River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin

River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB.

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Identification of the Characteristic Scale of Fine Ground Objects: A Case Study of the Core Observation Area in the Middle Reaches of the Heihe River Basin

Remote Sensing ◽

10.3390/rs13030362 ◽

2021 ◽

Vol 13 (3) ◽

pp. 362

Author(s):

Xiuyi Wu ◽

Wenping Yu ◽

Jinan Shi ◽

Mingguo Ma ◽

Xiaolu Li ◽

...

Keyword(s):

Spatial Heterogeneity ◽

River Basin ◽

Research Area ◽

Heihe River Basin ◽

Heihe River ◽

Characteristic Scale ◽

The Core ◽

Local Variance ◽

Observation Area ◽

The Heihe River Basin

Capturing the spatial heterogeneity and characteristic scale is the key to determining the spatial patterns of land surfaces. In this research, the core observation area of the middle reaches of the Heihe River Basin was selected as the study area, and the scale identification of several typical objects was carried out by implementing experiments on moderate- and high-resolution remotely sensed ASTER and CASI NDVI images. The aim was to evaluate the potential of the local variance and semivariance analysis to characterize the spatial heterogeneity of objects, track their changes with scale, and obtain their scales. Our results show that natural objects have multiscale structures. For a single object with a recognizable size, the results of the two methods are relatively consistent. For continuously distributed samples of indistinctive size, the scale obtained by the local variance is smaller than that obtained by the semivariance. As the image resolution becomes coarser and the research scopes expand, the scales of objects are also increasing. This article also indicates that with a small research area of uniform objects, the local variance and semivariance are easy to facilitate researchers to quickly select the appropriate spatial resolution of remote sensing data according to the research area.

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