Next Article in Journal
Specific Land Cover Class Mapping by Semi-Supervised Weighted Support Vector Machines
Previous Article in Journal
Urban Land Extraction Using VIIRS Nighttime Light Data: An Evaluation of Three Popular Methods
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(2), 177; doi:10.3390/rs9020177

Comparison of Two Simulation Methods of the Temperature Vegetation Dryness Index (TVDI) for Drought Monitoring in Semi-Arid Regions of China

Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China, Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwest China of Ministry of Education, Ningxia University, Yinchuan 750021, China
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch and Prasad S. Thenkabail
Received: 9 December 2016 / Revised: 20 January 2017 / Accepted: 16 February 2017 / Published: 20 February 2017
View Full-Text   |   Download PDF [13376 KB, uploaded 20 February 2017]   |  

Abstract

The Temperature Vegetation Dryness Index (TVDI), a drought monitoring index based on an empirical parameterization of the Land Surface Temperature (LST)–Normalized Difference Vegetation Index (NDVI) space, has been widely implemented in a variety of ecosystems worldwide because it does not depend on ancillary data. However, the simulation of dry/wet edges in the TVDI model can be problematic because remote sensing images do not have sufficient pixels to identify the wetness and dryness extremes of different vegetation coverages. In this study, an improvement in dry/wet edge simulation was proposed, and a comparison of the original TVDI and the modified Temperature Vegetation Dryness Index (TVDIm) was performed for drought monitoring in Ningxia Province, which is a typical semi-arid region in China. First, the difference between the land surface temperatures in day and night (∆LST) was used as an alternative to LST when building the TVDIm model. In addition, the wet edges were improved by removing outliers using a statistical method, and the dry edges were optimized by removing the “tail down” points in the NDVI range of 0.0–0.1. Here, the modeling process of TVDIm in 2005, one of recent extreme drought year is illustrated. The results show that both the TVDI and TVDIm can be used to monitor the temporal and spatial variations of drought, and the onset, duration, extent, and severity of drought can be reflected by TVDI and TVDIm maps. However, the magnitude of TVDI is higher than that of TVDIm, which could cause the TVDI-simulated drought condition to be elevated in normal years and underestimated in dry years. The TVDIm has higher coefficients of correlation with in situ meteorological drought index and agricultural drought statistical data than does the original TVDI, and it exhibits better performance in drought monitoring compared to that of the original TVDI in semi-arid regions of China. View Full-Text
Keywords: drought monitoring; temperature vegetation dryness index; dry/wet edges simulation; Moderate Resolution Imaging Spectroradiometer; semi-arid regions drought monitoring; temperature vegetation dryness index; dry/wet edges simulation; Moderate Resolution Imaging Spectroradiometer; semi-arid regions
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Du, L.; Song, N.; Liu, K.; Hou, J.; Hu, Y.; Zhu, Y.; Wang, X.; Wang, L.; Guo, Y. Comparison of Two Simulation Methods of the Temperature Vegetation Dryness Index (TVDI) for Drought Monitoring in Semi-Arid Regions of China. Remote Sens. 2017, 9, 177.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top