Abstract

This paper collects data on the ecological environment of the lower Yellow River through an IoT approach and provides an in-depth analysis of the ecological remote sensing big data. An impervious fusion of multisource remote sensing data cooperation and multimachine learning algorithm cooperation is proposed. The water surface extraction method has improved the extraction accuracy of the construction land and rural settlements in the Yellow River Delta. The data system, big data management platform, and application scenarios of the environmental data resource center are designed specifically, respectively. Based on the spherical mesh information structure to sort out environmental data, an environmental data system containing data characteristics such as information source, timeliness, and presentation is formed. According to the characteristics of various types of environmental data, the corresponding data access, storage, and analysis support system is designed to form the big data management platform. Strengthen the construction of ecological interception projects for farmland receding water. Speed up the construction of sewage treatment facilities. Carry out waste and sewage pipeline network investigation, speed up the construction of urban sewage collection pipeline network, and improve the waste and sewage collection rate and treatment rate. The management platform adopts the Hadoop framework, which is conducive to the storage of massive data and the utilization of unstructured data. Combined with the relevant national policy requirements and the current environmental protection work status, the application scenarios of environmental big data in environmental decision-making, supervision, and public services are sorted out to form a complete data resource center framework. Gray correlation analysis is used to identify the key influencing factors of different types of cities to elaborate the contents of the construction of water ecological civilization in different types of cities and to build a framework of ideas for the construction of urban water ecological civilization to improve the health of urban water ecological civilization. To realize the sustainable development of the lower reaches of the Yellow River, blind logging and reclamation should be avoided in the process of land development, and more efforts should be made to protect tamarisk scrub and reed scrub, which are vegetation communities with positive effects on the regional ecological environment. In urban planning, the proportion of green area and water area within the city should be reasonably increased, so that the city can develop towards a livable city that is more conducive to human-land harmony and sustainability.

Highlights

  • The rational use of resources and a good ecological environment are important conditions for sustainable development [1]

  • Using wetlands in central Kansas as the study area, multitemporal remote sensing data sources were used for the analysis, and the results showed that multitemporal remote sensing data can help in wetland change detection and can reflect the dynamic change of wetlands [8]

  • This chapter sorts out the types and characteristics of environmental data and maps the concept of big data to the environmental field, clarifies the concept of environmental big data in this paper, and compares the differences and correlations between environmental big data applications and traditional environmental applications

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Summary

Introduction

The rational use of resources and a good ecological environment are important conditions for sustainable development [1]. Satellite remote sensing technology, which can provide spatially continuous surface image data, has been used as an important tool for monitoring wetland dynamics, especially because of its ability to capture largescale, up-to-date temporal wetland information repetitively, making it possible to obtain satellite data on a regional or even global scale. With the continuous improvement of the level of environmental information technology and the gradual expansion of the scale of environmental data collection, the State has continuously emphasized the requirement for environmental protection departments at all levels to build environmental data resource centers for the unified collection, storage, management, and utilization of various types of environmental data At this stage, China has not yet formed a construction plan or guide for data resource centers; China’s provinces and cities are currently in the mapping stage of environmental data resource center construction design and lack research on the construction of the overall framework of environmental data resource centers. The user invokes different services in turn and can get a result of statistical analysis of data

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