Next Article in Journal
Preface: Remote Sensing in Coastal Environments
Previous Article in Journal
Highlighting Biome-Specific Sensitivity of Fire Size Distributions to Time-Gap Parameter Using a New Algorithm for Fire Event Individuation
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(8), 661;

Hyper-Temporal C-Band SAR for Baseline Woody Structural Assessments in Deciduous Savannas

Ecosystems Earth Observation, Natural Resources and the Environment, CSIR, Pretoria 0001, South Africa
Department of Geography, Geomatics and Meteorology, University of Pretoria, Pretoria 0028, South Africa
Remote Sensing Research Unit, Meraka Institute, CSIR, Pretoria 0001, South Africa
Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0001, South Africa
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
Author to whom correspondence should be addressed.
Academic Editors: Randolph H. Wynne and Prasad S. Thenkabail
Received: 28 June 2016 / Accepted: 3 August 2016 / Published: 17 August 2016
Full-Text   |   PDF [3481 KB, uploaded 17 August 2016]   |  


Savanna ecosystems and their woody vegetation provide valuable resources and ecosystem services. Locally calibrated and cost effective estimates of these resources are required in order to satisfy commitments to monitor and manage change within them. Baseline maps of woody resources are important for analyzing change over time. Freely available, and highly repetitive, C-band data has the potential to be a viable alternative to high-resolution commercial SAR imagery (e.g., RADARSAT-2, ALOS2) in generating large-scale woody resources maps. Using airborne LiDAR as calibration, we investigated the relationships between hyper-temporal C-band ASAR data and woody structural parameters, namely total canopy cover (TCC) and total canopy volume (TCV), in a deciduous savanna environment. Results showed that: the temporal filter reduced image variance; the random forest model out-performed the linear model; while the TCV metric consistently showed marginally higher accuracies than the TCC metric. Combinations of between 6 and 10 images could produce results comparable to high resolution commercial (C- & L-band) SAR imagery. The approach showed promise for producing a regional scale, locally calibrated, baseline maps for the management of deciduous savanna resources, and lay a foundation for monitoring using time series of data from newer C-band SAR sensors (e.g., Sentinel1). View Full-Text
Keywords: SAR; ASAR; hyper-temporal; C-band; canopy cover; canopy volume; savanna SAR; ASAR; hyper-temporal; C-band; canopy cover; canopy volume; savanna

Graphical abstract

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).

Share & Cite This Article

MDPI and ACS Style

Main, R.; Mathieu, R.; Kleynhans, W.; Wessels, K.; Naidoo, L.; Asner, G.P. Hyper-Temporal C-Band SAR for Baseline Woody Structural Assessments in Deciduous Savannas. Remote Sens. 2016, 8, 661.

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



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