Comparative Analysis of Different Methods for Extracting Water Body Area of Miyun Reservoir and Driving Forces for Nearly 40 Years

2020 ◽  
Vol 48 (3) ◽  
pp. 451-463
Author(s):  
Yuequn Lai ◽  
Jing Zhang ◽  
Yongyu Song ◽  
Yang Cao
Keyword(s):  
Comparative Analysis ◽  
Water Body ◽  
Driving Forces ◽  
Miyun Reservoir ◽  
Body Area

Transnational Corporations as the Driving Forces Behind the World's Research and Development Activity in Terms of R&D Expenditure

2019 ◽  
pp. 73-97
Author(s):  
Kamil M. Kraj
Keyword(s):  
Comparative Analysis ◽  
Research And Development ◽  
Driving Forces ◽  
Dominant Role ◽  
Science And Technology ◽  
Transnational Corporations ◽  
Financial Data ◽  
International Level ◽  
Development Activity

As discussed in the literaturę, more and more transnational corporations (TNCs) were attaching importance to research and development (R&D) activity from the 1970s through the 2000s. This growing involvement of TNCs in R&D resulted in their dominant role in global R&D expenditure. Indeed, a comparative analysis of financial data collected for the group of the 102 largest corporate R&D spenders worldwide in 2007 showed that this group of TNCs accounted for a significant share of the worlds R&D expenditure not only in 2007 alone but also in the period of 2000-2011. Moreover, a similarity between their home countries and the countries being top R&D spenders was found; however, most of these corporations were conducting their R&D at international level. Furthermore, the analysed TNCs operated mostly in technology-intensive industries, for which the foun- dations were provided by a multidisciplinary science and technology basis.

scholarly journals Estimation of Wheat Area using Sentinel-1 and Sentinel-2 Datasets (A Comparative Analysis)

2019 ◽  
Author(s):  
Ayesha Behzad ◽  
Muneeb Aamir ◽  
Syed Ahmed Raza ◽  
Ansab Qaiser ◽  
Syeda Yuman Fatima ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Random Forest ◽  
Water Body ◽  
Supervised Classification ◽  
Wheat Crop ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Wheat Cultivation ◽  
Erdas Imagine ◽  
Sentinel 2

Wheat is the basic staple food, largely grown, widely used and highly demanded. It is used in multiple food products which are served as fundamental constituent to human body. Various regional economies are partially or fully dependent upon wheat production. Estimation of wheat area is essential to predict its contribution in regional economy. This study presents a comparative analysis of optical and active imagery for estimation of area under wheat cultivation. Sentinel-1 data was downloaded in Ground Range Detection (GRD) format and applied the Random Forest Classification using Sentinel Application Platform (SNAP) tools. We obtained a Sentinel-2 image for the month of March and applied supervised classification in Erdas Imagine 14. The random forest classification results of Sentinel-1 show that the total area under investigation was 1089km2 which was further subdivided in three classes including wheat (551km2), built-up (450 km2) and the water body (89 km2). Supervised classification results of Sentinel-2 data show that the area under wheat crop was 510 km2, however the built-up and waterbody were 477 km2, 102 km2 respectively. The integrated map of Sentinel-1 and Sentinel-2 show that the area under wheat was 531 km2 and the other features including water body and the built-up area were 95 km2 and 463 km2 respectively. We applied a Kappa coefficient to Sentinel-2, Sentinel-1 and Integrated Maps and found an accuracy of 71%, 78% and 85% respectively. We found that remotely sensed algorithms of classifications are reliable for future predictions.

scholarly journals An Integrated Investigation of Spatiotemporal Habitat Quality Dynamics and Driving Forces in the Upper Basin of Miyun Reservoir, North China

2018 ◽  
Vol 10 (12) ◽  
pp. 4625 ◽  
Author(s):  
Shengjun Yan ◽  
Xuan Wang ◽  
Yanpeng Cai ◽  
Chunhui Li ◽  
Rui Yan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Habitat Quality ◽  
Driving Force ◽  
North China ◽  
Population Change ◽  
Driving Forces ◽  
Policy Formulation ◽  
Force Analysis ◽  
Miyun Reservoir ◽  
Driving Force Analysis

Understanding changes in habitat quality and the driving forces of these changes at landscape scales is a critical part of effective ecosystem management. The present study investigated spatiotemporal habitat quality dynamics and related driving forces from 2005 to 2015 in the upper basin of Miyun Reservoir in North China by constructing an effective framework integrated InVEST and binary logistic regression models. This framework expanded the driving force analysis into an assessment of changes in habitat quality and intuitively verified the effectiveness of relevant environmental policies. The proposed method of combining the equidistant random sampling method and the method of introducing spatial lag variables in logistic regression equation can effectively solve spatial autocorrelation with a large enough number of sampling points. Overall, habitat quality improved during the study period. Spatially, a concentrated loss of habitat occurred in the southeastern part of the basin between the reservoir and mountainous areas, while other areas gradually recovered. Driving force analysis showed that lower elevation mountain land, gentle slopes, locations near rural land or roads, larger areas of grain cultivation, and areas with little population change had a higher likelihood of having changed in habitat quality in the upper basin of Miyun Reservoir. These results suggested that the present policy of protecting the ecosystem had a positive effect on improving habitat quality. In the future, the human activity management related to habitat quality needs to be strengthened. The present study would provide a reference for land use policy formulation and biodiversity conservation.

