| Title |
Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery
|
|---|---|
| Published in |
Environmental Monitoring and Assessment, August 2015
|
| DOI | 10.1007/s10661-015-4766-1 |
| Pubmed ID | |
| Authors |
Jing Li, Carl E. Zipper, Patricia F. Donovan, Randolph H. Wynne, Adam J. Oliphant |
| Abstract |
Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 3% |
| United States | 1 | 2% |
| Unknown | 59 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 23% |
| Student > Ph. D. Student | 10 | 16% |
| Researcher | 7 | 11% |
| Student > Doctoral Student | 4 | 6% |
| Student > Bachelor | 2 | 3% |
| Other | 7 | 11% |
| Unknown | 18 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 11 | 18% |
| Agricultural and Biological Sciences | 8 | 13% |
| Engineering | 7 | 11% |
| Earth and Planetary Sciences | 7 | 11% |
| Computer Science | 3 | 5% |
| Other | 3 | 5% |
| Unknown | 23 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 August 2015.
All research outputs
#16,172,769
of 23,854,458 outputs
Outputs from Environmental Monitoring and Assessment
#1,407
of 2,748 outputs
Outputs of similar age
#157,876
of 267,179 outputs
Outputs of similar age from Environmental Monitoring and Assessment
#14
of 40 outputs
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