Collaborative Spatial Multicriteria Evaluation (SME) or GIS-based Multicriteria Evaluation (GME) is an effective means for decision makers, or a particular group of people to be engaged in participatory spatial decision making, urban planning, land use assessment, environmental assessment, etc. The paper follows two key objectives. The first objective is to provide a thorough and systematic literature review of collaborative SME. Specifically, it focuses on the tasks and tools used in collaborative SME processes. The study gives an overview of single- and multiple-model, intelligent, and interactive tools. It also demonstrates the evolution of tools based on geographic information trends and discusses usability evaluation of tools. The second objective focuses on evolving and future perspectives of collaborative SME tools. It proposes new tools and modern era of collaborative SME by integrating the tools with other relevant technologies/concepts.

The need for in-depth and fast observation of waste pollutions, increase in public concerns on environmental pollution and the effect of polluted environment on the physical and mental health of people have led to participatory environmental monitoring and protection. Citizens can act as volunteer, interactive, group, logical, smart, responsible, mobile, and dispersed observers/sensors to constantly monitor their surroundings and provide real-time data of waste pollutions that are not easily remotely sensed. The concept of volunteered geographic information (VGI) can be adopted as an effective phenomenon for participatory collection of environmental pollution data. However, the research problem is how to effectively use these citizen-contributed or volunteered information for waste management analyses and decision-making processes. Consequently, the objective of the present study is to develop a VGI-based environmental decision support tool that facilitates direct involvement of the public in generating waste pollution data and provides appropriate GIS-MCDA (multicriteria decision analysis) analytical tools for waste management and decision making using the citizen-contributed data. A web-based prototype of the decision support system was developed to demonstrate the practical feasibility, applicability and some functionalities of the system for pollution-related decision analyses.

Finding an appropriate vacant lot to buy is one of the most important land marketing problems in Tehran, Iran. Typically, the land selection and purchase processes in Tehran city are based on face-to-face meetings. Despite the face-to-face land sale and purchase strategies, a few online geo-marketing or real-estate websites have been developed. However, these geo-marketing real-estate web services have two main limitations. The services have focused on simple searches and selections from a set of predefined land parcels according to some basic criteria, such as land price, area etc. They do not consider spatially explicit criteria and spatial analyses relevant to a land selection process (e.g. proximity to transportation stations). The services are lacking a proper scientific foundation for spatial multi-criteria selection of land parcels. Moreover, the alternative land parcels are dynamically created by new sellers. However, the services are hard-coded based on a set of predefined land parcels and fail to support evaluation of the parcels added by new owners. To overcome these limitations, the study proposes a geo-marketing decision support system by integrating geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques into the web platform. The GIS-based MCDA tools provide appropriate analytical approaches and platforms to support decision makers/people in spatial decision-making processes based on individual values and interests. The paper demonstrates the implementation of a geo-marketing decision support system for land selection and purchase processes in district no. 22 of Tehran.