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Canopy biophysical properties play an important role in understanding forest health and productivity. Among these parameters, forest leaf area index (LAI), canopy cover fraction, and canopy chlorophyll content describe the vegetation abundance, photosynthetic capacity and primary productivity of forest stands. The new generation of remote sensing satellites such as Sentinel-2 with high spatial and temporal resolutions has provided vast opportunities for monitoring these parameters and assessing their interrelationships over vast forest landscapes. In this research, temporal Sentinel-2 data between 2017-2019 in the temperate mixed forest ecosystem of the Bavarian Forest National Park, Germany, was used to retrieve forest canopy biophysical variables. INFORM radiative transfer model was used to retrieve LAI and canopy chlorophyll content while the fraction of vegetation functional types were calculated using phenological parameters and empirical approaches. A recent landcover map of the Bavarian Forest National Park was applied to retrieve considered variables pursuant to the different land cover classes. The retrieved variables were validated using in situ measurements of LAI and canopy chlorophyll content. Primary productivity was then calculated using (i) vegetation index universal pattern decomposition approach and (ii) the process-based dynamic vegetation-terrestrial ecosystem model LPJ-GUESS model. The relationships between calculated productivities and estimated biophysical variables were then studied. Our results showed that there is a good agreement between primary productivities calculated from LPG GUESS and the decomposition approach. Among studied parameters, canopy chlorophyll content, which represents pigments and vegetation abundance within the canopy, showed a strong direct relationship with both calculated primary productivities and hence may be used to explain plant functioning. Our results also revealed that remotely sensed vegetation biophysical parameters- that are becoming more and more readily available due to the availability of Earth observation data- can be used as proxies for estimation of the primary productivity calculated using either approach. Calculation of primary productivity usually needs information about canopy life-cycle and geometry, which are often not available at large scales. The results of our study support our findings in the myVARIABLE pilot of the EuroGEOSS Showcases initiative (e-shape) on developing primary productivity as a remotely sensed- essential biodiversity variable describing ‘Ecosystem function.’

Continuous availability of Sentinel data has opened a new era for timely assessing vegetation biophysical and biochemical parameters - several identified as Essential Biodiversity Variables (EBVs) under GEOBON EBVs classes- over large areas. Such parameters like leaf area index (LAI) and chlorophyll content are important indicators of vegetation photosynthetic capacity, health, stress and productivity. While some of these relationships (e.g. the link between canopy chlorophyll content and vegetation stress) are well-studied, the relationship between plant biochemical and biophysical parameters and vegetation productivity (i.e. net primary productivity, NPP) needs further investigation. In this study, we estimated leaf area index (LAI), the fraction of vegetation functional type and canopy chlorophyll content (modulated using leaf chlorophyll content and LAI) using phenological parameters, empirical approaches and temporal Sentinel-2 data in a temperate mixed forest ecosystem of the Bavarian Forest National Park, Germany. The remotely sensed biophysical products were validated using a recent landcover map of the national park, temporal in situ measurements of LAI and chlorophyll content. The relationship between these variables and NPP calculated using vegetation index universal pattern decomposition approach was then studied to determine which of these variables is a better indicator of productivity and can be used as a proxy for estimation of NPP. Our results showed that among studied parameters, canopy chlorophyll content, which represents both leaf pigments and vegetation abundance, has a strong direct relationship with NPP and hence provide a critical understanding of plant functioning. The study demonstrates that remotely sensed vegetation biophysical parameters- that are becoming more and more readily available, thanks to the European Space Agency missions- can be used as proxies for estimation of the primary productivity, which need a wide array of canopy geometry and life-cycle dynamics, at large scales. These findings would facilitate and support the myVARIABLE pilot of the EuroGEOSS Showcases initiative (e-shape), developing primary productivity as a remotely sensed EBV describing ‘Ecosystem Physiology’ and ‘Species Physiology’.

Although the management of livestock numbers within the bounds of carrying capacity of African rangelands is a way to manage risks, both scientists and practitioners, caution against a momentary and local use of carrying capacity as a management indicator. Carrying capacity should be seen in wider spatial and temporal/seasonal context as well as in a social and economic context. Given the large numbers of conservancies across Kenya, and its Maasai Mara region in particular, with many more landowner members, it is difficult for conservancies’ managers to contextualize phenomena such as carrying capacity and market price over space and time. We report the results of an investigation in the Maasai Mara rangelands, into functional characteristics a tool for spatial-temporal carrying capacity assessment and livestock markets prices monitoring should have to provide relevant management information to conservancy managers and conservancy members. A scalable web-application called the Mara Rangeland Information System, or MARIS, was developed, which assesses, at 23 meter resolution and 10 day historic or 1-day near-future intervals, both grassland dry matter production, and consumption by 19 wildlife and livestock species, as well as rangeland carrying capacity. MARIS facilitates managers to develop scenarios by varying input variables of either grass production or consumption, or by drawing different management blocks on a carrying capacity map assessing different management practices under scenarios of rainfall. Managers can relate the carrying capacity scenarios to offtake prices at different markets that MARIS monitors over time. After testing MARIS in 6 workshop iterations across the whole development process, Maasai Mara rangeland managers concluded that the prototype is ready for pilot use in management plan development.

