The impact of gridding artifacts on the local spatial properties of MODIS data : Implications for validation, compositing, and band-to-band registration across resolutions
By Bin Tan, Curtis E. Woodcock, Jiannan Hu, Ping Zhang, Mutlu Ozdogan, Dong Huang, Wenze Yang, Yuri Knyazikhin, Ranga B. Myneni. 2006
298 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Ecology, Media Technology
View Paper: https://www.semanticscholar.org/paper/4e8717d72e6314a0aec4d7b10fe479f61fefca80
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology
- Caroline M. Gevaert
- F. J. García-Haro
- Chelsea Cervantes
- Shilong Piao
- Qinhuo Liu
- Yang Yang
- Yuri Knyazikhin
- Arindam Samanta
In Media Technology
- Caroline M. Gevaert
- F. J. García-Haro
- Chelsea Cervantes
- Yang Yang
- Mutlu Ozdogan
- R. Nemani
- Sangram Ganguly
- George Allez
Citations in the corpus
- Analysis of Global LAI/FPAR Products from VIIRS and MODIS Sensors for Spatio-Temporal Consistency and Uncertainty from 2012–2016 (2018, background): “Many studies proposed that the comparison of products over a much larger area than their native spatial resolution is an effective way to reduce potential geolocation errors and PSF impacts [3,34,35].”
- A Pixel-Based Landsat Compositing Algorithm for Large Area Land Cover Mapping (2013, unknown): “view angle into account [47], [52].”
- A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion (2015, background): “Gridding effects and the point spread function (PSF) cause the sensor observation in any grid cell to be only partially derived from the location of the cell (Gómez-chova et al., 2011; Tan et al., 2006).”
- Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011 (2013, methodology): “Even then, a pixel-by-pixel comparison between LAI3g and field-measured LAI values scaled to LAI3g spatial resolution is not feasible because: (a) the spatial location of the satellite pixel contains uncertainties due to geo-location errors and pixel-shift errors resulting from the point spread func”
- Remote Sensing of Irrigated Agriculture: Opportunities and Challenges (2010, background): “[64] showed that gridding artifacts between satellite observations and predefined grid cells strongly influence the local spatial properties of MODIS images.”