Jansle V. Rocha

Mapping global cropland and field size

A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

WOODSS — a spatial decision support system based on workflows

Abstract Environmental planning takes advantage of geographic information systems (GIS) to manage geographic data. GIS are, however, tools which require a great deal of training and programming expertise and, furthermore, have little support for decision makers during their planning activities. This paper presents WOrkflOw-based spatial Decision Support System ( woodss ) — a software developed at the University of Campinas, Brazil, to be used in conjunction with a GIS in order to provide spatial decision support involving environmental data. woodss was implemented on top of a commercial GIS and tested in the context of agri-environmental planning activities. woodss is centered on dynamically capturing user interactions with a GIS in real time and documenting them by means of scientific workflows. It keeps track of decision procedures, models applied and the choice of parameters in running these models. woodss s workflows can be updated on the fly, allowing testing and comparison of alternative planning strategies. They can, furthermore, be used as building blocks for the construction of complex decision procedures, supporting a divide-and-conquer problem solution style. These workflows interact directly with the GIS, sparing environmental planners and decision makers the burden of low-level programming.

The Need for Improved Maps of Global Cropland

Food security is a key global concern. By 2050, the global population will exceed 9 billion, and a 50% increase in annual agricultural output will be required to keep up with demand. There are significant additional pressures on existing agricultural land through increased competition from the biofuel sector and the need to elevate feed production, which is being driven by higher levels of meat consumption in low- and middle-income countries.

Variabilidade espacial dos atributos físicos do solo e da produtividade em um Latossolo Bruno distrófico da região de Cascavel, PR

Through geostatistics techniques, contour maps, were produced by interpolation using ordinary kriging, representing the spatial variability of the physical attributes; soil density [kg dm-3], soil water [g g-1] and penetration resistance [MPa] in the 0-10, 10-20 and 20-30 cm of depth, besides the soy bean productivity [t ha-1]. Soil attributes and yield data, derived from an unaligned stratified systematic sampling scheme, subdivided in portions with localized management (CML) and without localized management (SML) for the agricultural year 1998/99. The productivity maps in general presented a similar variability standard for the distribution in the non responding area as well as in the area with different chemical treatments applied in the CML plots. Where as the physical attributes presented a similar behavior for the two methods of management. Amongst the physical attributes studied, the penetration resistance in the 0-10 cm of depth was the variable which was best correlated with the productivity.

Modelos de regressão lineares para estimativa de produtividade da soja no oeste do Paraná, utilizando dados espectrais

O trabalho teve o objetivo de avaliar modelos lineares de regressao entre resposta espectral e produtividade em soja, na escala regional. Para isso, foram monitorados 36 municipios do oeste do Parana, utilizando cinco imagens do satelite Landsat 5/TM da safra de 2004/2005. Foram realizados os procedimentos de transformacao radiometrica e correcao atmosferica nas imagens, determinando valores fisicos das refletâncias aparente e de superficie. Posteriormente, foram calculados os indices de vegetacao NDVI e GVI, os quais, por meio de regressoes lineares simples e multiplas, compararam-se com as produtividades oficiais dos municipios, obtidas das estatisticas IBGE. Aplicou-se tambem uma analise de diagnostico, para detectar pontos influentes e de colinearidade. Os resultados mostraram que a media dos valores de NDVI e GVI de todas as imagens foi mais bem relacionada com a produtividade do que para cada data separadamente. O uso de regressoes multiplas com os dois indices, em todas as datas, propiciou melhores resultados de relacao com a produtividade.

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

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.

