Diyou Liu
Biographic Data
| ID | 6928213 |
|---|---|
| NAME | Diyou Liu |
| GIVEN NAMES | Diyou |
| FAMILY NAME | Liu |
| SIGNATURE | LIU D |
| AFFILIATIONS | China Agricultural University |
| ORCID | 0000-0002-7025-2137 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Rebound in China’s coastal wetlands following conservation and restoration
An Efficient Row Key Encoding Method with Ascii Code for Storing Geospatial Big Data in HBase
Recently, increasing amounts of multi-source geospatial data (raster data of satellites and textual data of meteorological stations) have been generated, which can play a cooperative and important role in many research works. Efficiently storing, organizing and managing these data is essential for their subsequent application. HBase, as a distributed storage database, is increasingly popular for the storage of unstructured data. The design of the…
An Unsupervised Crop Classification Method Based on Principal Components Isometric Binning
The accurate and timely access to the spatial distribution information of crops is of great importance for agricultural production management. Although widely used, supervised classification mapping requires a large number of field samples, and is consequently costly in terms of time and money. In order to reduce the need for sample size, this paper proposes an unsupervised classification method based on principal components isometric binning (PC…
An Efficient Row Key Encoding Method with Ascii Code for Storing Geospatial Big Data in HBase
Recently, increasing amounts of multi-source geospatial data (raster data of satellites and textual data of meteorological stations) have been generated, which can play a cooperative and important role in many research works. Efficiently storing, organizing and managing these data is essential for their subsequent application. HBase, as a distributed storage database, is increasingly popular for the storage of unstructured data. The design of the…
An Unsupervised Crop Classification Method Based on Principal Components Isometric Binning
The accurate and timely access to the spatial distribution information of crops is of great importance for agricultural production management. Although widely used, supervised classification mapping requires a large number of field samples, and is consequently costly in terms of time and money. In order to reduce the need for sample size, this paper proposes an unsupervised classification method based on principal components isometric binning (PC…
Rebound in China’s coastal wetlands following conservation and restoration
Geography (3 works) · Computer Science (2 works) · Data mining (2 works) · Remote sensing (2 works) · Remote Sensing in Agriculture (2 works) · Artificial Intelligence (1 works) · ASCII (1 works) · Cartography (1 works) · China (1 works) · Coastal and Marine Dynamics (1 works)