The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry o...The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.展开更多
In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal...In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.展开更多
Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and ...Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and histogram comparison of the MESSR image data of all bands for the flood season and dry season with the ER-DAS IMAGINE system, a classification model was established, which can be used to acquire the spatial distributing information of water bodies. Meanwhile a water depth index model was derived and built, and then a model for detecting the depth of water body based on the non-linear recursive analysis was presented. By the overlay analysis of the classification thematic images based on the model for extracting flood information, the flooding area and distributing information were acquired.展开更多
针对当前湿地环境监测工作耗时耗力、安全系数低、成本高和采样难度大的问题,提出基于STC89C52RC和HC-12的无人船湿地环境监测系统。系统以STC89C52RC单片机为主控单元,使用便携式移动电源供电,通过导线连接由nRF905无线通信模块、HC-1...针对当前湿地环境监测工作耗时耗力、安全系数低、成本高和采样难度大的问题,提出基于STC89C52RC和HC-12的无人船湿地环境监测系统。系统以STC89C52RC单片机为主控单元,使用便携式移动电源供电,通过导线连接由nRF905无线通信模块、HC-12无线通信模块、电机驱动系统、舵机驱动系统、水样采集系统、全球定位系统(global position system,GPS)和水质指标监测系统等构成的湿地环境监测无人船系统硬件部分,通过串口分别连接和烧写使用C#、keil软件制作上位机程序与nRF905单片机驱动程序,实现计算机通过串口通信方式完成单片机之间的无线通信和AT指令集的收发,从而达成计算机远距离实时遥控无人船进行定点水样采集与pH、浊度、温度指标监测的目的。野外实验结果证明,系统运行稳定,且水质指标测定结果精准。展开更多
基金This work was funded by the National Natural Science Foundation of China(U1603242)the Major Science and Technology Projects in Inner Mongolia,China(ZDZX2018054).
文摘The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.
文摘In recent years, grassland degradation has become one of the most important ecological problems in China under the interwoven influence of environmental and human factors. Based on the analysis of the spatial-temporal characteristics and driving factors of grassland degradation and in order to deeply understand the research status of grassland degradation monitoring methods and evaluation index system, this paper mainly investigates the research progress of grassland degradation remote sensing monitoring methods and evaluation indicators. Furthermore, this paper summarizes the more commonly used remote sensing monitoring methods and evaluation methods, analyzes the problems existing in the evaluation indicators of grassland degradation, and points out the research direction of the evaluation indicators in the future. Finally, a comprehensive remote sensing monitoring and evaluation system are established in this paper. Research findings: because of the variety of grassland degradation types and the emergence of remote sensing monitoring and evaluation methods, establishing a comprehensive remote sensing monitoring and evaluation system to classify and summarize the research methods of different grassland degradation can lay a foundation for the development of grassland degradation evaluation and monitoring in the future and provide research ideas. It is the trend of grassland degradation remote sensing research in the future.
文摘Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and histogram comparison of the MESSR image data of all bands for the flood season and dry season with the ER-DAS IMAGINE system, a classification model was established, which can be used to acquire the spatial distributing information of water bodies. Meanwhile a water depth index model was derived and built, and then a model for detecting the depth of water body based on the non-linear recursive analysis was presented. By the overlay analysis of the classification thematic images based on the model for extracting flood information, the flooding area and distributing information were acquired.
文摘针对当前湿地环境监测工作耗时耗力、安全系数低、成本高和采样难度大的问题,提出基于STC89C52RC和HC-12的无人船湿地环境监测系统。系统以STC89C52RC单片机为主控单元,使用便携式移动电源供电,通过导线连接由nRF905无线通信模块、HC-12无线通信模块、电机驱动系统、舵机驱动系统、水样采集系统、全球定位系统(global position system,GPS)和水质指标监测系统等构成的湿地环境监测无人船系统硬件部分,通过串口分别连接和烧写使用C#、keil软件制作上位机程序与nRF905单片机驱动程序,实现计算机通过串口通信方式完成单片机之间的无线通信和AT指令集的收发,从而达成计算机远距离实时遥控无人船进行定点水样采集与pH、浊度、温度指标监测的目的。野外实验结果证明,系统运行稳定,且水质指标测定结果精准。