Spectral characteristics of soybean during the vegetative cycle with landsat 5/TM images in the western Paraná, Brazil

The objective of this study was to analyze changes in the spectral behavior of the soybean crop through spectral profiles of the vegetation indexes NDVI and GVI, expressed by different physical values such as apparent bi-directional reflectance factor (BRF), surface BRF, and normalized BRF derived from images of the Landsat 5/TM. A soybean area located in Cascavel, Parana, was monitored by using five images of Landsat 5/TM during the 2004/2005 harvesting season. The images were submitted to radiometric transformation, atmospheric correction and normalization, determining physical values of apparent BRF, surface BRF and normalized BRF. NDVI and GVI images were generated in order to distinguish the soybean biomass spectral response. The treatments showed different results for apparent, surface and normalized BRF. Through the profiles of average NDVI and GVI, it was possible to monitor the entire soybean cycle, characterizing its development. It was also observed that the data from normalized BRF negatively affected the spectral curve of soybean crop, mainly, during the phase of vegetative growth, in the 12-9-2004 image.

ESTIMATIVA DE ÁREA CULTIVADA COM ARROZ IRRIGADO PARA O ESTADO DO RIO GRANDE DO SUL A PARTIR DE IMAGENS MODIS

Este trabalho teve como objetivo testar uma metodologia de baixo custo e facil implantacao, utilizando imagens MODIS, para definir as areas cultivadas com arroz irrigado no Rio Grande do Sul (RS) e monitorar o cultivo ao longo do ciclo para dez safras agricolas. O estudo foi realizado abrangendo as seis regioes orizicolas do Estado do RS. Foram utilizados dados oficiais de area cultivada com arroz irrigado e imagens NormalizedDifferenceVegetation Index/ ModerateResolutionImagingSpectroradiometer (NDVI/MODIS) referentes as safras agricolas de 2000/01 ate 2009/10. A metodologia testada baseou-se no comportamento espectro-temporal da cultura do arroz irrigado. As maiores diferencas entre os valores de area estimados e os oficiais, em nivel regional, foram de -11,5% na Planicie Interna e 5% na Depressao Central. Os menores desvios ocorreram nas regioes da Campanha e Fronteira Oeste, sendo respectivamente de 2,2% e -3,1%. Os resultados mostram que a metodologia proposta e eficiente e pode ser usada tanto para complementar o atual sistema nacional de previsao de safras, como para o monitoramento das areas cultivadas no RS.

NDVI MODIS temporal profiles, in sugarcane, late maturation.

This paper describes the development of a relational database and a tool for viewing MODIS NDVI temporal profile, using data from MOD09Q1 product, specifically the surface bidirectional reflectance factor relative to the RED and NIR wavelength, mosaic of 8-day temporal composition, and the quality band, in sugarcane fields in the state of Sao Paulo, for analysis of the late stubble-cane maturation. From sugarcane farms were obtained the historical data about yield, soil, variety, location of the each pixel for each subregion monitored. All data were integrated in a database developed in PostgreSQL. The tool was implemented using Java language and allowed a fast and automatic way of analyzing sugarcane phenological patterns. It concluded that the MODIS NDVI temporal profile using data from MOD09Q1 product is able to subsidize the monitoring of phenological changes in the sugarcane.

Identification of grain areas replaced by sugarcane and analysis of the relationship with family farming production in the state of Goiás

In Brazil, the State of Goias is one of sugarcane expansions frontiers to meet the growing demand for biofuels. The objective of this study was to identify the municipalities where there were replacement of annual crops (mainly grains) by sugarcane in the state of Goias, as well as indicate correlations between the sugarcane expansion and the family farming production, in the period between 2005 and 2010. For this purpose, grains crop mask and sugarcane crop mask, obtained from satellite images, were intersected using geoprocessing techniques. It was also used IBGE data of sugarcane production and planted area, and data of family farming production linked with the National Food Acquisition Program (PAA), in relation to the number of cooperatives and family farmers. The crops masks and data tables of the National Food Acquisition Program were provided by National Food Supply Agency. There were 95 municipalities that had crops replacement, totaling 281,554 hectares of grains converted to sugarcane. We highlight the municipalities of Santa Isabel, Iaciara, Maurilândia, and Itapaci, where this change represented more than half of their agricultural areas. In relation to family farming, the sugarcane expansion in the state of Goias has not affected their activities during the period studied.