| Title |
Land cover change of watersheds in Southern Guam from 1973 to 2001
|
|---|---|
| Published in |
Environmental Monitoring and Assessment, November 2010
|
| DOI | 10.1007/s10661-010-1760-5 |
| Pubmed ID | |
| Authors |
Yuming Wen, Shahram Khosrowpanah, Leroy Heitz |
| Abstract |
Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Australia | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 98 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 24% |
| Student > Master | 21 | 21% |
| Researcher | 13 | 13% |
| Student > Doctoral Student | 8 | 8% |
| Lecturer | 7 | 7% |
| Other | 19 | 19% |
| Unknown | 10 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 32 | 31% |
| Agricultural and Biological Sciences | 15 | 15% |
| Engineering | 14 | 14% |
| Earth and Planetary Sciences | 13 | 13% |
| Social Sciences | 6 | 6% |
| Other | 10 | 10% |
| Unknown | 12 | 12% |
Attention Score in Context
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#16,172,769
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Outputs of similar age from Environmental Monitoring and Assessment
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