Land Suitability Assessment and Gap Analysis for Sustainable Taro (Colocasia esculenta (L.) Schott) Production in Rwanda Using Remote Sensing Data and a Fuzzy AHP Model
文献类型：期刊论文
| 作者 | Nsigayehe, Jean Marie Vianney1,2; Mo, Xingguo1,2,3; Liu, Suxia1,2,3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2025-12-18 |
| 卷号 | 17期号:24页码:4062 |
| 关键词 | taro (Colocasia esculenta (L.) Schott) Fuzzy AHP-GIS land suitability production gap land use planning food security |
| DOI | 10.3390/rs17244062 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Highlights What are the main findings? The analysis revealed that a significant portion of Rwanda land is well-suited for taro, with 22.8% classified as highly suitable and 55.7% as moderately suitable. A key finding was that within existing farmland, over 28% of the highly suitable land remains untapped for taro cultivation, indicating substantial room for expansion, particularly in the Eastern province. Methodologically, this study is the first to integrate multi-source remote sensing data within a Fuzzy-AHP-GIS framework for Rwanda, creating a transferable model for assessing underutilized crops to enhance food security. What are the implications of the main findings? The findings offer an actionable blueprint for policymakers to direct the agricultural resources allocation and support services to high-potential districts via optimizing land use and investment. Closing the identified production gap through the adoption of improved practices on suitable land can transform taro from a marginal crop into a cornerstone of Rwanda climate-resilient agricultural strategy. This shift would enhance national food security, provide a global model for sustainable development for developing countries, and attract more research attention to orphan crops such as taro.Highlights What are the main findings? The analysis revealed that a significant portion of Rwanda land is well-suited for taro, with 22.8% classified as highly suitable and 55.7% as moderately suitable. A key finding was that within existing farmland, over 28% of the highly suitable land remains untapped for taro cultivation, indicating substantial room for expansion, particularly in the Eastern province. Methodologically, this study is the first to integrate multi-source remote sensing data within a Fuzzy-AHP-GIS framework for Rwanda, creating a transferable model for assessing underutilized crops to enhance food security. What are the implications of the main findings? The findings offer an actionable blueprint for policymakers to direct the agricultural resources allocation and support services to high-potential districts via optimizing land use and investment. Closing the identified production gap through the adoption of improved practices on suitable land can transform taro from a marginal crop into a cornerstone of Rwanda climate-resilient agricultural strategy. This shift would enhance national food security, provide a global model for sustainable development for developing countries, and attract more research attention to orphan crops such as taro.Abstract Taro (Colocasia esculenta (L.) Schott) is a nutritionally important and climate-resilient crop with high potential for enhancing food security. Despite its significance, taro remains underutilized and excluded from major agricultural policies in Rwanda, resulting in low national yields. This gap hinders evidence-based planning and limits the crop contribution to resilience amidst population growth and climate change. By taking Rwanda as an example, a worldwide top 10 taro-producing country but still facing food insecurity issues, this study conducted a nationwide land suitability assessment to identify optimal areas for taro cultivation and quantify the production gap. The Fuzzy Analytic Hierarchy Process (AHP) model was integrated with GIS, where climatic, topographic, and a remotely sensed soil dataset were weighted and combined to generate a composite suitability index. Results revealed that 22.8% of Rwanda's land is highly suitable (S1) and 55.7% is moderately suitable (S2) for taro cultivation. Within agricultural land, 30.2% is highly suitable, of which a significant portion (28.7%) remains largely underutilized, especially in the Eastern province. The national production gap was estimated at 32.4%, with over half of the districts exceeding 30%. The study highlights the importance of aligning taro cultivation with biophysical suitability and integrating spatial planning into national agricultural policies. The developed suitability map provides a critical decision-support tool for policymakers, agricultural planners, and extension services. By promoting sustainable taro production, improving farmer livelihoods and food security in Rwanda, it provides a global model for sustainable development for developing countries and advances research on orphan crops such as taro. The methodology offers a replicable framework for evaluating underutilized crops globally, contributing to sustainable agricultural diversification and food security. |
| URL标识 | 查看原文 |
| WOS关键词 | CLIMATE-CHANGE ; PERFORMANCE |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001647450500001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219429]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Mo, Xingguo |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China; 2.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 3.Univ Chinese Acad Sci, Sino Danish Ctr, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Nsigayehe, Jean Marie Vianney,Mo, Xingguo,Liu, Suxia. Land Suitability Assessment and Gap Analysis for Sustainable Taro (Colocasia esculenta (L.) Schott) Production in Rwanda Using Remote Sensing Data and a Fuzzy AHP Model[J]. REMOTE SENSING,2025,17(24):4062. |
| APA | Nsigayehe, Jean Marie Vianney,Mo, Xingguo,&Liu, Suxia.(2025).Land Suitability Assessment and Gap Analysis for Sustainable Taro (Colocasia esculenta (L.) Schott) Production in Rwanda Using Remote Sensing Data and a Fuzzy AHP Model.REMOTE SENSING,17(24),4062. |
| MLA | Nsigayehe, Jean Marie Vianney,et al."Land Suitability Assessment and Gap Analysis for Sustainable Taro (Colocasia esculenta (L.) Schott) Production in Rwanda Using Remote Sensing Data and a Fuzzy AHP Model".REMOTE SENSING 17.24(2025):4062. |
入库方式： OAI收割
来源：地理科学与资源研究所
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