State-Level Paddy Production, Yield, Remote-Sensing and Environmental Data for Malaysia, 2017–2024
Description
This dataset integrates Malaysian state-level paddy statistics with rice vegetation, climate and soil indicators for 2017–2024. It provides an analysis-ready state-year resource for agricultural, environmental and climate-resilience research. The primary dataset is 01_combined_paddy_climate_2017_2024.csv. Each observation represents a Malaysian state in a given year. It combines official agricultural statistics with indicators derived from established Earth observation, climate and soil products. No synthetic observations are used. DATA SOURCES Paddy planted area and production were obtained from Malaysian agricultural statistics and harmonised by state and year. Paddy yield is expressed in tonnes per hectare. Rice vegetation indicators were derived from Landsat imagery using Google Earth Engine (GEE). Climate indicators include rainfall and temperature-related variables. Soil characteristics were obtained from geospatial soil products. FILES 00_perangkaan_extracted_area_production.csv – extracted paddy statistics. 00_unmatched_state_years.csv – unmatched records, where applicable. 01_combined_paddy_climate_2017_2024.csv – primary integrated dataset. 02_missing_values.csv – missing-value assessment. 03_descriptive_statistics_with_CV.csv – descriptive statistics and CV. 04a_pearson_correlation_matrix.csv – Pearson correlations. 04b_spearman_correlation_matrix.csv – Spearman correlations. 05_climate_yield_relationships.csv – climate-yield relationships. 06_annual_climate_yield_summary.csv – annual summaries. 07_state_summary.csv – state summaries. 08_state_year_yield_t_ha.csv – state-year yield. 09_data_dictionary.csv – variable definitions, units and sources. 10_analysis_notes.json – processing and analysis notes. 11_spatial_metadata.csv – spatial metadata. PROCESSING Agricultural records were standardised by state and year. Earth observation, climate and soil indicators were spatially processed and aggregated to state level. State names and years were harmonised before integration. Missing and unmatched records were checked, and analytical outputs were derived from the integrated dataset. COVERAGE Country: Malaysia Spatial unit: State Period: 2017–2024 Temporal resolution: Annual Observation unit: State-year LIMITATIONS State-level environmental indicators should not be interpreted as farm-level measurements and may mask within-state variability. Reported correlations and climate-yield relationships represent exploratory associations, not causal effects. REUSE The dataset supports paddy-yield and climate-resilience research, spatiotemporal analysis, machine learning, visualisation, decision support and digital agriculture. Users should cite the Mendeley Data record and associated Data in Brief article when available.
Files
Steps to reproduce
Cite this dataset by Mohd Sharef, Nurfadhlina (2026), “State-Level Paddy Production, Yield, Remote-Sensing and Environmental Data for Malaysia, 2017–2024”, Mendeley Data, V1, doi: 10.17632/zzwvk2fzkk.1
Institutions
- Universiti Putra MalaysiaSelangor, Seri Kembangan