Annals of GIS最新文献

{"title":"Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices","authors":"Linchuan Yang, Yuan Liang, Qing Zhu, Xiaoling Chu","doi":"10.1080/19475683.2021.1906746","DOIUrl":"https://doi.org/10.1080/19475683.2021.1906746","url":null,"abstract":"ABSTRACT The adoption of bus rapid transit (BRT) systems has gained worldwide popularity over the past several decades. China is no exception as it has long been aiming at promoting public transportation. Prior studies have provided extensive evidence that BRT has substantial effects on house prices with traditional econometric techniques, such as hedonic pricing models. However, few of those investigations have discussed the non-linear relationship between BRT and house prices. Using the Xiamen data, this study employs a machine learning technique, namely the gradient boosting decision tree (GBDT), to scrutinize the non-linear relationship between BRT and house prices. This study documents a positive association between accessibility to BRT stations and house prices and a negative association between proximity to the BRT corridor and house prices. Moreover, it suggests a non-linear relationship between BRT and house prices and indicates that GBDT has more substantial predictive power than hedonic pricing models.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"90 1","pages":"273 - 284"},"PeriodicalIF":5.0,"publicationDate":"2021-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90673952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial search and a three level model based water layer extraction from C-band SAR image","authors":"Bipin Chandran, C. Rao, P. Sridevi","doi":"10.1080/19475683.2021.1897675","DOIUrl":"https://doi.org/10.1080/19475683.2021.1897675","url":null,"abstract":"ABSTRACT This paper describes a spatial search and a three-level model-based approach for automatic extraction of surface water layers from Sentinel-1 C-band SAR images at 10 m spatial resolution. The technique incorporates a connected component spatial search for segmenting low backscatter regions and uses the segmented image object for characterizing the segments. The water body is described here as a collection of different spatially connected segments. A three-level model is used to describe the connected segments of a water body in SAR data. Noise tolerance is achieved in this method by incorporating a speckle noise level into the model. The segmentation process further calculates contextual information which includes shadow estimated from DEM, polarization angle of the segment, and a boundary co-occurrence in both polarization to qualify the detected segments as a water body. The proposed method is found to have an accuracy of 94% in terms of f1 score. The algorithm, estimation of different parameters, and the results obtained in selected regions are explained in this paper.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"31 1","pages":"163 - 176"},"PeriodicalIF":5.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81861872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human mobility and COVID-19 transmission: a systematic review and future directions","authors":"Mengxi Zhang, Siqin Wang, T. Hu, Xiaokang Fu, Xiaoyue Wang, Yaxin Hu, B. Halloran, Zhenlong Li, Yunhe Cui, Haokun Liu, Zhimin Liu, S. Bao","doi":"10.1080/19475683.2022.2041725","DOIUrl":"https://doi.org/10.1080/19475683.2022.2041725","url":null,"abstract":"ABSTRACT Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, mathematical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from the Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve mathematical models used in analysing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"66 1","pages":"501 - 514"},"PeriodicalIF":5.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83836813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A user-driven process for INSPIRE-compliant land use database: example from Wallonia, Belgium","authors":"B. Beaumont, T. Grippa, M. Lennert","doi":"10.1080/19475683.2021.1875047","DOIUrl":"https://doi.org/10.1080/19475683.2021.1875047","url":null,"abstract":"ABSTRACT Regional land use monitoring at high spatial, temporal, and thematic resolution is an important expectation of Walloon stakeholders. Over the last decade, increased data-processing capacities and the annual acquisition of remotely sensed data have resulted in the production of a large amount of relevant geodata. The INSPIRE directive and its obligations for 2020 serve as a path for the development of a new user-driven and open-source hierarchical land use classification system mapping scheme, as presented in this paper. The process includes intensive user consultation, the development of an entire automatic processing chain, and efforts to address challenges such as big data handling, the variability of input data properties, and reproducibility. The thematically detailed land use map, with its 69 classes, is already widely used by Walloon stakeholders, and new demands for updating have already emerged. Based on a European classification system that is compulsory for all member states, INSPIRE-compliant land use maps will make it possible to carry out cross-border studies and compare spatial planning strategies between states.