Daniel Alves Aguiar

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.

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.

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.

STARS: A New Method for Multitemporal Remote Sensing

There is great potential for the development of remote sensing methods that integrate and exploit both multispectral and multitemporal information. This paper presents a new image processing method: Spectral-Temporal Analysis by Response Surface (STARS), which synthesizes the full information content of a multitemporal-multispectral remote sensing image data set to represent the spectral variation over time of features on the Earths surface. Depending on the application, STARS can be effectively implemented using a range of different models [e.g., polynomial trend surface (PTS) and collocation surface (CS)], exploiting data from different sensors, with varying spectral wavebands and acquiring data at irregular time intervals. A case study was used to test STARS, evaluating its potential to characterize sugarcane harvest practices in Brazil, specifically with and without preharvest straw burning. Although the CS model presented sharper and more defined spectral-temporal surfaces, abrupt changes related to the sugarcane harvest event were also well characterized with the PTS model when a suitable degree was set. Orthonormal coefficients were tested for both the PTS and CS models and performed more accurately than regular coefficients when used as input for three evaluated classifiers: instance based, decision tree, and neural network. Results show that STARS holds considerable potential for representing the spectral changes over time of features on the Earths surface, thus becoming an effective image processing method, which is useful not only for classification purposes but also for other applications such as understanding land-cover change. The STARS algorithm can be found at www.dsr.inpe.br/~mello.

Temporal series of EVI/MODIS to identify land converted to sugarcane

Time series of remote sensing EVI/MODIS data are an important source of information to evaluate the direct land conversion to sugarcane in response to increased ethanol production in Brazil. The present work uses a time series of EVI/MODIS data to identify the land use prior to the conversion to sugarcane in a dense cultivated region in Parana¿ State, Brazil. Some sugarcane fields were selected over MODIS images acquired during the period of 2000 to 2008 in order to obtain reference time series to perform the land use classification prior to 2005. Using the temporal behavior of the EVI curves it was possible to distinguish among pasture land, annual crops and sugarcane in order to identify the land use prior to sugarcane conversion. It was noticed that in 2000 several of the annual crop fields in 2005, were pasture land in 2000 which were gradually converted to annual crops until 2005 and then to sugarcane.

MODIS Time Series to Detect Anthropogenic Interventions and Degradation Processes in Tropical Pasture

The unavoidable diet change in emerging countries, projected for the coming years, will significantly increase the global consumption of animal protein. It is expected that Brazilian livestock production, responsible for close to 15% of global production, be prepared to answer to the increasing demand of beef. Consequently, the evaluation of pasture quality at regional scale is important to inform public policies towards a rational land use strategy directed to improve livestock productivity in the country. Our hypothesis is that MODIS images can be used to evaluate the processes of degradation, restoration and renovation of tropical pastures. To test this hypothesis, two field campaigns were performed covering a route of approximately 40,000 km through nine Brazilian states. To characterize the sampled pastures, biophysical parameters were measured and observations about the pastures, the adopted management and the landscape were collected. Each sampled pasture was evaluated using a time series of MODIS EVI2 images from 2000–2012, according to a new protocol based on seven phenological metrics, 14 Boolean criteria and two numerical criteria. The theoretical basis of this protocol was derived from interviews with producers and livestock experts during a third field campaign. The analysis of the MODIS EVI2 time series provided valuable historical information on the type of intervention and on the biological degradation process of the sampled pastures. Of the 782 pastures sampled, 26.6% experienced some type of intervention, 19.1% were under biological degradation, and 54.3% presented neither intervention nor trend of biomass decrease during the period analyzed.

Modis time series to assess pasture land

Land use conversion is a key factor in the mitigation of GHG emission. Maximum mitigation can be achieved when degraded pasture land is converted to biofuel crops. Remote sensing images, and in particular the MODIS time series data, have a great potential to asses degraded pasture land. This work has the objective to identify pasture land and its different levels of degradation in Mato Grosso do Sul state, Brazil. MODIS time series were used to obtain vegetation indices and fraction images. The wavelet technique was applied at various levels of decomposition to extract the input parameters in the WEKA J48 classifier. Pasture land was well distinguished from Cerrado. The distinction among different pasture land presented lower performance with best results for pasture with invasive plants followed by good pasture. Pasture land with bare soil patches and termite mounds were not distinguished from other classes of pasture.

Mapeamento das áreas de cana-de-açúcar na região norte fluminense - RJ por uso de técnicas de sensoriamento remoto

This study aimed to evaluate sugarcane growth dynamics occupation in land cultivated at six major cities of the North Fluminense, Rio de Janeiro, from 1984 to 2007. Eighteen images of Landsat TM sensor, visual interpretation and linear spectral mixing model (MLME) were used to generate thematic maps of sugar cane plantation spatial distribution and quantification. Based on these maps was possible to analyze the sugarcane field spatial distribution quantifying them in each municipality. The results indicated that between the years 2004 to 2007, there was a decrement in the total area occupied by the culture in 43,308.33 ha and, from 2000 to 2007 and increase of 24,422.72 ha, mainly in the Campos dos Goytacazes, Sao Francisco de Itabapoana and Cardoso Moreira municipalities. The MLME used allowed a real live mapping of the sugarcane areas.