WebGIS is a technology that allows spatial information to be presented in a user friendly format on the internet, allowing for data creation, editing, analysis, and querying. It also enables dissemination of data over the internet for a wider audience and includes capabilities like spatial analysis, 3D data viewing, and interactivity.
WebGIS is a technology that allows spatial information to be presented in a user friendly format on the internet, allowing for data creation, editing, analysis, and querying. It also enables dissemination of data over the internet for a wider audience and includes capabilities like spatial analysis, 3D data viewing, and interactivity.
This document provides an overview of research conducted on lake sediment classification and description in Mongolia. It discusses:
1) How lake sediments can provide geological and biological information about past climate and environmental changes.
2) The history of lake sediment research in Mongolia from the 1950s to present day.
3) Common types of sediments found in Mongolian lakes, including clay mud, silt mud, diatom mud, and carbonate mud.
4) Methods used in sediment research, such as sediment drilling, classification, and carbon-14 dating.
5) Examples of sediment research conducted on specific Mongolian lakes.
WebGIS is a technology that allows spatial information to be presented in a user friendly format on the internet, allowing for data creation, editing, analysis, and querying. It is more than just static maps and can disseminate data widely over the internet while also allowing for interactivity, spatial analysis, and visualization of 3D data. Popular platforms include Google Earth, Google Maps, Bing Maps, and OpenStreetMap.
The Securing Our Future water quality monitoring database program began in 2006 and is funded by the Dutch government for 3 years. It supports monitoring of chemical, hydrological, and aquatic insect parameters as well as habitat conditions at 163 sites on 129 streams in Mongolia between 2007-2009. Fieldwork was carried out during summer months to assess water quality in rivers in the Arctic Ocean, Central Asian Internal, and Pacific Ocean basins. Program contacts provided for additional information.
This document outlines a study to estimate above-ground biomass and carbon stock in boreal forests in Mongolia using satellite data and machine learning. Boreal forests cover about 9.2% of Mongolia but have been declining in recent decades. The study aims to develop a suitable machine learning model to map forest biomass and carbon stock. Random forest was the best performing model with an R2 of 0.24 and RMSE of 33 Mg/ha. Important input features included shortwave infrared band 1, green leaf index, and radar polarization data. The predicted forest biomass ranged from 32.5-122.5 Mg/ha and carbon stock ranged from 16.5-62.5 Mg C/ha. Some reference
The document outlines a study that uses multispectral drones and ground sampling to collect vegetation data from pasture sites over three sampling periods in June, July, and August. Various vegetation indices will be calculated from the drone and ground spectrometer data to analyze changes in biomass, chlorophyll content, and other vegetation metrics over time. A total of 285 sample points will be collected and various biophysical parameters will be measured at each point to analyze temporal changes in pasture sites.
The Mongolian Geospatial Association has a board that executes the CEO and Secretary. It has 9 technical commissions and 3 member communities. The association has regular, student, institutional, honorary, and advisory members. It partners internationally and participates in activities in countries like the US, UAE, Taiwan, South Korea, and others. In 2021, the association held webinars, talks, workshops and participated in a United Nations workshop on GNSS applications. It celebrates GIS day and holds monthly geo-meetings and quarterly geo-forums.
The document provides an overview of CHCNAV's AlphaUni 300/900/1300 mobile mapping solutions. It describes the key features and performance specifications of the AlphaUni series, including its universal lidar platform design, accuracy levels, data storage capabilities, and compatibility with various installation methods for airborne, vehicle, boat, and backpack use cases. The document also introduces CHC's new BB4 UAV platform as a high-payload professional solution for airborne lidar applications.
Mongolia has been involved in space technology since 1965 under the INTERCOSMOS program. The first satellite data receiving station and weather satellite ground station were established in 1970. In 1981, J. Gurragchaa became the first Mongolian cosmonaut. In 2017, Mazaalai, Mongolia's first satellite, was launched into space.
The Space Technology Association of Mongolia is the main organization related to space technology. It has a board, CEO, secretary and various technical commissions. Members include students, regular members, institutions and honorary members. The association partners with space organizations in countries around the world and participates in international conferences and workshops on space technology.
Mongolia began developing space technology in 1965 under the INTERCOSMOS program. Some key early developments included establishing the first satellite data receiving station in 1970 and a meteorological satellite data station. The first Mongolian cosmonaut launched in 1981. More recently, Mongolia launched its first satellite, Mazaalai, in 2017.
The Association of Mongolian Geodesy and Cartography brings together members involved in fields like photogrammetry, GIS, and surveying. It has over 1500 members across categories like students, institutions, and honorary members. The Association partners with space technology organizations internationally and runs various events and programs.
Demonstration of super map ai gis technology GeoMedeelel
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This document demonstrates SuperMap's AI GIS technology. It discusses geospatial deep learning and the AI GIS workflow, including data acquisition and preparation, model building and management, and model application. It provides examples of using deep learning models for tasks like object detection, segmentation, and classification of imagery. The workflow and tools for training models with SuperMap software and deploying trained models as web services are also described. A case study on building extraction is presented to illustrate the full AI GIS process.
Supermap gis 10i(2020) ai gis technology v1.0GeoMedeelel
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This document provides information about SuperMap Software Co., Ltd. It includes:
1. Background information on SuperMap such as its founding date and headquarters location.
2. Market share data showing SuperMap has the largest share of the GIS software market in China.
3. An overview of SuperMap's products and technologies including distributed GIS, cross-platform GIS, 3D GIS, big data GIS, and AI GIS.
Mongolia began developing space technology in 1965 under the INTERCOSMOS program. Some key developments include establishing the first satellite data receiving station in 1970, launching Mongolia's first cosmonaut in 1981, and launching the country's first satellite Mazaalai in 2017.
The Association of Mongolian Geodesy and Cartography brings together organizations involved in space technology. It has over 1500 members across different categories and works with international partners on projects related to remote sensing, GIS, and satellite data applications. The Association organizes various workshops and forums to advance space-related research and education.