Large‐Area Maize Yield Forecasting Using Leaf Area Index Based Yield Model

Baez-González, Alma Delia; Kiniry, James R.; Maas, Stephan J.; Tiscareno, Mario L.; Macías, C Jaime; Mendoza, José Luis Zambrano; Richardson, C. W.; Salinas, Garrido; Manjarrez, Juan R.

doi:10.2134/agronj2005.0418

Cited by 87 publications

(60 citation statements)

References 38 publications

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“…In this study, we used the NDVI and green-red vegetation index (GRVI) as vegetation indices because these indices are widely used in remote sensing studies [20,24]. The NDVI has been used to estimate variations in vegetation conditions [25,26]. The GRVI is a new vegetation index and has been used to detect subtle vegetation changes (e.g., leaf fall due to a typhoon or mowing of plants) or differences among ecosystem types [20,27].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

et al. 2015

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A ground-based network of spectral observations is useful for ecosystem monitoring and validation of satellite data. However, these observations contain inherent uncertainties due to the change of sunlight conditions. This study investigated the impact of changing solar zenith angles and diffuse/direct light conditions on the consistency of vegetation indices (normalized difference vegetation index (NDVI) and green-red vegetation index (GRVI)) derived from ground-based spectral measurements in three different types of cropland (paddy field, upland field, cultivated grassland) in Japan. In general, the vegetation indices decreased with decreasing solar zenith angle. This response was affected significantly by the growth stage and diffuse/direct light conditions. The decreasing response of the NDVI to the decreasing solar zenith angle was high during the middle growth stage (0.4 < NDVI < 0.8). On the other hand, a similar response of the GRVI was evident except in the early growth stage (GRVI < 0). The response of OPEN ACCESSRemote Sens. 2015, 7 14080 vegetation indices to the solar zenith angle was evident under clear sky conditions but almost negligible under cloudy sky conditions. At large solar zenith angles, neither the NDVI nor the GRVI were affected by diffuse/direct light conditions in any growth stage. These experimental results were supported well by the results of simulations based on a physically-based canopy reflectance model (PROSAIL). Systematic selection of the data from continuous diurnal spectral measurements in consideration of the solar light conditions would be effective for accurate and consistent assessment of the canopy structure and functioning.

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Section: Introductionmentioning

confidence: 99%

The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

et al. 2015

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“…Researchers have used remote sensing greatly to estimate fractional intercepted photosynthetically active radiation [13] Spectral measurements from crops can be used in estimating crop parameters such as leaf area index [18], plant population, and even canopy total nitrogen status during the growth cycle of the crop [19]. Vegetation indices are algorithms which simplify data from multiple reflectance bands to a single value correlating to physical vegetation parameters, such as biomass, productivity, leaf area index, or percent vegetation ground cover [14].…”

Section: Remote Sensing Applications In Crop Area Assessmentmentioning

confidence: 99%

“…The differences in leaf colours, textures, shapes or even how the leaves are attached to plants, determine the amount of reflected, absorbed, or transmitted energy, and such relationships are used to determine spectral signatures of individual plants, which are unique to plant species [23]. Spectral signatures make it possible to use remote sensing in studying changes in specific crop conditions in the field and relate these to final yield and quality [18].The comparison of the reflectance values at different wavelengths is used to determine plant vigour [24]. The most common index that is used for this purpose is the normalized deviation vegetative index (NDVI) [8].…”

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Remote Sensing Applications in Tobacco Yield Estimation and the Recommended Research in Zimbabwe

