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Estimating Sub-Pixel Soybean Fraction from Time-Series MODIS Data Using an Optimized Geographically Weighted Regression Model

Qiong Hu, Yaxiong Ma, Baodong Xu, Qian Song, Huajun Tang, Wenbin Wu
2018 Remote Sensing  
The optimized GWR model by combining an automated feature selection strategy has great potential for estimating sub-pixel crop area at regional scale based on remote sensing time-series data.  ...  in China, using time-series MODIS data and high-quality calibration information derived from Landsat data.  ...  Methodology This paper is focused on using an optimized GWR model to estimate the sub-pixel soybean fractions in Heilongjiang, province based on time-series MODIS data. 4000 training points were used to  ... 
doi:10.3390/rs10040491 fatcat:gv5hqhy635ayphcu57m5wyzn3y

Revisiting the use of red and near-infrared reflectances in vegetation studies and numerical climate models

Garik Gutman, Sergii Skakun, Anatoly Gitelson
2021 Science of Remote Sensing  
The proposed LAI model is then used with data from Landsat 8, Sentinel-2 and Planet/Dove, and the results are validated with in situ LAI measurements in Ukraine.  ...  In this paper, we propose an approach to estimate biophysical variables, such as Leaf Area Index (LAI), Canopy Chlorophyll Content (CCC) and Fraction of Photosynthetically Active Radiation (FPAR) absorbed  ...  We thank Timothy Arlkebauer, UNL, for sharing leaf area index data. Planet Lab is acknowledged for data over Nebraska. S. Skakun was supported by NASA [grant numbers 80NSSC18K0336, 80NSSC18M0039].  ... 
doi:10.1016/j.srs.2021.100025 fatcat:4qwzf2nbabbn5pvnjvz55zejeu

Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Qinchuan Xin, Mark Broich, Andrew E. Suyker, Le Yu, Peng Gong
2015 Agricultural and Forest Meteorology  
Annual GPP derived from inventory data (1848.4 ± 298.1 gC m −2 y −1 for corn and 908.9 ± 166.3 gC m −2 y −1 for soybean) are consistent with modeled GPP (1887.8 ± 229.8 gC m −2 y −1 for corn and 849.1  ...  In this study, we evaluate cropland ε * GPP in the MODIS Gross Primary Productivity (GPP) model (MOD17) using in situ measurements and inventory datasets across the Midwestern US.  ...  The MOD17 model is used to provide GPP/NPP estimates from MODIS data at 8-day and yearly time steps.  ... 
doi:10.1016/j.agrformet.2014.11.004 fatcat:i3vnzn4ke5d7phxuzkc5aqsk6u

Application of A Simple Landsat-MODIS Fusion Model to Estimate Evapotranspiration over A Heterogeneous Sparse Vegetation Region

Sajad Jamshidi, Shahrokh Zand-Parsa, Mojtaba Naghdyzadegan Jahromi, Dev Niyogi
2019 Remote Sensing  
To reduce the bias, the fusion model was modified to be applicable pixel-wise (i.e., implementing specific pixels for generating outputs), and an NDVI-based (Normalized Difference Vegetation Index) coefficient  ...  The fusion model performance was evaluated, and experiments were undertaken to investigate the frequency for updating Landsat-MODIS data into the fusion model during the growing season, to maintain model  ...  Acknowledgments: We gratefully acknowledge our colleague Mojtaba Pakparvar from Fars Agricultural and Natural Resources Research and Education Center, Shiraz, Iran for providing in-situ data that immensely  ... 
doi:10.3390/rs11070741 fatcat:daktkafznfbjhjs3fyzqi4peki

Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets

Clement Atzberger, Felix Rembold
2013 Remote Sensing  
We evaluate neural networks as a modeling tool for sub-pixel crop acreage estimation.  ...  When combined with current and future sensors, such as MODIS and Sentinel-3, the unmixing of AVHRR data can help in the building of an extended time series of crop distributions and cropping patterns dating  ...  Regression tree analysis was used by Chang et al. (2007) [9] for the percentage of the corn and soybean area mapping using 500-m MODIS time series dataset.  ... 
doi:10.3390/rs5031335 fatcat:ccl6xdizz5gwbghbz4s22ze2t4

Evaluation of modelled net primary production using MODIS and landsat satellite data fusion

Steven Jay, Christopher Potter, Robert Crabtree, Vanessa Genovese, Daniel J. Weiss, Maggi Kraft
2016 Carbon Balance and Management  
The proportion of each Landsat land cover type within each 0.004 degree resolution CASA pixel was used to influence the ecosystem model result by a pure-pixel interpolation method.  ...  Results: Seventeen Ameriflux tower flux records spread across the country were combined to evaluate monthly NPP estimates from the modified CASA model.  ...  This sub pixel analysis provides the opportunity to estimate NPP values without using the assumption that a MODIS pixel is a homogenous land cover as previous estimates have done [22, 26] .  ... 
doi:10.1186/s13021-016-0049-6 pmid:27330549 pmcid:PMC4889621 fatcat:o5eahfk6jne5llow4dpv4mquga

Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics

Jan Dempewolf, Bernard Adusei, Inbal Becker-Reshef, Matthew Hansen, Peter Potapov, Ahmad Khan, Brian Barker
2014 Remote Sensing  
We also tested deriving wheat area from the same MODIS time series using a regression-tree approach.  ...  Wheat yield was derived by regressing reported yield values against time series of four different peak-season MODIS-derived vegetation indices.  ...  wheat data layers; Peter Potapov developed the application for mapping wheat using time-series Landsat images; Ahmad Khan classified Landsat data for wheat used for training and contributed local expert  ... 
doi:10.3390/rs6109653 fatcat:rnu2dgd2xjaqrek4cxiwizvoay

