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
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.
4. 丱丶, 丱丐乘
USA
U.A.E
MONGOLIA
Taiwan
PRC
South Korea
Philippines
Czech
Finland
India
Australia
Vietnam
Turkey Japan
Azerbaijan
Netherlands
Fiji
Hungary
Belgium
Brazil
Thailand
Morocco
Austria/Italy
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2022 仂仆 勳
19
January
19
February
16
March
15
April
11
May
October
16
November
14
December
亠仂-于弍亳仆舒
Geo-webinar
亠仂-亠仄亳仆舒
Geo-workshop
亠仂-仍亞舒仆
Geo-forum
亠仂-仍亰舒仍
Geo-meeting
/GeoBEER/
亠仂-仍亰舒仍
Geo-meeting
/GeoBEER/
亠仂-仍亰舒仍
Geo-meeting
GISday
Asian Conference
on Remote
Sensing 2022