Svotwa¹,

Masuka²,

Maasdorp

et al. 2013

ISRN Agronomy

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Tobacco crop area and yield forecasts are important in stabilizing tobacco prices at the auction floors. Tobacco yield estimation in Zimbabwe is currently based on statistical surveys and ground-based field reports. These methods are costly, time consuming, and are prone to large errors. Remote sensing can provide timely information on crop spectral characteristics which can be used to estimate crop yields. Remote sensing application on agriculture in Zimbabwe is still very limited. Research should focus on identifying suitable reflectance indices that are related to tobacco growth and yield. Varietal yield response to fertiliser and planting dates as well as suitable temporal windows for spectral data collection should be identified. The challenges of the different tobacco land sizes have to be overcome by identifying suitable satellite platform, with sufficient spectral resolution to separate the tobacco crop from the adjacent competing crops and noncrop vegetative surfaces. The identified suitable index should be strongly correlated with tobacco in season dry mass and yield. The suitable vegetative indices can be employed in establishing tobacco cropped area and then apply the long-term area yield relationship from government and nongovernmental statistical departments to estimate yield from remote sensing derived cropped area. BackgroundZimbabwe is the largest producer of tobacco in Africa and the world's fourth-largest producer of flue-cured tobacco (Nicotiana tabacum), after China, Brazil, and the United States of America. Tobacco production has been the leading driver behind the 34% growth in Zimbabwe's agriculture and one of the major sources of foreign currency [1]. Tobacco crop plays an important role in the economy of Zimbabwe and in the 2012/2013 marketing season, 144 million kg of tobacco was sold, earning the country $525 million [2].Crop area and yield forecasts play an important role in stabilizing tobacco prices at the auction floors. Crop forecasting is the art of predicting crop yields and production before the harvest actually takes place, typically a couple of months in advance [2]. Zimbabwe mostly relies on crop statistical forecasting/estimation, crop reports/field visits from extension officers, and statistical crop forecasts for crop yield forecasts [3]. However, data from crop estimates, which are obtained through surveys conducted after harvests, are in most countries available quite late for early warning purposes.Crop yield estimation in many countries is based on conventional techniques of data collection and ground-based field reports [4]. A variety of mathematical models relating to crop yield have also been proposed in recent years for many crops [4,5]. In Zimbabwe crop surveys are mostly used in estimating crop yield [3]. The method is costly, time consuming, and prone to large errors due to incomplete ground observations, leading to poor crop yield assessment and crop area estimations [4]. Remote Sensing Applications in Crop Area AssessmentRemote sensing is defined as acquirin...

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“…SSCM is carried out with a greater degree of precision through the use of geospatial technologies. Geospatial technology is a combination of four essential tools: remote sensing, geographic information systems (GIS), global positioning systems (GPS), and information technology or data management [1][2][3][4][5][6][7]. SSCM has become very common in management of field and row crops during recent years.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing and Geospatial Technological Applications for Site-specific Management of Fruit and Nut Crops: A Review

Panda¹,

Hoogenboom

Paz

2010

Remote Sensing

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Site-specific crop management (SSCM) is one facet of precision agriculture which is helping increase production with minimal input. It has enhanced the cost-benefit scenario in crop production. Even though the SSCM is very widely used in row crop agriculture like corn, wheat, rice, soybean, etc. it has very little application in cash crops like fruit and nut. The main goal of this review paper was to conduct a comprehensive review of advanced technologies, including geospatial technologies, used in site-specific management of fruit and nut crops. The review explores various remote sensing data from different platforms like satellite, LIDAR, aerial, and field imaging. The study analyzes the use of satellite sensors, such as Quickbird, Landsat, SPOT, and IRS imagery as well as hyperspectral narrow-band remote sensing data in study of fruit and nut crops in blueberry, citrus, peach, apple, etc. The study also explores other geospatial technologies such as GPS, GIS spatial modeling, advanced image processing techniques, and information technology for suitability study, orchard delineation, and classification accuracy assessment. The study also provides an example of a geospatial model developed in ArcGIS ModelBuilder to automate the blueberry production suitability analysis. The GIS spatial model is developed using various crop characteristics such as chilling hours, soil permeability, drainage, and pH, and land cover to determine the best sites for growing OPEN ACCESSRemote Sensing 2010, 2 1974 blueberry in Georgia, U.S. The study also provides a list of spectral reflectance curves developed for some fruit and nut crops, blueberry, crowberry, redblush citrus, orange, prickly pear, and peach. The study also explains these curves in detail to help researchers choose the image platform, sensor, and spectrum wavelength for various fruit and nut crops SSCM.

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Large‐Area Maize Yield Forecasting Using Leaf Area Index Based Yield Model

Cited by 87 publications

References 38 publications

The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

Remote Sensing Applications in Tobacco Yield Estimation and the Recommended Research in Zimbabwe

Remote Sensing and Geospatial Technological Applications for Site-specific Management of Fruit and Nut Crops: A Review

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