Yuandong Wang

Retrieval of total suspended matter (TSM) and chlorophyll-a (Chl-a) concentration from remote-sensing data for drinking water resources

The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. Water sampling works were conducted on 15 July 2007 and 13 September 2008 concurrent with the Indian Remote-Sensing Satellite (IRS-P6) overpass of the Shitoukoumen Reservoir. Both empirical regression and back-propagation artificial neural network (ANN) models were established to estimate Chl-a and TSM concentration with both in situ and satellite-received radiances signals. It was found that empirical models performed well on the TSM concentration estimation with better accuracy (R2 = 0.94, 0.91) than their performance on Chl-a concentration (R2 = 0.62, 0.75) with IRS-P6 imagery data, and the models accuracy marginally improved with in situ spectra data. Our results indicated that the ANN model performed better for both Chl-a (R2 = 0.91, 0.82) and TSM (R2 = 0.98, 0.94) concentration estimation through in situ collected spectra; the same trend followed for IRS-P6 imagery data (R2 = 0.75 and 0.90 for Chl-a; R2 = 0.97 and 0.95 for TSM). The relative root mean square errors (RMSEs) from the empirical model for TSM (Chl-a) were less than 15% (respectively 27.2%) with both in situ and IRS-P6 imagery data, while the RMSEs were less than 7.5% (respectively 18.4%) from the ANN model. Future work still needs to be undertaken to derive the dynamic characteristic of Shitoukoumen Reservoir water quality with remotely sensed IRS-P6 or Landsat-TM data. The algorithms developed in this study will also need to be tested and refined with more imagery data acquisitions combined with in situ spectra data.

Spatial-temporal Characteristics of Land Use Intensity of Coastal Zone in China During 2000-2010

Based on remote sensing and GIS techniques, land use maps in 2000, 2005 and 2010 in China’s coastal zone were produced, and structural raster data of land use were further generated to calculate land use intensity comprehensive index (LUICI) for analyzing land use spatial-temporal characteristics at 1 km scale. Results show that: 1) from the perspective of spatial patterns of landforms at a macro scale, there is a significant difference in land use intensity between the north and the south of China’s coastal zone. Hotspots of changes mainly concentrated in metropolitan areas, estuaries and coastal wetlands; 2) elevation is an important factor that controlling land use spatial patterns at local scale. Land use intensity is much higher within areas below the elevation of 400 m and it decreased significantly as the elevation increasing; 3) there is a significant land-ocean gradient for land use intensity, which is low in island and near-shore areas, but high in the regions that 4–30 km far away the coastline because of much intensive human activities; however, in recent decades land use intensity had been promoted significantly in low near-shore area due to extensive sea reclamations; 4) significant differences of land use intensity were also found among provincial administrative units. A rising trend of land use intensity was found in provincial-level administrative units from 2000 to 2010. To sum up, elevation, land-ocean gradient, socio-economic status and policy are all influencing factors to the spatial patterns and temporal variations of land use intensity in China’s coastal zone.

Spectral Absorption Properties of Colored Dissolved Organic Matter (CDOM) and Total Suspended Matter (TSM) of Inland Waters

Spectral absorption properties of total suspended matter (TSM) and colored dissolved organic matter (CDOM) are important for the use of the bio-optical model to estimate water quality parameters. This study aims to investigate the variation in the absorption coefficients of TSM and CDOM of inland waters. A total of 92 water samples were collected from Shitoukoumen Reservoir and Songhua Lake in Northeast China, analyzed for TSM and Chl-a, and measured for the absorption coefficient of TSM, CDOM and total pigments using a laboratory spectrophotometer. The absorption coefficient of TSM has been decomposed for phytoplankton and inorganic sediments. The results show that for Shitoukoumen Reservoir, CDOM has strong absorptions with shallow absorption slopes (i.e., the coefficient S in a(λ)=a(λ0)exp[-S(λ- λ0)]) and large absorption at 355 nm; and for Songhua Lake, CDOM follows similar spectral absorption curves but less variation in the S value. The results also show TSM has the average absorption coefficient 5.7 m-1 at 440 nm and 0.93 m-1 at 675 nm, and their concentration is well correlated to TSM with R2 larger than 0.85 at 440 nm over both Songhu Lake and Shitoukoumen Reservoir. In summer, CDOM was mainly terrigenous and had a high proportion of humic acid derived from the decomposition of phytoplankton and there were no obvious difference of S value. The results indicate that inorganic sediments contributed much more absorption than phytoplankton pigments in Shitoukoumen Reservoir than that in Songhua Lake, and there is strong association of TSM concentration to absorption coefficient at 440 nm.

