| Title |
Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery
|
|---|---|
| Published in |
PLOS ONE, October 2012
|
| DOI | 10.1371/journal.pone.0046616 |
| Pubmed ID | |
| Authors |
Matteo Convertino, Rami S. Mangoubi, Igor Linkov, Nathan C. Lowry, Mukund Desai |
| Abstract |
The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 3 | 25% |
| United States | 2 | 17% |
| United Kingdom | 1 | 8% |
| Unknown | 6 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 83% |
| Scientists | 2 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Israel | 1 | 2% |
| Denmark | 1 | 2% |
| Argentina | 1 | 2% |
| Unknown | 57 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 26% |
| Student > Ph. D. Student | 14 | 23% |
| Student > Master | 12 | 20% |
| Student > Bachelor | 4 | 7% |
| Professor | 3 | 5% |
| Other | 9 | 15% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 18 | 30% |
| Agricultural and Biological Sciences | 12 | 20% |
| Earth and Planetary Sciences | 5 | 8% |
| Social Sciences | 5 | 8% |
| Computer Science | 3 | 5% |
| Other | 10 | 16% |
| Unknown | 8 | 13% |