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, 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.

[1]  R. Robel.  Water Depth and Turbidity in Relation to Growth of Sago Pondweed , 1961 .

[2]  L. M. Cowardin,et al.  Remote sensing for identification and classification of wetland vegetation , 1974 .

[3]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .

[4]  R. Kettig,et al.  Classification of Multispectral Image Data by Extraction and Classification of Homogeneous Objects , 1976, IEEE Transactions on Geoscience Electronics.

[5]  Michael G. Anderson,et al.  Distribution and Production of Sago Pondweed (Potamogeton Pectinatus L.) on a Northern Prairie Marsh , 1978 .

[6]  R. Kiefer,et al.  Wetland mapping from digitized aerial photography. [Sheboygen Marsh, Sheboygen County, Wisconsin , 1981 .

[7]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[8]  M. Barson,et al.  Remote sensing of Australian wetlands: An evaluation of Landsat TM data for inventory and classification , 1993 .

[9]  R. Bowman,et al.  TEMPORAL PATTERNS IN DIET OF NESTLING WHITE-CROWNED PIGEONS: IMPLICATIONS FOR CONSERVATION OF FRUGIVOROUS COLUMBIDS , 1994 .

[10]  S. Sader,et al.  Accuracy of landsat-TM and GIS rule-based methods for forest wetland classification in Maine , 1995 .

[11]  John Grimson Lyon,et al.  Wetland and Environmental Applications of GIS , 1995 .

[12]  Debbie Whitall,et al.  WETLANDS , 1995, Restoration & Management Notes.

[13]  Geoffrey J. Hay,et al.  An object-specific image-texture analysis of H-resolution forest imagery☆ , 1996 .

[14]  R. O'Neill,et al.  The value of the world's ecosystem services and natural capital , 1997, Nature.

[15]  J. P. Ball,et al.  AVIAN HABITAT SELECTION AND PRAIRIE WETLAND DYNAMICS: A 10‐YEAR EXPERIMENT , 1997 .

[16]  R. O'Neill,et al.  The value of the world's ecosystem services and natural capital , 1997, Nature.

[17]  Stephen V. Stehman,et al.  Selecting and interpreting measures of thematic classification accuracy , 1997 .

[18]  Douglas H. Johnson,et al.  Mallard duckling growth and survival in relation to aquatic invertebrates , 1998 .

[19]  B. Moss,et al.  Ecology of fresh waters : man and medium, past to future , 1998 .

[20]  O. Fromm,et al.  Ecological Structure and Functions of Biodiversity as Elements of Its Total Economic Value , 2000 .

[21]  G. Hill,et al.  Vegetation mapping of a tropical freshwater swamp in the Northern Territory, Australia: A comparison of aerial photography, Landsat TM and SPOT satellite imagery , 2001 .

[22]  E. Donk,et al.  Lakes in the Netherlands, their origin, eutrophication and restoration: state-of-the-art review , 2002 .

[23]  Nathan J. Heinert,et al.  Extending satellite remote sensing to local scales: land and water resource monitoring using high-resolution imagery , 2003 .

[24]  B. Moss,et al.  The structuring role of free-floating versus submerged plants in a subtropical shallow lake , 2003, Aquatic Ecology.

[25]  Bofu Yu,et al.  Comparing rainfall interpolation techniques for small subtropical urban catchments , 2005 .

[26]  Gerald J. Niemi,et al.  Mapping submergent aquatic vegetation in the US Great Lakes using Quickbird satellite data , 2005 .

[27]  M. Hung,et al.  Mapping and visualizing the Great Salt Lake landscape dynamics using multi‐temporal satellite images, 1972–1996 , 2005 .

[28]  Carmen Castañeda del Álamo,et al.  Landsat monitoring of playa-lakes in the Spanish Monegros desert , 2005 .

[29]  S. Silvestri,et al.  Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing , 2006 .

[30]  Peijun Li,et al.  Multispectral image segmentation by a multichannel watershed‐based approach , 2007 .

[31]  C. Bambaradeniya,et al.  Spatial distribution of aquatic birds in Anavilundawa Ramsar wetland sanctuary in Sri Lanka , 2009, Biological Invasions.

[32]  James J. Daniell,et al.  Development of a bathymetric grid for the Gulf of Papua and adjacent areas: A note describing its development , 2008 .

[33]  I. V. Ramana,et al.  Auto‐extraction technique‐based digital classification of saltpans and aquaculture plots using satellite data , 2008 .

[34]  Molly Reif,et al.  Satellite remote sensing of isolated wetlands using object-oriented classification of Landsat-7 data , 2009, Wetlands.

[35]  A. G. Valk,et al.  The restoration of sedge meadows: seed viability, seed germination requirements, and seedling growth ofCarex species , 1999, Wetlands.

[36]  Charlotte MacAlister,et al.  Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data. , 2009, Journal of environmental management.

[37]  Arnold G. van der Valk,et al.  The potential role of ducks in wetland seed dispersal , 2002, Wetlands.

[38]  M. Zakaria,et al.  Density and diversity of water birds and terrestrial birds at Paya Indah Wetland Reserve, Selangor Peninsular Malaysia , 2010 .

[39]  C. Brönmark,et al.  Waterfowl, macrophytes, and the clear water state of shallow lakes , 2010, Hydrobiologia.

[40]  L. Wainger,et al.  Realizing the Potential of Ecosystem Services: A Framework for Relating Ecological Changes to Economic Benefits , 2011, Environmental management.

[41]  Mohd Hasmadi Ismail,et al.  Remote sensing for mapping RAMSAR heritage site at Sungai Pulai Mangrove Forest Reserve, Johor, Malaysia. , 2011 .

[42]  N. Pettorelli,et al.  The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology , 2011 .

[43]  Hongxing Liu,et al.  Multi-temporal Sub-pixel Landsat ETM+ Classification of Isolated Wetlands in Cuyahoga County, Ohio, USA , 2012, Wetlands (Wilmington, N.C.).

[44]  J. Rossjohn,et al.  Recognition of the nonclassical MHC class I molecule H2-M3 by the receptor Ly49A regulates the licensing and activation of NK cells , 2012, Nature Immunology.

[45]  T. Keitt,et al.  Enhanced Migratory Waterfowl Distribution Modeling by Inclusion of Depth to Water Table Data , 2012, PloS one.

[46]  Hui Lin,et al.  Feature extraction for high-resolution imagery based on human visual perception , 2013 .

[47]  Naruemon Tantipisanuh,et al.  REPRESENTATION OF THREATENED VERTEBRATES BY A PROTECTED AREA SYSTEM IN SOUTHEAST ASIA: THE IMPORTANCE OF NON-FOREST HABITATS , 2013 .