Amostragem probabilística estratificada por pontos para estimar a área cultivada com soja

Adami, Marcos; Rizzi, Rodrigo; Moreira, Maurício Alves; Rudorff, Bernardo Friedrich Theodor; Ferreira, Camila C.

doi:10.1590/s0100-204x2010000600008

Cited by 7 publications

(3 citation statements)

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“…In fact, even under the worst conditions observed within the study area, there was still a 17% percent of probability to find cloud free pixels. Therefore, even under the worst conditions, it would probably still be possible to estimate crop acreage using sampling techniques which are already in use [35,59,65]. In addition, the integration of active sensors into the monitoring system could be an option.…”

Section: Discussionmentioning

confidence: 99%

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

et al. 2016

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Abstract:The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information.

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Section: Discussionmentioning

confidence: 99%

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

et al. 2016

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“…Apesar de a metodologia utilizada por órgãos oficiais ainda ser bastante empregada (Adami et al, 2010), a proposição e a incorporação de novos métodos é importante para complementar os dados da metodologia adotada em programas oficiais. O projeto Geosafras tem desenvolvido e testado metodologias objetivas, com uso de geotecnologias (Companhia Nacional de Abastecimento, 2009a).…”

Section: Introductionunclassified

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Johann

Rocha

Duft

et al. 2012

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi estimar e mapear as áreas com as culturas de soja e milho, no Paraná, com uso de imagens multitemporais EVI/Modis. Foram avaliados os anos-safra de 2004/2005 a 2007/2008. Em razão da alta dinâmica temporal e da heterogeneidade de datas de semeadura das culturas no estado, foram utilizadas cenas que contemplavam as fases de pré-plantio e de desenvolvimento inicial das culturas, para gerar a imagem de mínimo EVI (IMIE), e cenas que consideravam o pico vegetativo das culturas, para gerar a imagem de máximo EVI (IMAE). Estas imagens foram utilizadas para gerar a composição colorida RGB (R, IMAE; GB, IMIE), o que permitiu a confecção de máscara das áreas com soja e milho. As estimativas das áreas de máscara por município foram comparadas com dados oficiais de produção agrícola municipal, tendo-se observado bons ajustes (R²>0,84, d>0,95, c>0,85) entre os dados. Para a avaliação da exatidão espacial das máscaras, imagens Landsat-5/TM e AWiFS/IRS foram usadas como referência para construção da matriz de erros. Os resultados obtidos são indicativos de que a metodologia proposta é altamente eficiente e pode ser utilizada para mapeamento dessas culturas.Termos para indexação: classificação de imagens, distribuição espacial de culturas, índice de vegetação, mapeamento, previsão de safras, sensoriamento remoto. Estimation of summer crop areas in the state of Paraná, Brazil, using multitemporal EVI/Modis imagesAbstract -The objective of this work was to estimate and map crop areas with soybean and corn in the state of Paraná, Brazil, using EVI/Modis images. The crop seasons from 2004/2005 to 2007/2008 were evaluated. Due to the high temporal dynamics and difference in sowing dates of the cultures within the state, scenes containing the pre-planting and initial crop development phases were used to obtain the minimum EVI image (IMIE), and scenes at the peak of the crop cycle were used to obtain the maximum EVI image (IMAE). These images were used to generate the RGB color composition (R, IMAE; GB, IMIE), which allowed for the creation of masks of the areas planted with soybean and corn. The estimation of masked areas by municipality was compared with the municipal agricultural production official data, and good fits (R²>0. 84, d>0.95, c>0.85) were observed between data. For spatial accuracy assessment, Landsat-5/TM and AWiFS/IRS images were used as references to build the error matrix. The obtained results indicate that the proposed methodology is highly efficient and may be used as a model for cropland mapping.

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“…In some cases, these methods were preferable, considering their rapidity in obtaining the data (SAEBØ, 1983). In Brazil, the spatial sampling method was evaluated to estimate yields in agriculture (EPIPHANIO et al, 2002;LUIZ, 2003;ADAMI et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Planted forest area estimation in Santa Catarina using random sampling point

Cardoso,

Refosco,

Marcolin

et al. 2023

RAC

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Management of planted forests depends, among other information, on the knowledge of their extensions and spatial distribution. The current information about the area of planted forests in the state of Santa Catarina comes from sources without proper accuracy assessment. This work aimed to evaluate the use of random point sampling in estimating the planted forest area in the state of Santa Catarina. A minimum sample of 200 points per municipality was used, with a maximum standard error of 2%. The results indicated a total planted forest area of 1,135,481ha, with a standard error of 0.12%, in the state of Santa Catarina. The municipalities with the largest planted forest areas are in the mesoregions Serrana, Oeste Catarinense, and Norte Catarinense. The random point sampling methodology showed a precise result for the state of Santa Catarina in a simple and objective way, and may be effective for decision-making in planning.

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Amostragem probabilística estratificada por pontos para estimar a área cultivada com soja

Cited by 7 publications

References 10 publications

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Planted forest area estimation in Santa Catarina using random sampling point

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