The effect of weeding frequency and schedule on weeding operation time: a simulation study on a sugi (Cryptomeria japonica) plantation in Japan

This study quantified the effect of weeding frequency and weeding schedules on weeding operation time in a sugi(Cryptomeria japonica)plantation stand.A weeding operation time estimation model was developed;then the cumulative weeding operation time after six growing seasons was simulated using the developed model.The developed model included weed height,relative height of weeds to sugi,and initial planting density.The simulated cumulative weeding operation time decreased approximately 6%for each one-treatment decrease in weeding frequency.Under a three-treatment weeding frequency scenario,the simulated cumulative operation time when weeding was conducted during non-consecutive years was longer than that when weeding was conducted during three consecutive years.The results suggest that carrying out weeding treatment during consecutive years is the more effective for reduction of weeding costs.We conclude that weeding schedule as well as weeding frequency must be considered for reduction of weeding operation time.

Co-developing an international TLS network for the 3D ecological understanding of global trees:System architecture,remote sensing models,and functional prospects

Trees are spread worldwide,as the watchmen that experience the intricate ecological effects caused by various environmental factors.In order to better understand such effects,it is preferential to achieve finely and fully mapped global trees and their environments.For this task,aerial and satellite-based remote sensing(RS)methods have been developed.However,a critical branch regarding the apparent forms of trees has significantly fallen behind due to the technical deficiency found within their globalscale surveying methods.Now,terrestrial laser scanning(TLS),a state-of-the-art RS technology,is useful for the in situ three-dimensional(3D)mapping of trees and their environments.Thus,we proposed co-developing an international TLS network as a macroscale ecotechnology to increase the 3D ecological understanding of global trees.First,we generated the system architecture and tested the available RS models to deepen its ground stakes.Then,we verified the ecotechnology regarding the identification of its theoretical feasibility,a review of its technical preparations,and a case testification based on a prototype we designed.Next,we conducted its functional prospects by previewing its scientific and technical potentials and its functional extensibility.Finally,we summarized its technical and scientific challenges,which can be used as the cutting points to promote the improvement of this technology in future studies.Overall,with the implication of establishing a novel cornerstone-sense ecotechnology,the co-development of an international TLS network can revolutionize the 3D ecological understanding of global trees and create new fields of research from 3D global tree structural ecology to 3D macroecology.

Combining post-disturbance land cover and tree canopy cover from Landsat time series data for mapping deforestation,forest degradation,and recovery across Cambodia

Mapping of deforestation,forest degradation,and recovery is essential to characterize country-level forest change and formulate mitigation actions.Previous studies have mainly used a simple forest/non-forest classification after forest disturbance to identify deforestation and forest degradation.However,a more flexible approach that is applicable to different forest conditions is desirable.In this study,we examined an approach for mapping deforestation,forest degradation,and recovery using disturbance types and tree canopy cover estimates from annual Landsat time-series data from 1988 to 2020 across Cambodia.We developed models to estimate both disturbance types and tree canopy cover based on a random forest algorithm using predictor variables derived from a trajectory-based temporal segmentation approach.The estimated disturbance types and canopy cover in each year were then used in a rule-based classification of deforestation,forest degradation,and recovery.The producer’s and user’s accuracies ranged from 59.1%to 72.9%and 60.8%to 91.6%,respectively,for the forest change classes of mapping deforestation,forest degradation,and recovery.The approach developed here can be adjusted for different definitions of deforestation,forest degradation,and recovery according to research objectives and thus has the potential to be applied to other study areas.