Wanglin Yan

Radiation-Driven Migration: The Case of Minamisoma City, Fukushima, Japan, after the Fukushima Nuclear Accident

The emigration of residents following the Fukushima nuclear accident has resulted in aging and depopulation problems in radiation-contaminated areas. The recovery of affected areas, and even those areas with low radioactive pollution levels, is still heavily affected by this problem. This slow recovery consequently affects immigration patterns. This review aims to present possible factors that have contributed to this dilemma. We first present an overview of the evacuation protocol that was administered in the study area following the Fukushima accident. We then analyze characteristics of the subsequent exodus by comparing population data for both before and after the accident. Based on the findings of existing literature, we identify three causes of emigration: (1) The health risks of living in a low radiation zone are still unknown; (2) The post-disaster psychological disturbance and distrust of government information promotes the emigration of evacuees; (3) an absence of economic vitality and of a leading industry renders the area less attractive to individuals residing outside of the city. Further research is needed on this issue, especially with respect to countermeasures for addressing this problem.

Monitoring shoreline change on Djerba Island using GIS and multi-temporal satellite data

In the absence of a generic approach to study shoreline changes, this research focus on the development of a generic methodology to detect, measure, analyze, and predict shoreline changes to manage coastal environment. The unique strength of this approach is that it incorporates image processing techniques, remotely sensed derived data into a GIS to analyze measure, and predict and visualize shoreline changes. It is independent from the study region or the remote sensing data. This methodology uses Speeded Up Robust Feature to detect the study regions from satellite images automatically. Also, it proposes a model of shoreline using the Canny edge detector on Normalized Difference Water Index image. To measure the changes, Digital Shoreline Analysis System extension of ArcGIS was used and the End Point Rate (EPR) and Linear Regression Rate (LRR) approaches were used on the modeled shoreline. The EPR is calculated by dividing the distance of shoreline movement by the time elapsed between the oldest and the most recent shoreline. A LRR statistic can be determined by fitting a least-squares regression line to all shoreline points for a particular transect. Three regions of the island of Djerba in Tunisia were selected for this study; Rass Errmall, El Kastil, and Aghir. Accretions as well as erosion processes were observed in the study areas between 1984 and 2009. The average of the erosion was around −6.95xa0m/year in Aghir. The average of erosion is around −4.09xa0m/year and accretion trend is around +11.7xa0m/year in Rass Errmall. El Kastil was under a remarkable accretion with 21.14xa0m/year during the same period.

Island Coastline Change Detection Based on Image Processing and Remote Sensing

As an island ecosystem, Djerba, a region of Tunisia located on the southern shore of the Mediterranean Sea, is characterized by limited natural resources and threatened by land degradation due to rapid socio-economic development and heavy human-induced changes to the landscape. The objective of this study is to build a system based on computer vision and remote sensing data for monitoring changes in the coastal zones of an island. We employed monthly Landsat Thematic Mapper (TM) satellite images of the study area ranging from 1984 to 2009. The images were preprocessed using the Speeded Up Robust Features (SURF) algorithm to superimpose remote sensing images at exactly the same coordinates. We then used two comparison techniques to auto-validate the detection of changes. The first technique is based on a window-to-window comparison of the coastal zones and the second technique compares shoreline changes using edge detection. Three highly affected regions were identified. The Bin El-Ouidiane (in the southeast) and Rass Errmal (in the north) regions underwent deposition during the study period, whereas the region of Rass El Kastil (in the north) underwent high erosion.

Evaluating renewable natural resources flow and net primary productivity with a GIS-Emergy approach: A case study of Hokkaido, Japan

Renewable natural resources, such as solar radiation, rainfall, wind, and geothermal heat, together with ecosystem services, provide the elementary supports for the sustainable development of human society. To improve regional sustainability, we studied the spatial distributions and quantities of renewable natural resources and net primary productivity (NPP) in Hokkaido, which is the second largest island of Japan. With the help of Geographic Information System (GIS) software, distribution maps for each type of renewable natural resource were generated by kriging interpolation based on statistical records. A composite map of the flow of all types of renewable natural resources was also generated by map layer overlapping. Additionally, we utilized emergy analysis to convert each renewable flow with different attributes into a unified unit (i.e., solar equivalent joules [sej]). As a result, the spatial distributions of the flow of renewable natural resources of the Hokkaido region are presented in the form of thematic emergy maps. Thus, the areas with higher renewable emergy can be easily visualized and identified. The dominant renewable flow in certain areas can also be directly distinguished. The results can provide useful information for regional sustainable development, environmental conservation and ecological management.

Long-range wireless sensor networks for geo-location tracking: Design and evaluation

Nowadays, a long-range data transmission is required in numerous Internet of Things (IoT) applications. This paper introduces a long-range Wireless Sensor Networks (WSN) for geo-location tracking of mobile objects as one of the applications. In the proposed system, the geo-location information of moving objects is collected and sent over wireless networks with a reconfigured GPS and LoRa (Long Range) modules. This work presents the design of long-range WSN system and the prototype implementation. We implement multiple sensor nodes deployment, which move away from a static base station called dock. Further, the reliability of geo-location data collection and the quality of wireless communication are evaluated. The results from RSSI test show a high reliability of LoRa module as a transceiver for our targeted long-range geo-location tracking application.

