Abstract
Given the seasonal dynamics of wetland ecosystem, limited available data, and technological method of wetland investigation, wetland evaluation cannot be accurately accessed. Although the remote sensing technology has been widely employed on wetland investigation and identification, changeable weather conditions especially cloud interference are the main barrier to acquire clear remote sensing image for wetland identification and information extraction. The combination and precision evaluation of remote sensing data with high temporal-spatial resolution ratio from moderate-resolution imaging spectroradiometer (MODIS) and Landsat were conducted using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM): a comprehensively temporal-spatial reflectance model was built; the high-resolution image in the time series and Modified Normalized Difference Water Index were obtained. The main data obstacles in wetland resources monitoring were invalid. The typical wetland areas in Liaoning province of China were evaluated using combination algorithm and Landsat (Thematic Mapper) images. The results show that the MODIS and Landsat data can be combined well with high correlations in different wave ranges. The maximum Normalized Difference Water Index (NDWI) is 0.9678, followed by green wave (0.9630), near-infrared wave (0.9345), and blue wave (0.9018).The wetland seasonal change of Panjin was examined using the data combination method. Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and vegetation coverage index were extracted from combined images of Panjin from June 2016 to August 2016 and analyzed. Results showed that the NDVI was high in partial water area during the studied period indicating high chlorophyll contents.
Highlights
Wetlands play irreplaceable roles in climate regulation, water purification, biodiversity conservation, and natural ecology balancing [1]
Previous studies and this study suggest wetland resources are largely influenced by climate, and especially, the changeable meteorological conditions in Panjin between June and September with cloudy and rainy climate make the corresponding Landsat images unavailable
It is experimentally validated that moderate-resolution imaging spectroradiometer (MODIS) and Landsat images can be well fused and the fused images are highly correlated with the Thematic Mapper (TM) images
Summary
Wetlands play irreplaceable roles in climate regulation, water purification, biodiversity conservation, and natural ecology balancing [1]. Wetlands provide habitats for wild animals and plants, and guarantee climate modulation, pollutant deterioration and decomposition, flood detention, water conservation, soil erosion control, oxygen release from solid carbon, and ecological nutrient cycling [2]. Wetlands offer humans abundant animal and plant resources and necessary water sources, and provide turf and other special sources [3]. Due to natural and artificial interferences, numerous wetlands have been converted to farm lands or urban lands, and such fundamental variation of wetland properties has roused wide attention from researchers [4]. Though RS largely facilitates wetland research, the changeable meteorological conditions make cloud interference one of the major barriers against the acquisition of clear RS images, identification of wetlands, and information extraction.
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