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Soil moisture is a key hydrometeorological variable that can be derived from both modeling simulations and satellite observations. This study compares Global Land Data Assimilation System (GLDAS) output over the Murray Darling Basin against retrievals from a newly developed remote sensing product using the AMSR-E sensor onboard NASA's Aqua satellite. GLDAS is comprised of a number of land surface models, two of which include the Community Land Model (CLM) and NOAH land surface scheme, which provide a temporally and spatially consistent characterization of the hydrological cycle. GLDAS derived estimates are 3-hourly products with 0.25-degree spatial resolution, while satellite based observations offer twice-daily instantaneous retrievals at similar spatial scales. The models represent different soil moisture averaging depths (roughly 2, 5, and 10 cm in CLM and 10 cm in NOAH) and retrievals from AMSR-E C-band approximate the soil moisture in the top 1.5 cm layer. The spatial distribution and coherence of soil moisture are investigated seasonally and under both wetting and drying conditions. From the spatial aspect, AMSR-E observations and GLDAS simulations show similar seasonal patterns, while simulated soil moisture is slightly higher during summer and autumn over the north-eastern Murray Darling Basin (MDB). This may be explained by the positive biases of GLDAS forcing precipitation data. From the temporal perspective, the best match between AMSR-E soil moisture and model simulations is found over the regions with strong precipitation in warm months, e.g. north-eastern MDB. Over the regions with high precipitation during cool months, AMSR-E soil moisture is systematically higher than model simulations. For the regions with extremely low annual rainfall, the peak values in soil moisture between AMSR-E and model simulations match very well, while low values of soil moisture display the greatest differences. Generally, the agreements between AMSR-E observations and GLDAS simulations vary under different wetting and drying conditions. Both of them can represent the 'true' soil moisture to some extent. How to best blend soil moisture products derived from these two different techniques, in addition to data assimilation approaches, will be explored in future research.

Designing land use plans for areas with multiple stakeholders is becoming an increasingly complex task. This paper presents a method to interactively develop land use plans with multiple stakeholders and conflicting objectives. In this method, spatial information plays a central role. Maps are used to communicate and exchange knowledge among policy-makers and stakeholders. This is done through a series of interconnected workshops, where interaction between stakeholders is prompted through the use of maps, decision support tools and an instrument called the 'touch table'. The touch table is a touch-enabled screen, which is used to support stakeholder collaboration through common visualization and spatial information handling. Three types of workshops with different map use are distinguished: Design (map as design language), Analysis (map as research model) and Negotiation (map as decision agenda). The main goal of a Design workshop is to identify problems concerning the planning of an area using spatial information to prompt knowledge exchange. Participants are invited to explore and develop land use plans using three reference plans as a defined playing field. With the help of simple drawing tools users can provide feedback digitally and design alternative plans by drawing polygons in free-form mode and subsequently allocating land use classes. In an Analysis workshop, participants are invited to evaluate and adjust any of the reference plans. To create a new plan, the reference plans are used as the canvas, on which participants can 'paint' land use changes. As users 'paint' new land uses on parcels, feedback on suitability is provided dynamically on the touch table. The main goal of a Negotiation workshop is to reach a land use plan that increases both the objective values of the stakeholders and the total value of a reference plan. Functionality is incorporated into the touch table to help participants suggest land use changes. Multi-Criteria Analysis (MCA) is used to provide feedback on the relative qualities of the plan compared to the reference situation. A multi-user interface allows participants to display on the map the parcels that are both best and worst suited for their own specific interests. Having 'negotiable' parcels shown on the map, users can trade their 'bad' parcels with each other and proceed to paint a new 'negotiated' plan. By making these trades-offs explicit, users are prompted to work as a team in a collaborative environment to reach a plan that is the best possible for all. We have tested our approach during Design, Analysis and Negotiation workshops with stakeholders of the Bodegraven polder in the Netherlands. Land use must be reallocated in Bodegraven to meet new water level conditions. Surveys conducted revealed the participants' preference for the touch table over printed maps. They liked especially the possibilities to choose and combine background maps, navigate across the area, see what others do and add qualifications to a plan. The touch table increased their awareness of new aspects of the area's problems. Participants thought it can stimulate significantly the discussions and considered it to be most suitable for government representatives.

