Mapping vegetation index-derived actual evapotranspiration across croplands using the Google Earth Engine platform
Remote Sensing
Links
- More information: Publisher Index Page (via DOI)
- Open Access Version: Publisher Index Page
- Download citation as: RIS | Dublin Core
Abstract
Precise knowledge of crop water consumption is essential to better manage agricultural water use, particularly in regions where most countries struggle with increasing water and food insecurity. Approaches such as cloud computing and remote sensing (RS) have facilitated access, process, and visualization of big geospatial data to map and monitor crop water requirements. To find the most reliable Vegetation Index (VI)-based evapotranspiration (ETa) for croplands in drylands, we modeled and mapped ETa using empirical RS methods across the Zayandehrud river basin in Iran for two decades (2000–2019) on the Google Earth Engine platform using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index 2 (EVI2). Developed ET-VI products in this study comprise three NDVI-based ETa (ET-NDVI*, ET-NDVI*scaled, and ET-NDVIKc) and an EVI2-based ETa (ET-EVI2). We (a) applied, for the first time, the ET-NDVI* method to croplands as a crop-independent index and then compared its performance with the ET-EVI2 and crop ET, and (b) assessed the ease and feasibility of the transferability of these methods to other regions. Comparing four ET-VI products showed that annual ET-EVI2 and ET-NDVI*scaled estimations were close. ET-NDVIKc consistently overestimated ETa. Our findings indicate that ET-EVI2 and ET-NDVIKc were easy to parametrize and adopt to other regions, while ET-NDVI* and ET-NDVI*scaled are site-dependent and sensitive to image acquisition time. ET-EVI2 performed robustly in arid and semi-arid regions making it a better tool. Future research should further develop and confirm these findings by characterizing the accuracy of VI-based ETa over croplands in drylands by comparing them with available ETa products and examining their performance using crop-specific comparisons.
Suggested Citation
Abbasi, N., Nouri, H., Didan, K., Barreto-Muñoz, A., Chavoshi Borujeni, S., Opp, C., Nagler, P.L., Thenkabail, P., Siebert, S., 2023, Mapping vegetation index-derived actual evapotranspiration across croplands using the Google Earth Engine platform: Remote Sensing, v. 15, no. 4, 1017, 21 p., https://doi.org/10.3390/rs15041017.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Mapping vegetation index-derived actual evapotranspiration across croplands using the Google Earth Engine platform |
| Series title | Remote Sensing |
| DOI | 10.3390/rs15041017 |
| Volume | 15 |
| Issue | 4 |
| Publication Date | February 12, 2023 |
| Year Published | 2023 |
| Language | English |
| Publisher | MDPI |
| Contributing office(s) | Southwest Biological Science Center, Western Geographic Science Center |
| Description | 1017, 21 p. |