scholarly journals Monitoring and Mathematical Model Analysis of Dynamic Changes in Land Resources Based on SAR Sensor Image

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ying Li
Keyword(s):  
Remote Sensing ◽  
Dynamic Change ◽  
Current Situation ◽  
Sensor Data ◽  
Land Resource ◽  
Land Resources ◽  
Dynamic Information ◽  
Dynamic Changes ◽  
Time Service ◽  
Change Monitoring

The monitoring and analysis of dynamic changes in land resources can detect the changes of land aimed at a single-band or multiband remote sensing image of multiple phases in a given region or target with image processing methods and can also extract the change information and realize remote sensing monitoring through the comprehensive analysis of multiphase remote sensing images. Synthetic aperture radar (SAR) image change monitoring technology, with the advantages of high resolution, high precision, real-time service, and rapid imaging, can achieve qualitative or quantitative analysis of targets and is gradually widely used in quarterly monitoring, emergency monitoring, postbatch verification, law-enforcement inspection and land inspection, and other remote sensing data acquisitions and analyses. Therefore, on the basis of summarizing the research results of previous research works, this paper expounded the current situation and significance of the researches on the monitoring and analysis of dynamic changes in land resources; elaborated the development background, current situation, and future challenges of SAR sensor data; introduced the methods and principles of band setting, polarization mode, geometric correction, and image filtering; proposed the status target identification of land resources; explored the dynamic information discovery of land resources; conducted the dynamic change monitoring of land resources based on SAR sensor data; analyzed the basis and characteristics of SAR sensor data; performed the generalization and optimization of land resource information; demonstrated the dynamic change analysis of land resources based on SAR sensor data; compared the acceptance ability and accuracy of SAR sensor data; and discussed the discovery and extraction of dynamic information of land resources. The results show that the SAR sensor data can monitor the characteristics of scattering points in land resource observation scenes and can obtain the change information of ground object by distance component and band component, so that the SAR system can make two-dimensional imaging of land resources directly in front of the receiving platform. Thus, the SAR data obtained by multisystem parameters shows great application potential in land resource monitoring, which provides the possibility of decoupling to remove land resources and surface roughness and thus provides possible solutions for land resource analysis in complex environment. The results of this paper provide a reference for the follow-up studies on the monitoring and analysis of dynamic changes in land resources based on SAR sensor data.

scholarly journals Monitoring Coastline Changes of the Malay Islands Based on Google Earth Engine and Dense Time-Series Remote Sensing Images

2021 ◽  
Vol 13 (19) ◽  
pp. 3842
Author(s):  
Yaxin Ding ◽  
Xiaomei Yang ◽  
Hailiang Jin ◽  
Zhihua Wang ◽  
Yueming Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Large Scale ◽  
Dynamic Change ◽  
Google Earth ◽  
Tidal Range ◽  
Remote Sensing Images ◽  
Data Platform ◽  
Range Observation ◽  
Change Monitoring

The use of remote sensing to monitor coastlines with wide distributions and dynamic changes is significant for coastal environmental monitoring and resource management. However, most current remote sensing information extraction of coastlines is based on the instantaneous waterline, which is obtained by single-period imagery. The lack of a unified standard is not conducive to the dynamic change monitoring of a changeable coastline. The tidal range observation correction method can be used to correct coastline observation to a unified climax line, but it is difficult to apply on a large scale because of the distribution of observation sites. Therefore, we proposed a coastline extraction method based on the remote sensing big data platform Google Earth Engine and dense time-series remote sensing images. Through the instantaneous coastline probability calculation system, the coastline information could be extracted without the tidal range observation data to achieve a unified tide level standard. We took the Malay Islands as the experimental area and analyzed the consistency between the extraction results and the existing high-precision coastline thematic products of the same period to achieve authenticity verification. Our results showed that the coastline data deviated 10 m in proportion to a reach of 40% and deviated 50 m within a reach of 89%. The overall accuracy was kept within 100 m. In addition, we extracted 96 additional islands that have not been included in public data. The obtained multi-phase coastlines showed the spatial distribution of the changing hot regions of the Malay Islands’ coastline, which greatly supported our analysis of the reasons for the expansion and retreat of the coastline in this region. These research results showed that the big data platform and intensive time-series method have considerable potential in large-scale monitoring of coastline dynamic change and island reef change monitoring.

scholarly journals Analytical review of remote sensing data sources suitable for mapping of land resource in Chernivtsi region

2013 ◽  
pp. 331-338
Author(s):  
J. Smirnov
Keyword(s):  
Remote Sensing ◽  
Key Words ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
Remote Sensing Data ◽  
Data Sources ◽  
Land Resource ◽  
Land Resources ◽  
Sensing Data ◽  
Analytical Review

In the article described the sources of remote sensing data and analyzed their suitability for involvement in the process Chernivtsi region land resources mapping. Taken into account space surveying systems of different spatial resolution and aerial photographic surveys. As a result, have been identified the best sources of data that can be used in the Chernivtsi region land resources mapping. Key words: land resources, remote sensing, satellite imagery, mapping of land resources, sources of remote sensing data.

