract: This study’s overarching aim is to establish the areal extent and characteristics of the rapid sugarcane expansion and land use change in Sao Paulo state (Brazil) as a result of an increase in the demand for ethanol, using Landsat type remotely sensed data. In 2003 flex fuel automobiles started to enter the Brazilian consumer market causing a dramatic expansion of sugarcane areas from 2.57 million ha in 2003 to 4.45 million ha in 2008. Almost all the land use change, for the sugarcane expansion of crop year 2008/09, occurred on pasture and annual crop land, being equally distributed on each. It was also observed that during the 2008 harvest season, the burned sugarcane area was reduced to 50% of the total harvested area in response to a protocol that aims to cease sugarcane straw burning practice by 2014 for mechanized areas. This study indicates that remote sensing images have efficiently evaluated important characteristics of the sugarcane cultivation dynamic providing quantitative results that are relevant to the debate of sustainable ethanol production from sugarcane in Brazil.

The Soy Moratorium in the Amazon Biome Monitored by Remote Sensing Images

The Soy Moratorium is a pledge agreed to by major soybean companies not to trade soybean produced in deforested areas after 24th July 2006 in the Brazilian Amazon biome. The present study aims to identify soybean planting in these areas using the MOD13Q1 product and TM/Landsat-5 images followed by aerial survey and field inspection. In the 2009/2010 crop year, 6.3 thousand ha of soybean (0.25% of the total deforestation) were identified in areas deforested during the moratorium period. The use of remote sensing satellite images reduced by almost 80% the need for aerial survey to identify soybean planting and allowed monitoring of all deforested areas greater than 25 ha. It is still premature to attribute the recent low deforestation rates in the Amazon biome to the Soy Moratorium, but the initiative has certainly exerted an inhibitory effect on the soybean frontier expansion in this biome.

Multi‐temporal analysis of MODIS data to classify sugarcane crop

This paper presents a feasibility study using multi‐temporal Enhanced Vegetation Index (EVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) data to classify sugarcane crop. This study was carried out in São Paulo State which is the major sugarcane producer in Brazil, occupying more than 3.1 million hectares. Cloud‐free MODIS images (16 days mosaics) were acquired over a period of almost 15 months. Samples of sugarcane and non‐sugarcane were randomly selected and cluster analysis was performed to establish similar EVI temporal behaviour clusters. It was observed that EVI was sensitive to variations in land‐use cover mainly due to phenology and land management practices. Therefore, selection of sugarcane samples with similar EVI temporal behaviour for supervised classification was difficult due to both large planting and large harvesting periods. Consequently, cluster analysis was chosen to carry out an unsupervised classification. The best results were obtained in regions occupied by: natural and planted forest, soybean, peanuts, water bodies and urban areas which contrasted with the temporal‐spectral behaviour of sugarcane. The lowest performance was observed mainly in regions dominated by pasture, which has similar temporal‐spectral behaviour to sugarcane. This study provided useful information to define a MODIS image classification procedure for sugarcane crop for the whole State area based on the large amount of cloud‐free MODIS images when compared with other currently available optical sensors.

Análise espectral e temporal da cultura do café em imagens Landsat

Resumo – A definicao da resposta espectral da cultura do cafe e uma das etapas na identificacao de lavouras cafeeiras em imagens de satelites de sensoriamento remoto, para fins de mapeamento e estimativa de area plantada. O objetivo deste trabalho foi avaliar o potencial das imagens adquiridas pelos satelites da serie Landsat, no mapeamento da cultura do cafe para a previsao de safras. Foi feita uma analise temporal do comportamento espectral de lavouras de cafe-formacao e cafe-producao por meio de imagens livres de nuvens adquiridas nos anos de 1999 e 2001. Tambem foi analisado o comportamento espectral das classes pastagem e mata, que compoem os alvos de maior ocupacao na area de estudo. As imagens do periodo seco foram mais eficientes no mapeamento de lavouras de cafe-formacao e cafe-producao. As imagens da banda 4 dos dois sensores apresentaram melhor diferenciacao espectral entre cafe e os demais alvos da cena. A reflectância do cafe-producao apresentou grande variabilidade entre lavouras, que pode ser atribuida a idade, espacamento de plantas, cultivar, indicando a necessidade de trabalho em campo para a correta identificacao das lavouras de cafe nas imagens Landsat. Termos para indexacao: Coffea arabica, sensoriamento remoto, geoprocessamento, previsao de safra. Spectral and temporal behavior analysis of coffee crop in Landsat images

Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height

Hyperspectral crop reflectance data are useful for several remote sensing applications in agriculture, but there is still a need for studies to define optimal wavebands to estimate crop biophysical parameters. The objective of this work is to analyze the use of narrow and broad band vegetation indices (VI) derived from hyperspectral field reflectance measurements to estimate wheat (Triticum aestivum L.) grain yield and plant height. A field study was conducted during the winter growing season of 2003 in Campinas, Sao Paulo State, Brazil. Field canopy reflectance measurements were acquired at six wheat growth stages over 80 plots with four wheat cultivars (IAC-362, IAC-364, IAC-370, and IAC-373), five levels of nitrogen fertilizer (0, 30, 60, 90, and 120 kg of N ha-1) and four replicates. The following VI were analyzed: a) hyperspectral or narrow-band VI (1. optimum multiple narrow-band reflectance, OMNBR; 2. narrow-band normalized difference vegetation index, NB_NDVI; 3. first- and second-order derivative of reflectance; and 4. four derivative green vegetation index); and b) broad band VI (simple ratio, SR; normalized difference vegetation index, NDVI; and soil-adjusted vegetation index, SAVI). Hyperspectral indices provided an overall better estimate of biophysical variables when compared to broad band VI. The OMNBR with four bands presented the highest R2 values to estimate both grain yield (R2 = 0.74; Booting and Heading stages) and plant height (R2 = 0.68; Heading stage). Best results to estimate biophysical variables were observed for spectral measurements acquired between Tillering II and Heading stages.

Monitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery

The objective of this study was to assess correlations between coffee yield and MODIS derived vegetation indices. We assessed EVI and NDVI MODIS products in the south of Minas Gerais state whose production accounts for about one third of the Brazilian coffee production. Correlations were observed between variations on yield of coffee plots and variations on vegetation indices for pixels overlapping the same coffee plots. The vegetation index metrics best correlated to yield were the amplitude and the minimum values over the growing season. The best correlations were obtained between variation on vegetation indices and variation in yield the following year. In general EVI presented better results than those of NDVI for all vegetation index metrics evaluated. Although correlations were not enough to estimate coffee yield exclusively from vegetation indices, trends properly reflect the biennial bearing effect on coffee yield.

Geotecnologies to map coffee fields in the states of Minas Gerais and São Paulo

O uso operacional de imagens de satelites de sensoriamento remoto para mapear lavouras de cafe em grandes areas, para fins de obtencao de estatisticas agricolas confiaveis e oportunas, ainda se encontra em desenvolvimento. Diversos sao os fatores que dificultam a correta identificacao e mapeamento do parque cafeeiro. Contudo, os avancos tecnologicos observados nos ultimos anos em termos de aquisicao de imagens com melhor qualidade e em maior quantidade, bem como o desenvolvimento de novas ferramentas de analise, propiciam o desenvolvimento de um metodo operacional que pode contribuir na formacao das estatisticas agricolas oficiais do cafe no Brasil. Neste sentido, o presente trabalho tem por objetivo relatar a metodologia e apresentar os resultados do mapeamento das areas cultivadas com cafe nos Estados de Minas Gerais e Sao Paulo, utilizando imagens de sensoriamento remoto e tecnicas de geoprocessamento. A abordagem metodologica consiste em quatro fases: a) restauracao das imagens e georreferenciamento; b) classificacao nao supervisionada; c) interpretacao visual na tela do computador para minimizar erros de omissao e inclusao, e d) determinacao da area cultivada com cafe. Os resultados indicaram que a metodologia utilizada foi adequada para o mapeamento das lavouras de cafe de Minas Gerais e Sao Paulo.

Dados interferométricos para modelagem topográfica e caracterização ambiental do café em escala municipal

With the recent technical evolution and the free of charge access to several geo technologies, it has been observed that the use of these tools are relevant to the planning of agricultural activities in order to maximize the use of natural resources in a more sustainable manner. In this context, the physiographic conditions of a certain region may or may not allow agricultural exploration bringing direct consequences to crop yield and to the environment. O pilot area was selected in Minas Gerais State comprising the municipalities of Aguanil, Boa Esperanca, Campo Belo and Cristais. In order to achieve the proposed objectives a pre-processing with the SRTM regular grid was carried out, to correct for negative values. Following, an altimetry mash was associated to a cartographic projection system (UTM/SAD69) and organized in a geographic information system of public domain (SPRING). From the pre-processing and the application of derivative methods, the slope and slope orientation variables were obtained in spatial numerical format (regular mash) and thematic map. The results showed that it was possible to obtaining the coffee crop profile for each municipality with regard to these variables.

Processo analítico hierárquico na identificação de áreas favoráveis ao agroecossistema cafeeiro em escala municipal

O objetivo deste trabalho foi delimitar areas favoraveis ao agroecossistema cafeeiro, em quatro municipios do Estado de Minas Gerais, pela aplicacao do processo analitico hierarquico (AHP). Uma funcao de ponderacao aritmetica foi obtida, com base nas premissas de favorabilidade a cafeicultura, considerando-se as seguintes variaveis: solo, declividade, orientacao de vertentes, altimetria e as possiveis areas de preservacao permanente. Essa funcao permitiu combinar as condicoes adequadas ao cultivo do cafe e ressaltar as areas com maior favorabilidade. Foi verificado que os quatro municipios diferem entre si quanto a favorabilidade ao agroecossistema cafeeiro; porem, ao se considerar apenas as areas cultivadas com cafe, foi verificado que os municipios de Boa Esperanca e Cristais nao diferem entre si.

Wheat-area estimation using digital LANDSAT MSS data and aerial photographs

Abstract A procedure to estimate wheat (Triticum aestivum L) area using a sampling technique based on aerial photographs and digital LANDSAT MSS data was developed. Aerial photographs covering 720km2 were visually analysed. Computer classification of LANDSAT MSS data acquired on 4 September 1979 was performed using unsupervised and supervised algorithms and the classification results were spatially filtered using a post-processing technique. To estimate wheal area, a regression approach was applied using different sample sizes and various sampling units. Based on four decision criteria proposed in this study, it was concluded that (i) as the size of the sampling unit decreased, the percentage of the sample area required to obtain a similar estimation performance also decreased, (ii) the lowest percentage of the area sampled for wheat estimation under established precision and accuracy criteria through regression estimation was 13-09 per cent using 10 km2 as the sampling unit and (iii) wheat-area estimatio...