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Agricultural activities, especially reclamation, are considered major threats to the wetland ecosystems in Sanjiang Plain, the largest concentrated area of the freshwater wetlands in China. In the past decades, the area of the cultivated land and its grain production have been increased at the cost of wetlands shrinkage. The large-scale land reclamation severely affected the ecosystems in this region. However, such effects at the regional scale are seldom evaluated quantitatively. We used three datasets of LANDSAT MSS and/or TM imagery to estimate the area changes and the transition of land use types from 1980 to 2000. We also valued changes in ecosystem services delivered by each land category using value coefficients published by Costanza et al. Sensitivity analysis suggested that these estimates were relatively robust. Finally, the contribution of various ecosystem functions was ranked to the overall value of the ecosystem services in this study. According to our estimates, the total annual ecosystem service values in Sanjiang Plain have declined by about 40% between 1980 and 2000 (156284-182572.18 million US dollars in total over 20 years). This substantial decline is largely attributed to the 53.4% loss of wetlands. For individual ecosystem functions, waste treatment, water supply and disturbance regulation account for more than 60% to the total ecological values. During those two decades, the contribution of disturbance regulation, cultural and recreation decreased, while the contribution of water regulation, nutrient cycling, food production, raw materials and climate regulation increased during the same period. We also put forward a few proposals concerning the future land use policy formulation and sustainable ecosystems. They are adjusting the 'food first' agricultural policy, establishing more nature reserves for wetlands, creating systems for the rational use of water, harnessing the degraded cultivated land and encouraging eco-tourism.

Marshes in the Sanjiang Plain of Northeast China have undergone dramatic loss and fragmentation over the past decades. This paper analyzed the loss and fragmentation of these marshes for the period 1954-2005 using historical land-cover information and remote sensing data. In 1954, marshes covered one-third of the total land area but have decreased by 77% over the 50 year period. Results showed two distinct periods of impact : 1954-1986 and 1987-2005. In the earlier period, the number of marsh patches fell from 4,799 to 1,476 (−69.2%), and total marsh area decreased from 35,270 km 2 to 13,893 km 2 (−60.6%). In the latter period, the number of marshes declined from 1,476 to 1,037 (−29.7%), and the total area decreased from 13,893 km 2 to 8,100 km 2 (−41.7%). The rapid decrease in the number and area of marshes during 1954-1986 was largely attributed to extensive agricultural reclamation under the "Food First" agricultural policy. This resulted in many negative ecological consequences. In contrast, the slower reduction of marsh areas during 1987-2005 was due to the implementation of governmental policies for protecting and restoring marshes. Increasing air temperature would otherwise have enhanced crop yields and stimulated the conversion of marsh into crops.

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Due to human impact under climatic variations, western part of Northeast China has suffered substantial land degradation during past decades. This paper presents an integrated study of expansion process of salinized wasteland in Da'an County, a typical salt-affected area in Northeast China, by using Geographic Information Systems (GIS) and remote sensing. The study explores the temporal and spatial characteristics of salinized wasteland expansion from 1954 to 2004, and land use/cover changes during this period. During the past 50 years, the salinized wasteland in study area have increased by 135,995 ha, and in 2004 covers 32.31% of the total area, in the meantime grassland has decreased by 104,697 ha and in 2004 covers only 13.15% of the study area. Grasslands, croplands and swamplands were found the three main land use types converted into salinized wasteland. Land use/cover changes shows that between 1954 and 2004, 48.6% of grasslands, 42.5% of swamplands, and 14.1% of croplands were transformed into salinized wasteland, respectively. Lastly, the major factors influencing salinized wasteland expansion and land use/cover changes were also explored. In general, climatic factors supplied a potential environment for soil salinization. Human-related factors, such as policy, population, overgrazing, and intensified and unreasonable utilization of land and water resources are the main causes of salinized wasteland expansion.

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 (R (2) = 0.94, 0.91) than their performance on Chl-a concentration (R (2) = 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 (R (2) = 0.91, 0.82) and TSM (R (2) = 0.98, 0.94) concentration estimation through in situ collected spectra; the same trend followed for IRS-P6 imagery data (R (2) = 0.75 and 0.90 for Chl-a; R (2) = 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.

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