A TECHNIQUE OF SPATIO-TEMPORAL ANALYSIS OF DARKNEEDLE STANDS DESICCATION BASED ON LANDSAT REMOTE SENSING DATA

2011 ◽  
Author(s):  
Sergei Im
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Temporal Analysis ◽  
Sensing Data ◽  
Spatio Temporal

scholarly journals Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran

2015 ◽  
Vol 18 (1) ◽  
pp. 35-52 ◽  
Author(s):  
Mohsen Dadras ◽  
Helmi Z.M. Shafri ◽  
Noordin Ahmad ◽  
Biswajeet Pradhan ◽  
Sahabeh Safarpour
Keyword(s):  
Remote Sensing ◽  
Urban Growth ◽  
Remote Sensing Data ◽  
Temporal Analysis ◽  
Sensing Data ◽  
Spatio Temporal ◽  
Bandar Abbas

scholarly journals A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2333
Author(s):  
Lilu Zhu ◽  
Xiaolu Su ◽  
Yanfeng Hu ◽  
Xianqing Tai ◽  
Kun Fu
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Temporal Correlation ◽  
Local Association ◽  
Sensing Data ◽  
Multi Scale ◽  
Correlation Networks ◽  
Efficient Integration ◽  
Spatio Temporal ◽  
Query Algorithm

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.

Sign in / Sign up

Export Citation Format

Share Document