Leena Ruha

Leena Ruha
Natural Resources Institute Finland (Luke) · Natural Resources

PhD

About

38
Publications
9,139
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
390
Citations
Citations since 2017
26 Research Items
333 Citations
2017201820192020202120222023020406080
2017201820192020202120222023020406080
2017201820192020202120222023020406080
2017201820192020202120222023020406080
Introduction
Additional affiliations
July 2012 - present
University of Oulu
Position
  • PostDoc Position
September 2006 - June 2012
University of Oulu
Position
  • PostDoc Position

Publications

Publications (38)
Article
Full-text available
Efficient resource usage in edge computing requires clever allocation of the workload of application components. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks—a phenomenon we present as a reallocation st...
Article
Full-text available
The Iberian Peninsula is located at the intersection between the subtropical and temperate climate zones and the paleoclimate records from this region are key to elucidate the varying humidity and changing dominance of atmospheric circulation patterns in the Mediterranean-North African region in the past. Here we present a quantitative hydroclimate...
Preprint
Full-text available
In spatial data, location-dependent variation leads to connected structures known as features. Variations occur at different spatial scales and possibly originate from distinct underlying processes. Each of these scales is characterized by its own dominant features. Here we introduce a statistical method for identifying these scales and their domin...
Article
Precipitation is a key climate parameter of vegetation and ecosystems in the Iberian Peninsula. Here, we use a regional pollen–climate calibration model and fossil pollen data from eight sites from the Atlantic coast to southern Spain to provide quantitative reconstructions of annual precipitation trends and excursions and their regional patterns f...
Preprint
Full-text available
Location-allocation and partitional spatial clustering both deal with spatial data, seemingly from different viewpoints. Partitional clustering analyses data points by partitioning them into separate groups, while location-allocation places facilities in locations that best meet the needs of demand points. However, both partitional clustering and l...
Preprint
Full-text available
Capacitated spatial clustering, a type of unsupervised machine learning method, is often used to tackle problems in compressing, classifying, logistic optimization and infrastructure optimization. Depending on the application at hand, a wide set of extensions may be necessary in clustering. In this article we propose a number of novel extensions...
Article
Full-text available
The deployment of edge computing infrastructure requires a careful placement of the edge servers, with an aim to improve application latencies and reduce data transfer load in opportunistic Internet of Things systems. In the edge server placement, it is important to consider computing capacity, available deployment budget, and hardware requirements...
Article
Full-text available
Spatiotemporal interpolation provides estimates of observations in unobserved locations and time slots. In smart cities, interpolation helps to provide a fine-grained contextual and situational understanding of the urban environment, in terms of both short-term (e.g., weather, air quality, traffic) or long term (e.g., crime, demographics) spatio-te...
Article
Full-text available
Background: In the past two decades, the number of maternity hospitals in Finland has been reduced from 42 to 22. Notwithstanding the benefits of centralization for larger units in terms of increased safety, the closures will inevitably impair geographical accessibility of services. Methods: This study aimed to employ a set of location-allocatio...
Article
Full-text available
Context Changes in the structure of boreal old-growth forests are typically studied at a specific spatial scale. Consequently, little is known about forest development across different spatial scales. Objectives We investigated how and at what spatial scales forest structure changed over several decades in three 4 km² boreal old-growth forests lan...
Conference Paper
Full-text available
In this article, we study the scaling up of edge computing deployments. In edge computing, deployments are scaled up by adding more computational capacity atop the initial deployment, as deployment budgets allow. However, without careful consideration, adding new servers may not improve proximity to the mobile users, crucial for the Quality of Expe...
Preprint
Full-text available
Edge computing in the Internet of Things brings applications and content closer to the users by introducing an additional computational layer at the network infrastructure, between cloud and the resource-constrained data producing devices and user equipment. This way, the opportunistic nature of the operational environment is addressed by introduci...
Article
Fire is a major disturbance agent in the boreal forest, influencing many current and future ecosystem conditions and services. Surprisingly few studies have attempted to improve the accuracy of fire-event reconstructions even though the estimates of the occurrence of past fires may be biased, influencing the reliability of the models employing thos...
Article
Full-text available
Identifying the scales of variation in forest structures and the underlying processes are fundamental for understanding forest dynamics. Here, we studied these scale-dependencies in forest structure in naturally dynamic boreal forests on two continents. We identified the spatial scales at which forest structures varied, and analyzed how the scales...
Article
The study, based on the examination of 70 published and unpublished pollen profiles from Poland and supplementary data from the surrounding regions, shows that an abrupt, episodic Alnus population decline at the end of the first millennium CE was a much more widespread event than has been previously reported, spanning large areas of the temperate a...
Article
Full-text available
Time series of repeat aerial photographs currently span decades in many regions. However, the lack of calibration data limits their use in forest change analysis. We propose an approach where we combine repeat aerial photography, tree-ring reconstructions, and Bayesian inference to study changes in forests. Using stereopairs of aerial photographs f...
