Suchergebnisse

Community-based forestry (CBF) has been promoted as a potential win-win solution for improving forest conservation and livelihood outcomes. Incorporating location-specific factors from participants' perspectives in the design and implementation of CBF has been noted as an important prerequisite for ensuring positive outcomes. This study investigates benefits and challenges of CBF perceived by participating farmers in two Community Forests (HKM – Hutan Kemasyarakatan) in Lampung, Indonesia. Two sites were chosen systematically based on their distinct biophysical characteristics. Through qualitative assessments using interviews and focus group discussions with the farmers, we found that securing land tenure is the most important motivation for them to participate in CBF and abide by the government-imposed rules and regulations. Participants in both sites have experienced increased income, as well as other benefits, such as reduced fire incidents and illegal activities. However, benefits and challenges that the two HKMs face differ and are affected by their biophysical features, such as elevation, slope, proximity to village and roads. Participants, especially in the remote HKM in high elevation, perceive long-term and poorly monitored goals, such as reforestation, unrealistic. Site-specific and targeted technical supports are needed to identify overstory tree species that can also provide livelihood benefits. We argue for explicit considerations of biophysical features for CBF site designations and technical supports that meet site specific needs. This study provides a practical pathway to ensure economic benefits of CBF, which is an important factor for promoting CBF's success.

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record. ; Skyline queries identify skyline points, the minimal set of data points that dominate all other data points in a large dataset. The main challenge with skyline queries is executing the skyline query in the shortest possible time. To address and solve skyline query performance issues, we propose a decision tree-based method known as the decision tree-based comparator (DC). This method minimizes unnecessary dominance tests (i.e., pairwise comparisons) by constructing a decision tree based on the dominance testing. DC uses dominance relations that can be obtained from the decision rules of the decision tree to determine incomparability between data points. DC can also be easily applied to improve the performance of various existing skyline query methods. After describing the theoretical background of DC and applying it to existing skyline queries, we present the results of various experiments showing that DC can improve skyline query performance by up to 23.15 times. ; Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) ; Industrial Strategic Technology Development Program funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).