Highly efficient computer oriented octree data structure and neighbors search in 3D GIS spatial

Three Dimensional (3D) have given new perspective in various field such as urban planning, hydrology, infrastructure modeling, geology etc due to its capability of handling real world object in more realistic manners, rather than two-dimensional (2D) approach. However, implementation of 3D spatial analysis in the real world has proven difficult due to the complexity of algorithm, computational power and time consuming. Existing GIS system enables 2D and two-and-a-half dimensional (2.5D) spatial datasets, but less capable of supporting 3D data structures. Recent development in Octree see more effort to improve weakness of octree in finding neighbor node by using various address encoding scheme with specific rule to eliminate the need of tree traversal. This paper proposed a new method to speed up neighbor searching and eliminating the needs of complex operation to extract spatial information from octree by preserving 3D spatial information directly from Octree data structure. This new method able to achieve O(1) complexity and utilizing Bit Manipulation Instruction 2 (BMI2) to speedup address encoding, extraction and voxel search 700% compared with generic implementation

Pembuatan Peta Risiko Banjir Menggunakan Analisa Site Suitability dan Pemodelan Genangan Banjir Untuk Mitigasi Dengan Penentuan Titik Evakuasi dan Jalur Evakuasi

Kabupaten Lombok Barat merupakan kabupaten yang masuk dalam urutan ketiga di NTB yang memiliki risiko banjir tinggi, dimana daerahnya memiliki geografis pegunungan, perbukitan dan dataran rendah sehingga risiko bencana banjir daerah tersebut tinggi. Penelitian ini bertujuan untuk : 1.) Membuat peta risiko banjir di kabupaten Lombok Barat, 2.) Mengetahui model 2D luapan genangan banjir di kabupaten Lombok Barat, 3.) Mengetahui persebaran titik evakuasi dan jalur evakuasi banjir di Kabupaten Lombok Barat. Metode yang digunakan adalah analisa site suitability (kesuaian lokasi) dengan metode AHP atau skoring dan pembobotan dan pemodelan genangan banjir dianalisa menggunakan aplikasi HEC-RAS. Berdasarkan hasil yang didapatkan, tingkat risiko rendah yang berada di Kecamatan Sekotong dengan luas 31.991,52114 Ha, risiko sedang dan risiko tinggi berada di Kecamatan Gerung dengan luas 1.574,658109 Ha untuk risiko sedang dan 1.295,468354 Ha untuk risiko tinggi. Setelah dianalisis, menghasilkan 146 jalur evakuasi dan 75 titik evakuasi yang efektif dan terjangkau dari bencana di Kabupaten Lombok Barat

COMPARATIVE ANALYSIS OF 3D PHOTOGRAMMETRY MODELING SOFTWARE PACKAGES FOR DRONES SURVEY

Drones are becoming popular in spatial mapping or survey. The use of drones survey can be seen from it low flying heights (capable to create a clear images), accessible on difficult or non-friendly vehicle access areas, faster data acquisition and higher data resolution henceforth improve the quality of the survey. However, this paper focuses on the post-processing of drone images for 3D surface modeling. With the motivation of producing better 3D models, four software packages are used for comparison. Those software packages are eyesMap3D, Drone Deploy, Agisoft PhotoScan and Pix4Dmapper. The equipment used to ensure a high level of quality model is the Leica GPS1200+ stationary GPS module and the DJI Phantom 4 PRO drone. The Leica GPS1200+ stationary GPS module were used to track the exact position of tie points on the ground. Meanwhile the DJI Phantom 4 PRO drone is used as data inputs (images) for the software packages stated. In addition, the drone is used to fly over a golf course, with a challenge of homogenous surface for 3D surface modeling. Based on the output, it shows that each software packages produces slightly different outputs. This paper summarizes the outputs and discusses the key elements in each software packages. This variation might be useful for future references in 3D surface modeling that can conform in different applications requirements

