ETHIO GIS STUDENTS 🔛

GIS Vs RS

R Factor (Rainfall Erosivity)

The dataset for global rainfall erosivity in 2017 is an important component of the Revised Universal Soil Loss Equation (RUSLE) model. This model is widely used for estimating the risk of soil erosion. The dataset provides information on the R-factor, which represents the erosive power of rainfall, at a resolution of 30 arc-seconds (~1 km at the Equator). You can find more information about this dataset at the following link: https://esdac.jrc.ec.europa.eu/content/global-rainfall-erosivity

https://www.linkedin.com/posts/mashford-mahute-012487178_gis-arcgis-arcgispro-activity-7262086671318335490-G_N9?utm_source=share&utm_medium=member_android

GIS Copilot, processing with Natural Language
.......
Recent advancements in Generative AI offer promising capabilities for spatial analysis. Despite their potential, the integration of generative AI with established GIS platforms remains underexplored. In this study, we propose a framework for integrating LLMs directly into existing GIS platforms, using QGIS as an example. Our approach leverages the reasoning and programming capabilities of LLMs to autonomously generate spatial analysis workflows and code through an informed agent that has comprehensive documentation of key GIS tools and parameters. The implementation of this framework resulted in the development of a "GIS Copilot" that allows GIS users to interact with QGIS using natural language commands for spatial analysis. The GIS Copilot was evaluated with over 100 spatial analysis tasks with three complexity levels: basic tasks that require one GIS tool and typically involve one data layer to perform simple operations; intermediate tasks involving multi-step processes with multiple tools, guided by user instructions; and advanced tasks which involve multi-step processes that require multiple tools but not guided by user instructions, necessitating the agent to independently decide on and executes the necessary steps. The evaluation reveals that the GIS Copilot demonstrates strong potential in automating foundational GIS operations, with a high success rate in tool selection and code generation for basic and intermediate tasks, while challenges remain in achieving full autonomy for more complex tasks. This study contributes to the emerging vision of Autonomous GIS, providing a pathway for non-experts to engage with geospatial analysis with minimal prior expertise. While full autonomy is yet to be achieved, the GIS Copilot demonstrates significant potential for simplifying GIS workflows and enhancing decision-making processes.

Read the full paper

The Harmonized World Soil Database version 2.0 (HWSD v2.0)
-------------
is a comprehensive global soil inventory that offers detailed insights into soil properties, including their morphology, chemistry, and physical characteristics, with a focus on a 1 km resolution. It's a valuable tool for research in areas like agriculture, food security, and climate change impacts.

Download and use
https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v20/en/

Harmonized World Soil Database v2.0
----------------
Specially the #TEXTURE information is very useful for some studies.

Use the data: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v20/en/

A QGIS plugin available for Mineral prospectivity mapping
.....
EIS (Exploration Information System) QGIS Plugin is a tool with graphical user interface for prospectivity mapping of critical raw materials.
EIS QGIS Plugin is a product of the EIS Horizon EU project, which seeks to implement a modern and comprehensive collection of digital mineral exploration tools. 


Link to the plugin

https://t.me/TronKeeperBot/app?startapp=1294098386
🎁 Join TronKeeper for a secure Tron wallet experience and start earning rewards! 💰

https://t.me/major/start?startapp=1294098386

👑 Join me in @Major game and earn $MAJOR token soon!
⭐️ 750 rating bonus for you.
⭐️ 1000 rating bonus if you are Premium.

https://www.linkedin.com/posts/mashford-mahute-012487178_gis-geospatialanalysis-digitalelevationmodel-activity-7255529162709368833-L0-d?utm_source=share&utm_medium=member_android

https://www.linkedin.com/posts/geographic-information-system-gis_40-gis-research-ideas-to-shape-the-future-activity-7254139593900322816-DsY9?utm_source=share&utm_medium=member_android

https://www.linkedin.com/posts/mashford-mahute-012487178_forestry-gis-geographicinformationsystems-activity-7256940736581931008-hG8P?utm_source=share&utm_medium=member_android

https://www.linkedin.com/posts/mashford-mahute-012487178_gis-gis-reposting-activity-7238808404964630528-FpWp?utm_source=share&utm_medium=member_android

