This geographic information system combines detailed information and location coordinates for oil wells, gas wells, and pipelines from the Commission's files with base map data captured from U.S. Geological Survey 7.5 minute quadrangle maps. These interactive maps were developed using Environmental Systems Research Institute, Inc. (ESRI) ArcIMS software, and interface with the Commission's Production Data Query and Drilling Permit Query applications.

Provide the map data of the stormwater and sewer pipelines in Chiayi City, and use GIS software to import the SHP map data.

The subsurface utility mapping (SUM) market is experiencing robust growth, driven by increasing urbanization, infrastructure development projects, and the need to prevent costly damage to underground utilities. The market, valued at approximately $12 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, stringent regulations mandating utility mapping before excavation projects are significantly contributing to market demand. Secondly, technological advancements, such as the adoption of LiDAR, ground-penetrating radar (GPR), and GIS technologies, are improving the accuracy, efficiency, and cost-effectiveness of SUM. Furthermore, the rising adoption of 3D modeling and data analytics enhances the value proposition of SUM by providing comprehensive visualization and analysis of underground infrastructure. The market segmentation demonstrates a diverse landscape, with significant contributions from both the hardware (sensors, GPR systems) and software (data processing, analysis platforms) segments, catering to various applications like water pipelines, gas pipelines, electric cables, and telecommunications. North America and Europe currently hold the largest market share, reflecting advanced infrastructure and stringent regulatory environments. However, rapid infrastructure development in Asia-Pacific is projected to drive substantial market growth in the coming years. The restraints to market growth include the high initial investment costs associated with advanced SUM technologies and a shortage of skilled professionals capable of operating and interpreting the data generated. Despite these challenges, the long-term benefits of preventing utility damage, improving project efficiency, and ensuring public safety are driving the continued adoption of SUM. The competitive landscape is characterized by a mix of established companies specializing in specific technologies or services and emerging players focusing on innovative solutions. Future market growth will hinge on continued technological innovation, the development of user-friendly software, and the increasing integration of SUM data with other infrastructure management systems, paving the way for smarter cities and improved infrastructure management globally.

Location of all current Pipeline Licence Applications issued under the Petroleum and Geothermal Energy Act 2000 (the P&GE Act supersedes the Petroleum Act 2000), Petroleum (Submerged Lands) Act, 1982, or Petroleum (Submerged Lands) Act, 1967 for the purpose of conveying petroleum or another regulated substance from place to place which includes tanks, machinery and equipment necessary for, or associated with, its operation; and a part of a pipeline. Pipeline Licences provide exclusive tenure rights to operate the pipeline for which it relates, for 21 years (or a lesser term agreed between the pipeline licensee and the Minister).

Available format: ESRI Shape, MAPINFO Tab, Google Earth KMZ and WMS/WFS.

Instructions: From SARIG Map Layer, click on 'Petroleum Tenements', 'Petroleum Pipelines and Facilities Tenements', 'Application, Gas and Liquids Pipeline Licence (Petroleum)'.

To download dataset, instructions are available at: http://www.minerals.dmitre.sa.gov.au/sarighelp/map_layers#L5

800+ GIS Engineers with 25+ years of experience in geospatial, We provide following as Advance Geospatial Services:

Analytics (AI) Change detection Feature extraction Road assets inventory Utility assets inventory Map data production Geodatabase generation Map data Processing /Classifications
Contour Map Generation Analytics (AI) Change Detection Feature Extraction Imagery Data Processing Ortho mosaic Ortho rectification Digital Ortho Mapping Ortho photo Generation Analytics (Geo AI) Change Detection Map Production Web application development Software testing Data migration Platform development

AI-Assisted Data Mapping Pipeline AI models trained on millions of images are used to predict traffic signs, road markings , lanes for better and faster data processing

Our Value Differentiator

Experience & Expertise -More than Two decade in Map making business with 800+ GIS expertise -Building world class products with our expertise service division & skilled project management -International Brand “Mappls” in California USA, focused on “Advance -Geospatial Services & Autonomous drive Solutions”