3D model for indoor spaces using depth sensor

In recent years, 3D model for indoor spaces have become highly demanded in the development of technology. Many approaches to 3D visualisation and modelling especially for indoor environment was developed such as laser scanner, photogrammetry, computer vision, image and many more. However, most of the technique relies on the experience of the operator to get the best result. Besides that, the equipment is quite expensive and time-consuming in terms of processing. This paper focuses on the data acquisition and visualisation of a 3D model for an indoor space by using a depth sensor. In this study, EyesMap3D Pro by Ecapture is used to collect 3D data of the indoor spaces. The EyesMap3D Pro depth sensor is able to generate 3D point clouds in high speed and high mobility due to the portability and light weight of the device. However, more attention must be paid on data acquisition, data processing, visualizing, and evaluation of the depth sensor data. Hence, this paper will discuss the data processing from extracting features from 3D point clouds to 3D indoor models. Afterwards, the evaluation on the 3D models is made to ensure the suitability in indoor model and indoor mapping application. In this study, the 3D model was exported to 3D GIS-ready format for displaying and storing more information of the indoor spaces

Visualising urban air quality using aermod, calpuff and CFD models: A critical review

Degradation of air quality level can affect human's health especially respiratory and circulatory system. This is because the harmful particles will penetrate into human's body through exposure to surrounding. The existence of air pollution event is one of the causes for air quality to be low in affected urban area. To monitor this event, a proper management of urban air quality is required to solve and reduce the impact on human and environment. One of the ways to manage urban air quality is by modelling ambient air pollutants. So, this paper reviews three modelling tools which are AERMOD, CALPUFF and CFD in order to visualise the air pollutants in urban area. These three tools have its own capability in modelling the air quality. AERMOD is better to be used in short range dispersion model while CALPUFF is for wide range of dispersion model. Somehow, it is different for CFD model as this model can be used in wide range of application such as air ventilation in clothing and not specifically for air quality modelling only. Because of this, AERMOD and CALPUFF model can be classified in air quality modelling tools group whereas CFD modelling tool is classified into different group namely a non-specific modelling tool group which can be implemented in many fields of study. Earlier air quality researches produced results in two-dimensional (2D) visualization. But there are several of disadvantages for this technique. It cannot provide height information and exact location of pollutants in three-dimensional (3D) as perceived in real world. Moreover, it cannot show a good representation of wind movement throughout the study area. To overcome this problem, the 3D visualization needs to be implemented in the urban air quality study. Thus, this paper intended to give a better understanding on modeling tools with the visualization technique used for the result of performed research

Penggunaan Metode Spatial Multi-Criteria Evaluation (Smce) Untuk Penilaian Risiko Bencana Tsunami (Studi Kasus : Pesisir Kabupaten Cilacap)

