SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data
Precision agriculture harnesses data-driven techniques to optimize crop production, resource use, and sustainability. However, low-income countries like Bangladesh face a shortage of localized, high-quality datasets that reflect regional agroclimatic conditions and cropping practices. To address thi...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
|
| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235234092500455X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1839582694542934016 |
|---|---|
| author | Rup Chowdhury Fernaz Narin Nur Muhammad Nazrul Islam Md. Nazmul Islam Prapti Das Arafat Sahin Afridi |
| author_facet | Rup Chowdhury Fernaz Narin Nur Muhammad Nazrul Islam Md. Nazmul Islam Prapti Das Arafat Sahin Afridi |
| author_sort | Rup Chowdhury |
| collection | DOAJ |
| description | Precision agriculture harnesses data-driven techniques to optimize crop production, resource use, and sustainability. However, low-income countries like Bangladesh face a shortage of localized, high-quality datasets that reflect regional agroclimatic conditions and cropping practices. To address this gap, we present SPAS-Dataset-BD, a robust dataset compiled through a hybrid approach: secondary extraction from the Bangladesh Bureau of Statistics (BBS) 2022 Yearbook and primary on-field surveys of 223 farmers across ten diverse districts. The dataset comprises 4191 records over 73 crop types, with 12 agronomic and environmental features, including underrepresented species. Robustness is demonstrated via threshold-based missing-value handling (<5 % deletion, targeted imputation), hash-based deduplication, and cross-validation against official statistics. We illustrate potential applications, in machine learning (73-class crop classification, yield forecasting) and IoT-driven irrigation scheduling. SPAS-Dataset-BD’s scale, methodological transparency, and contextual richness make it a valuable resource for precision agriculture research and policy-making in South Asia. |
| format | Article |
| id | doaj-art-44ba2b4561b34c4885fefb62397af2d1 |
| institution | Matheson Library |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-44ba2b4561b34c4885fefb62397af2d12025-08-04T04:24:07ZengElsevierData in Brief2352-34092025-08-0161111727SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley DataRup Chowdhury0Fernaz Narin Nur1Muhammad Nazrul Islam2Md. Nazmul Islam3Prapti Das4Arafat Sahin Afridi5Department of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, BangladeshDepartment of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, Bangladesh; Corresponding author.Department of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, BangladeshDepartment of Computer Science and Engineering, Notre Dame University Bangladesh, 2/A, Arambagh, Motijheel, Dhaka, 1000, BangladeshDepartment of Computer Science and Engineering, Notre Dame University Bangladesh, 2/A, Arambagh, Motijheel, Dhaka, 1000, BangladeshDepartment of Computer Science and Engineering, Military Institute of Science and Technology, Mirpur Cantonment, Dhaka, 1216, BangladeshPrecision agriculture harnesses data-driven techniques to optimize crop production, resource use, and sustainability. However, low-income countries like Bangladesh face a shortage of localized, high-quality datasets that reflect regional agroclimatic conditions and cropping practices. To address this gap, we present SPAS-Dataset-BD, a robust dataset compiled through a hybrid approach: secondary extraction from the Bangladesh Bureau of Statistics (BBS) 2022 Yearbook and primary on-field surveys of 223 farmers across ten diverse districts. The dataset comprises 4191 records over 73 crop types, with 12 agronomic and environmental features, including underrepresented species. Robustness is demonstrated via threshold-based missing-value handling (<5 % deletion, targeted imputation), hash-based deduplication, and cross-validation against official statistics. We illustrate potential applications, in machine learning (73-class crop classification, yield forecasting) and IoT-driven irrigation scheduling. SPAS-Dataset-BD’s scale, methodological transparency, and contextual richness make it a valuable resource for precision agriculture research and policy-making in South Asia.http://www.sciencedirect.com/science/article/pii/S235234092500455XPrecision agricultureCrop predictionMachine learningAgricultural datasetBangladeshIoT |
| spellingShingle | Rup Chowdhury Fernaz Narin Nur Muhammad Nazrul Islam Md. Nazmul Islam Prapti Das Arafat Sahin Afridi SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data Data in Brief Precision agriculture Crop prediction Machine learning Agricultural dataset Bangladesh IoT |
| title | SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data |
| title_full | SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data |
| title_fullStr | SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data |
| title_full_unstemmed | SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data |
| title_short | SPAS-Dataset-BD: Dataset for smart precision agriculture system in BangladeshMendeley Data |
| title_sort | spas dataset bd dataset for smart precision agriculture system in bangladeshmendeley data |
| topic | Precision agriculture Crop prediction Machine learning Agricultural dataset Bangladesh IoT |
| url | http://www.sciencedirect.com/science/article/pii/S235234092500455X |
| work_keys_str_mv | AT rupchowdhury spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata AT fernaznarinnur spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata AT muhammadnazrulislam spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata AT mdnazmulislam spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata AT praptidas spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata AT arafatsahinafridi spasdatasetbddatasetforsmartprecisionagriculturesysteminbangladeshmendeleydata |