Value Added Services -Production environment with continuous improvement culture -Key metrics driven production processes to align customer’s goals and deliverables -Transparency & visibility to all stakeholder -Technology adaptation by culture

Flexibility -Customer driven resource management processes -Flexible resource management processes to ramp-up & ramp-down within short span of time -Robust training processes to address scope and specification changes -Priority driven project execution and management -Flexible IT environment inline with critical requirements of projects

Quality First -Delivering high quality & cost effective services -Business continuity process in place to address situation like Covid-19/ natural disasters -Secure & certified infrastructure with highly skilled resources and management -Dedicated SME team to ensure project quality, specification & deliverables

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Pipeline Integrity Management Market Size 2024-2028

The pipeline integrity management market size is forecast to increase by USD 2.16 billion at a CAGR of 4.5% between 2023 and 2028.

The market is driven by stringent regulations and the increasing trade of oil and gas. Regulatory bodies worldwide are enforcing stricter guidelines to ensure pipeline safety and prevent potential hazards, leading companies to invest heavily in pipeline integrity management solutions. Furthermore, the growing trade of oil and gas, particularly in developing economies, is fueling the demand for robust pipeline infrastructure to meet the increasing energy requirements. However, the market faces challenges, including the rising awareness of renewable energy sources and the high cost of pipeline maintenance and upgrades.
As renewable energy gains popularity, the demand for oil and gas may decrease, potentially impacting the market. Additionally, the high cost of maintaining and upgrading pipelines can hinder market growth, necessitating the need for cost-effective solutions and innovative technologies to address these challenges. Companies in the market must navigate these dynamics to capitalize on opportunities and effectively manage risks.

What will be the Size of the Pipeline Integrity Management Market during the forecast period?

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The pipeline integrity market is characterized by continuous evolution and dynamism, driven by the complexities and intricacies of managing the vast network of pipelines that transport essential resources across various industries. Pipeline integrity standards serve as the foundation, providing a robust framework for ensuring the safety and reliability of these critical assets. Pipeline integrity plans, strategies, and solutions are intricately interwoven, with ongoing innovation and optimization shaping the landscape. Pipeline integrity technologies, from sensors to simulation software, play a pivotal role in monitoring, assessing, and maintaining pipeline integrity. Engineering and design are essential components of pipeline integrity, with a focus on minimizing risk and maximizing asset life.
Repair, replacement, and rehabilitation are integral parts of the pipeline integrity lifecycle, requiring specialized expertise and advanced tools. Pipeline integrity regulations and programs shape the industry, with a growing emphasis on automation, consulting, and data management. Corrosion management and inspection are crucial aspects of pipeline integrity, with ongoing efforts to improve pipeline integrity analysis and modeling. The pipeline integrity market is a dynamic and ever-evolving landscape, with constant innovation and adaptation required to meet the demands of managing and maintaining these critical assets.

How is this Pipeline Integrity Management Industry segmented?

The pipeline integrity management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  Onshore
  Offshore


Geography

  North America

    US


  Europe

    Russia
    UK


  APAC

    China


  Rest of World (ROW)

By Deployment Insights

The onshore segment is estimated to witness significant growth during the forecast period.

Pipeline integrity is a critical concern for operators as these infrastructure systems are susceptible to various deterioration processes, including corrosion, erosion, and embrittlement, collectively referred to as aging. Additionally, pipelines can fail due to non-age-related damage processes, such as overpressure or third-party tampering. To ensure pipeline safety and regulatory compliance, operators employ pipeline integrity standards, plans, and frameworks. They invest in pipeline integrity solutions and technologies, such as pipeline integrity modeling software, sensors, and data management systems, to optimize pipeline performance and minimize risks. Pipeline integrity engineering plays a vital role in the design, construction, and maintenance phases.

