Digital Forestry as a concept was developed after the Digital Earth program.The Chinese scientists were not only among the pioneers who first proposed the concept of Digital Forestry,but also contributed a lot to the ...Digital Forestry as a concept was developed after the Digital Earth program.The Chinese scientists were not only among the pioneers who first proposed the concept of Digital Forestry,but also contributed a lot to the development of Digital Forestry.Digital Forestry is a digital framework to maintain forest planting,management,using,and protect.The synergetic use of computationally-intensive quantitative methods together with information technologies is the most important foundation for the development of Digital Forestry.Under this situation,the experience of Digital Forestry development in China is relatively rich.A number of academicians,scholars,and professional administrators were involved in discussing the Digital Forestry Construction Scheme.The Project of Digital Forestry Practicability approved by the State Forestry Administration is a major instance in developing Digital Forestry standard and key techniques.By introducing a case study of Digital Forestry,this paper reviews the concept of Digital Forestry,the way turning traditional forestry into Digital Forestry,and the future development of Digital Forestry.展开更多
Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health an...Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health and proper functioning of soils to sustain life on Earth. As such, the objective of this study was to investigate the applicability of a novel evolutionary genetic optimization-based adaptive neuro-fuzzy inference system （ANFIS-EG） in predicting and mapping the spatial patterns of SOC stocks in the Eastern Mau Forest Reserve, Kenya. Field measurements and auxiliary data reflecting the soil-forming factors were used to design an ANFIS-EG model, which was then implemented to predict and map the areal differentiation of SOC stocks in the Eastern Mau Forest Reserve. This was achieved with a reasonable level of uncertainty （i.e., root mean square error of 15.07 Mg C ha-l）, hence demonstrating the applicability of the ANFIS-EG in SOC mapping studies. There is potential for improving the model performance, as indicated by the current ratio of performance to deviation （1.6）. The mapping also revealed marginally higher SOC stocks in the forested ecosystems （i.e., an average of 109.78 M C ha-1） than in the aro-ecosvstems （i.e., an average of 95.9 Mg C ha-l）.展开更多
文摘Digital Forestry as a concept was developed after the Digital Earth program.The Chinese scientists were not only among the pioneers who first proposed the concept of Digital Forestry,but also contributed a lot to the development of Digital Forestry.Digital Forestry is a digital framework to maintain forest planting,management,using,and protect.The synergetic use of computationally-intensive quantitative methods together with information technologies is the most important foundation for the development of Digital Forestry.Under this situation,the experience of Digital Forestry development in China is relatively rich.A number of academicians,scholars,and professional administrators were involved in discussing the Digital Forestry Construction Scheme.The Project of Digital Forestry Practicability approved by the State Forestry Administration is a major instance in developing Digital Forestry standard and key techniques.By introducing a case study of Digital Forestry,this paper reviews the concept of Digital Forestry,the way turning traditional forestry into Digital Forestry,and the future development of Digital Forestry.
文摘Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health and proper functioning of soils to sustain life on Earth. As such, the objective of this study was to investigate the applicability of a novel evolutionary genetic optimization-based adaptive neuro-fuzzy inference system （ANFIS-EG） in predicting and mapping the spatial patterns of SOC stocks in the Eastern Mau Forest Reserve, Kenya. Field measurements and auxiliary data reflecting the soil-forming factors were used to design an ANFIS-EG model, which was then implemented to predict and map the areal differentiation of SOC stocks in the Eastern Mau Forest Reserve. This was achieved with a reasonable level of uncertainty （i.e., root mean square error of 15.07 Mg C ha-l）, hence demonstrating the applicability of the ANFIS-EG in SOC mapping studies. There is potential for improving the model performance, as indicated by the current ratio of performance to deviation （1.6）. The mapping also revealed marginally higher SOC stocks in the forested ecosystems （i.e., an average of 109.78 M C ha-1） than in the aro-ecosvstems （i.e., an average of 95.9 Mg C ha-l）.
