Information and communication technologies (ICTs) are playing an increasing role in addressing the problems faced by agriculture. The challenges faced by agriculture from climate change alone are enormous and the need for farming communities to adapt and become resilient is key to feeding the world’s growing population. Agriculture in Pakistan is significantly affected by short-term climate variability and longer-term climate change. Pakistan is ranked among the top ten most climate vulnerable countries in the world in the Global Climate Risk Index. Climate change threats are exacerbated in the country due to the arid climate and reliance on water from the glacial melt in the north. Periods of severe droughts, followed by devastating floods are common in the country and have contributed to low crop yields, loss of livestock, damage to irrigation infrastructure and food shortages in recent years. 

In this context, the Ministry of Food Security and Research (MinFSR) expressed the need to improve their capacities related to geospatial applications in order to improve the quality of agricultural statistics with remote sensing technologies, within the broader scope of national yield forecasting and food security. FAO provides support to the Ministry of Food Security and Research in developing E-agriculture applications and knowledge products using innovative ICT Technologies under the project TCP/PAK/3704 “Development of E-agriculture applications and knowledge products using innovative ICT Technologies”. 

FAO NSL Geospatial Unit is providing technical support to the project, in particular, on the preparation of the land cover map of Punjab province, six years after the provincial land cover database of Punjab published in 2015. Punjab contributes for two-thirds of the total national agricultural output, leading in major commodities meant for food security in the country. This updated version will apply a methodology that combines multi-temporal optical and radar data, object-based segmentation, the ISO Land Cover Meta Language (LCML) as well as ground-truth data and machine learning algorithms to produce more reliable, timely and accurate crop maps for the province of Punjab. Consistent dataset about the agriculture types, locations and extensions, home-made features as well as natural resources such as water, forest and other natural vegetation types,  represent basic information that can support a variety of different applications as well as short and medium-term analysis.

In addition, the FAO NSL Geospatial Unit has been providing technical support across the whole implementation of the expected outputs by conducting training on all geospatial activities related to the project, with the overall goal to allow the country to leverage the existing technologies to tackle food sustainability and security.