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Mapping the world’s land status and land potential — new data products and services 2018/2019
September 19, 2018 @ 3:30 pm - 6:30 pm
Public seminar and discussion panel
Prepared by: Tom Hengl (Envirometrix BV) and Martin Herold (WUR)
Venue: Speakers Corner, IMPULSE (how to get to IMPULSE)
Target groups: researchers, start-ups, global data users…
The technology and science supporting environmental and agricultural monitoring have expanded rapidly over the last 5–10 years (Herold et al. 2016; Ouma 2016; Erb et al. 2017). These trends reflect the exponential growth of internet technology, Remote Sensing missions, LiDAR, soil spectroscopy, mobile technology and automated sensor systems. In 2013 ESA (European Space Agency) initiated Sentinel RS missions which now deliver Terabytes of real-time data on land cover dynamics, soil moisture and surface water dynamics. The German Aerospace Center (DLR) TANDEM-x project is planning a release of global land surface model (including global map of forest canopy heights) at 100 m resolution and at unprecedented vertical accuracy (Martone et al. 2018). EU CAP in 2018 is now really starting to focus on Copernicus (Land) with planned performance-based CAP payments of $19bn. If we add to this list NASA’s and JAXA’s land survey missions (e.g. Shimada et al. 2014; Yamazaki et al. 2017), it is easy to conclude that access to management-ready land data, even at the farm level, should no longer represent a limitation. All the mentioned systems are increasingly open i.e. distributing data without limitation, which if especially important for all nature conservation and land restoration projects (Turner et al. 2014; Gibbs & Salmon, 2015). It is increasingly easy to download terabytes of free remote sensing data from the web. This however implies that we will have to change our ways of data storage, management and analysis.
The presenters will describe some new data products and services that are primarily based on the latest Copernicus Land programme, JAXA’s ALOS radar and topographic missions and similar open data projects. Presentations will include live demos of the functionality and instructions on how to access new data and services. Each presentation will take 20 minutes + 10 minutes for questions. After the presentations 30 minutes are reserved for a discussion panel.
- what are the new exciting global data projects in 2018/2019?
- what are the new areas/applications that could result from these data?
- what have we learned from previous global data releases?
- how can we prepare for the big new data workflows and how can we help make these data decision-ready and application-oriented?
(Working programme under construction)
- 15:30–15:40: (T. Hengl) Introduction and overview,
- 15:40–16:10: (M. Herold) Global Land Monitoring and Mapping at high resolution (20 min + 10 min discussion),
- 16:10–16:40: (T. Collins) Technological disruptions and challenges for land restoration (20 min + 10 min discussion),
- 16:40–17:10: (T. Hengl) Mapping Potential Natural Vegetation using machine learning and legacy scientific data / GBIF records (20 min + 10 min discussion),
- 17:10–17:20: (B. MacMillan): OpenGeoHub.org virtual school on spatial analysis launch
- 17:20–17:45: Discussion panel
- 17:45–18:00: OpenGeoHub.org borrel (official launch!)
- 18:00–21:00: OpenGeoHub dinner (Creative Garden Wageningen)
Copernicus Programme https://land.copernicus.eu/
Erb, K. H., Luyssaert, S., Meyfroidt, P., Pongratz, J., Don, A., Kloster, S., … & Haberl, H. (2017). Land management: data availability and process understanding for global change studies. Global change biology, 23(2), 512-533. https://doi.org/10.1111/gcb.13443
Gibbs, H. K., & Salmon, J. M. (2015). Mapping the world’s degraded lands. Applied geography, 57, 12-21. https://doi.org/10.1016/j.apgeog.2014.11.024
Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. (2018) Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential. PeerJ 6:e5457 https://doi.org/10.7717/peerj.5457
Herold, M., See, L., Tsendbazar, N., & Fritz, S. (2016). Towards an Integrated Global Land Cover Monitoring and Mapping System. Remote Sensing, 8(12). http://dx.doi.org/10.3390/rs8121036
Martone, M., Rizzoli, P., Wecklich, C., González, C., Bueso-Bello, J. L., Valdo, P., … & Moreira, A. (2018). The global forest/non-forest map from TanDEM-X interferometric SAR data. Remote Sensing of Environment, 205, 352-373. https://doi.org/10.1016/j.rse.2017.12.002
Ouma, Y. O. (2016). Advancements in medium and high resolution Earth observation for land-surface imaging: Evolutions, future trends and contributions to sustainable development. Advances in Space Research, 57(1), 110-126. https://doi.org/10.1016/j.asr.2015.10.038
Shimada, M., Itoh, T., Motooka, T., Watanabe, M., Shiraishi, T., Thapa, R., & Lucas, R. (2014). New global forest/non-forest maps from ALOS PALSAR data (2007–2010). Remote Sensing of Environment, 155, 13-31. https://doi.org/10.1016/j.rse.2014.04.014
The Global Land Outlook (GLO): http://www.unccd.int/glo
Turner, W., Rondinini, C., Pettorelli, N., Mora, B., Leidner, A. K., Szantoi, Z., … & Koh, L. P. (2015). Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173-176. https://doi.org/10.1016/j.biocon.2014.11.048
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O’Loughlin, F., Neal, J. C., … & Bates, P. D. (2017). A high accuracy map of global terrain elevations. Geophysical Research Letters. https://doi.org/10.1002/2017GL072874