Next Article in Journal
Using Multi-Spectral UAV Imagery to Extract Tree Crop Structural Properties and Assess Pruning Effects
Next Article in Special Issue
Seasonal and Decadal Groundwater Changes in African Sedimentary Aquifers Estimated Using GRACE Products and LSMs
Previous Article in Journal
Estimation of Grassland Canopy Height and Aboveground Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle
Previous Article in Special Issue
Monitoring Groundwater Storage Changes Using the Gravity Recovery and Climate Experiment (GRACE) Satellite Mission: A Review
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(6), 852; https://doi.org/10.3390/rs10060852

What Is the Spatial Resolution of grace Satellite Products for Hydrology?

1
Institute of Geodesy, University of Stuttgart, 70174 Stuttgart, Germany
2
Institute of Geodesy, Leibniz University of Hannover, 30167 Hannover, Germany
Current address: Bristol Glaciology Center, School of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, UK.
*
Author to whom correspondence should be addressed.
Received: 14 February 2018 / Revised: 11 May 2018 / Accepted: 29 May 2018 / Published: 31 May 2018
(This article belongs to the Special Issue Remote Sensing of Groundwater from River Basin to Global Scales)
Full-Text   |   PDF [2763 KB, uploaded 27 June 2018]   |  

Abstract

The mass change information from the Gravity Recovery And Climate Experiment (grace) satellite mission is available in terms of noisy spherical harmonic coefficients truncated at a maximum degree (band-limited). Therefore, filtering is an inevitable step in post-processing of grace fields to extract meaningful information about mass redistribution in the Earth-system. It is well known from previous studies that a number can be allotted to the spatial resolution of a band-limited spherical harmonic spectrum and also to a filtered field. Furthermore, it is now a common practice to correct the filtered grace data for signal damage due to filtering (or convolution in the spatial domain). These correction methods resemble deconvolution, and, therefore, the spatial resolution of the corrected grace data have to be reconsidered. Therefore, the effective spatial resolution at which we can obtain mass changes from grace products is an area of debate. In this contribution, we assess the spatial resolution both theoretically and practically. We confirm that, theoretically, the smallest resolvable catchment is directly related to the band-limit of the spherical harmonic spectrum of the grace data. However, due to the approximate nature of the correction schemes and the noise present in grace data, practically, the complete band-limited signal cannot be retrieved. In this context, we perform a closed-loop simulation comparing four popular correction schemes over 255 catchments to demarcate the minimum size of the catchment whose signal can be efficiently recovered by the correction schemes. We show that the amount of closure error is inversely related to the size of the catchment area. We use this trade-off between the error and the catchment size for defining the potential spatial resolution of the grace product obtained from a correction method. The magnitude of the error and hence the spatial resolution are both dependent on the correction scheme. Currently, a catchment of the size ≈63,000 km 2 can be resolved at an error level of 2 cm in terms of equivalent water height. View Full-Text
Keywords: grace; filtering; signal leakage; spatial resolution; hydrology grace; filtering; signal leakage; spatial resolution; hydrology
Figures

Figure 1

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

Share & Cite This Article

MDPI and ACS Style

Vishwakarma, B.D.; Devaraju, B.; Sneeuw, N. What Is the Spatial Resolution of grace Satellite Products for Hydrology? Remote Sens. 2018, 10, 852.

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