Addressing the need for improved land cover map products for policy support.

The continued increase of anthropogenic pressure on the Earth's ecosystems is degrading the natural environment and then decreasing the services it provides to humans. The type, quantity, and quality of many of those services are directly connected to land cover, yet competing demands for land continue to drive rapid land cover change, affecting ecosystem services. Accurate and updated land cover information is thus more important than ever, however, despite its importance, the needs of many users remain only partially attended. A key underlying reason for this is that user needs vary widely, since most current products - and there are many available - are produced for a specific type of end user, for example the climate modelling community. With this in mind we focus on the need for flexible, automated processing approaches that support on-demand, customized land cover products at various scales. Although land cover processing systems are gradually evolving in this direction there is much more to do and several important challenges must be addressed, including high quality reference data for training and validation and even better access to satellite data. Here, we 1) present a generic system architecture that we suggest land cover production systems evolve towards, 2) discuss the challenges involved, and 3) propose a step forward. Flexible systems that can generate on-demand products that match users' specific needs would fundamentally change the relationship between users and land cover products - requiring more government support to make these systems a reality.

Ten ways remote sensing can contribute to conservation.

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

The Spectral Species Concept in Living Color.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

Essential biodiversity variables for mapping and monitoring species populations.

Species distributions and abundances are undergoing rapid changes worldwide. This highlights the significance of reliable, integrated information for guiding and assessing actions and policies aimed at managing and sustaining the many functions and benefits of species. Here we synthesize the types of data and approaches that are required to achieve such an integration and conceptualize 'essential biodiversity variables' (EBVs) for a unified global capture of species populations in space and time. The inherent heterogeneity and sparseness of raw biodiversity data are overcome by the use of models and remotely sensed covariates to inform predictions that are contiguous in space and time and global in extent. We define the species population EBVs as a space-time-species-gram (cube) that simultaneously addresses the distribution or abundance of multiple species, with its resolution adjusted to represent available evidence and acceptable levels of uncertainty. This essential information enables the monitoring of single or aggregate spatial or taxonomic units at scales relevant to research and decision-making. When combined with ancillary environmental or species data, this fundamental species population information directly underpins a range of biodiversity and ecosystem function indicators. The unified concept we present links disparate data to downstream uses and informs a vision for species population monitoring in which data collection is closely integrated with models and infrastructure to support effective biodiversity assessment.

Wetland monitoring with Global Navigation Satellite System reflectometry.

Information about wetland dynamics remains a major missing gap in characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage. A review of current satellite methods to delineate and monitor wetland change shows some recent advances, but much improved sensing technologies are still needed for wetland mapping, not only to provide more accurate global inventories but also to examine changes spanning multiple decades. Global Navigation Satellite Systems Reflectometry (GNSS-R) signatures from aircraft over the Ebro River Delta in Spain and satellite measurements over the Mississippi River and adjacent watersheds demonstrate that inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. Advantages as well as constraints of GNSS-R are presented, and the synergy with various satellite observations are considered to achieve a breakthrough capability for multidecadal wetland dynamics monitoring with frequent global coverage at multiple spatial and temporal scales.