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Article

Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin

1
School of Geography and Tourism, Qufu Normal University, Rizhao 276826, China
2
Sino-Belgian Joint Laboratory of Geo-Information, Rizhao 276826, China
3
Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium
4
Department of Geography, Ghent University, 9000 Ghent, Belgium
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(23), 4507; https://doi.org/10.3390/rs16234507
Submission received: 22 September 2024 / Revised: 26 November 2024 / Accepted: 28 November 2024 / Published: 1 December 2024

Abstract

The ecological environment of the Yellow River Basin in China is characterized by drought, which has been exacerbated by global warming. It is critical to keep accurate track of the region’s agricultural drought conditions. To enhance the vegetation health index (VHI), the optimal time scale for the standardized precipitation evapotranspiration index (SPEI) was determined by using the maximum correlation coefficient method, and the calculation method for VHI was optimized. The contributions of the vegetation condition index (VCI) and the temperature condition index (TCI) to the VHI were scientifically optimized, leading to the development of the optimal VHI (VHIopt). Soil moisture anomaly (SMA) and the SPEI were employed for assessing the performance of VHIopt. Furthermore, the temporal and spatial evolution of agricultural drought in the Yellow River Basin (YRB) was analyzed using VHIopt. The results indicate the following: (1) In the YRB, the optimal contribution of the VCI to the VHI is lower than that of the TCI. (2) The drought monitoring accuracy of VHIopt in forests, grasslands, croplands, and other vegetation types exceeds that of the original VHI (VHIori). Additionally, it demonstrates a high level of consistency with the SMA and the SPEI03 regarding spatial and temporal characteristics. (3) Agricultural drought in the YRB is gradually diminishing; however, significant regional differences remain. Generally, the findings of this study highlight that VHIopt is better suited to the specific climate and vegetation conditions of the Yellow River Basin, enhancing its effectiveness for agricultural drought monitoring in this region.
Keywords: vegetation health index; yellow river basin; algorithm optimization; drought monitoring vegetation health index; yellow river basin; algorithm optimization; drought monitoring

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MDPI and ACS Style

Hang, Q.; Guo, H.; Meng, X.; Wang, W.; Cao, Y.; Liu, R.; De Maeyer, P.; Wang, Y. Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin. Remote Sens. 2024, 16, 4507. https://doi.org/10.3390/rs16234507

AMA Style

Hang Q, Guo H, Meng X, Wang W, Cao Y, Liu R, De Maeyer P, Wang Y. Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin. Remote Sensing. 2024; 16(23):4507. https://doi.org/10.3390/rs16234507

Chicago/Turabian Style

Hang, Qinghou, Hao Guo, Xiangchen Meng, Wei Wang, Ying Cao, Rui Liu, Philippe De Maeyer, and Yunqian Wang. 2024. "Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin" Remote Sensing 16, no. 23: 4507. https://doi.org/10.3390/rs16234507

APA Style

Hang, Q., Guo, H., Meng, X., Wang, W., Cao, Y., Liu, R., De Maeyer, P., & Wang, Y. (2024). Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin. Remote Sensing, 16(23), 4507. https://doi.org/10.3390/rs16234507

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