The models of the accuracy loss during rasterizing landuse vector data with multi-scale grid size

Author(s):  
Yang Cunjian ◽  
Liu Jiyuan ◽  
Zhang Zengxiang
Keyword(s):  
2020 ◽  
Vol 206 ◽  
pp. 03018
Author(s):  
Jia Zhang ◽  
Xiulian Wang ◽  
Xiaotong Zhang ◽  
Xiaofei Bai ◽  
Qiang Chen

In the face of ever-growing and complex massive multi-source spatiotemporal data, the traditional vector data model is increasingly difficult to meet the needs of efficient data organization, management, calculation and analysis. Based on the simple and widely used geographic grid data organization model, this paper designs a technical method to convert vector data into multi-scale grid data, establishes a unified, standardized and seamless land spatial grid data model, and analyses the area accuracy of multi-scale grid data. Practice shows that the model can better meet the needs of multi-scale geospatial information integration and analysis, and it is easy to carry out distributed data processing, which provides technical support for the efficient organization, fusion and analysis of spatiotemporal data.


Author(s):  
Rahul Neware ◽  
Mansi Thakare

The technique of obtaining information or data about any feature or object from afar, called in technical parlance as remote sensing, has proven extremely useful in diverse fields. In the ecological sphere, especially, remote sensing has enabled collection of data or information about large swaths of areas or landscapes. Even then, in remote sensing the task of identifying and monitoring of different water reservoirs has proved a tough one. This is mainly because getting correct appraisals about the spread and boundaries of the area under study and the contours of any water surfaces lodged therein becomes a factor of utmost importance. Identification of water reservoirs is rendered even tougher because of presence of cloud in satellite images, which becomes the largest source of error in identification of water surfaces. To overcome this glitch, the method of the shape matching approach for analysis of cloudy images in reference to cloud-free images of water surfaces with the help of vector data processing, is recommended. It includes the database of water bodies in vector format, which is a complex polygon structure. This analysis highlights three steps: First, the creation of vector database for the analysis; second, simplification of multi-scale vector polygon features; and third, the matching of reference and target water bodies database within defined distance tolerance. This feature matching approach provides matching of one to many and many to many features. It also gives the corrected images that are free of clouds.


2021 ◽  
Author(s):  
Yu Liu ◽  
Zhipeng Wang ◽  
Xuan Liu ◽  
Baolei Zhang

Abstract Urban morphology is a crucial contributor to urban heat island (UHI) effects. However, few studies have explored the complex effect of 2D/3D urban morphology on UHI from a multi-scale perspective. In this study, We chose the central area of Jinan city, which was commonly known as the “furnace”, as the case study area. novel 2D/3D urban morphology indexes-building coverage ratio (BCR)(for assessing the 2D building density), building volume density (BVD)( for assessing the 3D building density), and the frontal area index (FAI)(for assessing 3D ventilation conditions) were calculated and derived to investigated complexity of relationship between 2D/3D urban morphology and land surface temperature(LST) at different scales using the maximum information coefficient (MIC) and geographically weighted regression (GWR). The results indicated that (1) These newly 2D/3D urban morphology indexes as essential factors that are responsible for LST variation, BCR is the most important urban morphology index affecting the LST, followed by BVD and FAI. Importantly, the relationship between the BCR, BVD, and FAI and the LST was an inverse U-shaped curve. (2) The relationship between 2D/3D urban morphology and LST variation showed a significant scale effect. With increased grid size, the correlation between the BCR, BVD, and FAI and the LST strengthened, “inflection point” of inverse U-shaped curve was significantly declined, and their explanation rate to LST first increased and then decreased, with a maximum value at the 700-m scale. Additionally, the FAI exerted a stronger negative effect, while the BCR and BVD generally had stronger positive effects on LST as the grid size increasing. This study extends our scientific understanding of the complexity effect of urban morphology on LST and is of great practical significance for urban thermal environment regulation at multi-scale.


2016 ◽  
Vol 2016.65 (0) ◽  
pp. _227-1_-_227-2_
Author(s):  
Teppei SAIKI ◽  
Koji NAGATA ◽  
Yasuhiko SAKAI ◽  
Yasumasa ITO ◽  
Koji IWANO

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