Trust as a proxy indicator for intrinsic quality of Volunteered Geographic Information in biodiversity monitoring programs

In this article, we present a fuzzy model for intrinsic quality assessment of Volunteered Geographic Information (VGI) on species occurrences obtained by Citizen Science (CS) biodiversity monitoring programs. The proposed VGI quality assurance approach evaluates the thematic and positional quality of the crowdsourced biodiversity observation in terms of the trustworthiness of the observation by combining three indicators of consistency with habitat, consistency with surroundings, and reputation of contributor, that characterize the geographical and social aspects of trust in VGI. To evaluate the performance and usability of the proposed approach for evaluating the trustworthiness of crowdsourced observations and detecting thematic and positional errors in crowdsourced observations, the developed approach was applied to the crowdsourced observations on Acer macrophyllum collected through the CS biodiversity monitoring projects of E-Flora BC and iNaturalist. The result of a conformity test at the optimal acceptance threshold (sensitivity = 0.99, specificity = 0.8, and Cohen’s kappa = 0.79), the achieved area under the curve (AUC) value (AUC = 0.98), and the results of the complementary investigation on the predictions of the proposed model indicated that the proposed fuzzy trust model exhibited promising predictive performance and was able to flag the majority of attribute and positional errors in the crowdsourced biodiversity observations.

How is an informal transport infrastructure system formed? Towards a spatially explicit conceptual model

The informal transport infrastructure is an inseparable and critical element of the transportation system in that it provides pedestrian accessibility in planned or unplanned environments. Despite this important role, the informal infrastructure is usually neglected in formal studies, plans, reports or maps.A sophisticated understanding of the different dynamics and mechanisms behind the growth process of the informal infrastructure enables the researchers and practitioners to better plan, conserve and manage open spaces in planned and unplanned environments and helps them predict and manage the growth process of the informal infrastructure in the context of historical cities or informal settlements and model the mutual impacts of infrastructure growth and settlement growth in such areas.In the absence of a holistic spatially and temporally explicit model in the context of GIScience, this research aims to offer an outlook for some of the most important driving forces and aspects of informal infrastructure formation to establish the principal background for developing a spatially explicit, cognitively plausible conceptual model for future research.In this sense, this paper presents a critical review to cover a diverse range of topics in the different disciplines of this area and discuss the theoretical issues on the informal infrastructure formation process to explore, analyze and categorize the role of various human individual and collective-level behaviors and various human and environment interactions in emerging of the self-organizing patterns in the informal infrastructure system.

A fuzzy system for quality assurance of crowdsourced wildlife observation geodata

A conceptual model for quality assurance of species occurrence observations in citizen science projects is described below. We adopted the notion of trust as an indicator of VGI quality and define the concept of trustworthiness of a VGI record as a function of three main contexts: consistency with habitat, consistency with neighbors, and the reputation of the volunteer. Using fuzzy control system the quality of an observation is quantified in terms of the level of the trustworthiness of the volunteered species observation. The architecture of the proposed system is briefly described and some results presented. Finally, our paper ends with concluding remarks and some thoughts for future research directions.

Optical-Flow-Based Approach for the Detection of Shoreline Changes Using Remote Sensing Data

This research presents an automatic method to detect and evaluate the shoreline changes from Landsat satellite images. In fact, a method, that we called Lukas-Kanade Adapted for Coastal Changes (LKA2C), has been developed to calculate and detect the changes around the study region. Mainly the proposed method is based on SURF algorithm to detect the study region from the satellite image. Then, Canny edge detector was used on NDWI images to detect the shorelines. Finally, the pyramidal Lukas-Kanade optical flow algorithm was adapted to detect and to calculate the rates of changes. Realized experiments on real satellite images of the island of Djerba in Tunisia proved the effectiveness of the proposed method.

Applying DEM data to improve performance of water extraction indices using landsat 8 OLI images in mountainous area

Water is one of the most important earth resources which is essential to human health, society and environment. Studies on water extraction and changes have been subjects of academic studies for many years. Remote sensing as an efficient and reliable tool has been used in recent years and Landsat satellite imagery were one of the most common data due to their advantages in spatial resolution and cost. Improvement of new Landsat 8, the Operational Land Imager (OLI) data attracted more attentions recently. This study uses the Landsat 8 OLI imagery data source for water information extraction based on the Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI) and Automated Water Extraction Index (AWEI) to compare the effect of using The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) in mountainous area. The study area is Kermanshah, in west of Iran, a mountainous area which has difficulties for water extraction due to shadows and dark objects. Due to small area of water bodies in study area users accuracy were used for evaluation of results. User accuracy for water class gives results of 23.68%, 24.34% and 22.57% for NDWI, MNDWI and AWEI, respectively. In other words, around 77% of pixels which classified as water are not water and are misclassified pixels. Applying DEM data improves results to 27.44%, 29.1% and 27.22% for NDWI, MNDWI and AWEI, respectively which shows slight increase of 3.76%, 4.88% and 4.65%.