During the conceptual design phase, aerial photography and surface mapping are used to survey onshore pipeline routes to choose the most effective and cost-efficient path with the least environmental impact. Pipeline integrity training equips professionals with the necessary skills to analyze pipeline data and assess risks. Pipeline integrity repair, rehabilitation, and replacement strategies are implemented to address aging infrastructure and prevent potential failures. Corrosion management is a significant focus area, with pipeline integrity consulting services offering expertise in this domain. Automation and innovation are essential in pipeline integrity, with pipeline integrity automation and pipeline integrity tools streamlining processes a

The engineering-geologic map is derived electronically, using Geographic Information System (GIS) software, from the surficial-geologic map of the second segment of the proposed natural gas pipeline corridor through the upper Tanana valley, a 12-mi-wide (19.3-km-wide) area that straddles the Alaska Highway through the upper Tanana River valley from the Robertson River eastward to near Tetlin Junction in the Tanacross Quadrangle (Reger and Hubbard, PIR 2009-6A). Surficial-geologic units were initially identified by interpretation of false-color ~1:65,000-scale infrared aerial photographs taken in July 1978, August 1980, and August 1981 and locally verified by field checking in 2007 and 2008. The map shows the distribution of surficial-geologic and bedrock units grouped genetically with common properties that are typically significant for engineering applications.

ABSTRACT Soil maps provide a method for graphically communicating what is known about the spatial distribution of soil properties in nature. We proposed an optimized pipeline, named dino-soil toolbox, programmed in the R software for mapping quantitative and categorical properties of legacy soil data. The pipeline, composed of four main modules (data preprocessing, covariates selection, exploratory data analysis and modeling), was tested across a study area of 14,537 km 2 located between the departments of Cesar and Magdalena, Colombia. We assessed the feasibility of the toolbox to model three soil properties: pH at two depth intervals (0.00-0.30 and 0.30-1.00 m), soil taxonomy (great group) and taxonomic family by particle-size, according to a set of 25 environmental factors derived from auxiliary layers of climate, land cover and terrain. As a result, we successfully deployed the proposed semi-automatic and sequential pipeline, yielding rapid digital soil mapping (DSM) outputs across the study area. By providing multiple outputs such as tables, charts, maps, and geospatial data in four main modules, the pipeline offers considerable robustness to support outcomes and analysis of a DSM project. Future studies might be interesting to expand on further machine learning frameworks for predictive modeling of soil properties such as ensembles and deep learning models, which have shown a high performance for DSM.

These are several processed datasets for the purpose of investigating 4sU-induced toxicity, mapping impairment and the potential of grandRescue to alleviate these effects.

Published dataset: Narain dataset (Narain, et al.): https://doi.org/10.1016/j.molcel.2021.06.016

The zip files contain the full output from the processing pipeline (including the mapped reads, the scripts to run the pipeline and the output). The json file is required if you want to start from scratch. The *.tsv.gz files are the GRAND-SLAM output tables.

To generate the GRAND-SLAM output yourself, first prepare the mouse & human genomes. Then run the following command with the respective cit-files, prefixes (*.cit) and genomes (e.g. h.ens90 or m.ens102):

gedi -e Slam -trim5p 15 -reads *.cit -genomic m.ens102 -prefix grandslam_t15/* -plot -D -modelall

To generate the cit file you have to modify the first lines in start.bash to match the paths on your file system, and then run it.

You can also start from scratch (i.e., the json file):

Prepare the human/mouse genome and their rRNA sequence
Run: gedi -e Pipeline -r parallel -j *.json rnaseq_mapping.sh report.sh grandslam.sh

Software versions:

gedi toolkit 1.0.5
GRAND-SLAM 2.0.7
STAR version 2.7.10b

Spatial distribution map of roads, railways and pipelines in China Mongolia Russia economic corridor from 1990 to 2020 1) Spatial data of highway, railway and pipeline in 1990; Spatial data of roads, railways and pipelines in China Mongolia Russia economic corridor in 2015; Spatial data of roads, railways and pipelines in China Mongolia Russia economic corridor in 2020; 2) Download the remote sensing images within the China Mongolia Russia economic corridor on NASA website and use arcgis10 2 software manual interpretation and extraction of highway and railway; Map elements are marked with the help of Russian atlas; The pipeline data shall be manually marked with reference to relevant maps; 3) The scale of the atlas is 1:2500000, which clearly reflects the changes of traffic and pipelines in the China Mongolia Russia economic corridor in recent 30 years,; 4) The data shows in detail the changes of traffic and pipelines in the China Mongolia Russia economic corridor in recent 30 years, which provides a data basis for the later study of the impact of traffic and pipeline construction on the change of ecological environment.

