For effective REDD+ implementation with multiple readiness activities, agents and drivers of deforestation and forest degradation needs to be identified appropriately. This study examined how such identification can b...For effective REDD+ implementation with multiple readiness activities, agents and drivers of deforestation and forest degradation needs to be identified appropriately. This study examined how such identification can be utilized for instituting REDD+ activities design. We examined this question by using satellite imagery analysis and socioeconomic surveying around Gunung Palung National Park in Indonesia. After recognizing the deforestation rate in the area, the characteristics of agents and drivers of deforestation were explored by using statistical analysis. Several canonical discriminant analyses revealed that the agents and drivers could be classified effectively by using socioeconomic type rather than ethnic groups or geographical location. A principal component analysis and the associated scatter diagrams showed that various agents and drivers exist in a given area within the study region. Finally, these efforts led to the suggestion of options for REDD+ readiness activities based on the diverse features and underlying causes.展开更多
文摘For effective REDD+ implementation with multiple readiness activities, agents and drivers of deforestation and forest degradation needs to be identified appropriately. This study examined how such identification can be utilized for instituting REDD+ activities design. We examined this question by using satellite imagery analysis and socioeconomic surveying around Gunung Palung National Park in Indonesia. After recognizing the deforestation rate in the area, the characteristics of agents and drivers of deforestation were explored by using statistical analysis. Several canonical discriminant analyses revealed that the agents and drivers could be classified effectively by using socioeconomic type rather than ethnic groups or geographical location. A principal component analysis and the associated scatter diagrams showed that various agents and drivers exist in a given area within the study region. Finally, these efforts led to the suggestion of options for REDD+ readiness activities based on the diverse features and underlying causes.
