The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela
Abstract
The water supply for rainfed crops such as bananas in the Aragua state of Venezuela is often uncertain, particularly towards the beginning of the rainy season (April-May). Where climatic conditions are seasonal, the temporal evolution of the NDVI (Normalized Difference Vegetation Index) closely accompanies the interannual variation of vegetation growth in response to thermal and hydric factors. The aim of the study is to assess the relationship between NDVI, rainfall and potential evapotranspiration during the period of January/2016 to December/2017 in a Venezuelan banana plantation. In this study, the NDVI derived from the GIMMS MODIS Terra product, the daily accumulated precipitation data (mm) and the daily mean air temperature (°C) were used as the only way to estimate the potential evapotranspiration. The results showed that the GMOD09Q1-based NDVI reflects reasonably well the spatiotemporal variation in biomass accumulation. Besides, this provides information on the water stress conditions in banana plants at the plot level. The influence of Precipitation and potential evapotranspiration on the NDVI was more evident when a lag of 1 month was considered in terms of the Spearman r, implying that there is a delay in the banana phonological response to rainfall changes and dryness conditions. However, due to its low spatial resolution (i.e. 250 m), it is not adequate for the identification of banana wilt disease. Therefore, future studies are needed to assess other satellite-derived spectral indices for monitoring the health of banana plants over different sites in Venezuela.
Keywords
Full Text:
PDFReferences
Akoglu, H. (2018). User's guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(3), 91-93. https://doi.org/10.1016/j.tjem.2018.08.001
Alam, M. S., Lamb, D. W., & Rahman, M. M. (2018). A refined method for rapidly determining the relationship between canopy NDVI and the pasture evapotranspiration coefficient. Computers and Electronics in Agriculture, 147, 12-17. https://doi.org/10.1016/j.compag.2018.02.008
Berger, A., Ettlin, G., Quincke, C., & Rodríguez-Bocca, P. (2019). Predicting the Normalized Difference Vegetation Index (NDVI) by training a crop growth model with historical data. Computers and Electronics in Agriculture, 161, 305-311. https://doi.org/10.1016/j.compag.2018.04.028
Blesić, S., Zanchettin, D., & Rubino, A. (2019). Heterogeneity of Scaling of the Observed Global Temperature Data. Journal of Climate, 32(2), 349-367. https://doi.org/10.1175/JCLI-D-17-0823.1
Bouwmeester, H., Heuvelink, G. B. M., & Stoorvogel, J. J. (2016). Mapping crop diseases using survey data: The case of bacterial wilt in bananas in the East African highlands. European Journal of Agronomy, 74, 173-184. https://doi.org/10.1016/j.eja.2015.12.013
Clark, A., & McKechnie, J. (2020). Detecting Banana Plantations in the Wet Tropics, Australia, Using Aerial Photography and U-Net. Applied Sciences, 10(6), 2017. https://doi.org/10.3390/app10062017
Dannenberg, M., Wang, X., Yan, D., & Smith, W. (2020). Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing. Remote Sensing, 12(4), 671. https://doi.org/10.3390/rs12040671
Fensholt, R., & Proud, S. R. (2012). Evaluation of Earth Observation based global long term vegetation trends — Comparing GIMMS and MODIS global NDVI time series. Remote Sensing of Environment, 119, 131-147. https://doi.org/10.1016/j.rse.2011.12.015
Gillespie, T. W., Ostermann-Kelm, S., Dong, C., Willis, K. S., Okin, G. S., & MacDonald, G. M. (2018). Monitoring changes of NDVI in protected areas of southern California. Ecological Indicators, 88, 485-494. https://doi.org/10.1016/j.ecolind.2018.01.031
Heck, E., de Beurs, K. M., Owsley, B. C., & Henebry, G. M. (2019). Evaluation of the MODIS collections 5 and 6 for change analysis of vegetation and land surface temperature dynamics in North and South America. ISPRS Journal of Photogrammetry and Remote Sensing, 156, 121-134. https://doi.org/10.1016/j.isprsjprs.2019.07.011
Jedermann, R., Praeger, U., Geyer, M., & Lang, W. (2014). Remote quality monitoring in the banana chain. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 372(2017), 20130303. https://doi.org/10.1098/rsta.2013.0303
Jiang, L., Guli•Jiapaer, Bao, A., Guo, H., & Ndayisaba, F. (2017). Vegetation dynamics and responses to climate change and human activities in Central Asia. Science of The Total Environment, 599-600, 967-980. https://doi.org/10.1016/j.scitotenv.2017.05.012