Single molecule map stretch per scan in recent flowcells. Bases per pixel (bpp) is plotted for scans 1..n for each flowcell of mouse lemur molecules (purple). The first scan of each flowcell is indicated with a grey dashed line. The pre-adjusted molecule map stretch was determined by aligning molecule maps to the in silico maps. Data made available by P.A. Larsen, J. Rogers, A.D. Yoder and the Duke Lemur Center. (ZIP 55 kb)

Assembly of T. castaneum consensus genome maps with range of parameters. Detailed assembly metrics for assembled consensus genome maps using strict, default and relaxed “-T” parameter, p-value threshold are named Relaxed-T, Default-T and Strict-T respectively. The best “-T” parameter was used for two additional assemblies with either relaxed minimum molecule map length (relaxed-minlen) of 100 kb, rather than the 150 kb default, or a strict minimum molecule map length (strict-minlen) of 180 kb. (CSV 389 kb)

elPrep is a high-performance tool for preparing sequence alignment/map files for variant calling in sequencing pipelines. It can be used as a replacement for SAMtools and Picard for preparation steps such as filtering, sorting, marking duplicates, reordering contigs, and so on, while producing identical results. What sets elPrep apart is its software architecture that allows executing preparation pipelines by making only a single pass through the data, no matter how many preparation steps are used in the pipeline. elPrep is designed as a multithreaded application that runs entirely in memory, avoids repeated file I/O, and merges the computation of several preparation steps to significantly speed up the execution time. For example, for a preparation pipeline of five steps on a whole-exome BAM file (NA12878), we reduce the execution time from about 1:40 hours, when using a combination of SAMtools and Picard, to about 15 minutes when using elPrep, while utilising the same server resources, here 48 threads and 23GB of RAM. For the same pipeline on whole-genome data (NA12878), elPrep reduces the runtime from 24 hours to less than 5 hours. As a typical clinical study may contain sequencing data for hundreds of patients, elPrep can remove several hundreds of hours of computing time, and thus substantially reduce analysis time and cost.

These baseline studies cover the following topics with regards to the impacts of the Pacific Trail Pipeline: acid rock drainage and metal leaching, acoustic environment, air quality, archaeology, contaminated sites, fish and fish habitats, forestry, paleontological resources, physiography and geology, socio-economics, soils, terrestrial ecosystems and mapping, vegetation, and wildlife and wildlife habitats. Acid rock drainage and metal leaching, fish and fish habitat investigations, and a soil assessment are included in this dataset as they are pertinent to salmon in the Skeena; however, the remaining topics can be found on the provided link.

Overview

3DHD CityScenes is the most comprehensive, large-scale high-definition (HD) map dataset to date, annotated in the three spatial dimensions of globally referenced, high-density LiDAR point clouds collected in urban domains. Our HD map covers 127 km of road sections of the inner city of Hamburg, Germany including 467 km of individual lanes. In total, our map comprises 266,762 individual items.

Our corresponding paper (published at ITSC 2022) is available here.
Further, we have applied 3DHD CityScenes to map deviation detection here.

Moreover, we release code to facilitate the application of our dataset and the reproducibility of our research. Specifically, our 3DHD_DevKit comprises:

• Python tools to read, generate, and visualize the dataset,
• 3DHDNet deep learning pipeline (training, inference, evaluation) for
  map deviation detection and 3D object detection.

The DevKit is available here:

https://github.com/volkswagen/3DHD_devkit.

The dataset and DevKit have been created by Christopher Plachetka as project lead during his PhD period at Volkswagen Group, Germany.

When using our dataset, you are welcome to cite:

@INPROCEEDINGS{9921866,
  author={Plachetka, Christopher and Sertolli, Benjamin and Fricke, Jenny and Klingner, Marvin and 
  Fingscheidt, Tim},
  booktitle={2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)}, 
  title={3DHD CityScenes: High-Definition Maps in High-Density Point Clouds}, 
  year={2022},
  pages={627-634}}

Acknowledgements

We thank the following interns for their exceptional contributions to our work.

