scholarly journals Energy savings in HVAC systems by continuous monitoring. Results of a long term monitoring campaign on buildings

2013 ◽  
Vol 1 ◽  
pp. 169-174
Author(s):  
J. Toniolo ◽  
C. Silvi ◽  
M. Masoero
Keyword(s):  
Continuous Monitoring ◽  
Energy Savings ◽  
Hvac Systems ◽  
Monitoring Campaign ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Evaluation of the Continuous Monitoring of Land Disturbance Algorithm for Large-Scale Mangrove Classification

2021 ◽  
Vol 13 (19) ◽  
pp. 3978
Author(s):  
Katie Awty-Carroll ◽  
Pete Bunting ◽  
Andy Hardy ◽  
Gemma Bell
Keyword(s):  
Continuous Monitoring ◽  
Large Scale ◽  
Data Availability ◽  
Mangrove Forests ◽  
Mangrove Species ◽  
Land Disturbance ◽  
Long Term Monitoring ◽  
The Impact ◽  
Term Monitoring

Mangrove forests are of high biological, economic, and ecological importance globally. Growing within the intertidal zone, they are particularly vulnerable to the effects of climate change in addition to being threatened on local scales by over-exploitation and aquaculture expansion. Long-term monitoring of global mangrove populations is therefore highly important to understanding the impact of these threats. However, data availability from satellites is often limited due to cloud cover. This problem can be mitigated using a season-trend modelling approach such as Continuous Monitoring of Land Disturbance (COLD). COLD operates by using every available observation on a pixel-wise basis, removing the need for whole cloud free images. The approach can be used to better classify land cover by taking into account the underlying seasonal variability, and can also be used to extrapolate between data points to obtain more accurate long term trends. To demonstrate the utility of COLD for global mangrove monitoring, we applied it to five study sites chosen to represent a range of mangrove species, forest types, and quantities of available data. The COLD classifier was trained on the Global Mangrove Watch 2010 dataset and applied to 30 years of Landsat data for each site. By increasing the period between model updates, COLD was successfully applied to all five sites (2253 scenes) in less than four days. The method achieved an overall accuracy of 92% with a User’s accuracy of 77% and a Dice score of 0.84 for the mangrove class. The lowest User’s accuracy was for North Kalimantan (49.9%) due to confusion with mangrove palms. However, the method performed extremely well for the Niger Delta from the 2000s onwards (93.6%) despite the absence of any Landsat 5 data. Observation of trends in mangrove extent over time suggests that the method was able to accurately capture changes in extent caused by the 2014/15 mangrove die-back event in the Gulf of Carpentaria and highlighted a net loss of mangroves in the Matang Forest Reserve over the last two decades, despite ongoing management. COLD is therefore a promising methodology for global, long-term monitoring of mangrove extent and trends.

scholarly journals Estimation of the Main Factors Influencing Haze, Based on a Long-term Monitoring Campaign in Hangzhou, China

2011 ◽  
Vol 11 (7) ◽  
pp. 873-882 ◽  
Author(s):  
Zhi-mei Xiao ◽  
Yu-fen Zhang ◽  
Sheng-mao Hong ◽  
Xiao-hui Bi ◽  
Li Jiao ◽  
...  
Keyword(s):  
Monitoring Campaign ◽  
Factors Influencing ◽  
Long Term Monitoring ◽  
Main Factors ◽  
Term Monitoring

scholarly journals A Methodology for Long-Term Monitoring of Climate Change Impacts on Historic Buildings

Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 370 ◽  
Author(s):  
Annika Haugen ◽  
Chiara Bertolin ◽  
Gustaf Leijonhufvud ◽  
Tone Olstad ◽  
Tor Broström
Keyword(s):  
Climate Change ◽  
Early Stage ◽  
Climate Change Impacts ◽  
Historic Buildings ◽  
Registration System ◽  
World Heritage Sites ◽  
Monitoring Campaign ◽  
Long Term Monitoring ◽  
Term Monitoring

A new methodology for long-term monitoring of climate change impacts on historic buildings and interiors has been developed. This paper proposes a generic framework for how monitoring programs can be developed and describes the planning and arrangement of a Norwegian monitoring campaign. The methodology aims to make it possible to establish a data-driven decision making process based on monitored decay related to climate change. This monitoring campaign includes 45 medieval buildings distributed over the entirety of Norway. Thirty-five of these buildings are dated to before 1537 and include wooden buildings as well as 10 medieval churches built in stone while the remaining 10 buildings are situated in the World Heritage sites of Bryggen, in Bergen on the west coast of Norway, and in Røros, which is a mining town in the inland of the country. The monitoring is planned to run for 30 to 50 years. It includes a zero-level registration and an interval-based registration system focused on relevant indicators, which will make it possible to register climate change-induced decay at an early stage.

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