scholarly journals Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors

2017 ◽  
Vol 31 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Danang Sri Hadmoko ◽  
Franck Lavigne ◽  
Junun Sartohadi ◽  
Christopher Gomez ◽  
D Daryono
Keyword(s):  
Temporal Distribution ◽  
Rainfall Threshold ◽  
Short Term ◽  
Rainfall Events ◽  
Landslide Occurrence ◽  
Central Java ◽  
Causative Factors ◽  
Spatio Temporal ◽  
Gis Environment

Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1) the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2) their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %), Central Java (29 %) and East Java (4 %). Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.

scholarly journals Assessing the Spatial and Spatio-Temporal Distribution of Forest Species via Bayesian Hierarchical Modeling

Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 573 ◽  
Author(s):  
Óscar Rodríguez de Rivera ◽  
Antonio López-Quílez ◽  
Marta Blangiardo
Keyword(s):  
Hierarchical Modeling ◽  
Temporal Distribution ◽  
Short Term ◽  
Distribution Models ◽  
Address Climate Change ◽  
Bayesian Hierarchical ◽  
Temporal Models ◽  
Spatio Temporal ◽  
The Relationship

Climatic change is expected to affect forest development in the short term, as well as the spatial distribution of species in the long term. Species distribution models are potentially useful tools for guiding species choices in reforestation and forest management prescriptions to address climate change. The aim of this study is to build spatial and spatio-temporal models to predict the distribution of four different species present in the Spanish Forest Inventory. We have compared the different models and showed how accounting for dependencies in space and time affect the relationship between species and environmental variables.

scholarly journals Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Mark Ashworth ◽  
◽  
Antonis Analitis ◽  
David Whitney ◽  
Evangelia Samoli ◽  
...  
Keyword(s):  
Primary Care ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Air Pollutant ◽  
Respiratory Morbidity ◽  
Short Term ◽  
Short Term Exposure ◽  
Short And Long Term ◽  
Spatio Temporal

Abstract Background Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. Methods Daily primary care data, for 2009–2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. Results The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 μg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. Conclusions We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

scholarly journals CONSTRUCTION AND ANALYSIS OF LONG-TERM SURFACE TEMPERATURE DATASET IN FUJIAN PROVINCE

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1223-1227 ◽  
Author(s):  
W. E. Li ◽  
X. Q. Wang ◽  
H. Su
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface ◽  
Rapid Development ◽  
Temporal Distribution ◽  
Heat Fluxes ◽  
Urban Region ◽  
Fujian Province ◽  
Spatio Temporal

Land surface temperature (LST) is a key parameter of land surface physical processes on global and regional scales, linking the heat fluxes and interactions between the ground and atmosphere. Based on MODIS 8-day LST products (MOD11A2) from the split-window algorithms, we constructed and obtained the monthly and annual LST dataset of Fujian Province from 2000 to 2015. Then, we analyzed the monthly and yearly time series LST data and further investigated the LST distribution and its evolution features. The average LST of Fujian Province reached the highest in July, while the lowest in January. The monthly and annual LST time series present a significantly periodic features (annual and interannual) from 2000 to 2015. The spatial distribution showed that the LST in North and West was lower than South and East in Fujian Province. With the rapid development and urbanization of the coastal area in Fujian Province, the LST in coastal urban region was significantly higher than that in mountainous rural region. The LST distributions might affected by the climate, topography and land cover types. The spatio-temporal distribution characteristics of LST could provide good references for the agricultural layout and environment monitoring in Fujian Province.

scholarly journals Analisis Peningkatan Upah Minimum Terhadap Penyerapan Tenaga Kerja di Provinsi Jawa Tengah

2021 ◽  
Vol 10 (3) ◽  
pp. 134-143
Author(s):  
Annisa Yulianti ◽  
Hadi Sasana
Keyword(s):  
Economic Growth ◽  
Minimum Wage ◽  
Time Series Data ◽  
Series Data ◽  
Short Term ◽  
Central Java ◽  
Meaningful Relationship ◽  
Short Time ◽  
Relationship Of

 This study aims to analyze the short-term and long-term relationship of increasing the minimum wage in Central Java on employment. The research method used is ECM. The variables of this study include labor, minimum wages, PMDN, and economic growth. The data used are time-series data from 1990-2020. The results show that the minimum wage has a positive and significant relationship to the employment in the long term but not significantly in the short time. PMDN has a negative but significant correlation in the short and long term. At the same time, the variable economic growth has a positive but not meaningful relationship to employment absorption in the long and short term.

scholarly journals Spatio-Temporal Distribution of Chlorophyll-a In The Northern Waters of Central Java Using Aqua-MODIS

2019 ◽  
Vol 246 ◽  
pp. 012050
Author(s):  
Jusup Suprijanto ◽  
Ita Widowati ◽  
Anindya Wirasatriya ◽  
Uli Natul Khasanah
Keyword(s):  
Chlorophyll A ◽  
Temporal Distribution ◽  
Central Java ◽  
Spatio Temporal

Analysis of methodological and physical bias on borehole temperature reconstructions from a pseudo-proxy approach.

