# Shojiro TanakaHiroshima University of Economics, Japan · Department for Information Systems in Business

Shojiro Tanaka

PhD

## About

42

Publications

6,280

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337

Citations

Introduction

Exploring the interrelations of humans and environment with use of computational spatio-temporal data analysis. Lives in Hiroshima. #deforestation #modeling #statistics #remotesensing #satellites #SDGs #synanthrope #anthropocene
linktr.ee/shojiro.tanaka

Additional affiliations

October 1997 - March 2015

October 1997 - March 2015

## Publications

Publications (42)

Employing computer vision to extract useful information from images and videos is becoming a key technique for identifying phenotypic changes in plants. In this report, we review the emerging aspects of computer vision for automated plant phenotyping. Recent advances in image analysis empowered by machine learning-based techniques, including convol...

The advantage of using grid-cell data for socio-economic analysis should be the feasibility to incorporate satellite data that will enrich the regional analysis and has an important role to observe the relationship between socio-economics and nature. This advancement corresponds to the sustainable development goals that balance the socio-economic q...

When performing a search with MX-CIF quadtree, all the objects in the nodes which intersect a search-window will be taken as primary results, and then relations between the primary results and search-window are judged for an exact query. The amount of primary result is an important factor to affect time cost of query. This paper proposes an improve...

This research prosecutes topographic attributes on forest acreage ratio (F) decrease by human population interactions (N), from the none to full coverage in grid cells. Tanaka and Nishii [9] verified that altitude as well as the slope steepness, i.e., topographic attributes, indicate strong influence to the deforestation in cells 0 < F < 1. Two new...

Wei and Tanaka have proposed a variant of the Thorup algorithm which showed a better result than the original Thorup algorithm and the Fibonacci-based Dijkstra algorithm in practice. In this paper, we propose a faster algorithm based on their work. Our new algorithm has a faster speed when visiting vertices, it is achieved by decreasing the depth o...

Identification of the factors involved in deforestation could lead to a comprehensive understanding of deforestation on a broad scale, as well as a prediction capability. Tanaka and Nishii [7, 8] explored regression models with two explanatory variables - human population density (N) and relief energy (R), i.e., the difference between the maximum a...

This paper provides an improved Thorup algorithm which modified the component tree of the original Thorup algorithm to make it able to maintain the tentative distance of each vertex without the unvisited structure. According to the experimental result, our algorithm showed a better result than the original Thorup algorithm and Fibonacci-based Dijks...

An MX-CIF quadtree is a variant of quadtree which is for efficient spatial query such as whether objects are included by a spatial area. When query objects are indexed, a primary result with candidates which may intersect the query rectangle will be reported to have a successional precise inspection. We saved time from inspecting each of the object...

This paper establishes a statistical framework of forest coverage models
for spatio-temporal data. The forest coverage ratio of grid-cell data is
modeled by taking human population density and relief energy as
explanatory variables. The likelihood of the forest ratios is decomposed
by the product of two likelihoods. The first likelihood discussed b...

This paper explores statistical modeling of forest area with two covariates. The forest coverage ratio of grid-cell data was modeled by taking human population density and relief energy into account. The likelihood of the forest ratios was decomposed into the product of two likelihoods. The first likelihood was due to trinomial logistic distributio...

This paper considers statistical modeling of deforestation. Forest coverage ratio of grid-cell data was modeled by two covariates: human population density and relief energy. Conditional likelihood of the forest ratios given the covariates was decomposed by product of two likelihoods. The first one is due to trinomial logistic distributions on thre...

Identification of the factors involved in deforestation could lead to a comprehensive understanding of deforestation on a broad scale, as well as prediction capability. In this paper, regression models with two explanatory variables-human population and relief energy, i.e., the difference between the maximum and minimum altitudes in a sampled area-...

An algorithm of linear time complexity is presented to label connected components of a binary image by a quadtree. For a given node, the search for all adjacent nodes is carried out in O(1) (i.e., constant time complexity for the worst case) using our formerly presented algorithm in (Aizawa et al., 3rd International Symposium on Communications, Con...

Identification of limited number of factors shall provide comprehensive general understanding of deforestation at broad scale, as well as the projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in a sampled area) - were verified if they give sufficient elucidation of defo...

Deforestation is a result of complex causality chains in most cases. But identification of limited number of factors shall provide comprehensive general understanding of the vital phenomenon at broad scale, as well as projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in...

Tanaka and Nishii (2005) figured out that deforestation can be elucidated quantitatively by nonlinear logit regression models in four East Asian test fields: forest areal rate F as a target variable, and human population size (N) and relief energy (R: difference of minimum altitude from the maximum in a sampled area) as explanatory variables, whose...

