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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Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery
Schepaschenko, Dmitry ; See, Linda ; Lesiv, Myroslava ; Bastin, Jean-François ; Mollicone, Danilo ; Tsendbazar, Nandin-Erdene ; Bastin, Lucy ; McCallum, Ian ; Laso Bayas, Juan Carlos ; Baklanov, Artem ; Perger, Christoph ; Dürauer, Martina ; Fritz, Steffen - \ 2019
Surveys in Geophysics 40 (2019)4. - ISSN 0169-3298 - p. 839 - 862.
The land area covered by freely available very high-resolution (VHR) imagery has grown dramatically over recent years, which has considerable relevance for forest observation and monitoring. For example, it is possible to recognize and extract a number of features related to forest type, forest management, degradation and disturbance using VHR imagery. Moreover, time series of medium-to-high-resolution imagery such as MODIS, Landsat or Sentinel has allowed for monitoring of parameters related to forest cover change. Although automatic classification is used regularly to monitor forests using medium-resolution imagery, VHR imagery and changes in web-based technology have opened up new possibilities for the role of visual interpretation in forest observation. Visual interpretation of VHR is typically employed to provide training and/or validation data for other remote sensing-based techniques or to derive statistics directly on forest cover/forest cover change over large regions. Hence, this paper reviews the state of the art in tools designed for visual interpretation of VHR, including Geo-Wiki, LACO-Wiki and Collect Earth as well as issues related to interpretation of VHR imagery and approaches to quality assurance. We have also listed a number of success stories where visual interpretation plays a crucial role, including a global forest mask harmonized with FAO FRA country statistics; estimation of dryland forest area; quantification of deforestation; national reporting to the UNFCCC; and drivers of forest change.
Conflation of expert and crowd reference data to validate global binary thematic maps
Waldner, François ; Schucknecht, Anne ; Lesiv, Myroslava ; Gallego, Javier ; See, Linda ; Pérez-Hoyos, Ana ; andrimont, Raphaël D'; Maet, Thomas De; Bayas, Juan Carlos Laso ; Fritz, Steffen ; Leo, Olivier ; Kerdiles, Hervé ; Díez, Mónica ; Tricht, Kristof Van; Gilliams, Sven ; Shelestov, Andrii ; Lavreniuk, Mykola ; Simões, Margareth ; Ferraz, Rodrigo ; Bellón, Beatriz ; Bégué, Agnès ; Hazeu, Gerard ; Stonacek, Vaclav ; Kolomaznik, Jan ; Misurec, Jan ; Verón, Santiago R. ; Abelleyra, Diego De; Plotnikov, Dmitry ; Mingyong, Li ; Singha, Mrinal ; Patil, Prashant ; Zhang, Miao ; Defourny, Pierre - \ 2019
Remote Sensing of Environment 221 (2019). - ISSN 0034-4257 - p. 235 - 246.
With the unprecedented availability of satellite data and the rise of global binary maps, the collection of shared reference data sets should be fostered to allow systematic product benchmarking and validation. Authoritative global reference data are generally collected by experts with regional knowledge through photo-interpretation. During the last decade, crowdsourcing has emerged as an attractive alternative for rapid and relatively cheap data collection, beckoning the increasingly relevant question: can these two data sources be combined to validate thematic maps? In this article, we compared expert and crowd data and assessed their relative agreement for cropland identification, a land cover class often reported as difficult to map. Results indicate that observations from experts and volunteers could be partially conflated provided that several consistency checks are performed. We propose that conflation, i.e., replacement and augmentation of expert observations by crowdsourced observations, should be carried out both at the sampling and data analytics levels. The latter allows to evaluate the reliability of crowdsourced observations and to decide whether they should be conflated or discarded. We demonstrate that the standard deviation of crowdsourced contributions is a simple yet robust indicator of reliability which can effectively inform conflation. Following this criterion, we found that 70% of the expert observations could be crowdsourced with little to no effect on accuracy estimates, allowing a strategic reallocation of the spared expert effort to increase the reliability of the remaining 30% at no additional cost. Finally, we provide a collection of evidence-based recommendations for future hybrid reference data collection campaigns.
A comparison of global agricultural monitoring systems and current gaps
Fritz, Steffen ; See, Linda ; Bayas, Juan Carlos Laso ; Waldner, François ; Jacques, Damien ; Becker-Reshef, Inbal ; Whitcraft, Alyssa ; Baruth, Bettina ; Bonifacio, Rogerio ; Crutchfield, Jim ; Rembold, Felix ; Rojas, Oscar ; Schucknecht, Anne ; Velde, Marijn Van der; Verdin, James ; Wu, Bingfang ; Yan, Nana ; You, Liangzhi ; Gilliams, Sven ; Mücher, Sander ; Tetrault, Robert ; Moorthy, Inian ; McCallum, Ian - \ 2019
Agricultural Systems 168 (2019). - ISSN 0308-521X - p. 258 - 272.
Crop area - Crop calendars - Crop production - Earth observation - Gaps - Global agricultural monitoring - In-situ data - Spatial resolution - Yield

Global and regional scale agricultural monitoring systems aim to provide up-to-date information regarding food production to different actors and decision makers in support of global and national food security. To help reduce price volatility of the kind experienced between 2007 and 2011, a global system of agricultural monitoring systems is needed to ensure the coordinated flow of information in a timely manner for early warning purposes. A number of systems now exist that fill this role. This paper provides an overview of the eight main global and regional scale agricultural monitoring systems currently in operation and compares them based on the input data and models used, the outputs produced and other characteristics such as the role of the analyst, their interaction with other systems and the geographical scale at which they operate. Despite improvements in access to high resolution satellite imagery over the last decade and the use of numerous remote-sensing based products by the different systems, there are still fundamental gaps. Based on a questionnaire, discussions with the system experts and the literature, we present the main gaps in the data and in the methods. Finally, we propose some recommendations for addressing these gaps through ongoing improvements in remote sensing, harnessing new and innovative data streams and the continued sharing of more and more data.

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