International Conference on

Remote Sensing & GIS Integration in Veterinary, Agricultural & Health Sciences (RGVAHS-2022)

 Date: 23 & 24 February, 2022 (Hybrid Mode)

Organized by: Faculty of Veterinary and Animal Sciences

Venue: MNS-University of Agriculture, Multan

                Faculty of Veterinary and Animal Sciences, MNS University of Agriculture, Multan, Pakistan is organizing an International Conference (Hybrid mode) on “Remote Sensing & GIS Integration in Veterinary, Agricultural & Health Sciences (RGVAHS-2022)”  on 23 & 24 February 2022 in collaboration with Eberswalde University for Sustainable Development/ TRANSECT, Germany.

Over the past four decades, remote sensing has been continuously providing spatially and temporally consistent observation data with GIS visualization, applied for monitoring of vegetation status, agriculture, biological, health, and veterinary research. Remote sensing has also allowed us to extrapolate from what we know about a few smaller locations to a much larger region. Remote sensing provides various ways of modeling for nature-life interaction system that has been used to answer questions as to how this changing environment has impacted our health, animal health and agriculture production. The changing environment, in return, is having significant consequences on human society, agricultural production systems, and veterinary production including rising temperatures and sea levels, and increased frequency in natural disasters and human disease. Remote sensing and GIS hold promise by quantifying spatial and temporal variability of the crop status, guiding management and breeding decisions. In animal production, remote sensing also gained popularity due to its capability of telling both physical and chemical features of land cover. Incorporating longitudinal series of remotely sensed data into models is playing an important role in parameterizing the Spatio-temporal process of disease transmission in crops, animals, and humans.

Considering the impact and application of remote sensing in health, agriculture, and veterinary sciences, we invite you to submit your recent research on remote sensing integration studies. It is requested to participate/ submit abstract, till 10 February 2022, aligning the following thematic areas but not limited to:

  • Identification of crop types and monitoring of vegetation status
  • Remote sensing technologies and GIS methodologies of grazing lands, and livestock
  • Remote sensing with the integration of GIS for biodiversity, ecosystem, ecology, and climate change
  • Disease (human, agriculture, veterinary) modeling incorporating remotely sensed data with GIS visualization and information on disease forecasting and prediction
  • Impact of climate change on infectious and non-infectious diseases
  • Impact of climate change on agriculture, animal, poultry, and wildlife production
  • Remote monitoring along with GIS of animal population, behavior, management, nutrition, and grazing land management 
  • Remote monitoring of soil and water characteristics as relevant for agricultural and livestock production 
  • Advanced algorithms and techniques of remote sensing and GIS to solve agricultural problems, animal and human health issues
  • Physical, biological, chemical, and geological oceanography studies using remote sensing data and GIS methodology

 

Registration fee:
Online Mode: 500 PKR

Physical Mode: 1000 PKR
Accommodation & meal for physical attendee outside from city: 2000/night PKR (In addition to registration fee)

Bank: HBL
Account title: MNSUA, Multan
Account Number: 09917900854803

 Abstract submission and Registration:

https://docs.google.com/forms/d/e/1FAIpQLSeRtBXQF69FkIqMGXAv9nlNxsaXvRbDue_nmrvvr0CG16_i_g/viewform?vc=0&c=0&w=1&flr=0  

Note: International presenter/ participant may directly send abstract to email: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Contact us:

Prof. Dr. Muhammad Asif Raza (+923335552614)

Prof. Dr. Junaid Ali Khan (+923313544476)

Dr. Aziz Ul-Rahman (+923346988287)

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.