2020 ◽  
Author(s):  
Camilo Melo Aguilar ◽  
Fidel González Rouco ◽  
Elena García Bustamante ◽  
Norman Steinert ◽  
Jorge Navarro ◽  
...  
Keyword(s):  
Grid Point ◽  
Ground Surface ◽  
Temporal Distribution ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Last Millennium ◽  
Subsurface Temperature ◽  
Borehole Logs ◽  
Spatio Temporal

<p>The analysis of subsurface temperature measurements from boreholes is a well established approach for reconstructing last millennium (LM) surface air temperature (SAT). It is based on the assumption that SAT variations are strongly coupled to ground surface temperature (GST) variations and transferred to the subsurface by thermal conduction. We have evaluated the long-term SAT-GST coupling over the LM using an ensemble of both full- and single-forcing simulations form the Community Earth System Model-Last Millennium Ensemble (CESM-LME). Such a premise is explored by investigating the evolution of the long-term SAT–GST relationship. The results indicate that SAT–GST coupling is strong at global and above multi-decadal timescales in CESM-LME. However, at local to regional scales this relationship experiences considerable long-term changes mostly after the end of the 19th century. Land use land cover (LULC) changes stand as the main driver for locally and regionally decoupling SAT and GST, due to the changes in the energy fluxes at the surface. Snow cover feedbacks due to the influence of GHG forcing are also important for corrupting the long-term SAT–GST coupling. These processes may represent a source of bias for SAT reconstructions from GST borehole profiles. In light of these findings, we subsequently assessed the potential effects on SAT reconstructions from the borehole method in pseudo-proxy experiments that make use of the same set of simulations from the CESM-LME. First, a heat-conduction forward model has been used to estimate subsurface temperature-anomaly profiles using simulated GST as boundary conditions. Subsequently, singular value decomposition inversion (SVD) has been applied to reconstruct LM GST variations from the simulated profiles. We implemented and ideal scenario in which it is assumed the existence of borehole logs at every model grid point. Further, this scenario considers that all boreholes are logged homogenously at the same time. In addition, we implemented a more realistic approach in which the real-world spatio-temporal distribution of the global borehole network is considered. Results show that the SVD inversion is able to retrieve the long-term GST variations over the LM when an appropriated coverture of borehole logs is available. However, due to the limited spatio-temporal distribution of the actual borehole network, there is a lost in the accuracy to retrieve the simulated GST 20th century trends, with the temporal logging of the BTPs as the main sampling issue. Furthermore, in the surrogate reality of the CESM-LME the SAT-GST decoupling, due to the influence of LULC and GHG forcings, leads to a slightly underestimation of SAT warming during the industrial period across the CESM-LME. The level of impact is, however, highly depended on the realization of internal variability.</p>

scholarly journals Finding Action Tubes with a Sparse-to-Dense Framework

2020 ◽  
Vol 34 (07) ◽  
pp. 11466-11473
Author(s):  
Yuxi Li ◽  
Weiyao Lin ◽  
Tao Wang ◽  
John See ◽  
Rui Qian ◽  
...  
Keyword(s):  
Dynamic Feature ◽  
Video Streams ◽  
Short Term ◽  
Key Characteristics ◽  
Benchmark Datasets ◽  
Tube Output ◽  
Spatio Temporal ◽  
First Time ◽  
Temporal Action

The task of spatial-temporal action detection has attracted increasing researchers. Existing dominant methods solve this problem by relying on short-term information and dense serial-wise detection on each individual frames or clips. Despite their effectiveness, these methods showed inadequate use of long-term information and are prone to inefficiency. In this paper, we propose for the first time, an efficient framework that generates action tube proposals from video streams with a single forward pass in a sparse-to-dense manner. There are two key characteristics in this framework: (1) Both long-term and short-term sampled information are explicitly utilized in our spatio-temporal network, (2) A new dynamic feature sampling module (DTS) is designed to effectively approximate the tube output while keeping the system tractable. We evaluate the efficacy of our model on the UCF101-24, JHMDB-21 and UCFSports benchmark datasets, achieving promising results that are competitive to state-of-the-art methods. The proposed sparse-to-dense strategy rendered our framework about 7.6 times more efficient than the nearest competitor.

