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"This paper evaluates the use of local government websites for spatial data dissemination based on a survey conducted from 2 October to 28 November 2008...."

"The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. "

"This book explores computational structure of the exact and approximate spatial autoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function. "

"Studi ini menunjukkan bahwa kejahatan memiliki konsentrasi spasial. Konsentrasi spasial tersebut dipengaruhi oleh dua aspek: individu dan kontekstual. Secara individu, marginal cost (MC) yang sama mengarah pada keputusan lokasi kejahatan yang serupa. Secara kontekstual, studi ini melihat dua fenomena yang terkait dengan kejahatan, yaitu kemiskinan dan pengangguran. Studi ini bertujuan untuk (1) menyelidiki pola kejahatan yang spesifik secara spasial sehingga kita dapat memprediksi dan melawan kejahatan, (2) menyelidiki perilaku kriminal dan pengaruhnya terhadap pemilihan lokasi kejahatan dari perspektif spasial ekonomi, dan (3) melihat secara spesifik hubungan kejahatan dengan isu kemiskinan yang sudah mempertimbangkan efek spasial. Metode Exploratory Spatial Data Analysis (ESDA) digunakan dalam analisis spasial. Data kejahatan menurut jenisnya di area Polda Metro Jaya tahun 2011, dengan unit analisis Polsek, menunjukkan bahwa penodongan, perampasan, perjudian, pencurian sepeda motor, pembakaran pencurian mobil, pencurian berat, narkoba, kenakalan remaja dan pemerasan mempunyai otokorelasi spasial positif. Sebaliknya, perampokan, pembajakan, pemerkosaan, dan pembunuhan tidak mempunyai hubungan otokorelasi spasial. Model kompetisi spasial dalam pemilihan lokasi untuk melakukan kejahatan menunjukkan bahwa para pelaku kejahatan dengan biaya (marginal cost) yang sama mempunyai kecenderungan untuk memilih tempat yang serupa untuk melakukan kejahatan mereka. Data survei narapidana pencuri sepeda motor dari Polda Jawa Barat pada tahun 2011 menunjukkan bahwa pilihan teknologi (alat yang digunakan, lama melakukan, jumlah yang melakukan, dan waktu melakukan) mempengaruhi pemilihan lokasi dalam mencuri sepeda motor. Lebih lanjut lagi pilihan teknologi dipengaruhi oleh jejaring sosial dari pelaku kejahatan. Setelah mempertahankan jenis kejahatan yang mempunyai otokorelasi spasial, hasil menunjukkan bahwa hubungan spasial kejahatan dengan kemiskinan tidak sesederhana yang diduga. Walaupun ada hubungan spasial antara keduanya, hubungan itu tidak terjadi pada semua jenis kejahatan. Selain itu, studi ini menunjukkan bahwa dengan memakai unit analisis yang lebih kecil dan jenis kejahatan yang lebih spesifik, hasil yang didapat juga akan lebih spesifik dan berguna untuk melawan dan mencegah kejahatan.

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This study shows that crime has spatial concentration. Two aspects that can influence the incidence of crime are investigated: individual and contextual aspects. Individually, having similar marginal costs lead to decision to conduct crime in similar location. Contextually, two phenomena related to crime, namely, poverty and youth unemployment, are tested whether they are spatially correlated with crimes. This study has three objectives: (1) to investigate spatial specific patterns of specific crime to predict and fight crime, (2) to investigate criminal behavior and its effect on crime scene selection from an economic spatial perspective; and (3) to see the spatial relationship between crime and poverty and unemployment. The Exploratory Spatial Data Analysis (ESDA) method is used. Data of crime by type comes from a unique dataset collected by the Polda Metro Jaya (Metro Jaya Provincial Level Police Station) in 2010, with Polsek (subdistrict-level police station) as a unit of analysis. The results show that mugging, plundering, gambling, motorcycle theft, car theft firing, heavy theft, drugs, juvenile delinquency and extortion have positive spatial autocorrelation. In contrast, robbery, piracy, rape, and murder have no spatial autocorrelation relationship. The spatial competition model for crimes location decision shows that perpetrators with similar cost have a tendency to choose the same place to commit their crimes. The survey data of motorcycle thief inmates from Polda Jawa Barat in 2011 shows that the choice of technology (tools used, length of conduct, number people who conduct motorcycle theft, and time of conduct) affected site selection in stealing motorcycles. Furthermore, the choice of technology is affected by social network of the perps.After retaining the type of crime that has spatial autocorrelation for the analysis, the results show that the relationship is not straightforward: while there was a spatial relationship between crime and poverty, but they did not occur for all types of crime. In addition, this study demonstrates that using smaller analytical units and more specific types of crimes provide more specific and useful results to predict and fight crime."

