Agricultural opportunity costs assessment based on planting suitability:a case study in a mountain county in southwest China

Payment for ecosystem services(PES) has become an increasingly popular means of ecosystem conservation. Opportunity cost is an important factor to increase the investment efficiency of PES projects.However, the distribution of opportunity cost is usually unclear in mountainous regions due to the obvious environment changes. In this study, we developed a framework to assess the distribution of agricultural opportunity costs in mountainous regions and applied this method to Baoxing County, a typical mountainous county in Sichuan Province of southwest China. Planting suitability of 17 crops was assessed based on agricultural statistics and natural conditions data within a GIS environment.Agricultural opportunity cost was quantified with a weighted summation of farmers' willingness to cultivate and each crop's opportunity cost. Finally,specific agricultural opportunity cost was obtained according to the spatial areas of the protection programs and land use status. The results showed that agricultural opportunity costs of PES in Baoxing County were estimated to be more than $30 million,with a mean of 400.85 $/ha. Agricultural opportunity costs in mountainous regions displayed some obvious spatial variation and areas with lower agricultural opportunity costs could be selected as priority areas for PES. Our findings revealed that the planting suitability evaluation can make agricultural opportunity costs mapping more reasonable. It will be helpful for the PES programs implementation in mountainous regions.

A case-based reasoning approach for task-driven spatial-temporally aware geospatial data discovery through geoportals

There is a critical need to develop a means for fast,task-driven discovery of geospatial data found in geoportals.Existing geoportals,however,only provide metadata-based means for discovery,with little support for task-driven discovery,especially when considering spatial–temporal awareness.To address this gap,this paper presents a Case-Based Reasoning-supported Geospatial Data Discovery(CBR-GDD)method and implementation that accesses geospatial data by tasks.The advantages of the CBR-GDD approach is that it builds an analogue reasoning process that provides an internal mechanism bridging tasks and geospatial data with spatial–temporal awareness,thus providing solutions based on past tasks.The CBR-GDD approach includes a set of algorithms that were successfully implemented via three components as an extension of geoportals:ontology-enhanced knowledge base,similarity assessment model,and case retrieval nets.A set of experiments and case studies validate the CBR-GDD approach and application,and demonstrate its efficiency.