• Benjamin Sertolli: Major contributions to our DevKit during his master thesis
• Niels Maier: Measurement campaign for data collection and data preparation

The European large-scale project Hi-Drive (www.Hi-Drive.eu) supports the publication of 3DHD CityScenes and encourages the general publication of information and databases facilitating the development of automated driving technologies.

The Dataset

After downloading, the 3DHD_CityScenes folder provides five subdirectories, which are explained briefly in the following.

1. Dataset

This directory contains the training, validation, and test set definition (train.json, val.json, test.json) used in our publications. Respective files contain samples that define a geolocation and the orientation of the ego vehicle in global coordinates on the map.

During dataset generation (done by our DevKit), samples are used to take crops from the larger point cloud. Also, map elements in reach of a sample are collected. Both modalities can then be used, e.g., as input to a neural network such as our 3DHDNet.

To read any JSON-encoded data provided by 3DHD CityScenes in Python, you can use the following code snipped as an example.

import json

json_path = r"E:\3DHD_CityScenes\Dataset\train.json"
with open(json_path) as jf:
  data = json.load(jf)
print(data)

2. HD_Map

Map items are stored as lists of items in JSON format. In particular, we provide:

• traffic signs,
• traffic lights,
• pole-like objects,
• construction site locations,
• construction site obstacles (point-like such as cones, and line-like such as fences),
• line-shaped markings (solid, dashed, etc.),
• polygon-shaped markings (arrows, stop lines, symbols, etc.),
• lanes (ordinary and temporary),
• relations between elements (only for construction sites, e.g., sign to lane association).

3. HD_Map_MetaData

Our high-density point cloud used as basis for annotating the HD map is split in 648 tiles. This directory contains the geolocation for each tile as polygon on the map. You can view the respective tile definition using QGIS. Alternatively, we also provide respective polygons as lists of UTM coordinates in JSON.

Files with the ending .dbf, .prj, .qpj, .shp, and .shx belong to the tile definition as “shape file” (commonly used in geodesy) that can be viewed using QGIS. The JSON file contains the same information provided in a different format used in our Python API.

4. HD_PointCloud_Tiles

The high-density point cloud tiles are provided in global UTM32N coordinates and are encoded in a proprietary binary format. The first 4 bytes (integer) encode the number of points contained in that file. Subsequently, all point cloud values are provided as arrays. First all x-values, then all y-values, and so on. Specifically, the arrays are encoded as follows.

• x-coordinates: 4 byte integer
• y-coordinates: 4 byte integer
• z-coordinates: 4 byte integer
• intensity of reflected beams: 2 byte unsigned integer
• ground classification flag: 1 byte unsigned integer

After reading, respective values have to be unnormalized. As an example, you can use the following code snipped to read the point cloud data. For visualization, you can use the pptk package, for instance.

import numpy as np
import pptk

file_path = r"E:\3DHD_CityScenes\HD_PointCloud_Tiles\HH_001.bin"
pc_dict = {}
key_list = ['x', 'y', 'z', 'intensity', 'is_ground']
type_list = ['

Whole-genome sequencing is a powerful tool for analyzing genetic variation on a global scale. One particularly useful application is the identification of mutations obtained by classical phenotypic screens in model species. Sequence data from the mutant strain is aligned to the reference genome, and then variants are called to generate a list of candidate alleles. A number of software pipelines for mutation identification have been targeted to C. elegans, with particular emphasis on ease of use, incorporation of mapping strain data, subtraction of background variants, and similar criteria. Although success is predicated upon the sensitive and accurate detection of candidate alleles, relatively little effort has been invested in evaluating the underlying software components that are required for mutation identification. Therefore, we have benchmarked a number of commonly used tools for sequence alignment and variant calling, in all pair-wise combinations, against both simulated and actual datasets. We compared the accuracy of those pipelines for mutation identification in C. elegans, and found that the combination of BBMap for alignment plus FreeBayes for variant calling offers the most robust performance.

