Automatic detection of forest fire disturbance based on dynamic modelling from MODIS time-series observations

2018 ◽  
Vol 39 (12) ◽  
pp. 3801-3815 ◽  
Author(s):  
Li Tian ◽  
Jindi Wang ◽  
Hongmin Zhou ◽  
Jian Wang
Keyword(s):  
Time Series ◽  
Forest Fire ◽  
Dynamic Modelling ◽  
Automatic Detection ◽  
Fire Disturbance

Baumartenwechsel in den Walliser Waldföhrenwäldern verstärkt nach grossen Störungen

2018 ◽  
Vol 169 (5) ◽  
pp. 260-268 ◽  
Author(s):  
Thomas Wohlgemuth ◽  
Violette Doublet ◽  
Cynthia Nussbaumer ◽  
Linda Feichtinger ◽  
Andreas Rigling
Keyword(s):  
Scots Pine ◽  
Forest Fire ◽  
Tree Regeneration ◽  
Fire Disturbance ◽  
Pine Forests ◽  
The Past ◽  
Vegetation Shift ◽  
Tree Demography ◽  
Scots Pine Forests ◽  
High Share

Vegetation shift in Scots pine forests in the Valais accelerated by large disturbances In the past dozen years, several studies have concluded a vegetation shift from Scots pine to oak (pubescent and sessile) forests in the low elevated zones of the Valais. It is, however, not fully clear in which way such a vegetation shift actually occurs and on which processes such a shift would be based. Two studies, one on the tree demography in the intact Pfynwald and the other on the tree regeneration on the large Leuk forest fire patch, serve to discuss different aspects of the shift from Scots pine to oak. The forest stands of Pfynwald consist of 67% Scots pines and 14% oaks. Regenerating trees are 2–3.5 times more frequent in small gaps than under canopy. In gaps of the Upper Pfynwald, seedlings and saplings of Scots pine are three times more abundant than oaks, while both species regenerate in similar quantities under canopy. In the Lower Pfynwald, young oaks – especially seedlings – are more frequent than Scots pines. A different process is going on at the lower part in the Leuk forest fire patch where Scots pines prevailed before the burn of 2003. While Scots pines regenerate exclusively close to the edge of the intact forest, oaks not only resprout from trunk but also profit from unlimited spreading of their seeds by the Eurasian jay. Regeneration from seeds are hence observed in the whole studied area, independent of the proximity of seed trees. After the large fire disturbance, a mixed forests with a high share of oaks is establishing, which translates to a rapid vegetation shift. The two trajectories are discussed in the light of climate change.

Automatic fault detection for Building Integrated Photovoltaic (BIPV) systems using time series methods

2018 ◽  
Vol 8 (2) ◽  
pp. 160-170 ◽  
Author(s):  
Mohsen Shahandashti ◽  
Baabak Ashuri ◽  
Kia Mostaan
Keyword(s):  
Time Series ◽  
Automatic Detection ◽  
Cost Effective ◽  
Performance Ratio ◽  
Solar Irradiation ◽  
Short Term ◽  
Content Type ◽  
Structure Changes ◽  
Cost Effective Approach ◽  
Building Integrated Photovoltaic

PurposeFaults in the actual outdoor performance of Building Integrated Photovoltaic (BIPV) systems can go unnoticed for several months since the energy productions are subject to significant variations that could mask faulty behaviors. Even large BIPV energy deficits could be hard to detect. The purpose of this paper is to develop a cost-effective approach to automatically detect faults in the energy productions of BIPV systems using historical BIPV energy productions as the only source of information that is typically collected in all BIPV systems.Design/methodology/approachEnergy productions of BIPV systems are time series in nature. Therefore, time series methods are used to automatically detect two categories of faults (outliers and structure changes) in the monthly energy productions of BIPV systems. The research methodology consists of the automatic detection of outliers in energy productions, and automatic detection of structure changes in energy productions.FindingsThe proposed approach is applied to detect faults in the monthly energy productions of 89 BIPV systems. The results confirm that outliers and structure changes can be automatically detected in the monthly energy productions of BIPV systems using time series methods in presence of short-term variations, monthly seasonality, and long-term degradation in performance.Originality/valueUnlike existing methods, the proposed approach does not require performance ratio calculation, operating condition data, such as solar irradiation, or the output of neighboring BIPV systems. It only uses the historical information about the BIPV energy productions to distinguish between faults and other time series properties including seasonality, short-term variations, and degradation trends.

scholarly journals Dynamic Modelling of Sharia-Based Corporate, Islamic Index and Exchange Rate: VAR Model Application

2020 ◽  
Vol 6 (2) ◽  
pp. 195
Author(s):  
Hasrun Afandi Umpusinga ◽  
Atika Riasari ◽  
Fajrin Satria Dwi Kesumah
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Dynamic Modelling ◽  
Series Data ◽  
Var Model ◽  
Suitable Model ◽  
Data Set ◽  
Dynamic Relationship

Indonesia is one of largest users of sharia-based compliant recently which bring into many concerns how the sharia stocks listing in the most valuable sharia stocks index in Indonesia perform and correlate with other variables, particularly exchange rates. The study aims to analysis the causal relationship and to forecast the performances of sharia-based stocks and its Islamic index in Indonesia along with the volatility of exchange rate. Vector Autoregressive (VAR) model is applied as the method to analyse the multivariate time series as it is believed as the suitable model in predicting such time-series data in the scope of multivariate variables. The finding suggests VAR(1) model is the fitted model as such to both analyse its dynamic relationship and forecast the data set for the next 24 weeks. While the prediction shows the JII has an increasing data, both ANTM and EXR are predicted to have a stable volatility. In addition, granger causality defines variables to have effect in its respective variables, and IRF describes the shocks in one variable cause another variable is relatively difficult in reaching its zero condition in short-term period.

scholarly journals The effect of sea surface temperature on the structure and connectivity of species landings interaction networks in a multispecies recreational fishery.

2022 ◽  
Author(s):  
Kayla Mackenzie Blincow ◽  
Brice X Semmens
Keyword(s):  
Time Series ◽  
Dynamic Modelling ◽  
Single Species ◽  
Unintended Consequences ◽  
Interaction Networks ◽  
Multispecies Fisheries ◽  
Recreational Fishery ◽  
Species Management ◽  
Management Approaches ◽  
Modelling Methods

Multispecies fisheries, particularly those that routinely adapt the timing, location, and methods of fishing to prioritize fishery targets, present a challenge to traditional single-species management approaches. Efforts to develop robust management for multispecies fisheries require an understanding of how priorities drive the network of interactions between catch of different species, especially given the added challenges presented by climate change. Using 35 years of landings data from a southern California recreational fishery, we leveraged empirical dynamic modelling methods to construct causal interaction networks among the main species targeted by the fishery. We found strong evidence for dependencies among species landings time series driven by apparent hierarchical catch preference within the fishery. In addition, by parsing the landings time series into anomalously cool, normal, and anomalously warm regimes (the last reflecting ocean temperatures anticipated by 2040), we found that network complexity was highest during warm periods. Our findings suggest that as ocean temperatures continue to rise, so too will the risk of unintended consequences from single species management in this multispecies fishery.

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