# Fine-Scale (10 m) Dynamics of Smallholder Farming through COVID-19 in Eastern Thailand
## 5 Conclusions  
While numerous studies have explored the immediate ramifications of the COVID-19 pandemic on agricultural systems, only a limited number have delved into the enduring effects of this global health crisis. This study assessed the spatiotemporal patterns of change in tropical crop cultivation in Eastern Thailand across periods preceding, during, and subsequent to the pandemic. Additionally, we sought to evaluate the role of COVID-19 in driving such changes. Given the traditional cultivation of a diverse array of tropical crops on small-holder farmlands in Thailand, we examined the effectiveness of a high-resolution (10 m) Sentinel-2 dense image time series. These data, incorporated into harmonic regression and random forest methodologies, were employed for mapping various crops, including durian, rice, rubber, eucalyptus, oil palm, pineapple, sugarcane, cassava, mangosteen, coconut, and others. Our approach demonstrated efficacy in mapping the majority of the studied crop types, particularly in situations involving intercropping--an established practice of cultivating multiple plant species simultaneously in the same patch of land. However, when attempting to map multiple crop types within a single framework, notable variations in accuracy were observed. Overestimation occurred, notably in young plantations characterized by open tree canopies and grass-covered ground surfaces. Furthermore, we identified the short-term impact of the pandemic on labor-intensive crops, such as rubber and durian. Nevertheless, no discernible impact was observed throughout the entire study period. In contrast, farmers' decisions regarding crop cultivation appeared more influenced by factors such as financial gain and climate change. There was a significant increase in durian cultivation even during the pandemic, which ironically prompted Thai farmers to adopt e-commerce to meet the escalating international demand, particularly from China.  
Conceptualization, G.C., C.H., S.A. and N.T.; methodology, G.C., A.R.T., W.W.H., H.M.R., M.G.C., G.M.B. and J.E.K.III; validation, A.R.T., W.W.H., H.M.R., M.G.C., G.M.B. and J.E.K.III; formal analysis, A.R.T., W.W.H., H.M.R., M.G.C., G.M.B. and J.E.K.III; resources, G.C., S.A., N.T.; data curation, G.C.; writing--original draft preparation, G.C., A.R.T., W.W.H., H.M.R., M.G.C., G.M.B. and J.E.K.III; writing--review and editing, G.C. and C.H.; project administration, G.C.; funding acquisition, G.C. and C.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the U.S. National Science Foundation (OISE #2153579).  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors would like to thank numerous contributors who provided vital field and technical support, including [PERSON], [PERSON], [PERSON],  
Figure 10: **Left**: A drone spraying pesticide. **Right**: Drone-captured NDVI of durian tree health monitoring, presented by a farmer. Photos taken in summer 2023 (credit: [PERSON]).  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON]. The authors are also grateful to the editor and three anonymous reviewers for their constructive comments, which helped to improve this paper.  
The authors declare no conflicts of interest.