Phenology-adaptive / static MODIS composites: seamless multi-annual (2005+-2) and seasonal (POS, EOS, MOS) image composites across Zambia

Published: 23-01-2017| Version 1 | DOI: 10.17632/bj7jn39ds2.1
Contributors:
David Frantz,
Achim Röder,
Marion Stellmes,
Joachim Hill

Description

This dataset contains seasonal, multi-annual MODIS reflectance composites generated across Zambia for 2005 +-2 years. The data is associated to following paper: D. Frantz, A. Röder, M. Stellmes, and J. Hill (2017): Phenology-Adaptive Pixel-Based Compositing using Optical Earth Observation Imagery. Remote Sensing of Environment 190, 331-347. DOI: 10.1016/j.rse.2017.01.002 A parametric compositing technique was employed to produce composites from very dense MODIS reflectance images (MOD09GA product, 1-2 day temporal resolution). Composites were generated for three phenological seasons: peak of season (POS), end of season (EOS) and minimum of season (MOS). Two different sets were produced: (1) phenology-adaptive composites that explicitly consider the land surface phenology of each pixel and (2) static composites that use a fixed and global target DOY representative for the seasons. The images are in Standard ENVI Format. Naming convention: 20050228_PBC_INF_zambia.dat - First 8 digits: Mean date of selected observations; the temporal sequence is POS, EOS, and MOS - PBC_INF / PBC_REF: composite criteria / reflectance composite The reflectance composites are 6-band (0.469µm, 0.555µm, 0.645µm, 0.859µm, 1.640µm, 2.130µm), 16bit bsq images. The composite criteria images are 4-band (number of observations, selected DOY, diff. to target DOY, diff. to target year), 16bit bsq images. Acknowledgements The MODIS MOD09GA data products were retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/data_access/data_pool. The MODIS MOD13Q1/MYD13Q1 data products were retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/data_access/data_pool. Land Surface Phenology was inferred from MOD13Q1/MYD13Q1 data with the Spline Analysis of Time Series (SpliTS) algorithm, courtesy of Dr. Sebastian Mader, Trier University, Trier, Germany.

Steps to reproduce

The data can be reproduced by application of the compositing techniqe described in D. Frantz, A. Röder, M. Stellmes, and J. Hill (2017): Phenology-Adaptive Pixel-Based Compositing using Optical Earth Observation Imagery. Remote Sensing of Environment 190, 331-347. DOI: 10.1016/j.rse.2017.01.002