scholarly journals Dynamic Changes Analysis of Land Resource Balance in North Maluku Province, Indonesia

2020 ◽  
Vol 37 (2) ◽  
Author(s):  
Elya Pratiwi Isti Faroh ◽  
Fatih Cinderaswari Puspaningrani ◽  
Gema Reinadova ◽  
Muhammad Rais Akbar ◽  
Novanna Dwi Septyo Anggraeni ◽  
...  
Keyword(s):  
Land Use ◽  
Carrying Capacity ◽  
Paddy Fields ◽  
Population Increase ◽  
Land Resource ◽  
Land Resources ◽  
Dynamic Changes ◽  
Land Carrying Capacity ◽  
Paddy Land ◽  
Water Nutrients

Land resources are part of nature related to the availability of water, nutrients, and food that are dynamic and play an important role in the lives of living creatures, including humans. From time to time, land use experiences changes in response to human activities that benefit their lives. This research was conducted to determine trends in land use change in North Maluku Province, Indonesia, as well as to find out the land resource balance and land carrying capacity in the province. The methods comprised a simple descriptive and quantitative analysis along with spatial analysis using GIS. The results showed that land use in North Maluku Province for paddy fields was higher than that for non-paddy land use. However, the increase in non-paddy land use was greater every year compared with the increase in paddy land use. The land resource balance in North Maluku Province in 2010–2018 also showed a decrease in non-agricultural protected forest, by 150,895.79 ha, as well as an increase in 4,286 ha of irrigated paddy fields. Meanwhile, the land carrying capacity during this same period was found to be declining at a rate of 6% per year, based on the population increase each year within a permanent land area.

scholarly journals TRACKING DYNAMIC CHANGES AND MONITORING SOCIOECONOMIC PARAMETERS IN ALGERIA BETWEEN 1993 AND 2012, USING NIGHTTIME LIGHT REMOTE SENSING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1127-1135 ◽  
Author(s):  
B. Faouzi ◽  
P. Washaya
Keyword(s):  
Remote Sensing ◽  
Dynamic Change ◽  
Remote Sensing Data ◽  
Calibration Method ◽  
Gas Production ◽  
Data Availability ◽  
Dynamic Changes ◽  
Human Settlements ◽  
Gas Flaring ◽  
Nighttime Light

This paper is based on using DMSP-OLS data from satellites nighttime light observations to detect both sources of light emissions in Algeria from human settlement areas and gas flaring from oil-extraction and natural gas production. We used the time series of data from DMSP-OLS images to examine the spatial and temporal characteristics of urban development in 48 Algerian provinces from 1993 to 2012. A systematic nighttime light calibration method was used to improve the consistency and comparability of the DSMPOSL images and then a separation is made between light detected from human settlements and light detected from gas flaring in order to allow us to study human settlements without other light emissions and then assess the suitability of using DMSP data in southern Algeria and its ability to monitor gas flaring. Linear regression methods were developed to identify the dynamic change of nighttime light and estimated its growth directions at pixel level. This work is the first to use nighttime light observations to detect and monitor the growth of human settlements in North Africa. In this study, we made use of DMSP-OLS data as a return ticket to the years of crises and we found the most affected provinces during that period. The DMSP-OLS data proved to be an index of growth in the economy during the period of stability in Algeria expressed by positive dynamic changes in the lighted area in all Algerian provinces. We used NTL data as an alternative to annual growth indexes for each province, which are unavailable, and its help as a monitoring system for socioeconomic parameters to fill the gap of data availability. We also proposed nighttime light remote sensing data as a useful tool to control and reduce CO2 emissions in Algeria’s petroleum sector.

scholarly journals Development of Land Resource Management Data System Based on MAPGIS

2012 ◽  
Vol 6-7 ◽  
pp. 367-372
Author(s):  
Hao Tao
Keyword(s):  
Remote Sensing ◽  
Resource Management ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data System ◽  
Land Resource ◽  
Land Resources ◽  
Fully Integrated ◽  
Development Platform ◽  
Three Dimensional Space

MapGIS is an implementation of remote sensing processing and GIS fully integrated to support air, ground, and surface, underground true three-dimensional space integration GIS development platform. The task of the management of land resources data system is grasp timely, fully and correctly the utilization status of the land resources of great significance for strengthening the management of land resources. The paper presents the development of land resource management data system based on MAPGIS. The MAPGIS software platform can from remote sensing images for land resources information to help the digital land resource management, modern and scientific.

scholarly journals Measuring Dynamic Changes in the Spatial Pattern and Connectivity of Surface Waters Based on Landscape and Graph Metrics: A Case Study of Henan Province in Central China

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 471
Author(s):  
Bo Mu ◽  
Guohang Tian ◽  
Gengyu Xin ◽  
Miao Hu ◽  
Panpan Yang ◽  
...  
Keyword(s):  
Surface Water ◽  
Nearest Neighbor ◽  
Dynamic Change ◽  
Henan Province ◽  
Central China ◽  
Node Degree ◽  
Human Society ◽  
Stepping Stones ◽  
Dynamic Changes ◽  
Graph Metrics

