This paper introduced the theory and approaches of building driving forcemodels revealing the changes in land utilization level by integrating RS, GPS, and GIS technologiesbased on the example of Yuanmou County of Yun...This paper introduced the theory and approaches of building driving forcemodels revealing the changes in land utilization level by integrating RS, GPS, and GIS technologiesbased on the example of Yuanmou County of Yunnan Province. We first created the land utilizationtype database, natural driving forces for land utilization database, and human driving forces forland utilization database. Then we obtained the dependent and the independent variables of changesin land utilization level by exploring various data. Lastly we screened major factors affectingchanges in land utilization level by using the powerful spatial correlation analysis and maincomponent analysis module of GIS and obtained a multivariable linear regression model of thechangesin land utilization level by using GIS spatial regression analysis module.展开更多
This year marks the40th anniversary of China’s opening up to the world.One of the key decisions during the early period after opening-up was the restoration of the national college entrance exam.As of today,China has...This year marks the40th anniversary of China’s opening up to the world.One of the key decisions during the early period after opening-up was the restoration of the national college entrance exam.As of today,China has produced nearly100million college students and6million overseas students,which provided a solid human resource background for China’s opening-up and economic growth.展开更多
为了探究中国土地利用变化驱动机制和未来土地利用状况,该文利用中国科学院资源环境科学数据库中的2000年和2005年土地利用数据,结合区域土地利用变化与影响模型CLUE-S(the conversion of land use and its effects at small regional e...为了探究中国土地利用变化驱动机制和未来土地利用状况,该文利用中国科学院资源环境科学数据库中的2000年和2005年土地利用数据,结合区域土地利用变化与影响模型CLUE-S(the conversion of land use and its effects at small regional extent)和面向地理过程动态环境模型Dinamica EGO(environment for geoprocessing objects)模拟2000-2020年中国土地利用状况,并借助于Logistic回归结果和贝叶斯估计结果,探讨了中国2000-2005年土地利用适宜性和土地利用变化的驱动力空间特征。以2005年土地利用数据对模拟结果进行验证表明,CLUE-S模型和Dinamica EGO模型在LUCC预测上与实际结果一致性较好,并且CLUE-S模型在预测总体精度上优于Dinamica EGO模型。但在土地利用变化类型的数量预测上,Dinamica EGO模型的Markov过程可以准确预测,并且Dinamica EGO模拟的土地利用变化在空间分布上与经验结果较一致。从2020年中国土地利用预测结果来看,耕地、林地、水域和建设用地将会增加,草地会出现大面积的缩减,未利用地在CLUE-S模型预测中出现增加,而在Dinamica EGO模型中减少。该文可为国土资源规划和耕地资源保护政策的制定提供科学依据。展开更多
Ganzhou Orange Industrial Clusters （GOIC for short） is mainly characterized as follows. （1）The Government＇s driving force is the key factor for the formation and development of GOIC; （2）the interaction between ...Ganzhou Orange Industrial Clusters （GOIC for short） is mainly characterized as follows. （1）The Government＇s driving force is the key factor for the formation and development of GOIC; （2）the interaction between market and industry; （3）the specific geography and natural resources act as a carrier; （4）with a strong sense of innovation; （5）it is still at the early stage of development, with a certain high cost.展开更多
文摘This paper introduced the theory and approaches of building driving forcemodels revealing the changes in land utilization level by integrating RS, GPS, and GIS technologiesbased on the example of Yuanmou County of Yunnan Province. We first created the land utilizationtype database, natural driving forces for land utilization database, and human driving forces forland utilization database. Then we obtained the dependent and the independent variables of changesin land utilization level by exploring various data. Lastly we screened major factors affectingchanges in land utilization level by using the powerful spatial correlation analysis and maincomponent analysis module of GIS and obtained a multivariable linear regression model of thechangesin land utilization level by using GIS spatial regression analysis module.
文摘This year marks the40th anniversary of China’s opening up to the world.One of the key decisions during the early period after opening-up was the restoration of the national college entrance exam.As of today,China has produced nearly100million college students and6million overseas students,which provided a solid human resource background for China’s opening-up and economic growth.
文摘为了探究中国土地利用变化驱动机制和未来土地利用状况,该文利用中国科学院资源环境科学数据库中的2000年和2005年土地利用数据,结合区域土地利用变化与影响模型CLUE-S(the conversion of land use and its effects at small regional extent)和面向地理过程动态环境模型Dinamica EGO(environment for geoprocessing objects)模拟2000-2020年中国土地利用状况,并借助于Logistic回归结果和贝叶斯估计结果,探讨了中国2000-2005年土地利用适宜性和土地利用变化的驱动力空间特征。以2005年土地利用数据对模拟结果进行验证表明,CLUE-S模型和Dinamica EGO模型在LUCC预测上与实际结果一致性较好,并且CLUE-S模型在预测总体精度上优于Dinamica EGO模型。但在土地利用变化类型的数量预测上,Dinamica EGO模型的Markov过程可以准确预测,并且Dinamica EGO模拟的土地利用变化在空间分布上与经验结果较一致。从2020年中国土地利用预测结果来看,耕地、林地、水域和建设用地将会增加,草地会出现大面积的缩减,未利用地在CLUE-S模型预测中出现增加,而在Dinamica EGO模型中减少。该文可为国土资源规划和耕地资源保护政策的制定提供科学依据。
文摘Ganzhou Orange Industrial Clusters （GOIC for short） is mainly characterized as follows. （1）The Government＇s driving force is the key factor for the formation and development of GOIC; （2）the interaction between market and industry; （3）the specific geography and natural resources act as a carrier; （4）with a strong sense of innovation; （5）it is still at the early stage of development, with a certain high cost.
