Climate change is amplifying the risk of extreme weather disasters by increasing the destructive power of storms and floods. At the same time, rising seas, shifting rainfall patterns, drought and other slow-onset changes are eroding people’s land, natural resources and security, and magnifying existing vulnerabilities.

In this paper, we present an optimized Machine Learning (ML) algorithm for predicting land suitability for crop (sorghum) production, given soil properties information. We set-up experiments using Parallel Random Forest (PRF), Linear Regression (LR), Linear Discriminant Analysis (LDA), KNN, Gaussian Naïve Bayesian (GNB) and Support Vector Machine (SVM). Experiments were evaluated using 10 cross fold validation. We observed that, parallel random forest had a better accuracy of 0.96 and time of execution of 1.7 sec. Agriculture is the main stream of food security.

This gender-sensitive toolkit enables civil society organisations, women and communities, as well as other actors to assess each country’s current legal framework and tenure governance arrangements in line with the provisions of the VGGTS and the AU F&G.

Better soil health can increase agricultural productivity. Restoration activities can build on-farm resilience and contribute to climate change adaptation and mitigation.

Land and soil health surveys can improve crop modeling predictions under various climate scenarios and guide more targeted interventions.

Currently, most assessments of land and soil health do not consider the social, ecological, and biophysical constraints, or acknowledge the variations in the landscape.

This report is a product of a partnership between Terra Firma and the International Institute for Environment and Development (IIED), contributing to a study of changing land access in sub-Saharan Africa supported by the International Fund for Agricultural Development (IFAD).

Dietary guidelines urge Brazilians to increase their consumption of raw vegetables. Yet key issues must be tackled by the government and civil society, not only to foster consumers’ appetite for healthier food, but more importantly to diminish the gaps between local demand and production, determined by food and land accessibility. We examine whether vegetable production in Brazil meets the demand to provide Brazilians the daily amount of fresh food recommended by the World Health Organization (WHO).

With challenges from global climate change, it is imperative to enhance food production using climate-smart technologies and maximize farm efficiency. Fifty-six households in Rudhiapada and Badamahulidiha, Odisha, India were selected to evaluate farmers’ efficiency using conservation agriculture (CA) cropping system practices. Data envelopment analysis (DEA) and regression analysis were used to estimate farmer efficiency and the determinants of yield.

Ce document décrit le Sénégal sur le plan de l'Agriculture Intelligente face au Climat (AIC). Le concept d’agriculture intelligente face au climat (AIC) traduit l’ambition d’assurer une meilleure intégration du développement de l’agriculture et de la réactivité face au climat. Il vise à assurer la sécurité alimentaire et atteindre les objectifs de développement plus larges dans un contexte