Assessment of Canopy Chlorophyll Content Retrieval  in Maize and Soybean: Implications of Hysteresis  on the Development of Generic Algorithms

Yi, Peng; Nguy-Robertson, Anthony L.; Arkebauer, Timothy J.; Gitelson, Anatoly A.

doi:10.3390/rs9030226

Cited by 97 publications

(73 citation statements)

References 60 publications

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“…The use of MTCI also has limitations because we have assumed that the trend of MTCI is linear and the V cmax, 25 , chlorophyll content and MTCI share the same trend. Although the correlations between V cmax, 25 and chlorophyll content (Croft et al, ; Houborg et al, ) and between chlorophyll content and MTCI (Nguy‐Robertson et al, ; Peng et al, ) are strong, more studies that directly use of MTCI for GPP modeling, such as Alton (), Boyd et al (), Dong et al (), Harris & Dash (), and Loozen et al (), will further strengthen the conclusion of this study.…”

Section: Discussionsupporting

confidence: 50%

Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Chen

Croft

et al. 2017

Geophysical Research Letters

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The magnitude and variability of the terrestrial CO2 sink remain uncertain, partly due to limited global information on ecosystem nitrogen (N) and its cycle. Without N constraint in ecosystem models, the simulated benefits from CO2 fertilization and CO2‐induced increases in water use efficiency (WUE) may be overestimated. In this study, satellite observations of a relative measure of chlorophyll content are used as a proxy for leaf photosynthetic N content globally for 2003–2011. Global gross primary productivity (GPP) and evapotranspiration are estimated under elevated CO2 and N‐constrained model scenarios. Results suggest that the rate of global GPP increase is overestimated by 85% during 2000–2015 without N limitation. This limitation is found to occur in many tropical and boreal forests, where a negative leaf N trend indicates a reduction in photosynthetic capacity, thereby suppressing the positive vegetation response to enhanced CO2 fertilization. Based on our carbon‐water coupled simulations, enhanced CO2 concentration decreased stomatal conductance and hence increased WUE by 10% globally over the 1982 to 2015 time frame. Due to increased anthropogenic N application, GPP in croplands continues to grow and offset the weak negative trend in forests due to N limitation. Our results also show that the improved WUE is unlikely to ease regional droughts in croplands because of increases in evapotranspiration, which are associated with the enhanced GPP. Although the N limitation on GPP increase is large, its associated confidence interval is still wide, suggesting an urgent need for better understanding and quantification of N limitation from satellite observations.

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Section: Discussionsupporting

confidence: 50%

Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Chen

Croft

et al. 2017

Geophysical Research Letters

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“…The consistent outperformance of MTCI compared to other VIs for both the B-K sub-region and the 1AF region is likely due in part to its greater sensitivity to canopy chlorophyll content [15,24]. Potentially more important is the fact that MTCI is much less affected by atmospheric conditions because its calculation is based on the difference in reflectance between two nearby bands that will be similarly affected by atmospheric scattering [15].…”

Section: Discussionmentioning

confidence: 99%

Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa

et al. 2017

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Accurate measurements of crop production in smallholder farming systems are critical to the understanding of yield constraints and, thus, setting the appropriate agronomic investments and policies for improving food security and reducing poverty. Nevertheless, mapping the yields of smallholder farms is challenging because of factors such as small field sizes and heterogeneous landscapes. Recent advances in fine-resolution satellite sensors offer promise for monitoring and characterizing the production of smallholder farms. In this study, we investigated the utility of different sensors, including the commercial Skysat and RapidEye satellites and the publicly accessible Sentinel-2, for tracking smallholder maize yield variation throughout a~40,000 km 2 western Kenya region. We tested the potential of two types of multiple regression models for predicting yield: (i) a "calibrated model", which required ground-measured yield and weather data for calibration, and (ii) an "uncalibrated model", which used a process-based crop model to generate daily vegetation index and end-of-season biomass and/or yield as pseudo training samples. Model performance was evaluated at the field, division, and district scales using a combination of farmer surveys and crop cuts across thousands of smallholder plots in western Kenya. Results show that the "calibrated" approach captured a significant fraction (R 2 between 0.3 and 0.6) of yield variations at aggregated administrative units (e.g., districts and divisions), while the "uncalibrated" approach performed only slightly worse. For both approaches, we found that predictions using the MERIS Terrestrial Chlorophyll Index (MTCI), which included the red edge band available in RapidEye and Sentinel-2, were superior to those made using other commonly used vegetation indices. We also found that multiple refinements to the crop simulation procedures led to improvements in the "uncalibrated" approach. We identified the prevalence of small field sizes, intercropping management, and cloudy satellite images as major challenges to improve the model performance. Overall, this study suggested that high-resolution satellite imagery can be used to map yields of smallholder farming systems, and the methodology presented in this study could serve as a good foundation for other smallholder farming systems in the world.

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“…This noise source would most likely increase as the growing season progressed as tassel, ear, and stem surface areas become larger components of the canopy "total foliage" area index. In addition, the visual separation of canopy leaf area into green and non-green classes is inherently subjective and, thus, it is likely an additional noise source in the relationships developed from the data sets [25,26]. Further details on the quantification of green leaf area index at the study sites are in [27].…”

Section: Leaf Area Index Measurementmentioning

confidence: 99%

Toward Generic Models for Green LAI Estimation in Maize and Soybean: Satellite Observations

et al. 2017

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Abstract:Informative spectral bands for green leaf area index (LAI) estimation in two crops were identified and generic models for soybean and maize were developed and validated using spectral data taken at close range. The objective of this paper was to test developed models using Aqua and Terra MODIS, Landsat TM and ETM+, ENVISAT MERIS surface reflectance products, and simulated data of the recently-launched Sentinel 2 MSI and Sentinel 3 OLCI. Special emphasis was placed on testing generic models which require no re-parameterization for these species. Four techniques were investigated: support vector machines (SVM), neural network (NN), multiple linear regression (MLR), and vegetation indices (VI). For each technique two types of models were tested based on (a) reflectance data, taken at close range and resampled to simulate spectral bands of satellite sensors; and (b) surface reflectance satellite products. Both types of models were validated using MODIS, TM/ETM+, and MERIS data. MERIS was used as a prototype of OLCI Sentinel-3 data which allowed for assessment of the anticipated accuracy of OLCI. All models tested provided a robust and consistent selection of spectral bands related to green LAI in crops representing a wide range of biochemical and structural traits. The MERIS observations had the lowest errors (around 11%) compared to the remaining satellites with observational data. Sentinel 2 MSI and OLCI Sentinel 3 estimates, based on simulated data, had errors below 8%. However the accuracy of these models with actual MSI and OLCI surface reflectance products remains to be determined.

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Assessment of Canopy Chlorophyll Content Retrieval in Maize and Soybean: Implications of Hysteresis on the Development of Generic Algorithms

Cited by 97 publications

References 60 publications

Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa

Toward Generic Models for Green LAI Estimation in Maize and Soybean: Satellite Observations

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Assessment of Canopy Chlorophyll Content Retrieval in Maize and Soybean: Implications of Hysteresis on the Development of Generic Algorithms

Cited by 97 publications

References 60 publications

Nitrogen Availability Dampens the Positive Impacts of CO2 Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Nitrogen Availability Dampens the Positive Impacts of CO2 Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa

Toward Generic Models for Green LAI Estimation in Maize and Soybean: Satellite Observations

Contact Info

Product

Resources

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Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles

Nitrogen Availability Dampens the Positive Impacts of CO₂ Fertilization on Terrestrial Ecosystem Carbon and Water Cycles