An understanding of the scientific layout of surface water space is crucial for the sustainable development of human society and the ecological environment. The objective of this study was to use land-use/land-cover data to identify the spatiotemporal dynamic change processes and the influencing factors over the past three decades in Henan Province, central China. Multidisciplinary theories (landscape ecology and graph theory) and methods (GIS spatial analysis and SPSS correlation analysis) were used to quantify the dynamic changes in surface water pattern and connectivity. Our results revealed that the water area decreased significantly during the periods of 1990–2000 and 2010–2018 due to a decrease in tidal flats and linear waters, but increased significantly in 2000–2010 due to an increase in patchy waters. Human construction activities, socioeconomic development and topography were the key factors driving the dynamics of water pattern and connectivity. The use of graph metrics (node degree, betweenness centrality, and delta probability of connectivity) in combination with landscape metrics (Euclidean nearest-neighbor distance) can help establish the parameters of threshold distance between connected habitats, identify hubs and stepping stones, and determine the relatively important water patches that require priority protection or development.

scholarly journals Temporal association between human upper respiratory and gut bacterial microbiomes during the course of COVID-19 in adults

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Rong Xu ◽  
Renfei Lu ◽  
Tao Zhang ◽  
Qunfu Wu ◽  
Weihua Cai ◽  
...  
Keyword(s):  
Dynamic Change ◽  
Temporal Association ◽  
Rrna Gene ◽  
Type I ◽  
Dynamic Changes ◽  
Multiple Organs ◽  
Community Types ◽  
Upper Respiratory ◽  
Rrna Gene Sequencing ◽  
16 S Rrna

AbstractSARS-CoV-2 is the cause of COVID-19. It infects multiple organs including the respiratory tract and gut. Dynamic changes of regional microbiomes in infected adults are largely unknown. Here, we performed longitudinal analyses of throat and anal swabs from 35 COVID-19 and 19 healthy adult controls, as well as 10 non-COVID-19 patients with other diseases, by 16 S rRNA gene sequencing. The results showed a partitioning of the patients into 3-4 categories based on microbial community types (I-IV) in both sites. The bacterial diversity was lower in COVID-19 patients than healthy controls and decreased gradually from community type I to III/IV. Although the dynamic change of microbiome was complex during COVID-19, a synchronous restoration of both the upper respiratory and gut microbiomes from early dysbiosis towards late more diverse status was observed in 6/8 mild COVID-19 adult patients. These findings reveal previously unknown interactions between upper respiratory and gut microbiomes during COVID-19.

scholarly journals Spatial and Temporal Changes in Vegetation in the Ruoergai Region, China

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 76
Author(s):  
Yahui Guo ◽  
Jing Zeng ◽  
Wenxiang Wu ◽  
Shunqiang Hu ◽  
Guangxu Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Linear Trend ◽  
Spectral Characteristics ◽  
Growth Conditions ◽  
Temporal Changes ◽  
Vegetation Coverage ◽  
Dynamic Changes ◽  
Spatial And Temporal Changes ◽  
Temporal And Spatial

Timely monitoring of the changes in coverage and growth conditions of vegetation (forest, grass) is very important for preserving the regional and global ecological environment. Vegetation information is mainly reflected by its spectral characteristics, namely, differences and changes in green plant leaves and vegetation canopies in remote sensing domains. The normalized difference vegetation index (NDVI) is commonly used to describe the dynamic changes in vegetation, but the NDVI sequence is not long enough to support the exploration of dynamic changes due to many reasons, such as changes in remote sensing sensors. Thus, the NDVI from different sensors should be scientifically combined using logical methods. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI are combined using the Savitzky–Golay (SG) method and then utilized to investigate the temporal and spatial changes in the vegetation of the Ruoergai wetland area (RWA). The dynamic spatial and temporal changes and trends of the NDVI sequence in the RWA are analyzed to evaluate and monitor the growth conditions of vegetation in this region. In regard to annual changes, the average annual NDVI shows an overall increasing trend in this region during the past three decades, with a linear trend coefficient of 0.013/10a, indicating that the vegetation coverage has been continuously improving. In regard to seasonal changes, the linear trend coefficients of NDVI are 0.020, 0.021, 0.004, and 0.004/10a for spring, summer, autumn, and winter, respectively. The linear regression coefficient between the gross domestic product (GDP) and NDVI is also calculated, and the coefficients are 0.0024, 0.0015, and 0.0020, with coefficients of determination (R2) of 0.453, 0.463, and 0.444 for Aba, Ruoergai, and Hongyuan, respectively. Thus, the positive correlation coefficients between the GDP and the growth of NDVI may indicate that increased societal development promotes vegetation in some respects by resulting in the planting of more trees or the promotion of tree protection activities. Through the analysis of the temporal and spatial NDVI, it can be assessed that the vegetation coverage is relatively large and the growth condition of vegetation in this region is good overall.

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