"Agriculture is the biggest economic sector in Indonesia, and uses about 95 % of developed land. To optimize agricultural sector in land, recommendation on the availability of technology, location, and specific commodity are required. Those recommendation depend on typology of region that characterized by physical and social economic environment and also social infrastructure as rich asset culture. This study use landform approach and it is used as mapping unit. Landform data can support information regional potency and would be a database for Indonesian region planning as a whole. Making a good identification of regional potency, tent to reduce of error on plan of using land in the region. The aim of this study were: a). To know distribution pattern and area of land that suitable for agro industry commodity base on delineation of landform and administration; b) To develop spatial model developing of agro industry plantation by comparing between providing of land agro industry and characteristic of landform to achieve sustainable development. The problems that want to be answered is how distribution pattern of land suitability for agro industry commodity and how many land forms are suitable for agriculture. Data and information are provided on geographic information system (GIS) with user interface is map on scale 1:100.000. Collecting data use observation, systematic and non direct method. Data's consist of primer and secondary. Analysis used ranking method, and qualitative properties. Parameter which used are spatial and non spatial or attribute. Those parameter consist of 11 (eleven) types, those are mean temperature, precipitation, length of dry month, drainage, texture, soil depth, pH, slope, erosion hazard, inundation, and outcrops. Technical of analysis is overlay (for spatial analysis) and joint item (for tabular analysis). Analysis results showed that the suitable level in Sasamba area are class S2 (moderately suitable), class S3 (marginally suitable), and not suitable (N). Based on administration boundary (kecamatan), showed that the area that is recommended for development of agroindustry (area has more than 20.000 ha) are Kecamatan Samarinda Ilir (26.567 ha) , Samboja (65.576 ha), Loajanan (58.986 ha), Muarajawa (49.073 ha). Based on morphology, land suitability for development of agro industry appointed on plain (79,48 %) and hilly area (20,52 %). Based on morphogenesis, land suitability for development of agro industry located on Denudasional (59,53 %), Fluvial (22,05 %), Marine (12,60 %), Structural (5,82 %)."

"ABSTRAKSpatial inequality occurs because the rate of availability of geospatial data has not been able to catch up and meet user needs. The root of the problem occurs because the network nodes in the area have not yet been formed or dissolved. The institutional status of network nodes at the provincial level as of October 2018, only 20 out of 34 provinces are operational, with 4 institutional options, namely UPT, Bappeda, Ad Hoc Regional Secretary and Ad Hoc Diskominfotik. This triggered anxiety for 14 regions that had not yet formed network nodes and 3 other UPTDs that were still awaiting evaluation results. To determine the institution of ideal geospatial information, BIG has conducted a study of institutional arrangements to realize effective and efficient regional apparatus organizations according to their duties and functions. The study with qualitative research methods was carried out by analyzing criteria and rating on institutional aspects in order to strengthen IDSN, based on applicable policies and laws as well as the results of the network node operationalization questionnaire in the province. Furthermore, the study was strengthened using quantitative research methods by comparing the costs and benefits of each institutional option (cost and benefit analysis) through the net present value approach. The results of the two methods are 2 alternative institutional geospatial information with the best value, namely Option 1 UPTB Ideal for the long term and Option 3 Ad Hoc in Regional Secretary Quick Win for the medium term."

"This book discusses human factors research directed towards realizing and assessing sustainability in the built environment. It reports on advanced engineering methods for sustainable infrastructure design, as well as on assessments of the efficient methods and the social, environmental, and economic impact of various designs and projects. The book covers a range of topics, including the use of recycled materials in architecture, ergonomics in buildings and public design, sustainable design for smart cities, design for the aging population, industrial design, human scale in architecture, and many more. Based on the AHFE 2018 International Conference on Human Factors, Sustainable Urban Planning and Infrastructure, held on July 21–25, 2018, in Orlando, Florida, USA, it offers various perspectives on sustainability and ergonomics. As such, it is a valuable reference resource for designers, urban engineers, architects, infrastructure professionals, public infrastructure owners, policy makers, government engineers and planners, as well as operations managers and academics active in urban and infrastructure research."