绘制贝宁小农腰果种植园地图以指导可持续木本作物扩张
Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin
AI总结：
本文利用高分辨率遥感影像和深度学习算法绘制贝宁首张全国腰果地图，揭示2015至2021年腰果种植园扩张特征及集约化潜力。
摘要：
腰果由全球40多个国家的300多万小农种植，是其主要收入来源。作为非洲第三大腰果生产国，贝宁拥有近20万小农腰果种植者，贡献了该国国家出口收入的15%。然而，缺乏关于腰果树在全国何处以及如何生长的信息，阻碍了能够支持增加腰果产量和减贫的决策。通过利用2.4米Planet Basemaps和0.5米航空影像、新开发的深度学习算法以及大规模地面真值数据集，我们成功制作了贝宁首张全国腰果地图，并刻画了2015年至2021年间腰果种植园的扩张特征。特别是，我们开发了一种带注意力的时空分类（STCA）模型来绘制腰果种植园的分布，该模型能够充分捕捉生长季中具有判别力的时间步的纹理信息。我们进一步开发了一种聚类增强自监督时序分类（CASTC）模型，通过自动特征提取和优化聚类来区分高密度与低密度腰果种植园。结果表明，STCA模型的总体准确率超过85%，CASTC模型达到了76%的总体准确率。我们发现，贝宁的腰果面积从2015年到2021年几乎翻了一番，其中60%的新种植园开发来自农田或休耕地，而腰果种植园对保护区的侵占增加了55%。2021年只有一半的腰果种植园是高密度的，这表明集约化潜力巨大。我们的研究展示了将高分辨率遥感影像与最先进的深度学习算法相结合，以更好地理解异质小农景观中木本作物的能力。
英文摘要：
Cashews are grown by over 3 million smallholders in more than 40 countries worldwide as a principal source of income. As the third largest cashew producer in Africa, Benin has nearly 200,000 smallholder cashew growers contributing 15% of the country's national export earnings. However, a lack of information on where and how cashew trees grow across the country hinders decision-making that could support increased cashew production and poverty alleviation. By leveraging 2.4-m Planet Basemaps and 0.5-m aerial imagery, newly developed deep learning algorithms, and large-scale ground truth datasets, we successfully produced the first national map of cashew in Benin and characterized the expansion of cashew plantations between 2015 and 2021. In particular, we developed a SpatioTemporal Classification with Attention (STCA) model to map the distribution of cashew plantations, which can fully capture texture information from discriminative time steps during a growing season. We further developed a Clustering Augmented Self-supervised Temporal Classification (CASTC) model to distinguish high-density versus low-density cashew plantations by automatic feature extraction and optimized clustering. Results show that the STCA model has an overall accuracy over 85% and the CASTC model achieved an overall accuracy of 76%. We found that the cashew area in Benin almost doubled from 2015 to 2021 with 60% of new plantation development coming from cropland or fallow land, while encroachment of cashew plantations into protected areas has increased by 55%. Only half of cashew plantations were high-density in 2021, suggesting high potential for intensification. Our study illustrates the power of combining high-resolution remote sensing imagery and state-of-the-art deep learning algorithms to better understand tree crops in the heterogeneous smallholder landscape.
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