Fast and accurate quantification of the available pasture biomass is essential to support grazing management decisions in intensively managed fields. The increasing temporal and spatial resolutions ...offered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely sensed data. Here, we assessed the feasibility of using spectral and textural information derived from PlanetScope imagery for estimating pasture aboveground biomass (AGB) and canopy height (CH) in intensively managed fields and the potential for enhanced accuracy by applying the extreme gradient boosting (XGBoost) algorithm. Our results demonstrated that the texture measures enhanced AGB and CH estimations compared to the performance obtained using only spectral bands or vegetation indices. The best results were found by employing the XGBoost models based only on texture measures. These models achieved moderately high accuracy to predict pasture AGB and CH, explaining 65% and 89% of AGB (root mean square error (RMSE) = 26.52%) and CH (RMSE = 20.94%) variability, respectively. This study demonstrated the potential of using texture measures to improve the prediction accuracy of AGB and CH models based on high spatiotemporal resolution PlanetScope data in intensively managed mixed pastures.
Crop identification is an important task in the process of yield estimation; however, sometimes it can be difficult when using images of medium to low spatial resolution due to mixing of ...heterogeneous areas within the pixel. Therefore, selecting pixels that best represent an area/crop could be an alternative to input data in yield estimate models. The objective of this study was to select soya bean pixels based on temporal stability technique and test the ability of these pixels to predict yield. The study was conducted at county level in Paraná state, Brazil, during 11 years of soya bean growing season. To estimate yield, we created a linear regression model and used accumulated enhanced vegetation index during four periods according to soya bean phenological stages, which are as follows: emergence to maturity, emergence to flowering, flowering to grain filling, and flowering to maturity. Among all periods of the crop season, emergence to flowering showed the lowest precision while flowering to maturity was the period with the best agreements when compared with official data; the root mean square error ranged from 0.07 to 0.37 t ha –¹. The temporal stability method has proven to be an efficient tool to select pixel that could represent the crop for predicting yield. In addition, we could verify the most suitable period for making soya bean yield prediction.
In Brazil, the State of Goiás is one of sugarcane expansion's 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 Goiás, 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 Goiás has not affected their activities during the period studied.
Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. ...The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.
The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution ...that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.
Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts ...for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.
The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production ...in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.
O trabalho teve o objetivo de avaliar modelos lineares de regressão entre resposta espectral e produtividade em soja, na escala regional. Para isso, foram monitorados 36 municípios do oeste do ...Paraná, utilizando cinco imagens do satélite Landsat 5/TM da safra de 2004/2005. Foram realizados os procedimentos de transformação radiométrica e correção atmosférica nas imagens, determinando valores físicos das refletâncias aparente e de superfície. Posteriormente, foram calculados os índices de vegetação NDVI e GVI, os quais, por meio de regressões lineares simples e múltiplas, compararam-se com as produtividades oficiais dos municípios, obtidas das estatísticas IBGE. Aplicou-se também uma análise de diagnóstico, para detectar pontos influentes e de colinearidade. Os resultados mostraram que a média 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 regressões múltiplas com os dois índices, em todas as datas, propiciou melhores resultados de relação com a produtividade.
The main objective of this work was to evaluate the linear regression between spectral response and soybean yield in regional scale. In this study were monitored 36 municipalities from the west region of the states of Parana using five images of Landsat 5/TM during 2004/05 season. The spectral response was converted in physical values, apparent and surface reflectances, by radiometric transformation and atmospheric corrections and both used to calculate NDVI and GVI vegetation indices. Those ones were compared by multiple and simple regression with government official yield values (IBGE). Diagnostic processing method to identify influents values or collinearity was applied to the data too. The results showed that the mean surface reflectance value from all images was more correlated with yield than individual dates. Further, the multiple regressions using all dates and both vegetation indices gave better results than simple regression.
Apesar de recente no Brasil, o agroturismo se vem expandindo como um meio promotor de desenvolvimento rural, de aumento da renda dos pequenos produtores rurais e da conservação dos recursos naturais, ...culturais e paisagísticos de espaços agrários, mas há falta de planejamento adequado da atividade em relação ao meio ambiente e orientação aos proprietários rurais, que tem interesse em desenvolvê-lo. Neste estudo se propõe avaliar indicadores e apresentar uma estratégia metodológica que possa qualificar o potencial agroturístico de uma propriedade rural e impactos, pela integração de premissas de conservação e de planejamento ambiental. Como estudo de caso foi selecionada a Fazenda Fartura, em Socorro, SP, município situado em região turística mas que apresenta alto potencial natural de risco de erosão do solo. Indicadores foram avaliados para agricultura e pecuária, para conservação dos elementos naturais, para o turismo e para a infraestrutura física e social; cujos resultados obtidos apontaram as limitações e potencialidades da propriedade rural para o desenvolvimento do agroturismo e da estratégia apresentada.
Agro-tourism is recent in Brazil, but is growing as a means of promoting agricultural development, to increase the income of small rural producers and the preservation of natural resources, and of cultural and agricultural landscape aspects. However, there is lack of adequate planning of the activity regarding the environment and orientation to the farmers who have interest in developing it. Thus, this study proposes to evaluate indicators and to present a methodological strategy that can qualify the agro-tourism potential of the farm and impacts by integration of premises of conservation and environmental planning. As a case study the Fazenda Fartura, located in Socorro, SP, was selected. This city is part of the touristic region, but has a high natural potential risk for soil erosion. Indicators were evaluated for the agriculture and cattle raising, conservation, tourism and for the physical and social infrastructure. The results obtained point out the restrictions and potentialities of the farm for the agro-tourism development, as well as of the presented strategy.
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.
PDF