Deforestation is a result of complex causality chains in most cases. But identification of limited number of factors shall provide comprehensive general understanding of the vital phenomenon at a broad scale, as well as projection for the future. Only two factors -- human population size (N) and relief energy (R: difference of minimum altitude from...

The authors examined discriminant analysis of land-cover
categories based on multivariate Gaussian fields. A parameter-estimation
method by the ground-truth data consisting of pure and mixed cells with
known category-proportions was discussed, and test data were
discriminated by a penalized likelihood. With actual Landsat data, their
procedure show...

Several measures assessing accuracy of land-cover classification
are available, e.g., overall and class-averaged accuracies. Also the
kappa statistic is widely used for this purpose. The authors discuss
properties of these criteria and point out that the kappa statistic has
an unfavorable feature. They propose an alternative coefficient based on
Ku...

Remotely-sensed information of forest coverage was extended by applying grid-cell data in typical human dimension: population. The authors demonstrated that process of deforestation have strong dependence on human population in an explicit form of a mathematical model. Relative appropriateness to real data of the relation was compared with other po...

A new feature extraction method for land-cover classification is proposed. New variables are produced by a simple linear combination of two variables in the original measurement vector. They correspond to the first and second principal componets. At first, an equivalent relation is proven to exist in coefficient matrices for the proposed variable s...

An efficient classification method using a triplet tree is
proposed for target land-cover categories with significance weight. The
weights are determined by user in the view of importance in actual
classification. In the proposed method, a triplet tree classifier for
land cover classification is used. The triplet tree classifier has two
types of no...

A differential equation was employed in modelling deforestation by human population interactions to yield an explicit mathematical model. The theoretical relation and many possible models were applied to the grid cell data in Hiroshima Prefecture, and relative appropriateness of each model was evaluated by Akaike's information criterion (AIC) using...

Several measures assessing the accuracy of land-cover classification are available, e.g., overall and class- averaged accuracies. Also kappa statistic is widely used for this purpose. In this article, we discuss the properties of these criteria, and point out that the kappa statistic has an unfavorable feature. We propose alternative coefficients b...

A multistep method for segmentation of feature space using triplet decision tree is developed, and another approach to cope with uncertain samples by extended Bayesian discriminant function is introduced. The latter has the lower limit for posterior probability of classification. The triplet-decision tree includes a division-wait mechanism that pos...

Thermal infrared measurements of Band 6 acquired by Landsat TM
sensor have lower spatial resolution than those of the other six bands.
The authors propose a statistical approach to enhance the resolution of
low spatial resolution image by using remaining bands. They employ a
multivariate normal distribution for the seven band values. The values
of...

Using a random coefficient regression model, sex-specific longitudinal analyses of height were made on 801 (392 male and 409 female) atomic-bomb survivors exposed in utero to detect dose effects on standing height. The data set resulted from repeated measurements of standing height of adolescents (age 10-18 y). The dose effect, if any, was assumed...

A bold, but effective analytical method was demonstrated to extract dominant factors of deforestation, in a complex, non-controlled, interrelated, and multi-dimensional data structure of actual environment. Human population was obtained as the factor in test field, followed by modeling based on the analytical result. An explicit mathematical relati...

Representability of training areas is primarily focused on its qualitative spectrum features. But it was revealed by this study that the representability by a quantitative application of prior frequencies of each land-cover item also plays an important role for more accurate classification in remote sensing, increasing the rate by ten to fifteen pe...

Deforestation is a result of complex causality chains in most cases. But identifi- cation of limited number of factors shall provide comprehensive general understanding of the vital phenomenon at a broad scale, as well as projection for the future. Only two factors — human pop- ulation and relief energy (difference of minimum altitude from the maxi...

We examine classiers of land-cover categories based on multispectral data. First, a parameter-estimation method by training data consisting of pure and mixed cells is discussed. By actual data, it is shown that the use of mix- els in the training data improves unmixing results signicantly. Next, classiers taking spatial con- tinuity of categories i...

The Landsat TM sensor for thermal infrared measurements, Band 6, has lower resolution than those of other six bands. The authors propose a statistical approach to enhance the resolution of low resolution thermal infrared image by using other band images. They employ a multivariate normal distribution for the joint distribution of 7 band values. The...

## Projects

Projects (2)

Environmental data, especially satellite digital imagery, requires various computational techniques for faster calculations.

With use of satellite data as well as the ground truth, terrestrial environment changes are to be attempted to analyze, and the spatio-temporal functional forms explored.