Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 449232
Title Assessing error sources for Landsat time series analysis for tropical test sites in Viet Nam and Ethiopia
Author(s) Schultz, M.; Verbesselt, J.; Herold, M.; Avitabile, V.
Source In: Earth Resources and Environmental Remote Sensing/GIS Applications IV, 23-25 September, 2013, Dresden, Germany. - Dresden, Germany : - p. 11 - 11.
Event Dresden, Germany : Earth Resources and Environmental Remote Sensing/GIS Applications IV, Dresden, Germany, 2013-09-23/2013-09-25
Department(s) Laboratory of Geo-information Science and Remote Sensing
Publication type Contribution in proceedings
Publication year 2013
Abstract Researchers who use remotely sensed data can spend half of their total effort analysing prior data. If this data preprocessing does not match the application, this time spent on data analysis can increase considerably and can lead to inaccuracies. Despite the existence of a number of methods for pre-processing Landsat time series, each method has shortcomings, particularly for mapping forest changes under varying illumination, data availability and atmospheric conditions. Based on the requirements of mapping forest changes as defined by the United Nations (UN) Reducing Emissions from Forest Degradation and Deforestation (REDD) program, the accurate reporting of the spatio-temporal properties of these changes is necessary. We compared the impact of three fundamentally different radiometric preprocessing techniques Moderate Resolution Atmospheric TRANsmission (MODTRAN), Second Simulation of a Satellite Signal in the Solar Spectrum (6S) and simple Dark Object Subtraction (DOS) on mapping forest changes using Landsat time series data. A modification of Breaks For Additive Season and Trend (BFAST) monitor was used to jointly map the spatial and temporal agreement of forest changes at test sites in Ethiopia and Viet Nam. The suitability of the pre-processing methods for the occurring forest change drivers was assessed using recently captured Ground Truth and high resolution data (1000 points). A method for creating robust generic forest maps used for the sampling design is presented. An assessment of error sources has been performed identifying haze as a major source for time series analysis commission error. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
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