Capacity building on Earth observation and GIT for in-season crop mapping, yield estimation, and damage assessment

Organisers: ICIMOD, MoALD

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About the training

The Geographic Information System (GIS) and Statistics Unit of the Ministry of Agriculture and Livestock Development (MoALD), Nepal, and ICIMOD’s SERVIR Hindu Kush Himalaya (SERVIR-HKH) Initiative are co-developing an operational service using remote sensing and machine learning for crop area and yield estimation. They are also working to establish information services to facilitate data and knowledge communication among the relevant departments and broader user community. This will help design and impart specialised training on agricultural planning, crop mapping, flood inundation assessment, and drought monitoring for field-level staff and central professionals.

The SERVIR-HKH Initiative, a joint initiative of ICIMOD, USAID, and NASA, is working on developing information services using Earth Observation (EO) and climate modelling technology. One of the key priority areas under this initiative is the capacity building of agriculture professionals to use new technologies to keep research aligned with recent technological advancements. EO technologies have tremendous potential to support the implementation of long-term and large-scale research and development programmes and resolve data and information gaps in the agriculture sector, which include status and changes in land use, agricultural production, and resilience for food security, among many other aspects.

As part of the capacity building work, we are organising a provincial training in collaboration with MoALD on the use of remote sensing data and geospatial information technology for crop monitoring as a first part of training in Bardibas and spatial crop modelling training for managing and monitoring agricultural systems as a second part of training in ICIMOD, Lalitpur.

Objectives

The training aims to provide agriculture professionals from MoALD with a better understanding of:

• Using Geo-information science and EO in crop monitoring and damage assessment
• An overview of SERVIR-HKH’s approach to the in-season crop mapping and related tools on field data collection and crop classification apps, including Geofairy and RiceMapEngine
• Soil & Water Assessment Tool modelling and its applications

Expected participants

• A total of 30 nominated officials from MoALD are expected to participate in the capacity-building training in Bardibas, Mahottari. Out of these participants, 21 are from the Bagmati, Madhesh and Koshi provinces, while 9 participants are from central ministry (MoALD) officials
• A total of 10 participants will take part in the second part of the training at ICIMOD, with 4 from MoALD and the others from ICIMOD

Resource persons

MoALD

• Chet Bahadur Roka, Senior Statistics Officer, Chief of Agriculture GIS Section
• Richa Shah, Agri-Economist
• Sabita Dhakal, Computer Engineer

ICIMOD

• Rajesh Bahadur Thapa, Senior Remote Sensing and Geo-information Specialist
• Poonam Tripathi, Geospatial Training Analyst
• Sravan Shrestha, Remote Sensing and Geo-information Associate
• Rajesh Shrestha, Programme Associate

U.S. Department of Agriculture

• Varaprasad Bandaru, Research Scientist
• Arun Bawa, Assistant Professor
• Raghavan Srinivasan, Director of the Spatial Sciences Laboratory

Background

The UN Sustainable Development Goal (SDG) 2 (“Zero hunger”) aims to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture. The Government of Nepal (GoN) recognises the prevailing situation of food insecurity across the country and attaches high importance to ensuring food security for all. However, there is a need to build upon significant capacity in food security planning, monitoring, and evaluation within the GoN to enable it to provide reliable and timely information to support planning and policy decision-making processes.

Monitoring and estimating crop acreage at a national scale is required to determine the national or sub-national food demand and supply balance and to gauge food security. Whether during world food shortages or during periods of surplus, monitoring and estimating crop acreage requires long-term efforts. The SDGs also include an upswing in the productivity and incomes of smallholders as key targets. Policymakers rely heavily on forecasts of crop area and yield estimates to plan agricultural production and food supply monitoring. The operational use of open-source satellite-based and model information to monitor climate and crops at daily and seasonal levels for integrated analysis of crop performance provides a cost-effective means to support decision-making processes.