Estimates of current status of forest types in Kolli Hill using remote sensing

2000 ◽  
Vol 28 (2-3) ◽  
pp. 141-151 ◽  
Author(s):  
S Jayakumar ◽  
D I Arockiasamy ◽  
S John Britto
Keyword(s):  
Remote Sensing ◽  
Current Status ◽  
Forest Types

scholarly journals Bibliometric Analysis of Remote Sensing Research Trend in Crop Growth Monitoring: A Case Study in China

2019 ◽  
Vol 11 (7) ◽  
pp. 809 ◽  
Author(s):  
Lijuan Wang ◽  
Guimin Zhang ◽  
Ziyi Wang ◽  
Jiangui Liu ◽  
Jiali Shang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Crop Growth ◽  
Future Trend ◽  
Current Status ◽  
Research Trend ◽  
Growth Monitoring ◽  
Knowledge Mapping ◽  
Area Index ◽  
Quantitative Visualization

Remote sensing of crop growth monitoring is an important technique to guide agricultural production. To gain a comprehensive understanding of historical progression and current status, and future trend of remote sensing researches and applications in the field of crop growth monitoring in China, a study was carried out based on the publications from the past 20 years by Chinese scholars. Using the knowledge mapping software CiteSpace, a quantitative and qualitative analysis of research development, current hotspots, and future directions of crop growth monitoring using remote sensing technology in China was conducted. Furthermore, the relationship between high-frequency keywords and the emerging hot topics were visually analyzed. The results revealed that Chinese researchers paid more attention on keywords such as “vegetation index”, “crop growth”, “winter wheat”, “leaf area index (LAI)”, and “model” in the field of crop growth monitoring, and “LAI” and “unmanned aerial vehicle (UAV)”, appeared increasingly in frontier research of this discipline. Overall, bibliometric results from this CiteSpace-aided study provide a quantitative visualization to enrich our understanding on the historical development, current status, and future trend of crop growth monitoring in China.

scholarly journals Remote Sensing Support for the Gain-Loss Approach for Greenhouse Gas Inventories

2020 ◽  
Vol 12 (11) ◽  
pp. 1891 ◽  
Author(s):  
Ronald E. McRoberts ◽  
Erik Næsset ◽  
Christophe Sannier ◽  
Stephen V. Stehman ◽  
Erkki O. Tomppo
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Greenhouse Gas ◽  
Good Practice ◽  
Remotely Sensed ◽  
Current Status ◽  
Remotely Sensed Data ◽  
Activity Data ◽  
Greenhouse Gas Inventories ◽  
Gain Loss

For tropical countries that do not have extensive ground sampling programs such as national forest inventories, the gain-loss approach for greenhouse gas inventories is often used. With the gain-loss approach, emissions and removals are estimated as the product of activity data defined as the areas of human-caused emissions and removals and emissions factors defined as the per unit area responses of carbon stocks for those activities. Remotely sensed imagery and remote sensing-based land use and land use change maps have emerged as crucial information sources for facilitating the statistically rigorous estimation of activity data. Similarly, remote sensing-based biomass maps have been used as sources of auxiliary data for enhancing estimates of emissions and removals factors and as sources of biomass data for remote and inaccessible regions. The current status of statistically rigorous methods for combining ground and remotely sensed data that comply with the good practice guidelines for greenhouse gas inventories of the Intergovernmental Panel on Climate Change is reviewed.

Integration of GIS with Remote Sensing and GPS for Disaster Mitigation

2015 ◽  
Vol 10 (2) ◽  
pp. 225-230
Author(s):  
Sikander Nawaz Khan ◽  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Spatial Information ◽  
Service Providers ◽  
Disaster Mitigation ◽  
Sensor Nodes ◽  
Physical Contact ◽  
Current Status ◽  
Target Area ◽  
Full Potential

Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information on natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provides precise and accurate locations and other related information like speed, track, direction and distance of target objects to emergency responders.Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing a vital role in disaster management.Early in Geographic Information System (GIS) was used to collect, arrange, and map the spatial information, but now it has the capability to analyze spatial data. This analytical ability of GIS is the main cause of its adoption by different emergency service providers like the police and ambulance service.The full potential of these so called 3S technologies cannot be used alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases, including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

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