Article
Full-text available
The temporal and spatial data analysed in, for example, ecology or climatology, are often hierarchically structured, carrying information in different scales. An important goal of data analysis is then to decompose the observed signal into distinctive hierarchical levels and to determine the size of the features that each level represents. Using di...
Conference Paper
Full-text available
Global environmental change alters forest dynamics, but the effects vary regionally and the changes often occur at various spatial and temporal scales. Hence, and due to the slow ecosystem responses to environmental changes, long-term, multi-scale studies are needed to understand how forests respond these changes. We studied scale-dependent changes...
Article
Forest fires are a key disturbance in boreal forests, and characteristics of fire regimes are among the most important factors explaining the variation in forest structure and species composition. The occurrence of fire is connected with climate, but earlier, mostly local scale studies in the northern European boreal forests have provided little in...
Article
Full-text available
In Finnish Lapland, reindeer herders’ activity is strongly dependent on the surrounding natural environment, which is directly exposed to environmental changes and climatic variations. By assessing whether there is any evidence of change in climate in Fell Lapland over the last 50 years, this paper attempts to link global climatic trends with local...
Article
Full-text available
Oceanic and atmospheric modes play a key role in modulating climate variations, particularly on interannual and interdecadal scales, causing an indirect response of regional climate to external forcings. This study comprehensively investigated the time-varying linkages among dominant oceanic and atmospheric modes of the Pacific and Atlantic areas o...
Conference Paper
Full-text available
Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary...
Conference Paper
Full-text available
The boreal forest provides a variety of ecosystem services that are threatened under the ongoing climate warming. Along with the climate, there are several factors (fire, human-impact, pathogens), which influence boreal forest dynamics. Combination of short and long-term studies allowing complex assessment of forest response to natural abiotic and...
Article
Full-text available
We propose a new scale space method for the discovery of structure in the correlation between two time series. The method considers the possibility that correlation may not be constant in time and that it might have different features when viewed at different time scales. The time series are first decomposed into additive components corresponding t...
Article
Variation of marine temperature at different time scales is a central environmental factor in the life cycle of marine organisms, and may have particular importance for various life stages of anadromous species, for example, Atlantic salmon. To understand the salient features of temperature variation we employ scale space multiresolution analysis,...
Article
Full-text available
The goal of statistical scale space analysis is to extract scale-dependent features from noisy data. The data could be for example an observed time series or digital image in which case features in either different temporal or spatial scales would be sought. Since the 1990s, a number of statistical approaches to scale space analysis have been devel...
Article
Full-text available
LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i) controlling false posit...
Article
Full-text available
We consider the detection of land cover changes using pairs of Landsat ETM+ satellite images. The images consist of eight spectral bands and to simplify the multidimensional change detection task, the image pair is first transformed to a one-dimensional image. When the transformation is non-linear, the true change in the images may be masked by com...
Article
A scale space multiresolution feature extraction method is proposed for time series data. The method detects intervals where time series features differ from their surroundings, and it produces a multiresolution analysis of the series as a sum of scale-dependent components. These components are obtained from differences of smooths. The relevant seq...
Conference Paper
Full-text available
Two new statistical scale space methodologies are discussed. The first method aims to detect differences between two images obtained from the same object at two different instants of time. Both small scale sharp changes and large scale average changes are detected. The second method detects features that differ in intensity from their surroundings...
Article
Full-text available
This article considers the detection of image features in different spatial scales. The main focus is on capturing the scale-dependent differences in a pair of noisy images, but the technique developed can also be applied to the analysis of single images. The approach proposed uses Bayesian statistical modeling and simulation-based inference, and i...
Article
A method to capture the scale-dependent features in a random signal is proposed with the main focus on images and spatial fields defined on a regular grid. A technique based on scale space smoothing is used. However, while the usual scale space analysis approach is to suppress detail by increasing smoothing progressively, the proposed method instea...
Article
Full-text available
This paper is concerned with detecting image features that appear in different scales or resolutions. A new ap- proach is proposed that uses Bayesian statistical modeling and simulation based inference. The method can be viewed as a further development of SiZer technology, originally de- signed for nonparametric curve fitting. A strength of the Bay...
Article
Full-text available
In this paper, two different auditory feedback schemes related to graphical buttons are compared to each other and to a visual-only condition. The results show that aesthetically pleasing auditory design is clearly preferred among the users, and can lead to performance benefits over not only a design with no auditory enhancements, but also a design...

Network

Cited By