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

[230+ Pages Report] The global Geospatial Imagery Analytics market size is expected to grow from USD 61.5 billion to USD 126.01 billion by 2028, at a CAGR of 12.70% from 2022-2028

Levee stations, usually in feet but in some cases miles, snapped to 2017 Delta levee centerlines (derived from the 2017 Delta LiDAR). Base source for station locations are surveyed field markers on the levees or distance-derived CAD files, in either case as supplied by local maintaining agency's engineers. DWR collected station location data and snapped the stations into the levee centerline file from 2012. After updated levee centerlines were created, the existing points were snapped to the new lines. So there is some small difference between the supplied station locations, previous station locations and these station locations. In some cases, multiple series of stations exist for a district, generally associated with distinct waterways. Also, district levees may be demarked in feet or in miles. The label fields are simply cartographic support, the label data are identical in all cases, but are provided to support fast labeling at more infrequent intervals as needed. Stationing is not as simple as it may seem. In some cases, multiple sets of stationing exist for a district's levees (see Sherman Island for example). What this dataset intends to represent is the current stationing used by District engineers for that District on levee maintenance and improvement projects. As changes are made to the stationing, and the new stationing data become available to the Levee Program, they will be added to this database. Some islands also have separate groups of stations for various parts of the district. This version is current as of 03/24/2020. Source of the original levee stationing is DWR Delta Levees Program, compiled from data provided by internal files, from CSU Chico State, MBK Engineers, KSN Engineers, Siegfried Engineers, Malani & Associates, Green Mountain Engineers, and DCC Engineers. Processing work done by CA DWR, Division of Engineering, Geodetic Branch, Geospatial Data Support Section, specifically by Arina Ushakova (Research Data Analyst I), and initial QC by Joel Dudas (Senior Engineer, Water Resources).

In the Delta Anatomy Mapping Project, all levee anatomies were delineated using slope grids built from available LIDAR data points. LIDAR data points were converted to digital elevation models and subsequently into slope grids. Thresholds were identified that capture the levee crown, levee landside, levee waterside, ramps and toe ditches. Visual interpretations of slope thresholds were used in conjunction with heads-up digitizing to maintain smooth boundaries at a scale of 1:550. The delineation thresholds were derived from a combination of mapping scale, slope grid resolution and slope thresholds used for each anatomy classification. All anatomy has gone through internal quality control processes to ensure a minimum accuracy of +/- 3 feet. Once the levee anatomy was created and accepted, the Esri geoprocessing tool "Polygon to Centerline" was used to create a levee crown centerline. From there, the centerlines were merged by LMA, with a single line for each LMA. After the centerlines were accepted and any errors fixed, the centerlines were split by reach and attribute fields (such as project or non-project). This data depicts the levee anatomy at the time of the LiDAR survey (2017) and are only accurate for that time. Users should be aware that temporal changes may have occurred since this data set was created and some parts of this data may no longer represent actual surface conditions. This data is an update to the previous Atlas dataset with Delta Levee Centerlines, derived from the 2007 Delta LiDAR. Processing and digitizing work done by CA DWR, Division of Engineering, Geodetic Branch, Geospatial Data Support Section, specifically by Arina Ushakova (Research Data Analyst I), and initial QC by Joel Dudas (Senior Engineer, Water Resources).

[230+ Seiten Bericht] Der globale Markt für Geospatial Imagery Analytics wird voraussichtlich von 61.5 Milliarden USD auf 126.01 Milliarden USD bis 2028 wachsen, bei einer CAGR von 12.70 % von 2022-2028