Indonesia menduduki peringkat kedua sebagai negara yang paling sering dilanda tsunami dengan 71 kejadian atau hampir 9% dari jumlah tsunami yang terjadi di seluruh dunia. Dari sepuluh negara yang mengalami jumlah kejadian terbesar tsunami di dunia, dari kurun waktu 2000 tahun sebelum masehi sampai tahun 2005, Indonesia menempati posisi rangking ketiga dari sisi banyaknya kejadian setelah Jepang dan USA, namun dari jumlah korban yang meninggal menempati rangking satu Tsunami merupakan bencana sekunder yang dipicu oleh berbagai kejadian sebelumnya, seperti gempabumi, letusan gunungapi, objek ekstraterestrial dan atau sebab antropogenik, yang mampu menyebabakan dislokasi vertikal dasar laut. Kabupaten Cilacap berada di rangking ketiga dalam tingkat nasional kerawanan bencana kelas rawan tinggi. Dalam penelitian ini digunakan pemodelan genangan akibat tsunami dengan persamaan Berryman dan penaksiran cepat Penelitian ini dimasudkan untuk mengetahui konsistensi model genangan hasil taksiran cepat dengan model Berryman di Pesisir Kabupaten Cilacap dengan parameter tinggi gelombang awal, kemiringan, dan koefisien kekasaran permukaan dan menggunakan kerentanan yang terdapat pada wilayah tersebut dan disatukan dengan metode Spatial Multi-Criteria Evaluation (SMCE). Hasil menunjukkan bahwa metode SMCE dapat diterapkan untuk mengetahui dampak tsunami dengan menggukanan parameter dan skoring untuk mendapatkan tingkat risiko bencana tsunami. Pada metode inipun dapat digunakan beberapa model ketinggian tsunami, pada tsunami 7 meter didapat hasil luasan 1280,344 Hektar luas tingkat risiko rendah mencapai 109,288 Hektar, tingkat risiko sedang yaitu 1001,582 Hektar, dan tingkat risiko tinggi yaitu 169,473 Hektar, Sedangkan luas terdampak tsunami jika dibagi tiap Kecamatannya yaitu pada Kecamatan Adipala terdampak seluas 671,441 Hektar, pada Kecamatan Binangun seluas 91,936 Hektar, Kecamatan Cilacap Selatan seluas 178,743 Hektar ,pada Kecamatan Cilacap Utara seluas 25,222 Hektar, Kecamatan Kesugihan seluas 161,094 Hektar dan Nusawungu seluas 151,908 Hektar. =============================================================================================== Indonesia has ranked second as the most frequently hit country by the tsunami with 71 events or almost 9% of tsunamis that occurred throughout the world. From ten countries that experienced the largest number of tsunami incidents in the world from 2000 BC until 2005, Indonesia has ranked on third in terms of the number of events after Japan and the USA, but ranked one from the number of victims who died. Tsunami was a secondary disaster triggered by various previous events, such as earthquakes, volcanic eruptions, extraterrestrial objects and / or anthropogenic causes, which are capable of causing a vertical dislocation of the seabed. Cilacap Regency has ranked third in the national high level of disaster vulnerability. In this study used tsunami inundation modeling with Berryman's equation and rapid assessment. This study was intended to find out the consistency of rapid estimation inundation models with Berryman's model in the Cilacap Regency with parameters of initial wave height, slope, surface roughness coefficient, using vulnerabilities that found in the region and integrated with the Spatial Multi-Criteria Evaluation (SMCE) method. The results show that the SMCE method can be applied to determine the impact of the tsunami by using parameters and scoring to get the level of tsunami disaster risk. In this method, several tsunami altitude models can be used. In the tsunami with 7 meters height, the results of the area are 1280.344 hectares. The low risk level reaches 109.288 hectares. The extent of the risk level reaches 1001.582 hectares, and the high risks level reaches 169.473 hectares. While the area affected by the tsunami consisted of the defected Adipala Subdistrict covering an area of 671.441 hectares, in Binangun Subdistrict covering 91.936 hectares, Cilacap Selatan Subdistrict covering 178.743 hectares, Cilacap Utara Subdistrict covering 25.222 hectares, Kesugihan District covering 161.094 hectares and Nusawungu covering 151.908 hectares

Influence of georeference for saturated excess overland flow modelling using 3D volumetric soft geo-objects

Existing 2D data structures are often insufficient for analysing the dynamism of saturation excess overland flow (SEOF) within a basin. Moreover, all stream networks and soil surface structures in GIS must be preserved within appropriate projection plane fitting techniques known as georeferencing. Inclusion of 3D volumetric structure of the current soft geo-objects simulation model would offer a substantial effort towards representing 3D soft geo-objects of SEOF dynamically within a basin by visualising saturated flow and overland flow volume. This research attempts to visualise the influence of a georeference system towards the dynamism of overland flow coverage and total overland flow volume generated from the SEOF process using VSG data structure. The data structure is driven by Green-Ampt methods and the Topographic Wetness Index (TWI). VSGs are analysed by focusing on spatial object preservation techniques of the conformal-based Malaysian Rectified Skew Orthomorphic (MRSO) and the equidistant-based Cassini-Soldner projection plane under the existing geodetic Malaysian Revised Triangulation 1948 (MRT48) and the newly implemented Geocentric Datum for Malaysia (GDM2000) datum. The simulated result visualises deformation of SEOF coverage under different georeference systems via its projection planes, which delineate dissimilar computation of SEOF areas and overland flow volumes. The integration of Georeference, 3D GIS and the saturation excess mechanism provides unifying evidence towards successful landslide and flood disaster management through envisioning the streamflow generating process (mainly SEOF) in a 3D environment

