Map.Minu.mn IntroGeoMedeelelThis document discusses the MINU Map system, a web GIS and geo data processing platform for Mongolia. It provides an overview of popular world maps and their limitations for Mongolia. MINU Map aims to address these limitations by providing Mongolian content and frequent data updates. Key features of MINU Map discussed include search functionality, routing, traffic info, 360 degree views of Ulaanbaatar, and an open platform for integration. The document also covers MINU Map's architecture, data collection processes, assigning of virtual addresses, and data correction and monitoring procedures.
Map.Minu.mn IntroGeoMedeelelThis document discusses the MINU Map system, a web GIS and geo data processing platform for Mongolia. It provides an overview of popular world maps and their limitations for Mongolia. MINU Map aims to address these limitations by providing Mongolian content and frequent data updates. Key features of MINU Map discussed include search functionality, routing, traffic info, 360 degree views of Ulaanbaatar, and an open platform for integration. The document also covers MINU Map's architecture, data collection processes, assigning of virtual addresses, and data correction and monitoring procedures.
2b intro num-cube_sat_v3GeoMedeelelThe document outlines the BIRDS (Joint Global Multi-Nation Birds) project, which aims to build and launch a constellation of 1U CubeSats from five countries including Mongolia and Japan. The project will provide hands-on engineering experience for students and help non-space faring countries enter the space field. It details the satellite design, integration and testing process, ground station setup, operations plan and timeline, with a total cost of around $100,000 USD per satellite.
Wcs buuveibaatarGeoMedeelelThis document discusses using geographic information systems (GIS) and remote sensing to study and conserve two endangered ungulate species in Mongolia, the Asiatic wild ass or khulan and the goitered gazelle. GPS collars were used to track the movements of 20 khulans and 10 gazelles, finding that they range widely, including important habitat areas outside of protected areas. Ground surveys estimated populations of around 36,000 khulans and 28,000 gazelles in Southern Gobi. Spatial modeling identified surface water and human disturbance as most influencing species distributions, with around 25% of suitable habitat for each located within protected areas. GIS and remote sensing were useful conservation planning tools.
Amgaa 201703150GeoMedeelelThis document analyzes dust weather categorization in Mongolia using satellite data from 2000-2013. Ground-based meteorological data from 113 stations is compared to satellite-retrieved aerosol optical depth to categorize dust haze, blowing dust, and dust storms. Dust phenomenon types are categorized based on the correlation between aerosol optical depth and horizontal visibility. The study finds a good exponential relationship between aerosol optical depth and visibility in April, allowing dust weather to be categorized from satellite data with spatial frequencies consistent with ground reports.
Presentation the impact of forest fire on forest cover types 03-march2017GeoMedeelelThis study analyzed the impact of forest fires on forest cover types in Eruu county, Mongolia between 2000 and 2011 using Landsat imagery. The forest was classified into seven types including cedar, pine, larch, birch, birch-pine mixed, birch-larch mixed and cedar-larch mixed. Overall accuracy of the forest maps was 86.33% in 2000 and 93.75% in 2011. Large fires between 2007-2009 impacted over 25,000 hectares, changing forests to burnt areas and over 52,000 hectares to grasslands. Major changes included reductions in cedar-larch mixed and increases in burnt areas.
Presentation 20220316 nandiaGeoMedeelelThis 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
Drone 20201216GeoMedeelelThe 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.
Intro mga 15dec2021 (1)GeoMedeelelThe 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.
Chcnav moblie mapping solution2GeoMedeelelThe 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.
Intro mga 18may2021GeoMedeelelMongolia 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.
Intro mga 14apr2021GeoMedeelelMongolia 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 GeoMedeelelThis 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 v1.0GeoMedeelelThis 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.