scholarly journals Statistical behaviours of earthquake occurrences in the Central Anatolian Region of Turkey: region-time-magnitude analyses

Baltica ◽  
2021 ◽  
pp. 157-173
Author(s):  
Serkan Öztürk
Keyword(s):  
Fault Zone ◽  
Earthquake Hazard ◽  
B Value ◽  
Short Term ◽  
Small Magnitude ◽  
Strong Earthquakes ◽  
Recurrence Times ◽  
Z Value ◽  
Spatio Temporal

The main objective of this work is to make detailed region-time-magnitude analyses by describing the statistical behaviours of earthquakes in the Central Anatolian Region of Turkey. In this scope, several seismic and tectonic parameters such as Mcomp, b-value, Dc-value, Z-value, recurrence times and annual probabilities were evaluated. For the analyses, a homogeneous catalogue including 10,146 earthquakes with 1.0 ≤ Md ≤ 5.7 between 30 July 1975 and 29 December 2018 was used and spatio-temporal changes of earthquake behaviours were mapped for the beginning of 2019. Earthquake magnitudes varied from 1.9 to 3.0 on average, and hence Mcomp was considered to be 2.6. The b-value was calculated as 1.26 ± 0.07, and this relatively large value indicates that small-magnitude events are dominant. The Dc-value was computed as 1.31 ± 0.03. This small value means that distances between epicentres approach the diameter of the cluster, and seismic activity is more clustered at smaller scales or in larger regions. The spatio-temporal analyses of recurrence times suggest that the Central Anatolian Region has an intermediate/long-term earthquake hazard in comparison to occurrences of strong earthquakes in the short term. Several anomaly regions of a small b-value and a large Z-value were found in and around the Tuzgölü Fault Zone, Central Anatolian Fault Zone, Salanda fault and Niğde fault at the beginning of 2019. Thus, a combination of the regions with a lower b-value, a higher Z-value and also moderate recurrence times may give significant clues for the future possible earthquakes, and detected regions may be thought to be the most likely areas for strong/large events in the Central Anatolian Region.

scholarly journals Crop-management factor calculation using weights of spatio-temporal distribution of rainfall erosivity

2018 ◽  
Vol 13 (No. 3) ◽  
pp. 150-160
Author(s):  
Brychta Jiří ◽  
Janeček Miloslav ◽  
Walmsley Alena
Keyword(s):  
Temporal Distribution ◽  
Geographic Location ◽  
Crop Management ◽  
Rainfall Erosivity ◽  
Spatial And Temporal Variability ◽  
R Factor ◽  
Factor Evaluation ◽  
Spatio Temporal ◽  
Gis Environment ◽  
Crop Management Factor

Inappropriate integration of USLE or RUSLE equations with GIS tools and Remote Sensing (RS) data caused many simplifications and distortions of their original principles. Many methods of C and R factor estimation were developed due to the lack of optimal data for calculations according to original methodology. This paper focuses on crop-management factor evaluation (C) weighted by fully distributed form of rainfall erosivity factor (R) distribution throughout the year. We used high resolution (1-min) data from 31 ombrographic stations (OS) in the Czech Republic (CR) for monthly R map creation. All steps of the relatively time-consuming C calculation were automated in GIS environment with an innovative procedure of R factor weight determination for each agro-technical phase by land parcel geographic location. Very high spatial and temporal variability of rainfall erosivity within each month and throughout the year can be observed from our results. This highlights the importance of C factor calculation using a correctly presented method with emphasis on the geographic location of given land parcels.

A Logic-Based Approach to Activity Recognition

2013 ◽  
pp. 1-13
Author(s):  
Alexander Artikis ◽  
Marek Sergot ◽  
Georgios Paliouras
Keyword(s):  
Activity Recognition ◽  
Human Activities ◽  
Video Content ◽  
Short Term ◽  
Event Calculus ◽  
Video Frames ◽  
Detailed Evaluation ◽  
Spatio Temporal ◽  
Complex Activities

The authors have been developing a system for recognising human activities given a symbolic representation of video content. The input of the system is a stream of time-stamped short-term activities detected on video frames. The output of the system is a set of recognised long-term activities, which are pre-defined spatio-temporal combinations of short-term activities. The constraints on the short-term activities that, if satisfied, lead to the recognition of a long-term activity, are expressed using a dialect of the Event Calculus. The authors illustrate the expressiveness of the dialect by showing the representation of several typical complex activities. Furthermore, they present a detailed evaluation of the system through experimentation on a benchmark dataset of surveillance videos.

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