How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

Yanghui Kang, Mutlu Özdoğan, Samuel Zipper, Miguel Román, Jeff Walker, Suk Hong, Michael Marshall, Vincenzo Magliulo, José Moreno, Luis Alonso, Akira Miyata, Bruce Kimball (+1 others)
2016 Remote Sensing  
Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator.  ...  This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.  ...  Since MODIS has a coarse resolution of 1 km, which is larger than most of the soybean and maize fields, the LAI time series used average values of only the pure maize or soybean pixels, which are defined  ... 
doi:10.3390/rs8070597 pmid:30002923 pmcid:PMC6038712 fatcat:ynkvkxleejgf7nh56i52qx4ch4

Scaling net primary production to a MODIS footprint in support of Earth observing system product validation

D. P. Turner, S. Ollinger, M.-l. Smith, O. Krankina, M. Gregory
2004 International Journal of Remote Sensing  
Release of an annual global terrestrial net primary production (NPP) data layer has begun in association with the Moderate Imaging Spectroradiometer (MODIS) sensor, a component of the NASA Earth Observing  ...  Generally, the optimal procedure for scaling NPP to a MODIS footprint will depend on local vegetation type, the scale of spatial heterogeneity, and available resources.  ...  The workshop was supported by the US LTER Network Office and by the NASA Terrestrial Ecology Program.  ... 
doi:10.1080/0143116031000150013 fatcat:x2hhctcobrdbnh5melgobc46hy

Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion

Yun Yang, Martha C. Anderson, Feng Gao, Christopher R. Hain, Kathryn A. Semmens, William P. Kustas, Asko Noormets, Randolph H. Wynne, Valerie A. Thomas, Ge Sun
2017 Hydrology and Earth System Sciences  
The retrieved daily ET time series agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation  ...  The fusion system ingests ET estimates from the Two-Source Energy Balance Model (TSEB) applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms  ...  images of surface temperature data and vegetation cover fraction from polar-orbiting or airborne systems, to run the TSEB at sub-pixel scales over each ALEXI pixel area.  ... 
doi:10.5194/hess-21-1017-2017 fatcat:bbuk3fben5cndikueymyt544xu

MODIS-based corn grain yield estimation model incorporating crop phenology information

Toshihiro Sakamoto, Anatoly A. Gitelson, Timothy J. Arkebauer
2013 Remote Sensing of Environment  
A crop yield estimation model using time-series MODIS WDRVI was developed.  ...  The main feature of the proposed model is the incorporation of crop phenology detection using MODIS data, called the "Shape-Model Fitting Method".  ...  Dave Scoby for providing the field measurement data related to crop phenology and biophysical parameters. We are grateful to Dr. Tetsuhisa Miwa of NIAES for his valuable comments on statistical work.  ... 
doi:10.1016/j.rse.2012.12.017 fatcat:3xz5pnvzi5azxbna4cox52hi2u

The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts

Martha C. Anderson, Cornelio A. Zolin, Paulo C. Sentelhas, Christopher R. Hain, Kathryn Semmens, M. Tugrul Yilmaz, Feng Gao, Jason A. Otkin, Robert Tetrault
2016 Remote Sensing of Environment  
accumulation (LAI from the Moderate Resolution Imaging Spectroradiometer; MODIS).  ...  The strength and timing of peak ESI-yield correlations are compared with results using remotely sensed anomalies in water supply (rainfall from the Tropical Rainfall Mapping Mission; TRMM) and biomass  ...  For example, Esquerdo et al. (2011) found that a full-season averaging window was optimal for estimating soybean yields in PR using NDVI.  ... 
doi:10.1016/j.rse.2015.11.034 fatcat:t4gsfirbczfyja6e2hjayblbqa

The potential of satellite-observed crop phenology to enhance yield gap assessments in smallholder landscapes

John M. A. Duncan, Jadunandan Dash, Peter M. Atkinson
2015 Frontiers in Environmental Science  
However, on a practical level the spatial mismatch between the resolution at which crop phenology can be estimated from satellite remote sensing data and the scale of yield variability in smallholder croplands  ...  inhibits its use in this context.  ...  Brown and de Beurs (2008) compared start-of-season estimates derived from NDVI-Arhum regression models (trained using NDVI data from AVHRR, SPOT, and MODIS sensors) with rainfall based start-of-season  ... 
doi:10.3389/fenvs.2015.00056 fatcat:kfbw6w5bdzefro4kp3fllxtpuy

Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion

Yun Yang, Martha C. Anderson, Feng Gao, Christopher R. Hain, Kathryn A. Semmens, William P. Kustas, Asko Noormets, Randolph H. Wynne, Valerie A. Thomas, Ge Sun
2016 Hydrology and Earth System Sciences Discussions  
hourly geostationary satellite data at 4-km resolution, daily 1-km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), and bi-weekly Landsat thermal data sharpened to 30-m.  ...  The fusion system ingests ET estimates from a Two-Source Energy Balance (TSEB) model applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms:  ...  images of surface temperature data and vegetation cover fraction from polar-orbiting or airborne systems, to run the TSEB at sub-pixel scales over each ALEXI pixel area.  ... 
doi:10.5194/hess-2016-198 fatcat:g2psxyelabcldazhbompg4bqie

Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping

Andrii Shelestov, Mykola Lavreniuk, Nataliia Kussul, Alexei Novikov, Sergii Skakun
2017 Frontiers in Earth Science  
Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale  ...  The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger  ...  ACKNOWLEDGMENTS This research was conducted in the framework of the "Large scale crop mapping in Ukraine using SAR and optical data fusion" Google Earth Engine Research Award funded by the Google Inc.  ... 
doi:10.3389/feart.2017.00017 fatcat:ghufyqrfgjdfzgblwxthctnk7m
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