Retrival of total suspended matter (TSM) using remotely sensed images in Shitoukoumen Reservior, Northeast China

The Shitoukoumen Reservoir is the major drinking water resources for the Changchun metropolitan region. The concentration of total suspended matter (TSM) is major water quality parameter that could be retrieved using remotely sensed data. 225 samples were analyzed during 12 times of field works from April 2006 to September 2008, in which the field work conducted on 17th July 2007 and 13th September 2008 were concurrent with IRS-P6 satellite over pass. Empirical regression models were established to analysis the relationship between TSM and satellite-received radiances. It was found that the regression model performed well on the TSM concentration estimation with higher accuracy (R2=0.94, 0.91) with IRS-P6 visible and near infrared bands as inputs. The high concentration of TSM made it the dominant upwelling signature captured by IRS-P6 satellite data, which may explain why the regression model relatively accurate. The RMSE for the TSM was less than 15%. Future work will need to be undertaken to refine model for Shitoukoumen Reservoir water quality monitoring with remotely sensed images or hyperspectral imaging data is to be launched in the near future.

Ecological risk caused by land use change in the coastal zone: a case study in the Yellow River Delta High-Efficiency Ecological Economic Zone

Chinas coastal zone plays an important role in ecological services production and social-economic development; however, extensive and intensive land resource utilization and land use change have lead to high ecological risk in this area during last decade. Regional ecological risk assessment can provide fundamental knowledge and scientific basis for better understanding of the relationship between regional landscape ecosystem and human activities or climate changes, facilitating the optimization strategy of land use structure and improving the ecological risk prevention capability. In this paper, the Yellow River Delta High-Efficiency Ecological Economic Zone is selected as the study site, which is undergoing a new round of coastal zone exploitation and has endured substantial land use change in the past decade. Land use maps of 2000, 2005 and 2010 were generated based on Landsat images by visual interpretation method, and the ecological risk index was then calculated. The index was 0.3314, 0.3461 and 0.3176 in 2000, 2005 and 2010 respectively, which showed a positive transition of regional ecological risk in 2005.

Analysis on the spectral reflectance response to snow contaminants in northeast China

By simulating atmospheric deposition experiment, this paper analyzed the relationship between the measured spectral reflectance and the concentrations of contaminants in the snow. It is found that the visible spectrum is sensitive to snow contaminants. From 350nm to 850nm, with the increase concentrations of contaminants in snow, snow reflectivity dramatically decreases. We get the conclusion that the most sensitive bands to snow contaminants are 384nm, 450nm and 1495nm.Using the non-linear regression method to analyze the relationship between spectral reflectance and the contaminants. The results showed the reflectivity of snow at visible bands logarithmically decreases with the snow contaminants increasing; the R2 can reach 0.9.To the contrary, the spectral reflectance at nearinfrared increases with the snow contaminants increasing. Therefore, this method can be combined satellite image to forecast the contaminants in the snow at large-scale.

Estimating the Net Ecosystem Carbon Exchange for a Deciduous Broadleaf Forest by Exclusive Use of MODIS Data

Many current models of ecosystem carbon exchange based on remote sensing such as the MODIS17 product are complex and require considerable input variables from ground-based meteorological measurements. They can introduce substantial errors into the carbon exchange estimates because these data are often not available at the same spatial scale as the remote sensing imagery. Here we propose a new net ecosystem carbon exchange (NEE) model solely based on MODIS data. Presumed that NEE can be simulated based only on the enhanced vegetation index (EVI), this model, termed the Temperature and Greenness (TG) model, also includes the land surface temperature (LST) product and land surface water index (LSWI) from MODIS. Site-specific data from the deciduous-dominated Harvard Forest AmeriFlux site were used. We analyzed 6 years (2001-2006) of CO2 flux data, the first four years used for model building and the others as validated set. The research showed that combination of the three parameters in the model could well reflect the correlation between predicted and measured NEE by eddy covariance technique at Harvard forest site. Furthermore, the TG model provided substantially better predictions of seasonal dynamics of NEE. Although it may be possible to improve the precision of various satellite-based production efficiency models through improved parameterization, our study suggests simpler empirical model based entirely on MODIS data could reliably estimate NEE.