Marcos Adami

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.

Remote Sensing Images in Support of Environmental Protocol: Monitoring the Sugarcane Harvest in Sao Paulo State, Brazil

Traditional manual sugarcane harvesting requires the pre-harvest burning practice which should be gradually banned by 2021 for most of Sao Paulo State, Brazil, on cultivated sugarcane land (terrain slope ≤12%) according to State Law number 11241. To forward the end of this practice to 2014, a “Green Ethanol” Protocol was established in 2007. The present work aims at analyzing five years of continuous sugarcane harvest monitoring, based on remote sensing images, to evaluate the effectiveness of the Protocol, thus helping decision makers to establish public policies to meet the Protocol’s expected goals. During the last five crop years, sugarcane acreage expanded by 1.5 million ha, which was compensated by a correspondent increase in the green harvested land. However, no significant reduction was observed in the amount of pre-harvest burned land over the same period. Based on the current trend, this goal is likely to be achieved one or two years later (2015–2016), which will be five or six years ahead of 2021 as the goal in the State Law number 11241 states. We thus conclude that the“Green Ethanol” Protocol has been effective with a positive impact on the increase of GH, especially on recently expanded sugarcane fields.

Recent cropping frequency, expansion, and abandonment in Mato Grosso, Brazil had selective land characteristics

This letter uses satellite remote sensing to examine patterns of cropland expansion, cropland abandonment, and changing cropping frequency in Mato Grosso, Brazil from 2001 to 2011. During this period, Mato Grosso emerged as a globally important center of agricultural production. In 2001, 3.3 million hectares of mechanized agriculture were cultivated in Mato Grosso, of which 500 000 hectares had two commercial crops per growing season (double cropping). By 2011, Mato Grosso had 5.8 million hectares of mechanized agriculture, of which 2.9 million hectares were double cropped. We found these agricultural changes to be selective with respect to land attributes?significant differences (p?<?0.001) existed between the land attributes of agriculture versus non-agriculture, single cropping versus double cropping, and expansion versus abandonment. Many of the land attributes (elevation, slope, maximum temperature, minimum temperature, initial soy transport costs, and soil) that were associated with an increased likelihood of expansion were associated with a decreased likelihood of abandonment (p?<?0.001). While land similar to agriculture and double cropping in 2001 was much more likely to be developed for agriculture than all other land, new cropland shifted to hotter, drier, lower locations that were more isolated from agricultural infrastructure (p?<?0.001). The scarcity of high quality remaining agricultural land available for agricultural expansion in Mato Grosso could be contributing to the slowdown in agricultural expansion observed there over 2006 to 2011. Land use policy analyses should control for land scarcity constraints on agricultural expansion.

High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data

Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project - called TerraClass - are available at INPEs web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php).

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

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.

A Web Platform Development to Perform Thematic Accuracy Assessment of Sugarcane Mapping in South-Central Brazil

Abstract: The ability to monitor sugarcane expansion in Brazil, the world’s largest producer and exporter of sugar and second largest producer of ethanol, is important due to its agricultural, economic, strategic and environmental relevance. With the advent of flex fuel cars in 2003 the sugarcane area almost doubled over the last decade in the South-Central region of Brazil. Using remote sensing images, the sugarcane cultivation area was annually monitored and mapped between 2003 and 2012, a period of major sugarcane expansion. The objective of this work was to assess the thematic mapping accuracy of sugarcane, in the crop year 2010/2011, with the novel approach of developing a web platform that integrates different spatial and temporal image resolutions to assist interpreters in classifying a large number of points selected by stratified random sampling. A field campaign confirmed the suitability of the web platform to generate the reference data set. An overall accuracy of 98% with an area estimation error of −0.5% was achieved for the sugarcane map of 2010/11. The accuracy assessment indicated that the map is of excellent quality, offering very accurate sugarcane area estimation for the purpose of agricultural statistics. Moreover, the web platform showed to be very effective in the construction of the reference dataset.

Soybean crop area estimation by Modis/Evi data

The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatistica. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.

Remote sensing images for monitoring the sugarcane harvest.

The agricultural practice of burning the sugarcane straw has the intention of facilitating the manual harvest. In Sao Paulo state this practice is subjected to a rigorous environmental legislation, due to the negative impact for the environment. It is anticipated that sugarcane burning should gradually be eliminated until 2017. The present work has the objective of evaluating the sugarcane area harvested with and without burning in the entire state of Sao Paulo. For that purpose, available images from TM sensor, on board of Landsat-5 satellite, were used. Images were acquired from April to December 2006, which corresponds to the sugarcane harvest period. These images were analyzed by using digital processing and visual interpretation techniques. The sugarcane area harvested without burning was estimated as 1,085,730 ha and corresponds to 34.7% of the total mechanized harvested area. This is according to the expectation of 30% established by the environmental legislation for the year of 2006. The temporal image sequence acquired between April and December allows us to identify the sugarcane areas harvested without burning and, therefore, distinguish them from the sugarcane areas harvested with burning.