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"94 1","pages":"211 - 224"},"PeriodicalIF":5.0,"publicationDate":"2021-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82322806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of channel shifting of Karnali Megafan in Nepal using remote sensing and GIS","authors":"Biplob Rakhal, T. R. Adhikari, Sanjib Sharma, G. Ghimire","doi":"10.1080/19475683.2021.1871950","DOIUrl":"https://doi.org/10.1080/19475683.2021.1871950","url":null,"abstract":"ABSTRACT River flow exhibits morphological changes over time. The shifting of river channels is a common natural phenomenon which often poses risk to life and property. Channel shifting is mostly associated with weak geology, extreme floods, and land cover alterations. Here we assess the changing morphology of the largest depositional landform in Nepal, called the Karnali Megafan, over the period of 1977–2013. We applied geographic information system (GIS) and remote sensing techniques to analyse the spatiotemporal changes in the Karnali Megafan. We obtained historical channel information from Landsat Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TRIS) satellite image, Landsat Enhanced Thematic Mapper Plus (ETM+), Thematic Mapper (TM) and Multispectral Scanner (MSS) for years 1977, 1990, 2000, 2010 and 2013. The channel shifting depicts a generally increasing trend in the right branch while the trend is less prominent in the left branch. We find that the extreme rainfall and flooding contribute to channel shifting in the Karnali Megafan. This study identifies the channel shifting spatiotemporal trends along the Karnali Megafan and are of practical use in developing and implementing appropriate river management strategies.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"45 1","pages":"177 - 188"},"PeriodicalIF":5.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88629601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting land use/cover changes and its association to agricultural production on the slopes of Mount Kilimanjaro, Tanzania","authors":"Mateso Said, C. Hyandye, H. Komakech, I. C. Mjemah, L. Munishi","doi":"10.1080/19475683.2020.1871406","DOIUrl":"https://doi.org/10.1080/19475683.2020.1871406","url":null,"abstract":"ABSTRACT Increasing demand for food production results in Land use and land cover (LULC) changes, which afflicts the provision of ecosystem services in high mountain areas. This work used time-series LULC and selected spatial metrics to predict the LULC changes for Kikafu-Weruweru-Karanga (KWK) watershed (on the southern slopes of Mt. Kilimanjaro) for the next decade. LULC maps were generated by classifying time-series satellite images. We further predicted the implications for selected staple crop production over the next decade. The simulated LULC shows expansion in built-up (by 32.55%/27.04 km2) and agriculture (by 39.52%/52.0 km2) areas from 2018 to 2030. These results suggest that urbanization is likely the next biggest threat to water availability and food production. Grasslands and wetlands are expected to decrease by 57.24% and 39.29%, respectively. The forest area is likely to shrink by 6.37%, about 9.82 km2, and 1.26 km2 being converted to agriculture and built-up areas, respectively. However, expansion in agricultural land shows very little increase in staple food crop production records, suggesting that farm size plays a minor role in increasing crop production. Predicting the near future LULC around KWK is useful for evaluating the likelihood of achieving development and conservation targets that are set locally, nationally and internationally.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"2010 1","pages":"189 - 209"},"PeriodicalIF":5.0,"publicationDate":"2021-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86295671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction modelling of riverine landscape dynamics in the context of sustainable management of floodplain: a Geospatial approach","authors":"Nasibul Alam, Subrata Saha, Srimanta Gupta, S. Chakraborty","doi":"10.1080/19475683.2020.1870558","DOIUrl":"https://doi.org/10.1080/19475683.2020.1870558","url":null,"abstract":"ABSTRACT Presently, sustainability of floodplain, a diverse element of the riverine landscape, provides an ideal research setting for investigating complex interaction between anthropogenic disturbance and eco-environmental degradation. Nowadays, these floodplains are continually degraded and fragmented on account of unsustainable land use. To analyse the spatial and temporal changes of landuse/landcover, a supervised classification (maximum likelihood algorithm) method has been made for the period 1998 to 2018. Present research simulates and predicts landuse/landcover dynamics of lower stretch of the Ganges river up to 2038 to analyse future riverine landscape dynamics stressed by various natural and socio-economic factors based on Cellular Automata-Artificial Neuron Network (CA-ANN) model clubbed with Modules for Land Use Change Evaluation (MOLUSCE) plugin of QGIS software. Outcome of research reveals that the trend of agriculture land, sand, and inland waterbody areas is reduced by 15.75, 5.71, and 1.95%, whereas, for orchard, agricultural fallow and bare land areas increased by 7.94, 7.92, and 5.69% for the period from 1998 to 2018. The simulation model predicted a continuation of the similar trend till 2038. The significant reduction of agricultural land and sand areas is largely an attribute to floodplain degradation in an altered hydrological regime. Ultimately, hydro-morphological changes, increasing population pressure, and agriculture intensification in floodplain landscape were identified as main driving forces in temporal landuse/landcover changes. The prediction of future forecast indicates that if the present rate of landuse/landcover trend persists in the study stretch of Ganges river without appropriate sustainable development practice, severe floodplain degradation will ensue. This study provides a holistic measure for understanding long-term environmental degradation related to anthropogenic activities and impact of climate changes in floodplain landscape at local and regional scale.