Your conditions: 吴炳方
  • Big Earth Data Promotes Assessment of Even Development

    Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》

    Abstract: Uneven progresses have been widely detected among goals or regions in global sustainable development, which are ascribed to the heterogeneous resource and environmental conditions and trade-offs among goals. In-depth understanding and efforts to reduce such uneven progresses are essential for the holistic achievement of the sustainable development goals (SDGs). This study discusses how bBig Earth Data supports the assessment of the even development among targets and regions by pointing out its advantages in providing high-frequency and more timely data products with higher spatial resolution for the currently poorly achieved SDGs regarding essential human needs and environmental protection. Moreover, the Big Earth Data brings deeper insights into the pattern and cause of the uneven development and disentangles the core issues that restrict the holistic achievement of SDGs.

  • Big Earth Data Supports Sustainable Food Production: Practices and Prospects

    Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》

    Abstract: Ensuring food security is a fundamental issue for global sustainable development. Sustainable food production is the basis for food security and an effective approach to address global challenges such as climate change, land degradation, and ecological degradation. At present, there is a data gap in the monitoring and assessment of the sustainability of food production, and the supporting role of the Big Earth Data is increasingly prominent. This paper summarizes the current practice of Big Earth Data in support of sustainable food production, including the role of Earth observation technology in the monitoring of various elements of food production system, and the application of multi-source data fusion in the monitoring of comprehensive food production system and the assessment of the sustainability of food production. Based on the review, according the framework of four levers for achieving Sustainable Development Goals (SDGs), we promote two suggestions for future development on Big Earth Data in support of sustainable food production: (1) integrating Big Earth Data with multidisciplinary models to promote knowledge discovery thus supporting governance, and (2) integrating Big Earth Data with technological innovation to build intelligent agriculture for on farm sustainable food production system.

  • Big Data Methods for Environmental Data

    Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-19 Cooperative journals: 《中国科学院院刊》

    Abstract: Resource and environmental monitoring have always been an important part of land sustainable management which ground survey and remote sensing monitoring are two fundamental ways. The crowd sourcing geographic data (CSGD) brought by smart phones provides new opportunity for the ground investigation of resources and environment. Meanwhile, the rapid development of cloud computing makes it possible to allow people to process massive remote sensing data much more efficient and accurate. Compared with traditional data acquisition methods, data in the cloud is easier to acquire and process. Based on this, a big data method for environment monitoring is introduced based on CSGD and cloud-based resource data. The large amount of human resources required for traditional resource environment monitoring are no longer needed as the professional services of cloud computing are proposed. It will gradually replace the traditional governmental business on resource survey. The participation of the public avoids a large amount of investment. This approach ultimately leads to efficient and crowd-sourced resource management.