We present a problem for benchmarking the robustness of cellular up-links, in an automatic weather station (AWS) testbed. Based on the problem, we conduct a small-scale measurement study of robustness, where the AWS i...We present a problem for benchmarking the robustness of cellular up-links, in an automatic weather station (AWS) testbed. Based on the problem, we conduct a small-scale measurement study of robustness, where the AWS is equipped with four (4) cellular modems for weather data delivery. The effectiveness of up-links is challenging because of overlapping spatial-temporal factors such as the presence of good reflectors that lead to multi-path effects, interference, network load or other reasons. We argue that, there is a strong need for independent assessments of their robustness, to perform end-to-end network measurement. However, it is yet difficult to go from a particular measurement to an assessment of the entire network. We extensively measure the variability of Radio Signal Strength (RSSI) as link metric on the cellular modems. The RSSI is one of the important link metrics that can determine the robustness of received RF signals, and explore how they differed from one another at a particular location and instant time. We also apply the statistical analysis that quantifies the level of stability by considering the robustness, referring short-term variation, and determines good up-link in comparison to weak one. The results show that the robustness of cellular up-links exists for an unpredictable period of time and lower than one could hope. More than 50% of up-links are intermittent. Therefore, we plan to extend our work by exploring RSSI thresholds, to develop a classification scheme supporting a decision whether a link is either intermittent or not. This will help in normalizing the level of stability, to design the RSSI estimation metric for the robust routing protocol in weather data networks.展开更多
Grassland degradation is influenced by climate change and human activities,and has become a major obstacle for the development of arid and semi-arid areas,posing a series of environmental and socio-economic problems.A...Grassland degradation is influenced by climate change and human activities,and has become a major obstacle for the development of arid and semi-arid areas,posing a series of environmental and socio-economic problems.An in-depth understanding of the inner relations among grassland vegetation dynamics,climate change,and human activities is therefore greatly significant for understanding the variation in regional environmental conditions and predicting future developmental trends.Based on MODIS(moderate resolution imaging spectroradiometer)NDVI(normalized difference vegetation index)data from 2000 to 2020,our objective is to investigate the spatiotemporal changes of NDVI in the Xilin Gol grassland,Inner Mongolia Autonomous Region,China.Combined with 12 natural factors and human activity factors in the same period,the dominant driving factors and their interactions were identified by using the geographic detector model,and multiple scenarios were also simulated to forecast the possible paths of future NDVI changes in this area.The results showed that:(1)in the past 21 a,vegetation cover in the Xilin Gol grassland exhibited an overall increasing trend,and the vegetation restoration(84.53%)area surpassed vegetation degradation area(7.43%);(2)precipitation,wind velocity,and livestock number were the dominant factors affecting NDVI(the explanatory power of these factors exceeded 0.4).The interaction between average annual wind velocity and average annual precipitation,and between average annual precipitation and livestock number greatly affected NDVI changes(the explanatory power of these factors exceeded 0.7).Moreover,the impact of climate change on NDVI was more significant than human activities;and(3)scenario analysis indicated that NDVI in the Xinlin Gol grassland increased under the scenarios of reduced wind velocity,increased precipitation,and ecological protection.In contrast,vegetation coverage restoration in this area was significantly reduced under the scenarios of unfavorable climate conditions and excessive human activities.This study provides a scientific basis for future vegetation restoration and management,ecological environmental construction,and sustainable natural resource utilization in this area.展开更多
文摘We present a problem for benchmarking the robustness of cellular up-links, in an automatic weather station (AWS) testbed. Based on the problem, we conduct a small-scale measurement study of robustness, where the AWS is equipped with four (4) cellular modems for weather data delivery. The effectiveness of up-links is challenging because of overlapping spatial-temporal factors such as the presence of good reflectors that lead to multi-path effects, interference, network load or other reasons. We argue that, there is a strong need for independent assessments of their robustness, to perform end-to-end network measurement. However, it is yet difficult to go from a particular measurement to an assessment of the entire network. We extensively measure the variability of Radio Signal Strength (RSSI) as link metric on the cellular modems. The RSSI is one of the important link metrics that can determine the robustness of received RF signals, and explore how they differed from one another at a particular location and instant time. We also apply the statistical analysis that quantifies the level of stability by considering the robustness, referring short-term variation, and determines good up-link in comparison to weak one. The results show that the robustness of cellular up-links exists for an unpredictable period of time and lower than one could hope. More than 50% of up-links are intermittent. Therefore, we plan to extend our work by exploring RSSI thresholds, to develop a classification scheme supporting a decision whether a link is either intermittent or not. This will help in normalizing the level of stability, to design the RSSI estimation metric for the robust routing protocol in weather data networks.
基金supported by the National Natural Science Foundation of China(31500384,31971464)the Young Science and Technology Talents Support Program in Inner Mongolia Autonomous Region(NJYT-19-B31)the Liaoning Province Joint Fund Project(2020-MZLH-11)。
文摘Grassland degradation is influenced by climate change and human activities,and has become a major obstacle for the development of arid and semi-arid areas,posing a series of environmental and socio-economic problems.An in-depth understanding of the inner relations among grassland vegetation dynamics,climate change,and human activities is therefore greatly significant for understanding the variation in regional environmental conditions and predicting future developmental trends.Based on MODIS(moderate resolution imaging spectroradiometer)NDVI(normalized difference vegetation index)data from 2000 to 2020,our objective is to investigate the spatiotemporal changes of NDVI in the Xilin Gol grassland,Inner Mongolia Autonomous Region,China.Combined with 12 natural factors and human activity factors in the same period,the dominant driving factors and their interactions were identified by using the geographic detector model,and multiple scenarios were also simulated to forecast the possible paths of future NDVI changes in this area.The results showed that:(1)in the past 21 a,vegetation cover in the Xilin Gol grassland exhibited an overall increasing trend,and the vegetation restoration(84.53%)area surpassed vegetation degradation area(7.43%);(2)precipitation,wind velocity,and livestock number were the dominant factors affecting NDVI(the explanatory power of these factors exceeded 0.4).The interaction between average annual wind velocity and average annual precipitation,and between average annual precipitation and livestock number greatly affected NDVI changes(the explanatory power of these factors exceeded 0.7).Moreover,the impact of climate change on NDVI was more significant than human activities;and(3)scenario analysis indicated that NDVI in the Xinlin Gol grassland increased under the scenarios of reduced wind velocity,increased precipitation,and ecological protection.In contrast,vegetation coverage restoration in this area was significantly reduced under the scenarios of unfavorable climate conditions and excessive human activities.This study provides a scientific basis for future vegetation restoration and management,ecological environmental construction,and sustainable natural resource utilization in this area.
