Soil mapping using machine learning in Lao PDRThe GIS unit of the Department of Agricultural Land Management (DALaM) of the Ministry of Agriculture and Forest of Lao PDR is develop a new national level soil map. Working through the project “Strengthening Agro-climatic Monitoring and Information Systems (SAMIS) to improve adaptation to climate change and food security in Lao PDR” funded by GEF and implemented by FAO, the activity is inserted in a broader exercise focusing on developing a national level decision making schemes for long term land planning.The soil map based on the World Soil Classification Systems is ongoing. The samples were finalized in the provinces of Phongsaly, Bokeo, Luangnamtha, Xayabouly, Oudomxay, Luangprabang, Houaphanh, Champasack, Salavan, Xekong, and Attapue.All soil profiles records name of the profile, soil depth, date, land use type, complete soil description, GPS coordinates, photos of the soil profiles, and description of the land use situation. The laboratory analysis is ongoing. So far, half of the soil samples were analyzed and the map will be ready the end of 2019.

The leaflet present the activities of the third component of the project “Strengthening Agro-climatic Monitoring and Information Systems (SAMIS) to improve adaptation to climate change and food security in Lao PDR”. The component, implemented in strict collaboration with the Ministry of Natural Resources and Environment (MONRE); Ministry of Agriculture and Forestry (MAF); and CAWA project, is titled “Knowledge management, dissemination of information, lessons learned for local application, planning and evaluation”. This leaflet explain how the FAO GEF project will communicate information generated from Components 1 and 2 to the different stakeholders at national, provincial, and local levels. This provides knowledge management and dissemination of information and lessons learned for planning, monitoring and evaluation. At local level, the weather, climate, land resources, and climate-change impact information will be disseminated to farmer groups through established farmer field schools (FFS)

Cropland cover mapping using machine learning in Lao PDRThe GIS unit of the Department of Agricultural Land Management (DALaM) of the Ministry of Agriculture and Forest of Lao PDR is develop a new national level cropland cover map. Working through the project “Strengthening Agro-climatic Monitoring and Information Systems (SAMIS) to improve adaptation to climate change and food security in Lao PDR” funded by GEF and implemented by FAO, the activity is inserted in a broader exercise focusing on developing a national level decision making schemes for long term land planning.Filtered composition and mosaicking is run using the SEPAL, a cloud computing-based platform for autonomous land monitoring using remotely-sensed data. It allows users to access powerful cloud-computing resources to query, access and process satellite data quickly and efficiently for creating advanced analyses. The cropland cover map is developed using the ESA Sentinel 2A sensor and classified using the Land Cover Classification System (LCCS), the ISO standard (ISO 19144-1) classification system developed by FAO and UNEP.

This Monitoring and Evaluation (M&E) Plan is prepared for the project “Strengthening Agro-climatic Monitoring and Information Systems (SAMIS) to improve adaptation to climate change and food security in Lao PDR”. The project is funded by the Global Environmental Facility (GEF) under its Least Developed Country Fund (LDCF). The M&E Plan covers monitoring of project performance and evaluation of project impacts. Monitoring is used for performance evaluation through assessing success of the project in achieving its time bound targets and objectives whereas the project impacts evaluation is done through the data generated from project studies and analysis as well as baseline survey, midterm survey and end of the project evaluation. Both project performance and impact evaluation will contribute to improve decision making and management, for keeping the project on track towards achieving the outcomes and objectives and by integrating lessons learnt into planning.