The Dynamic of Qinghai Lake Area for Remote Sensing Monitoring and the Analysis of its Driving Force

2014 ◽  
Vol 971-973 ◽  
pp. 2162-2167
Author(s):  
Bao Kang Liu ◽  
Yu E Du ◽  
Ai Jun Hu
Keyword(s):  
Remote Sensing ◽  
Water Body ◽  
Driving Force ◽  
Qinghai Lake ◽  
Lake Area ◽  
Body Area ◽  
Large Lakes ◽  
Important Means ◽  
Area Variation ◽  
Environmental Mitigation

Remote sensing (RS) and geographic information system (GIS) are an important means of monitoring water body areas for large lakes and water reservoirs. This study is based on environment and mitigation satellite CCD data characteristics of China's own R & D, using the combining method of multi-band and single-band to construct a water body identification patterns based on environmental mitigation satellite and extracting the water body area of Qinghai Lake since the September of 2008 to 2011 during April - November each year. Then the variations characters of the annual, seasonal and monthly were analyzed during 2008 and 2011. At last, induced its driving force of area variation of Qinghai Lake.

scholarly journals Monitoring the spatiotemporal dynamics of surface water body of the Xiaolangdi Reservoir using Landsat-5/7/8 imagery and Google Earth Engine

2021 ◽  
Vol 13 (1) ◽  
pp. 1290-1302
Author(s):  
Ruimeng Wang ◽  
Li Pan ◽  
Wenhui Niu ◽  
Rumeng Li ◽  
Xiaoyang Zhao ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Vegetation Index ◽  
Yellow River ◽  
Google Earth ◽  
Body Type ◽  
Body Area ◽  
Surface Water Body ◽  
Google Earth Engine ◽  
Xiaolangdi Reservoir

Abstract Xiaolangdi Reservoir is a key control project to control the water and sediment in the lower Yellow River, and a timely and accurate grasp of the reservoir’s water storage status is essential for the function of the reservoir. This study used all available Landsat images (789 scenes) and adopted the modified normalized difference water index, enhanced vegetation index, and normalized difference vegetation index to map the surface water from 1999 to 2019 in Google Earth Engine (GEE) cloud platform. The spatiotemporal characteristics of the surface water body area changes in the Xiaolangdi Reservoir in the past 21 years are analyzed from the water body type division, area change, type conversion, and the driving force of the Xiaolangdi water body area changes was analyzed. The results showed that (1) the overall accuracy of the water body extraction method was 98.86%, and the kappa coefficient was 0.96; (2) the maximum water body area of the Xiaolangdi Reservoir varies greatly between inter-annual and intra-annual, and seasonal water body and permanent water body have uneven spatiotemporal distribution; (3) in the conversion of water body types, the increased seasonal water body area of the Xiaolangdi Reservoir from 1999 to 2019 was mainly formed by the conversion of permanent water body, and the reduced permanent water body area was mainly caused by non-water conversion; and (4) the change of the water body area of the Xiaolangdi Reservoir has a weak negative correlation with natural factors such as precipitation and temperature, and population. It is positively correlated with seven indicators such as runoff and regional gross domestic product (GDP). The findings of the research will provide necessary data support for the management and planning of soil and water resources in the Xiaolangdi Reservoir.

scholarly journals Dynamic Monitoring of Surface Water Area during 1989–2019 in the Hetao Plain Using Landsat Data in Google Earth Engine

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3010 ◽  
Author(s):  
Ruimeng Wang ◽  
Haoming Xia ◽  
Yaochen Qin ◽  
Wenhui Niu ◽  
Li Pan ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Water Body ◽  
Vegetation Index ◽  
Water Area ◽  
Google Earth ◽  
Body Area ◽  
Hetao Plain ◽  
Google Earth Engine

The spatio-temporal change of the surface water is very important to agricultural, economic, and social development in the Hetao Plain, as well as the structure and function of the ecosystem. To understand the long-term changes of the surface water area in the Hetao Plain, we used all available Landsat images (7534 scenes) and adopted the modified Normalized Difference Water Index (mNDWI), Enhanced Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) to map the open-surface water from 1989 to 2019 in the Google Earth Engine (GEE) cloud platform. We further analyzed precipitation, temperature, and irrigated area, revealing the impact of climate change and human activities on long-term surface water changes. The results show the following. (1) In the last 31 years, the maximum, seasonal, and annual average water body area values in the Hetao Plain have exhibited a downward trend. Meanwhile, the number of maximum, seasonal, and permanent water bodies displayed a significant upward trend. (2) The variation of the surface water area in the Hetao Plain is mainly affected by the maximum water body area, while the variation of the water body number is mainly affected by the number of minimum water bodies. (3) Precipitation has statistically significant positive effects on the water body area and water body number, which has statistically significant negative effects with temperature and irrigation. The findings of this study can be used to help the policy-makers and farmers understand changing water resources and its driving mechanism and provide a reference for water resources management, agricultural irrigation, and ecological protection.

Going Online in the PC Graveyard

2011 ◽  
pp. 180-199 ◽  
Author(s):  
Inkyu Kang
Keyword(s):  
Comparative Analysis ◽  
Internet Use ◽  
Driving Forces ◽  
Mobile Internet ◽  
Japanese Language ◽  
Common Belief ◽  
Internet Adoption ◽  
Internet Diffusion ◽  
The Common ◽  
Internet Penetration

This chapter explores how the keitai (mobile) Internet has come to dominate Japan, marginalizing the PC-based Internet. The discussion focuses on the country’s cultural and ideological aspects that have worked as driving forces behind its mobile Internet boom. Special emphasis will be given to the validity of the common belief that the Japanese language has been a barrier to PC and Internet diffusion. This chapter argues that the Japanese language has actually encouraged rather than discouraged Internet adoption in Japan. Relying on media comparative analysis, this essay examines how Japan has developed a qualitatively different Internet use pattern that cannot be revealed in statistics like “number of Internet subscribers” or “household Internet penetration rates.”

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