Regime change analysis of interval-valued time series with an application to PM10

Democratic governance has been seen as a catalyst for inclusive growth and meaningful development in many countries. Shifting from authoritarian rule to more democratic rule has also been seen as essential for many governments worldwide. Democratic governance is often a problem for developing countries, including most African countries and particularly The Gambia. This paper analyses the shift towards a more democratic governance style that is heated debated in The Gambia. The debate started when one of the coalition government members asserted that they could achieve regime change; however, a democratic system change remains lacking. This paper has sought to analyze whether the shift toward a more democratic leadership style in The Gambia is one of system change or regime change and ascertain what has democratically changed and bad governance in the new government. This article’s main objective is to create political awareness and enlighten the readers on the change’s misconceptions towards democratic governance. The discussion focuses on democratic governance and the collective action theory of governance to explain the democratic process in New Gambia. This study adopts qualitative case study research methods; the research employed a systematic review of the existing scholarly journal articles, books, newspapers, and television interview recordings. The observation used to identify, understand, and interpret the democratic governance situation in The Gambia from 2017 to 2019. The findings show that the coalition government has succeeded in achieving a democratic regime change; however, the democratic system change itself is too slow, or it is not happening. For the first time in The Gambia’s history, a seating president defeat through the ballot box. In conclusion, the democratic governance system change is far-fetched. It is vital to state that there is little or no difference between Jammeh’s regime and the current regime under President Barrow’s leadership. The same problems continue to persist. Finally, the transparency and accountability mechanisms must be enhanced to address the endemic problem of corruption.

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INFLUENCE OF SPATIAL AND TEMPORAL RESOLUTION ON TIME SERIES-BASED COASTAL SURFACE CHANGE ANALYSIS USING HOURLY TERRESTRIAL LASER SCANS

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-2-2021-137-2021 ◽

2021 ◽

Vol V-2-2021 ◽

pp. 137-144

Author(s):

K. Anders ◽

L. Winiwarter ◽

H. Mara ◽

R. C. Lindenbergh ◽

S. E. Vos ◽

...

Keyword(s):

Time Series ◽

Temporal Resolution ◽

Input Data ◽

Laser Scanning ◽

Poor Performance ◽

Computational Effort ◽

Spatial Extent ◽

Change Analysis ◽

Surface Change ◽

Natural Surface

Abstract. Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that removes the need to select analysis periods, providing so-called 4D objects-by-change (4D-OBCs). This involves higher computational effort than pairwise change detection, and efforts scale with (i) the temporal density of input data and (ii) the (variable) spatial extent of delineated changes. These two factors determine the cost and number of Dynamic Time Warping distance calculations to be performed for deriving the metric of time series similarity. We investigate how a reduction of the spatial and temporal resolution of input data influences the delineation of twelve erosion and accumulation forms, using an hourly five-month TLS time series of a sandy beach. We compare the spatial extent of 4D-OBCs obtained at reduced spatial (1.0 m to 15.0 m with 0.5 m steps) and temporal (2 h to 96 h with 2 h steps) resolution to the result from highest-resolution data. Many change delineations achieve acceptable performance with ranges of ±10 % to ±100 % in delineated object area, depending on the spatial extent of the respective change form. We suggest a locally adaptive approach to identify poor performance at certain resolution levels for the integration in a hierarchical approach. Consequently, the spatial delineation could be performed at high accuracy for specific target changes in a second iteration. This will allow more efficient 3D change analysis towards near-realtime, online TLS-based observation of natural surface changes.

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