Satellite data provide high potential for estimating crop yield, which is crucial to understanding determinants of yield gaps and therefore improving food production, particularly in sub-Saharan Africa (SSA) regions. However, accurate assessment of crop yield and its spatial variation is challenging in SSA because of small field sizes, widespread intercropping practices, and inadequate field observations. This study aimed to firstly evaluate the potential of satellite data in estimating maize yield in intercropped smallholder fields and secondly assess how factors such as satellite data spatial and temporal resolution, within-field variability, field size, harvest index and intercropping practices affect model performance. Having collected in situ data (field size, yield, intercrops occurrence, harvest index, and leaf area index), statistical models were developed to predict yield from multisource satellite data (i.e., Sentinel-2 and PlanetScope). Model accuracy and residuals were assessed against the above factors. Among 150 investigated fields, our study found that nearly half were intercropped with legumes, with an average plot size of 0.17 ha. Despite mixed pixels resulting from intercrops, the model based on the Sentinel-2 red-edge vegetation index (VI) could estimate maize yield with moderate accuracy (R² = 0.51, nRMSE = 19.95%), while higher spatial resolution satellite data (e.g., PlanetScope 3 m) only showed a marginal improvement in performance (R² = 0.52, nRMSE = 19.95%). Seasonal peak VI values provided better accuracy than seasonal mean/median VI, suggesting peak VI values may capture the signal of the dominant upper maize foliage layer and may be less impacted by understory intercrop effects. Still, intercropping practice reduces model accuracy, as the model residuals are lower in fields with pure maize (1 t/ha) compared to intercropped fields (1.3 t/ha). This study provides a reference for operational maize yield estimation in intercropped smallholder fields, using free satellite data in Southern Malawi. It also highlights the difficulties of estimating yield in intercropped fields using satellite imagery, and stresses the importance of sufficient satellite observations for monitoring intercropping practices in SSA.

Climate change and variability are a threat to sustainable agricultural production in semi-arid areas of Malawi. Overdependence on subsistence rain-fed agriculture in these areas calls for the identification of sustainable adaptation strategies. A study was therefore conducted in Chikwawa, a semi-arid district in southern Malawi, to: (1) assess community’s perception of a changing climate against empirical evidence, (2) determine their local adaptive measures, (3) evaluate the potential of irrigated agriculture as an adaptive measure in household food security and (4) challenges over access to available water resources. The study employed focus group discussions and key informant interviews to assess people’s perceptions of climate change and variability and their desired interventions. To validate the people’s perceptions, rainfall and temperature data for the period 1960–2010 were analysed. A participatory complete randomised experimental design in both rain-fed and dry season–irrigated conditions was conducted to assess a maize cropping system that would improve adaptation. The study established persistent declining yields from rain-fed production in part because of perennial rainfall failure. In response, the community has shifted its focus to irrigation as an adaptation strategy, which has in turn triggered water conflicts in the community over the control of the resource. Water legislation however fails to adequately provide for rules governing sharing of water resources between various stakeholders. This article therefore recommends development of an appropriate institutional framework that forms a strong basis for equitable distribution of water for irrigation in areas most vulnerable to extreme climate events – including droughts and floods.Keywords: Food Security; Climate Change and Variability; Rainfall Variability; Irrigation; Water Resources; Governance Crisis