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"384 2 1","pages":"299 - 314"},"PeriodicalIF":5.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73124534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction to advancements of GIS in the new IT era","authors":"Weiwei Song, Changshan Wu","doi":"10.1080/19475683.2021.1890920","DOIUrl":"https://doi.org/10.1080/19475683.2021.1890920","url":null,"abstract":"","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"122 1","pages":"1 - 4"},"PeriodicalIF":5.0,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87971396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Status analysis of geographic information science major in Chinese higher education","authors":"Shuliang Zhang, Ying Chen, Xin Yang, Li-yang Xiong, Zhenzhen Liu, G. Tang","doi":"10.1080/19475683.2021.1883108","DOIUrl":"https://doi.org/10.1080/19475683.2021.1883108","url":null,"abstract":"ABSTRACT Geographic Information Science (GIS) Major in China has been developing and flourishing for nearly 40 years. Chinese educators have made many achievements on major construction in GIS. However, opportunities and challenges coexist under the new situation of ‘Double First-Rate’ major construction in China. Thus, investigating and analysing the major status comprehensively are necessary for enhancing the development of the GIS major. This study analyses the enrolment magnitude of undergraduate and postgraduate students, student development, construction of teaching team and professional curriculum construction for GIS majors in mainland Chinese universities. The professional survey results showed that there are about 30,000 undergraduates and 4,000 postgraduates who graduate with GIS degrees every year. However, most of the undergraduates in this major do not take gGIS as their first choice in college major selection. In addition, 190 colleges and universities have set up GIS majors, who have played an important role in the development of GIS and industry. These colleges and universities are mostly concentrated in China’s central and eastern regions. The Education and Popularization Science Working Committee of the China Association for Geographic Information Society and the Ministry of Education’s Education Committee and other institutions have also organized several meaningful activities to strengthen the guidance of the GIS professional construction. A complete education system has been established to train undergraduates and postgraduates for the development of the geographic information industry in China.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"285 1","pages":"111 - 126"},"PeriodicalIF":5.0,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77881733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial analysis of malaria mortality in the kintampo health and demographic surveillance area of central Ghana","authors":"K. Wiru, Felix Boakye Oppong, Stephaney Gyaase, Oscar Agyei, S. Abubakari, S. Amenga‐Etego, Charles Zandoh, Kwaku Poku Asante","doi":"10.1080/19475683.2020.1853231","DOIUrl":"https://doi.org/10.1080/19475683.2020.1853231","url":null,"abstract":"ABSTRACT Malaria remains a menace to the existence of humanity in most contexts. Geospatial analysis of malaria mortality is crucial to identifying clusters of high disease burden and areas with limited access to malaria care for targeted control and remedial interventions. This study identified spatial and space-time clusters of malaria mortality in the Kintampo area of central Ghana. We used 1301 malaria deaths archived from 2005 to 2017 and Global Positioning System (GPS) point locations of the sub-districts in which these deaths occurred for our analysis. Mortality risks were smoothed and mapped using the Spatial Empirical Bayesian smoothing technique in Geoda (version 1.12.1.161) whereas spatial and spatio-temporal clustering analysis was done using SaTScan (version 9.6). Malaria mortality risks ranged between 1.2 and 2.4 deaths per 1000 population for persons of all ages and between 3.3 and 6.0 deaths per 1000 population for children under five years of age by sub-district. Two spatial clusters were detected for all-age malaria mortality with only the primary cluster (RR = 1.42, p = 0.001) being statistically significant. Also, two statistically significant space-time clusters were detected for all-age malaria mortality in the study area. The most likely cluster occurred between 2006 and 2011 in five sub-districts with a relative risk of 2.12 (p < 0.001) whilst the secondary cluster which had a relative risk of 2.47 (p < 0.001) occurred between 2005 and 2010 in four sub-districts. Similarly, only the most likely spatial cluster of under-five malaria mortality was statistically significant (RR = 1.36, p = 0.024). Furthermore, three spatio-temporal clusters of under-five malaria mortality were detected in the study area. The primary and second secondary clusters were statistically significant whilst the first secondary cluster had borderline significance. The primary cluster (RR = 4.49, p = 0.002) occurred in two sub-districts between 2006 and 2007. The first secondary cluster (RR = 2.21, P = 0.005) covered four sub-districts and was detected between 2006 and 2011 whereas the second secondary cluster (RR = 2.51, p = 0.003) covered two sub-districts between 2008 and 2013. Ultimately, our analysis identified a number of substantial spatial and apace-time clusters of malaria mortality in the study context, which could aid in the strategic planning, implementation and monitoring of targeted malaria control interventions.","PeriodicalId":46270,"journal":{"name":"Annals of GIS","volume":"3 1","pages":"139 - 149"},"PeriodicalIF":5.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84216484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}