Geomorphometry 2020. Conference Proceedings

Geomorphometry is the science of quantitative land surface analysis. It gathers various mathematical, statistical and image processing techniques to quantify morphological, hydrological, ecological and other aspects of a land surface. Common synonyms for geomorphometry are geomorphological analysis, terrain morphometry or terrain analysis and land surface analysis. The typical input to geomorphometric analysis is a square-grid representation of the land surface: a digital elevation (or land surface) model. The first Geomorphometry conference dates back to 2009 and it took place in Zürich, Switzerland. Subsequent events were in Redlands (California), Nánjīng (China), Poznan (Poland) and Boulder (Colorado), at about two years intervals. The International Society for Geomorphometry (ISG) and the Organizing Committee scheduled the sixth Geomorphometry conference in Perugia, Italy, June 2020. Worldwide safety measures dictated the event could not be held in presence, and we excluded the possibility to hold the conference remotely. Thus, we postponed the event by one year - it will be organized in June 2021, in Perugia, hosted by the Research Institute for Geo-Hydrological Protection of the Italian National Research Council (CNR IRPI) and the Department of Physics and Geology of the University of Perugia. One of the reasons why we postponed the conference, instead of canceling, was the encouraging number of submitted abstracts. Abstracts are actually short papers consisting of four pages, including figures and references, and they were peer-reviewed by the Scientific Committee of the conference. This book is a collection of the contributions revised by the authors after peer review. We grouped them in seven classes, as follows: • Data and methods (13 abstracts) • Geoheritage (6 abstracts) • Glacial processes (4 abstracts) • LIDAR and high resolution data (8 abstracts) • Morphotectonics (8 abstracts) • Natural hazards (12 abstracts) • Soil erosion and fluvial processes (16 abstracts) The 67 abstracts represent 80% of the initial contributions. The remaining ones were either not accepted after peer review or withdrawn by their Authors. Most of the contributions contain original material, and an extended version of a subset of them will be included in a special issue of a regular journal publication

Landslide susceptibility evaluation and validation at a regional scale

Tese de doutoramento, Geografia (Geografia Física), Universidade de Lisboa, Instituto de Geografia e Ordenamento do Território, 2014This dissertation aims to deepen the knowledge about the causes that influence the spatial and temporal occurrence of slope instability at a regional scale. The study area, located 90km north from Lisbon, comprises three sub‐catchments, named Arnoia, Tornada and Alfeizerão (275.9 km2). These sub‐catchments were chosen for their geological and geomorphological features and because it is an area prone to slope instability. Many methods have been proposed worldwide to evaluate landslide hazard. In this dissertation there are presented and performed two approaches that, according to Guzzetti (2002), are the most promising: physically‐based methods; and statisticallybased methods. Methodologies were applied for acquisition of their input data. In addition, within the physically‐based methods was also implemented a temporal dynamic approach, which simulated the hydrology over time and evaluated its effects on slope stability. Thereby, in order to obtain the overall goal the following 10 specific objectives were stated: 1) Acquisition of multi‐temporal landslide inventories; 2) Acquisition and production of new themes based on modeling and field observation (e.g. detailed lithological map, morpho‐structural map, DEM, soil depth); 3) Acquisition of soil characteristics according to the hydrogeological and geotechnical properties of soils (through field work, laboratory measurements and back analysis; 4) Landslide susceptibility assessment using the hydrological model coupled to slope stability model under static temporal conditions and its validation through the quantification of the degree of prediction rate; 5) Acquisition, processing and modeling of long term climatic data (e.g., rainfall and temperature); 6) Landslide susceptibility assessment using hydrological model coupled to slope stability model under dynamic temporal conditions and its validation through the quantification of the degree of prediction rate; 7) Comparison between physically base models: static and dynamic approach; 8) Sensitivity analysis and hierarchy of the landslide predisposing factors; 9) Landslide susceptibility assessment using statistically‐based method (Information Value Method) and its validation through the quantification of prediction and success rate; 10) Comparison between statistically and physically static models. Some input data, of extreme importance for every method used in this dissertation, proved to be very difficult to obtain. It is worth mention the case of the geological map, which was only available at a 1:50,000 scale. Thus, being aware that landslides are greatly conditioned by the lithological properties of the terrain, a detailed lithological map at a 10,000 scale was performed through the stereoscopic interpretation of aerial photographs and field work validation.The quality of the landslide inventory is of crucial importance for any prediction model. Thus, a multi‐temporal landslide inventory was achieved through aerial photo‐interpretation, orthophotomaps interpretation and field work. Since the models obtained through the Infinite Slope method aim to predict the areas susceptible to shallow translational slides, a validation was made based on the shallow translational slides validated through field work. Further, all the landslides types from each landslide inventory were modeled through a bivariated statistical method (Information Value Method). A comparison, between the shallow translational slides susceptible model obtained from different approaches was also performed. The main conclusions of the work are the following: 1) The detailed lithological map has a better discriminating power than the original lithological map; 2) Trough a spatial and temporal dynamic physically‐based method it is possible to inferred the possible conditions that triggered shallow translational slides; 3) the static physically‐based method, presented better skills for predicting the spatial occurrence of shallow translational slides over the study area than the statistically‐based method.Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/46816/2008

