Document Type
Article
Publication Date
2-15-2024
Abstract
Monitoring crop growth, soil conditions, and hydrological dynamics are imperative for sustainable agriculture and reduced environmental impacts. This interdisciplinary study integrates remote sensing, digital soil mapping, and hydrological data to elucidate intricate connections between these factors in the state of Ohio, USA. Advanced spatiotemporal analysis techniques were applied to key datasets, including the MODIS sensor satellite imagery, USDA crop data, soil datasets, Aster GDEM, and USGS stream gauge measurements. Vegetation indices derived from MODIS characterized crop-specific phenology and productivity patterns. Exploratory spatial data analysis show relationships of vegetation dynamics and soil properties, uncovering links between plant vigor, edaphic fertility, and nutrient distributions. Correlation analysis quantified these relationships and their seasonal evolution. Examination of stream gauge data revealed insights into spatiotemporal relationships of nutrient pollution and stream discharge. By synthesizing diverse geospatial data through cutting-edge data analytics, this work illuminated complex interactions between crop health, soil nutrients, and water quality in Ohio. The methodology and findings provide actionable perspectives to inform sustainable agricultural management and environmental policy. This study demonstrates the significant potential of open geospatial resources when integrated using a robust spatiotemporal framework. Integrating additional measurements and high-resolution data sources through advanced analytics and interactive visualizations could strengthen these insights.
Keywords
data integration, exploratory geospatial analysis, MODIS NDVI, nutrient distribution, soil-crop monitoring
Language
English
Publication Title
Journal of Geovisualization and Spatial Analysis
Grant
2133576
Rights
© The Author(s) 2024. This is an Open Access work distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Akanbi, O.D., Bhuvanagiri, D.C., Barcelos, E.I. et al. Integrating Multiscale Geospatial Analysis for Monitoring Crop Growth, Nutrient Distribution, and Hydrological Dynamics in Large-Scale Agricultural Systems. J geovis spat anal 8, 9 (2024). https://doi.org/10.1007/s41651-023-00164-y
Included in
Agricultural Science Commons, Geographic Information Sciences Commons, Physical Sciences and Mathematics Commons
Manuscript Version
Final Publisher Version