Snapshot img

Utility Locator Market Size 2024-2028

The utility locator market size is forecast to increase by USD 1.93 billion at a CAGR of 5.48% between 2023 and 2028.

The market is experiencing significant growth, driven by increasing safety and security concerns surrounding the protection of underground utilities. With the rise in gas pipeline laying projects, the demand for utility locators is on the rise. However, the market is not without challenges. The complexity and high costs associated with retrofitting existing infrastructure with utility locating technology pose significant obstacles. Despite these challenges, companies can capitalize on the market's growth potential by investing in innovative solutions that streamline the utility locating process and reduce costs. Additionally, partnerships and collaborations with pipeline operators and construction companies can provide opportunities for market expansion. Overall, the market presents a compelling investment opportunity for companies seeking to address growing safety concerns and capitalize on the increasing demand for utility locating technology.

What will be the Size of the Utility Locator Market during the forecast period?

Request Free SampleThe market in the United States is experiencing significant growth due to the increasing demand for safety and protection during excavation projects. This market encompasses technologies used for detecting and locating subsurface gas pipelines, electricity, oil and gas, and other underground utilities. Traditional digging practices have given way to technologically advanced tools such as Ground Penetrating Radar (GPR) and advanced utility locators that utilize electromagnetic fields. Stringent regulations mandate the use of utility locating services to prevent damage to subterranean facilities, ensuring food security and public safety. The aging infrastructure of utility systems also necessitates continuous inspection and maintenance, further fueling market growth. Additionally, the evolution of utility locating technologies has led to the emergence of referral services and specialized leak detection tools. The market's size is substantial, with continued expansion driven by the growing importance of efficient excavation practices and the need for reliable utility infrastructure in the face of water shortages and increasing energy demands.

How is this Utility Locator Industry segmented?

The utility locator industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeElectromagnetic fieldGPREnd-userOil and gasElectricityTransportationOthersGeographyNorth AmericaUSCanadaEuropeGermanyUKAPACJapanSouth AmericaMiddle East and Africa

By Type Insights

The electromagnetic field segment is estimated to witness significant growth during the forecast period.Utility locating technologies, driven by advanced electromagnetic field locators, have gained significant traction in the industry due to their high efficiency and cost-effectiveness compared to conventional methods. These solutions are primarily used for detecting, mapping, and surveying metallic utilities such as piped natural gas lines, water pipes, and telecommunications cables. The market's growth is further fueled by the increasing demand for technologically advanced products from key participants. For instance, 3M DigiFinder DF-1500, an electromagnetic locator, offers real-time detection and high accuracy, making it a preferred choice for excavation projects. Digital technologies, including GPS-enabled verifiers and geophysical technologies like ground-penetrating radar (GPR), are also gaining popularity in utility locating. GPR, in particular, is increasingly being used for subsurface site characterizations and leak detection in subterranean facilities, including gas lines and water pipes. Additionally, the adoption of 5G technology in utility locating is expected to revolutionize the industry by enabling faster and more precise locating. Safety and protection are paramount in utility infrastructure, and utility locating solutions play a crucial role in ensuring excavation safety. Stringent regulations mandate the use of comprehensive referral services and electromagnetic locators to prevent damage to underground utilities during digging practices. The market's growth is further driven by the increasing importance of preserving food security, transportation infrastructure, and water resources by preventing damage to subsurface utility infrastructure. Non-metallic utilities, such as high-speed rail projects and electricity lines, also require specialized utility locating solutions. Innovative solutions, such as those based on digital technologies, are increasingly being adopted to meet the unique challenges posed by these

This Application for an Environmental Assessment Certificate for the KSL Project has been prepared pursuant to Section 16(1) of the B.C. Environmental Assessment Act. The Application includes a description of the project, an outline of the Public and First Nations Consultation Program and an assessment of the potential environmental, social, economic, and land use effects that may result from the construction, operation and abandonment of the Project. In addition, plans for mitigation and monitoring are included that are designed to avoid or reduce the significance of the identified impacts. These resources provide information about the Pacific Trail Pipelines Report that are related to the Skeena watershed fish species. See link for other chapters and figures related to the report.