Primary productivity is recognized as an Essential Biodiversity Variables (EBVs) under EBVs ‘Ecosystem Function’ class by GEOBON. According to existing literature, primary productivity has been one of the most important applications attempted by satellite remote sensing. The wide array of canopy geometry and life-cycle dynamics at large scales makes the estimation of primary production from remote sensing data very challenging. Primary productivity is either directly or indirectly linked to a number of other remote sensing- enabled biodiversity products including canopy chlorophyll content, leaf fraction exposed to light, absorbed photosynthetic active radiation, leaf area index and land use/cover change which are critical to understanding plant functioning. In the myVARIABLE pilot of the EuroGEOSS Showcases initiative (e-shape), we aim to develop primary productivity as an RS-EBV describing ‘Ecosystem Physiology’ and ‘Species Physiology’, being calibrated and validated by European observation networks including eLTER and other in situ data to support delivery at European level. Estimation of primary productivity involves using process-based models, semi-empirical light use efficiency (LUE) models or statistical models. The complexity and uncertainty of parameterization of process-based models, underlying assumptions in LUE models and dependency of statistical models to altering environmental conditions will be evaluated and assessed in order to propose and select the best approach for estimation of primary productivity at the European level using Sentinel-2 data.

Earth observation data is an ideal platform for capturing change in biodiversity at various resolutions, both spatially and temporally, while GEOBON creates an explicit structure for monitoring biodiversity by proposing EBV candidates. It is not only important to generate remote sensing (RS)-enabled biodiversity products using high-resolution data, but more than ever, it is necessary to address the biodiversity loss at the global scale from satellite acquisitions. In this regard, under the biodiversity pilot of the NextGEOSS initiative, the ITC biodiversity community portal (http://nextgeoss.itc.utwente.nl/ebv/) provides a self-service framework to generate RS-enabled biodiversity products for better understanding of biodiversity loss and ecosystem changes for the remote sensing and biodiversity communities. In addition, the WENR Biodiversity community portal (https://www.synbiosys.alterra.nl/nextgeoss) applies the RS-enabled biodiversity products as predictors, as well as in situ vegetation plot data for EUNIS habitat suitability modelling. Different users, including research and development institutions, public and private stakeholders, and decision-makers, are also making use of these resources. Currently, users can access the ITC Biodiversity community portal to generate Leaf Area Index as an RS-enabled biodiversity product in GEOBON EBV class ‘Ecosystem Function’, and also as one of the most important vegetation biophysical variable on a global scale using high-resolution satellite data (Sentinel-2, 20m) processed online using Cloud services (Terradue Cloud service). Also, under the EuroGEOSS project, additional remote sensing biodiversity products (Net primary productivity, chlorophyll content, habitat type, and fragmentation) are being moved and mirrored from the ITC biodiversity community portal to the GEOBON biodiversity portal, where they will be permanently available for use by the biodiversity and remote sensing communities.

EBVs have been proposed as a layer between biodiversity observation and biodiversity indicators, used in policy. More specifically, EBV classes – such as species traits, species populations, ecosystem functions as well as ecosystem structure – are being implemented by ecologists to identify global monitoring priorities. To support this there is an urgent need for remote sensing enabled EBVs to fill the spatial and temporal gaps between in situ observation data of biodiversity. In other words, without remotely sensed synoptic, systematic and continuous observations, a global framework for monitoring biodiversity cannot exist. Several RS-EBVs are anticipated to be derived from satellite remote sensing, because satellite remote sensing is the only methodology able to provide a global coverage and continuous measures across space at relatively high spatial and temporal resolutions. Habitats are very significant as an indicator for biodiversity and habitats have a strong links to species of which many are not being monitored at all. The NextGEOSS habitat mapping suitability interactive web facility (https://www.synbiosys.alterra.nl) uses more than 1 million European in-situ vegetation plot data in combination with climate, topographic, soil data, next to RS-enabled EBVs to produce European habitat suitability maps for each EUNIS habitat type (at level 3) using the MAXENT habitat distribution model (HDM). In situ plot observation data (derived from the EVA database; http://euroveg.org/eva-database) are available for 160 EUNIS terrestrial habitats . The model can be executed by end-users by making a aselection of currently 30 predictors, comprising 7 climate parameters, 7 soil parameters, and 13 RS-EBVs (LULC, vegetation height, Inundation, Phenology, LAI). For the modelling Maxent version 3.4.1 is used. The habitat suitability model is running in the cloud on Terradue servers. Model raster output can be downloaded by the client for further processing. End-users are invited not only to use the NextGeoss community portal for finetuning European habitat suitability maps but also to give their feedback.

