Next Article in Journal
Prediction of Canopy Heights over a Large Region Using Heterogeneous Lidar Datasets: Efficacy and Challenges
Previous Article in Journal
Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(9), 11016-11035; doi:10.3390/rs70911016

Tracking Ecosystem Water Use Efficiency of Cropland by Exclusive Use of MODIS EVI Data

1
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
2
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
3
Department of Soil, Water and Climate, University of Minnesota, St. Paul, MN 55108, USA
4
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
5
Key Laboratory of Poyang Lake Wetland and Watershed Research (Jiangxi Normal University), Ministry of Education, Nanchang 330022, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Pablo J. Zarco-Tejada, Yoshio Inoue and Prasad S. Thenkabail
Received: 28 July 2015 / Revised: 13 August 2015 / Accepted: 20 August 2015 / Published: 26 August 2015
View Full-Text   |   Download PDF [1106 KB, uploaded 26 August 2015]   |  

Abstract

One of the most important linkages that couple terrestrial carbon and water cycles is ecosystem water use efficiency (WUE), which is relevant to the reasonable utilization of water resources and farming practices. Eddy covariance techniques provide an opportunity to monitor the variability in WUE and can be integrated with Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Scaling up in situ observations from flux tower sites to large areas remains challenging and few studies have been reported on direct estimation of WUE from remotely-sensed data. This study examined the main environmental factors driving the variability in WUE of corn/soybean croplands, and revealed the prominent role of solar radiation and temperature. Time-series of MODIS-derived enhanced vegetation indices (EVI), which are proxies for the plant responses to environmental controls, were also strongly correlated with ecosystem WUE, thereby implying great potential for remote quantification. Further, both performance of the indirect MODIS-derived WUE from gross primary productivity (GPP) and evapotranspiration (ET), and the direct estimates by exclusive use of MODIS EVI data were evaluated using tower-based measurements. The results showed that ecosystem WUE were overpredicted at the beginning and ending of crop-growth periods and severely underestimated during the peak periods by the indirect estimates from MODIS products, which was mainly attributed to the error source from MODIS GPP. However, a simple empirical model that is solely based on MODIS EVI data performed rather well to capture the seasonal variations in WUE, especially for the growing periods of croplands. Independent validation at different sites indicates the method has potential for broad application. View Full-Text
Keywords: water use efficiency; cropland; MODIS; vegetation index; GPP; ET water use efficiency; cropland; MODIS; vegetation index; GPP; ET
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

Tang, X.; Li, H.; Griffis, T.J.; Xu, X.; Ding, Z.; Liu, G. Tracking Ecosystem Water Use Efficiency of Cropland by Exclusive Use of MODIS EVI Data. Remote Sens. 2015, 7, 11016-11035.

Show more citation formats Show less citations formats

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