Next Article in Journal
Correction: Yin, J., et al. Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach. ISPRS International Journal of Geo-Information 2016, 5, 187
Previous Article in Journal
An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization
Article Menu
Issue 12 (December) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2016, 5(12), 225; doi:10.3390/ijgi5120225

A Biophysical Image Compositing Technique for the Global-Scale Extraction and Mapping of Barren Lands

1
Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
2
Department of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai, Wakaba-ku, Chiba 265-8501, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 17 July 2016 / Revised: 18 September 2016 / Accepted: 24 November 2016 / Published: 30 November 2016
View Full-Text   |   Download PDF [4238 KB, uploaded 30 November 2016]   |  

Abstract

As the barren lands play a key role in the interaction between land cover dynamics and climate system, an efficient methodology for the global-scale extraction and mapping of the barren lands is important. The discriminative potential of the existing soil/bareness indexes was assessed by collecting globally distributed reference data belonging to major land cover types. The existing soil/bareness indexes parameterized at the local scale did not work satisfactorily everywhere at the global level. A new technique called the Biophysical Image Composite (BIC) is proposed in the research by exploiting time-series of the multi-spectral data to capture global-scale barren land attributes effectively. The BIC is a false color composite image made up of Normalized Difference Vegetation Index (NDVI), short wave infrared reflectance, and green reflectance, which were specially selected from the highest vegetation activity period by avoiding signals from the seasonal snowfall. The drastic contrast between the barren lands and vegetation as exhibited by the BIC provides a robust extraction and mapping of the barren lands, and facilitates its visual interpretation. Random Forests based supervised classification approach was applied on the BIC for the mapping of global barren lands. A new global barren land cover map of year 2013 was produced with high accuracy. The comparison of the resulted map with an existing map of the same year showed a substantial discrepancy between two maps due to methodological variation. To cope with this problem, the BIC based mapping methodology, with a special account of the land surface phenological changes, is suggested to standardize the global-scale estimates and mapping of the barren lands. View Full-Text
Keywords: barren lands; Biophysical Image Composite (BIC); MODIS; random forests; visualization; global mapping; 2030 Agenda for Sustainable Development barren lands; Biophysical Image Composite (BIC); MODIS; random forests; visualization; global mapping; 2030 Agenda for Sustainable Development
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 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

Sharma, R.C.; Tateishi, R.; Hara, K. A Biophysical Image Compositing Technique for the Global-Scale Extraction and Mapping of Barren Lands. ISPRS Int. J. Geo-Inf. 2016, 5, 225.

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]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top