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.

Dry spells are one of the climate change hazards that continue to exert pressure on the agriculture sector, hence affecting food security. Understanding dry spell characteristics of an area helps in coming up with interventions and adaptive measures among other advantages. This study aimed at understanding characteristics of dry spells for Malawi by using climate hazards group infrared precipitation with stations precipitation data from 1981 to 2019. The study focused on the spatial distribution, maximum number of dry days, trend of maximum dry days and time of occurrence of dry spells. Data was analysed using Mann–Kendal trend analysis in R software. The results indicate a high number of occurrences of dry spells in the southern region than the other two regions of Malawi. In addition, the southern region experienced the highest maximum number of dry days. However, there is an upward trend for maximum days of dry spells in central region than all other regions. Local scale topographic influences on dry spell occurrence were also apparent. The study further established that the number of dry spell occurrence in the rainfall season starts to increase towards end of March. In this regard, although rainfall season in the study area is considered to be from November to April, the study recommends that growing season should be considered to be November to March so that crops are not affected by end of season dry spells which are common. Farmers should ensure that they plant crops that will mature with this growing period.

Climate change can enhance extreme weather conditions thereby significantly influencing change in precipitation patterns. This results in change to both rainfall intensity and distribution in many parts of the world. The increase in rainfall intensity triger hazards such as flooding and geohazards such as landslides. The impact and scale of flooding hazards are well evaluated and documented. However, geohazards from extreme weather events are not well documented in many developing countries making it difficult to quantify trends, frequency and spatial distribution. This knowledge gap is particularly evident in countries like Malawi, which have been significantly impacted by climate-related extremes, including cyclones. For instance, Tropical Cyclone Freddy which made a landfall in Southern Africa, induced above normal torrential rains in Malawi in March 2023. These rains triggered landslides, mudslides, debris flow and floods which affected 14 districts in the southern region of Malawi (GoM,2023).The size, magnitude and effect of flood hazard from the Tropical Cyclone Freddy was well studied. However, quantifying and mapping spatial patterns of geohazards was not well documented and less prioritized. In this study, we used sentinel 2 and rainfall data to a) characterise geohazard from extreme weather events, b) develope inventory for geohazards c) quantify the relationship between extreme weather events and occurrence of geohazard in southern parts of Malawi. Field survey was conducted for ground truthing in the landslide scarps in Blantyre, Thyolo and Zomba districts to improve accuracy of mapping and validating data from remote sensing analysis. Preliminery results on inventory indicate more than 10 landslides within the study area with Mulanje, Thyolo and Zomba registering highest number of landslides. These ranged in size from localized to more than 30m along the slope. On the time of occurrence, it was observed that most of the hazards occurred on different times even if they were exposed to same extreme weather, but all occured within a period of four days from onset of high intensity rains. This correlates to the period of high rainfall intensity in many areas. The characteristics of the material from the landslide scarps varied from loam clay, boulders to debri . However, most of the areas were charecterised with steep slopes of above 60o slope angle. Thus, other than extreme weather, landslides were highly influenced by the slope angle. Type of material on the slope had minor influence and this was in agreement with the results from regression analysis. These study results will act as guide to predict the occurrence of future geohazards and understand their patterns which is key in predicting future occurrences of the hazards. Keywords: Remote Sensing, climate change, Cyclone Freddy, geohazards, Malawi References Government of Malawi. 2023. Malawi 2023 Tropical Cyclone Freddy Post-Disaster Needs Assessment. Lilongwe: Government of Malawi.

Climate change can enhance extreme weather conditions thereby significantly influencing change in precipitation patterns. This results in change to both rainfall intensity and distribution in many parts of the world. The increase in rainfall intensity triger hazards such as flooding and geohazards such as landslides. The impact and scale of flooding hazards are well evaluated and documented. However, geohazards from extreme weather events are not well documented in many developing countries making it difficult to quantify trends, frequency and spatial distribution. This knowledge gap is particularly evident in countries like Malawi, which have been significantly impacted by climate-related extremes, including cyclones. For instance, Tropical Cyclone Freddy which made a landfall in Southern Africa, induced above normal torrential rains in Malawi in March 2023. These rains triggered landslides, mudslides, debris flow and floods which affected 14 districts in the southern region of Malawi (GoM,2023).The size, magnitude and effect of flood hazard from the Tropical Cyclone Freddy was well studied. However, quantifying and mapping spatial patterns of geohazards was not well documented and less prioritized.In this study, we used sentinel 2, rainfall and field data to a) characterise geohazard from extreme weather events, b) analyse extent of landslides c) develope inventory for geohazards d) quantify the relationship between extreme rainfall events and occurrence of geohazard in southern parts of Malawi. Field survey was conducted in the landslide scarps in Southern Malawi (Blantyre, Thyolo, Phalombe, Chiradzulu and Zomba districts) for ground truthing, mapping landslides, improving accuracy of mapping and validating data from remote sensing analysis. A total of 21 landslides were identified and mapped through field surveys. These ranged in size from localized to more than 50m along the slope. Through remote sensing analysis, it was observed that most of the hazards occurred on different times even if they were exposed to same extreme weather, but all occured within a window period of three days from onset of high intensity rains. This correlates to the peak rainfall intensity observed across many areas. The characteristics of the material from the landslide scarps varied from loam clay, boulders to debri. However, most of the areas were charecterised with steep slopes of above 60o slope angle. Additionally, in some areas geological influence of landlside occurrence was evident, this was inform of dolerite dyke intrustion and some faults. Thus, other than extreme rainfall occurence, landslides were highly influenced by the slope angle and geological factors. Type of material on the slope had minor influence and this was in agreement with the results from regression analysis. These study results will act as guide to predict the occurrence of future geohazards and understand their patterns which is key in predicting future occurrences of the hazards. Keywords: Remote Sensing, climate change, Cyclone Freddy, landslides, MalawiReferencesGovernment of Malawi. 2023. Malawi 2023 Tropical Cyclone Freddy Post-Disaster Needs Assessment. Lilongwe Malawi: Tropical Cyclone Freddy Department of Disaster Management Affairs (DoDMA) Situation Report No3 (2023)