Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing
Tropical wetlands support high biodiversity and ecological services, but in most areas they suffer from a paucity of baseline data to support management. We demonstrate how modern technology can be used to develop ecological baseline data including, landuse/landcover, water depth, water quality, lak...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/35135/ http://psasir.upm.edu.my/id/eprint/35135/1/Quantifying%20tropical%20wetlands%20using%20field%20surveys.pdf |
| _version_ | 1848847970112372736 |
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| author | Salari, Abdollah Hussin, Mohamed Zakaria Nielsen, Charlene C. Boyce, Mark S. |
| author_facet | Salari, Abdollah Hussin, Mohamed Zakaria Nielsen, Charlene C. Boyce, Mark S. |
| author_sort | Salari, Abdollah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Tropical wetlands support high biodiversity and ecological services, but in most areas they suffer from a paucity of baseline data to support management. We demonstrate how modern technology can be used to develop ecological baseline data including, landuse/landcover, water depth, water quality, lake-level fluctuation, and normalized difference vegetation index (NDVI). For the first time we quantified and mapped these metrics for the Paya Indah Wetlands, Malaysia using the new high-spatial-resolution World View 2 imagery. Landuse/landcover classifications were validated by field visits and visual interpretation of the imagery. NDVI was extracted based on red and near infra-red 2 bands. Topo to Raster method was used for interpolation of water depths. Annual mean of a water-quality index and annual water-level fluctuation of lakes were interpolated across lakes using the inverse-distance weighting method. Qualitative and quantitative accuracy assessment of classification (75 % overall accuracy, user’s accuracies ranged from 60 % to 90 % and producer’s accuracy ranged from 60 % to 97 %) was promising and clearly illustrated that World View 2 imagery can yield fast and reasonably precise identification of ecosystem characteristics for ecological baselines. |
| first_indexed | 2025-11-15T09:27:03Z |
| format | Article |
| id | upm-35135 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:27:03Z |
| publishDate | 2014 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-351352017-10-31T07:37:21Z http://psasir.upm.edu.my/id/eprint/35135/ Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing Salari, Abdollah Hussin, Mohamed Zakaria Nielsen, Charlene C. Boyce, Mark S. Tropical wetlands support high biodiversity and ecological services, but in most areas they suffer from a paucity of baseline data to support management. We demonstrate how modern technology can be used to develop ecological baseline data including, landuse/landcover, water depth, water quality, lake-level fluctuation, and normalized difference vegetation index (NDVI). For the first time we quantified and mapped these metrics for the Paya Indah Wetlands, Malaysia using the new high-spatial-resolution World View 2 imagery. Landuse/landcover classifications were validated by field visits and visual interpretation of the imagery. NDVI was extracted based on red and near infra-red 2 bands. Topo to Raster method was used for interpolation of water depths. Annual mean of a water-quality index and annual water-level fluctuation of lakes were interpolated across lakes using the inverse-distance weighting method. Qualitative and quantitative accuracy assessment of classification (75 % overall accuracy, user’s accuracies ranged from 60 % to 90 % and producer’s accuracy ranged from 60 % to 97 %) was promising and clearly illustrated that World View 2 imagery can yield fast and reasonably precise identification of ecosystem characteristics for ecological baselines. Springer 2014-06 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/35135/1/Quantifying%20tropical%20wetlands%20using%20field%20surveys.pdf Salari, Abdollah and Hussin, Mohamed Zakaria and Nielsen, Charlene C. and Boyce, Mark S. (2014) Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing. Wetlands Ecology and Management, 34 (3). pp. 565-574. ISSN 0923-4861; ESSN: 1572-9834 http://link.springer.com/article/10.1007%2Fs13157-014-0524-3 10.1007/s13157-014-0524-3 |
| spellingShingle | Salari, Abdollah Hussin, Mohamed Zakaria Nielsen, Charlene C. Boyce, Mark S. Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title | Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title_full | Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title_fullStr | Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title_full_unstemmed | Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title_short | Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| title_sort | quantifying tropical wetlands using field surveys, spatial statistics and remote sensing |
| url | http://psasir.upm.edu.my/id/eprint/35135/ http://psasir.upm.edu.my/id/eprint/35135/ http://psasir.upm.edu.my/id/eprint/35135/ http://psasir.upm.edu.my/id/eprint/35135/1/Quantifying%20tropical%20wetlands%20using%20field%20surveys.pdf |