Recent travel forecasting models have focussed upon the fact that travel is derived from the activities in which people participate, such as work, school, shopping, sport, leisure, and social events. Non-discretionary activities such as work and school may be explained by the traveller's sociodemographic characteristics and generalised travel costs, as well as long-term decisions such as a decision to move to a particular town. Participation in social and leisure activities is determined by one's friends and the groups that one is a member of, i.e., their household, their workplace/school, sporting groups, voluntary organisations and clubs. These acquaintances form part of an individual's social network: a representation of the people one interacts with. This demonstrates a shift in the activity-travel modelling field from “where” to “what” and now towards “who with”. On top of this, our changing use of ICT is influencing our activity and travel patterns, as some activities can now be replaced by online activities, and online activities can lead to actual travel. Some researchers are already looking beyond households to the influence of social networks. However, we are not aware of any agent-based urban models considering activity-travel choice of individuals. Existing work is in the conceptual or early implementation phases. The aim of this project is to develop and validate a model combining social (“who with”) and spatial (“where”) networks for investigating and predicting social activities. In this paper, we describe the design of our model. Agent-based modelling is a good fit for our model. Our system consists of different people, their relationships and interactions with each other, and their activities in and possible movement around the environment. The topology is not homogeneous and clusters may form. We have used a combination of the metamodels found in mature agent-oriented software engineering methodologies to design our model, focussing on system goals, the environment, acquaintances, roles, and services. The design successfully caters for the description of the environment, the nature of activities, and the dynamics of individuals and their networks. The individuals in our model each have an agenda, and interact and negotiate with others to schedule social activities, in particular negotiating about the nature of the activity, participants, time, and location. Existing models do not capture the actual joint decision making process behind activity scheduling, and although some work on joint decisions has been undertaken, these models focus on outcomes of interactions within households and have not considered personal social networks at large. We use existing multi-issue negotiation theory to describe an interaction design, which is shown to satisfy a number of basic properties, such as termination, liveness, and safety. Due to the current interest in predicting social activities and the changing nature of social activities due to our use of ICT, this type of model is of increasing importance to planners who need to be able to predict social activities and travel. The model is currently being implemented in Java, and will be validated using an extensive dataset of people's activity participation and personal networks, collected in Eindhoven, Netherlands. Future work includes more empirical experimentation with the protocols and implementation of and experimentation with the entire model.

Designing land use plans for areas with multiple stakeholders is becoming an increasingly complex task. This paper presents a method to interactively develop land use plans with multiple stakeholders and conflicting objectives. In this method, spatial information plays a central role. Maps are used to communicate and exchange knowledge among policy-makers and stakeholders. This is done through a series of interconnected workshops, where interaction between stakeholders is prompted through the use of maps, decision support tools and an instrument called the 'touch table'. The touch table is a touch-enabled screen, which is used to support stakeholder collaboration through common visualization and spatial information handling. Three types of workshops with different map use are distinguished: Design (map as design language), Analysis (map as research model) and Negotiation (map as decision agenda). The main goal of a Design workshop is to identify problems concerning the planning of an area using spatial information to prompt knowledge exchange. Participants are invited to explore and develop land use plans using three reference plans as a defined playing field. With the help of simple drawing tools users can provide feedback digitally and design alternative plans by drawing polygons in free-form mode and subsequently allocating land use classes. In an Analysis workshop, participants are invited to evaluate and adjust any of the reference plans. To create a new plan, the reference plans are used as the canvas, on which participants can 'paint' land use changes. As users 'paint' new land uses on parcels, feedback on suitability is provided dynamically on the touch table. The main goal of a Negotiation workshop is to reach a land use plan that increases both the objective values of the stakeholders and the total value of a reference plan. Functionality is incorporated into the touch table to help participants suggest land use changes. Multi-Criteria Analysis (MCA) is used to provide feedback on the relative qualities of the plan compared to the reference situation. A multi-user interface allows participants to display on the map the parcels that are both best and worst suited for their own specific interests. Having 'negotiable' parcels shown on the map, users can trade their 'bad' parcels with each other and proceed to paint a new 'negotiated' plan. By making these trades-offs explicit, users are prompted to work as a team in a collaborative environment to reach a plan that is the best possible for all. We have tested our approach during Design, Analysis and Negotiation workshops with stakeholders of the Bodegraven polder in the Netherlands. Land use must be reallocated in Bodegraven to meet new water level conditions. Surveys conducted revealed the participants' preference for the touch table over printed maps. They liked especially the possibilities to choose and combine background maps, navigate across the area, see what others do and add qualifications to a plan. The touch table increased their awareness of new aspects of the area's problems. Participants thought it can stimulate significantly the discussions and considered it to be most suitable for government representatives.

Soil moisture is a key hydrometeorological variable that can be derived from both modeling simulations and satellite observations. This study compares Global Land Data Assimilation System (GLDAS) output over the Murray Darling Basin against retrievals from a newly developed remote sensing product using the AMSR-E sensor onboard NASA's Aqua satellite. GLDAS is comprised of a number of land surface models, two of which include the Community Land Model (CLM) and NOAH land surface scheme, which provide a temporally and spatially consistent characterization of the hydrological cycle. GLDAS derived estimates are 3-hourly products with 0.25-degree spatial resolution, while satellite based observations offer twice-daily instantaneous retrievals at similar spatial scales. The models represent different soil moisture averaging depths (roughly 2, 5, and 10 cm in CLM and 10 cm in NOAH) and retrievals from AMSR-E C-band approximate the soil moisture in the top 1.5 cm layer. The spatial distribution and coherence of soil moisture are investigated seasonally and under both wetting and drying conditions. From the spatial aspect, AMSR-E observations and GLDAS simulations show similar seasonal patterns, while simulated soil moisture is slightly higher during summer and autumn over the north-eastern Murray Darling Basin (MDB). This may be explained by the positive biases of GLDAS forcing precipitation data. From the temporal perspective, the best match between AMSR-E soil moisture and model simulations is found over the regions with strong precipitation in warm months, e.g. north-eastern MDB. Over the regions with high precipitation during cool months, AMSR-E soil moisture is systematically higher than model simulations. For the regions with extremely low annual rainfall, the peak values in soil moisture between AMSR-E and model simulations match very well, while low values of soil moisture display the greatest differences. Generally, the agreements between AMSR-E observations and GLDAS simulations vary under different wetting and drying conditions. Both of them can represent the 'true' soil moisture to some extent. How to best blend soil moisture products derived from these two different techniques, in addition to data assimilation approaches, will be explored in future research.