Johansen, K., Sohlbach, M., Sullivan, B., Stringer, S., Peasley, D., & Phinn, S. (2014). Mapping Banana Plants from High Spatial Resolution Orthophotos to Facilitate Plant Health Assessment. Remote Sensing, 6(9), 8261-8286. https://doi.org/10.3390/rs6098261
Machovina, B. L., Feeley, K. J., & Machovina, B. J. (2016). UAV remote sensing of spatial variation in banana production. Crop and Pasture Science, 67(12), 1281-1287. https://doi.org/10.1071/CP16135
Martínez-Solórzano, G., Rey-Brina, J. C., Rodríguez, D., Jiménez, C., Rodríguez, Y., Rumbos, R., Pargas-Pichardo, R., Manzanilla, E., & Martínez, E. (2020). Análisis de la situación fitopatológica actual de las musáceas comestibles en Venezuela. Agronomía Tropical, 70, 1-20. https://doi.org/https://doi.org/10.5281/zenodo.4323272
Olivares, B. O. (2018). Tropical rainfall conditions in rainfed agriculture in Carabobo, Venezuela. LA GRANJA. Revista de Ciencias de la Vida, 27(1), 86-102. https://doi.org/10.17163/lgr.n27.2018.07
Olivares, B. O., Araya-Alman, M., Acevedo-Opazo, C., Rey, J. C., Cañete-Salinas, P., Kurina, F. G., Balzarini, M., Lobo, D., Navas-Cortés, J. A., Landa, B. B., & Gómez, J. A. (2020). Relationship Between Soil Properties and Banana Productivity in the Two Main Cultivation Areas in Venezuela. Journal of Soil Science and Plant Nutrition, 20(4), 2512-2524. https://doi.org/10.1007/s42729-020-00317-8
Olivares, B. O., & López-Beltrán, M. A. (2019). Normalized Difference Vegetation Index (NDVI) applied to the agricultural indigenous territory of Kashaama, Venezuela. UNED Research Journal, 11(2). https://doi.org/10.22458/urj.v11i2.2299
Olivares, B. O., Rey, J. C., Lobo, D., Navas-Cortés, J. A., Gómez, J. A., & Landa, B. B. (2021). Fusarium Wilt of Bananas: A Review of Agro-Environmental Factors in the Venezuelan Production System Affecting Its Development. Agronomy, 11(5), 986. https://doi.org/10.3390/agronomy11050986
Oliveira, C. W., da Silva, W. N., Campos, P. E. R., Meireles, A. C. M., & Batista, D. d. S. (2019). Detection of banana crop expansion in cariri cearense by orbital images. Revista Brasileira de Agricultura Irrigada, 13(5), 3676-3682. https://doi.org/10.7127/rbai.v13n5001130
Rahimi, J., Khalili, A., & Butterbach-Bahl, K. (2019). Projected changes in modified Thornthwaite climate zones over Southwest Asia using a CMIP5 multi-model ensemble. International Journal of Climatology, 39(12), 4575-4594. https://doi.org/10.1002/joc.6088
Rey-Brina, J. C., Martínez-Solórzano, G., Ramírez, H., & Pargas-Pichardo, R. (2020). Relación de las condiciones agroecológicas de un lote de planicie lacustrina con la marchitez del banano Cavendish en Aragua, Venezuela. Agronomía Tropical, 70, 1-12. https://doi.org/10.5281/zenodo.4346251
Sharifi, A. (2020). Remotely sensed vegetation indices for crop nutrition mapping. Journal of the Science of Food and Agriculture, 100(14), 5191-5196. https://doi.org/10.1002/jsfa.10568
Teixeira, A. H. d. C., Leivas, J. F., Pacheco, E. P., Garçon, E. A. M., & Takemura, C. M. (2021). Biophysical Characterization and Monitoring Large-Scale Water and Vegetation Anomalies by Remote Sensing in the Agricultural Growing Areas of the Brazilian Semi-Arid Region. In Advances in Remote Sensing for Natural Resource Monitoring (pp. 94-109). https://doi.org/10.1002/9781119616016.ch7
Vásquez, Z. E., & Paredes-Trejo, F. (2020). SINCRONIZADA TEMPORAL ENTRE EL ÍNDICE DE VEGETACIÓN NDVI Y LA PRECIPITACIÓN EN UNA PLANTACIÓN DE Eucalyptus spp. Revista Agrollania de Ciencia y Tecnología, 19, 75 - 79. http://revistas.unellez.edu.ve/index.php/agrollania/article/view/969
Verrelst, J., Camps-Valls, G., Muñoz-Marí, J., Rivera, J. P., Veroustraete, F., Clevers, J. G. P. W., & Moreno, J. (2015). Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review. ISPRS Journal of Photogrammetry and Remote Sensing, 108, 273-290. https://doi.org/10.1016/j.isprsjprs.2015.05.005
Ye, H., Huang, W., Huang, S., Cui, B., Dong, Y., Guo, A., Ren, Y., & Jin, Y. (2020). Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing. Remote Sensing, 12(6), 938. https://doi.org/10.3390/rs12060938
Zhou, R., Wang, H., Duan, K., & Liu, B. (2021). Diverse responses of vegetation to hydroclimate across temporal scales in a humid subtropical region. Journal of Hydrology: Regional Studies, 33, 100775. https://doi.org/10.1016/j.ejrh.2021.100775
Refbacks
- There are currently no refbacks.