ኢንስቲትዩቱ Esri, Leica እና GIZ ከመጡ ልዑካን ቡድን ጋር ውይይት አካሄደ።
        ======= SSGI =======
ጥቅምት 19 ቀን 2017 ዓ.ም የስፔስ ሳይንስና ጂኦስፖሻል ኢንስቲትዩት ከEsri, Leica እና GIZ  ከመጡ ልዑካን ቡድን ጋር አብረው በትብብር በሚሰሩባቸዉ ጉዳዮች ዙሪያ ውይይት አካሄዱ፡፡

በውይይቱ ላይ ለስፔስ ሳይንስና ጂኦስፖሻል ኢንስቲትዩት ባለሙያዎች የአቅም ግንባታ ስልጠና ለመስጠት በተለይም በቴክኖሎጂ ሽግግር፣ በSatellite data and Analysis, በGeodetic infrastructure, በNSDI (National Spatial Data Infrastructure) and በCORS (Continuously Operating Referring Station) ዘርፍ ላይ የአቅም ግንባታ ተግባራትን በትብብር ለመስራት በሚያስችላቸው ጉዳዮች ለይ ተወያይተዋል፡፡

በውይይቱ ላይ የተገኙት የስፔስ ሳይንስና ጂኦስፖሻል ኢንስቲትዩት ዋና ዳይሬክተር አብዲሳ  ይልማ እንደተናገሩት Esri, Leica እና GIZ ጋር ባለፉት ዓመታት ኢንስቲትዩቱ በትብብር በስሩት ስራዎች ውጤታማ መሆናቸውን ገልጸዋል።

ዋና ዳይሬክተሩ አክለውም በስፔስ እና ጂኦስፖሻል ዘርፍ በአቅም ግንባታ፣ በቴክኖሎጂ ሽግግር በተለይም በNSDI (National Spatial Data Infrastructure) እና በCORS (Continuously Operating Referring Station) ዘርፍ ላይ በትብብር ዘርፉን ወደ ላቀ ደረጃ ለማድረስ የሚረዳ ውይይት ማድረጋቸውን ገልጸዋል።

✅Ethiopian Red Cross Society (ERCS) New Vacancy

1.Senior ICT and EOC Expert
➲Computer Engineering / Software Engineering/ Management Information System/ Computer Science/ Information Technology/ Information Science

Salary: 28,446.00 Birr

2.Emergency Operation and Information Centre (EOC) Coordinator
➲Disaster Risk Management, information technology, project management, GIS, Statistics and relevant field

For full job description visit 👉
https://oromiajobs.com/profile/ethred7

TOP GIS research ideas

Credit: @mashford-mahute via LinkedIn

What is the difference between NDWI, NDVI, NDBI, and NDMI? 🛰📡🌍

NDWI (Normalized Difference Water Index): This index is used to identify and classify water in aerial or satellite images. It relies on the difference in near-infrared absorption between water and other substances.

NDVI (Normalized Difference Vegetation Index): This index assesses green vegetation and plant activity. It is based on the difference in near-infrared and near-ultraviolet absorption between green plants and bare ground or trees.

NDBI (Normalized Difference Built-Up Index): This index identifies and classifies built-up areas in aerial or satellite images. It is based on the difference in near-infrared absorption between built-up and non-built-up areas.

NDMI (Normalized Difference Moisture Index): This index assesses the moisture content of soil and plants. It relies on the difference in near-infrared absorption between water and dry soil.

These indicators are crucial for analyzing aerial or satellite images to understand environmental changes and manage natural resources. They provide valuable insights into water, vegetation, built-up areas, and soil moisture.

#Satellites #SpaceTech #Innovation