Many projects and research efforts implement geo-information (GI) workflows, ranging from very basic ones to complicated software processing chains. The creation of these workflows normally needs considerable expertise and sharing them is often hampered by undocumented and non-interoperable geoprocessing implementations. We believe that the visual representation of workflows can help in the creation, sharing and understanding of software processing of geodata. In our efforts we aim at bridging abstract and concrete workflow representations for the sake of easing the creation and sharing of simple geoprocessing logic within and across projects. We have implemented a first version of our workflow approach in one of our current projects. MARIS, the Mara Rangeland Information System, is being developed in the Mau Mara Serengeti SustainableWater Initiative (MaMaSe). It is a web client that uses the Integrated Land and Water Information System (ILWIS), our open source Remote Sensing and GIS software. It aims to integrate historic, near real time and near future forecast of rainfall, biomass, carrying capacity and livestock market information for the sustainable management of rangelands by conservancies in the Maasai Mara in Kenya. More importantly it aims to show results of a carrying capacity model implemented in a comprehensive geoprocessing workflow. In this paper we briefly describe our software and show the workflow implementation strategy and discuss the innovative aspects of our approach as well as our project evaluation and the opportunities for further grounding of our software development.

In NextGEOSS Biodiversity Pilot WP 6.2.1, we focus on creating the NextGEOSS European remote sensing-enabled EBVs (RS enabled-EBVs) data-hub by identifying and populating available RS-enabled EBVs products. 123 variables were compiled as EBV candidates for five out of six EBV classes, as the genetic composition cannot be measured using remote sensing data. All EBV candidates were prioritized based on different criteria and observation requirements including relevancy to Aichi biodiversity targets, availability through remote sensing data (i.e., feasibility), and a measure of accuracy and maturity of remote sensing technologies and techniques. The 30 highest-prioritized RS-enabled EBVs were selected, and from these available RS-enabled EBVs products were identified with special consideration to their spatial resolution and scales. Metadata was created for each considered RS- enabled EBVs products with respect to the data provider and inserted in the NextGEOSS data-hub

The poster summarizes the implementation of the Innovative Pilot on Biodiversity; WP 6.2.1 developed within NextGEOSS project. The pilot focuses on generating remote sensing –enabled essential biodiversity variables (RS-enabled EBVs) by means of high- resolution satellite data using an empirical approach. From the RS-enabled EBVs, which were initially proposed to be derived from high-resolution satellite data, leaf area index (LAI) was selected as one of the most important vegetation biophysical parameters as well as the EBVs. Sentinel-2 data (Level-2A product) was used and further LAI was retrieved using the relationship between LAI and Enhanced Vegetation Index

In NextGEOSS Biodiversity Pilot WP 6.2.1, we focus on creating the NextGEOSS European remote sensing-enabled EBVs (RS enabled-EBVs) data-hub by identifying and populating available RS-enabled EBVs products. 123 variables were compiled as EBV candidates for five out of six EBV classes, as the genetic composition cannot be measured using remote sensing data. All EBV candidates were prioritized based on different criteria and observation requirements including relevancy to Aichi biodiversity targets, availability through remote sensing data (i.e., feasibility), and a measure of accuracy and maturity of remote sensing technologies and techniques. The 30 highest-prioritized RS-enabled EBVs were selected, and from these available RS-enabled EBVs products were identified with special consideration to their spatial resolution and scales. Metadata was created for each considered RS-enabled EBVs products with respect to the data provider and inserted in the NextGEOSS data-hub.

Continuous monitoring on farming practices is urgently needed provided the challenges faced by rice fields. Information of seasonal parameters supplies crucial inputs for monitoring rice fields as well as improving other applications, such as biomass monitoring, yield estimation, integrated pest management, irrigation water management, and precision farming. We extracted the heading stages using multi-temporal MODerate resolution Imaging Spectroradiometer (MODIS) imageries in rice fields in northern districts of West Java, Indonesia. The spatial distribution of the heading stages in the whole year suggests complex cropping pattern of rice fields in West Java. The monthly average of EVI shows that green waves move northward as the results of stipulated cropping calendar. The Root Mean Square Error (RMSE) for the heading stages is 12.77 days. The heading stages periods of most rice fields are from the middle of February to the middle of March and from the middle of June to the middle of July for rendeng and gadu, consecutively. The findings provide timely and cost effective information for monitoring rice fields.

Projectnr.: 173081.

Over de rol van de media tijdens oorlogen, conflict- en rampsituaties citeerde NRC Handelsblad op 7 maart 1995 de toenmalige minister van Defensie Joris Voorhoeve: "Pas als televisiecamera's het leed in de huiskamer brengen, komt de internationale gemeenschap op gang". En, zo vervolgde hij ietwat somber: "Dat is vaak te laat". Maar weinig mensen zullen het met deze opvatting van de minister oneens zijn. Immers, voordat de publieke opinie kan worden gemotiveerd hulp te bieden en voordat iiberhaupt kan worden bepaald welke hulp noodzakelijk is, onverschillig of dat bij een natuurramp of een gewapend treffen is, zal er eerst bekendheid aan zo'n gebeurtenis moeten worden gegeven. De rol van de media is daarbij meervoudig: zij confronteren en verbinden het westerse geweten met het lijden in ramp- en oorlogsgebieden, en zij zijn zodoende degene die het menselijk leed dat voortvloeit uit zo'n ramp, ongeluk of oorlog op de publieke agenda plaatsen.