Pemanfaatan Data Penginderaan Jauh Dan Sistem Informasi Geografis Untuk Analisa Banjir (Studi Kasus : Banjir Provinsi DKI Jakarta)

Banjir merupakan salah satu fenomena alam yang sering terjadi di berbagai wilayah. Banjir dalam dua pengertian, yaitu : 1) meluapnya air sungai yang disebabkan oleh debit sungai yang melebihi daya tampung sungai pada keadaan curah hujan tinggi, 2) genangan pada daerah dataran rendah yang datar yang biasanya tidak tergenang. Banjir merupakan salah satu bencana yang sering terjadi di Indonesia, khususnya kota-kota besar seperti Jakarta.Daerah bahaya banjir dapat diidentifikasi secara cepat dengan menggunakan memanfaatkan data Penginderaan Jauh yaitu tumpang susun/overlay terhadap parameter-parameter banjir, seperti : curah hujan, bentuk penggunaan lahan (landuse), tekstur tanah, dan kemiringan lereng. Serta perpaduan visualisasi persebaran banjir dengan SIG (Sistem Informasi Geografi). Pembagian kelas dari setiap parameter yang digunakan secara umum disesuaikan dengan kelas parameter yang dimiliki oleh daerah yang diamati.Nilai bobot dan skor juga menyesuaikan dengan daerah penelitian yang diamati. Dalam penelitian ini, nilai bobot dan skor yang digunakan merupakan modifikasi dari vi nilai bobot dan skor. Dari hasil bobot dan skoring lalu menghitung Nilai potensi suatu daerah terhadap genangan ditentukan dari total penjumlahan skor masing-masing parameter genangan. Daerah yang sangat berpotensi terhadap genangan akan memiliki skor total dengan jumlah paling besar dan sebaliknya daerah yang tidak berpotensi terhadap genangan akan mempunyai total skor yang rendah. Tabel berikut menunjukkan tingkat potensi genangan berdasarkan nilai penjumlahan skor masing-masing parameter genangan.Hasil yang didapatkan penetapan kawasan bahaya banjir, ternyata daerah bahaya banjir yang dibuat Pemerintah Provinsi DKI 100% semuanya masuk dalam daerah sangat bahaya banjir berdasarkan hasil penelitian.Hal ini terjadi karena memang setiap musim penghujan daerah-daerah bahaya tersebut selalu mengalami banjir atau langganan banjir. ================================================================================================== Flood is one of the natural phenomenon that often occurs in the various regions. Floods in two senses : 1) the overflow of river water caused by the river flow exceeds the capacity of the river in the state of high rainfall, 2) a puddle on the flat lowland areas are usually flows. Flood is one disaster which often occurs in Indonesia, especially big cities likes Jakarta. Flood can be identified quickly by using Remote Sensing utilize data that is overlay with against flood parameters, such as rainfall, land uses, soil texture,elevation and slope. As well as the visualization of the distribution of flood blend with GIS (Geographic Information System). Class divisions of each of the parameters used are generally tailored to the class parameter owned by local weights and scores.The Value also adjust the study area were observed. In this study, the value of weights and scores are used is a modification of the weights and scores. From the results of the scoring weights and then calculating the value of the potential of an area of the inundation determined from the total sum score of each flood parameter . Area that is potentially against inundation will have a total score with the greatest number and vice versa areas without the potential for inundation will have a low total viii score. The following table shows the level of potential inundation based on the value of the sum of scores of each parameter obtained. Result of determination of flood hazard areas, it turns out the flood hazard area made the city administration 100% all in danger of flooding in the area is based on the results of this happened .Iindeed every rainy season danger areas are always flooded