Zongming Wang

Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China

Abstract On the basis of AVHRR GIMMS NDVI and MODIS NDVI, we constructed monthly NDVI sequences covering Northeast China from 1982 to 2009 using a per-pixel unary linear regression model. The expanded NDVI passed the consistency check and were well used for analysis. The monthly NDVI trends were highly correlated with climatic changes. Spatially averaged NDVI in summer exhibited a downward trend with increased temperature and significantly decreased precipitation in the 28 years. NDVI trends were spatially heterogeneous, corresponding with the regional climatic features of different seasons. NDVI for the 95 meteorological stations exhibited significant correlations with monthly mean temperature and monthly precipitation during the study period. The NDVI–temperature correlation was stronger than NDVI–precipitation correlation in most stations and for all vegetation types. Different vegetation types showed various spatial responses to climatic changes.

IDENTIFYING WETLAND CHANGE IN CHINA'S SANJIANG PLAIN USING REMOTE SENSING

Maximum likelihood supervised classification and post-classification change detection techniques were applied to Landsat MSS/TM images acquired in 1976, 1986, 1995, 2000, and 2005 to map land cover changes in the Small Sanjiang Plain in northeast China. A hotspots study identified land use changes in two National Nature Reserves. These were the Honghe National Nature Reserve (HNNR) and the Sanjiang National Nature Reserve (SNNR). Landscape metrics were used in both reserves to identify marsh landscape pattern dynamics. The results showed that the Small Sanjiang plain had been subject to much change. This resulted from direct and indirect impacts of human activities. Direct impacts, resulting in marsh loss, were associated with widespread reclamation for agriculture. Indirect impacts (mainly in HNNR) resulted from alterations to the marsh hydrology and this degraded the marsh ecosystem. Marsh landscape patterns changed significantly due to direct impacts in SNNR between 1976 and 1986 and again between 2000 and 2005, and, in HNNR between 1976 and 1986. Indirect impacts in HNNR after 1986 appeared to cause little change. It was concluded that effective wetland protection measures are needed, informed by the change analysis.

Wetlands shrinkage, fragmentation and their links to agriculture in the Muleng-Xingkai Plain, China.

In the past five decades, the wetlands in the Muleng-Xingkai Plain, Northeast China, have experienced rapid shrinkage and fragmentation. In this study, wetlands cover change and agricultural cultivation were investigated through a time series of thematic maps from 1954, and Landsat satellite images representing the last five decades (1976, 1986, 1995, 2000, and 2005). Wetlands shrinkage and fragmentation were studied based on landscape metrics and the land use changes transition matrix. Furthermore, the driving forces were explored according to socioeconomic development and major natural environmental factors. The results indicate a significant decrease in the wetlands area in the past five decades, with an average annual decrease rate of 9004 ha/yr. Of the 625,268 ha of native wetlands in 1954, approximately 64% has been converted to other land use types by 2005, of which conversion to cropland accounts for the largest share (83%). The number of patches decreased from 1272 (1954) to 197 (1986) and subsequently increased to 326 (2005). The mean patch size changed from 480 ha (1954) to 1521 ha (1976), and then steadily decreased to 574 ha (2005). The largest patch index (total core area index) indicates wetlands shrinkage with decreased values from 31.73 (177,935 ha) to 3.45 (39,421 ha) respectively. Climatic changes occurred over the study period, providing a potentially favorable environment for agricultural development. At the same time population, groundwater harvesting, and fertilizer application increased significantly, resulting in wetlands degradation. According to the results, the shrinkage and fragmentation of wetlands could be explained by socioeconomic development and secondarily aided by changing climatic conditions.

Quantifying changes in multiple ecosystem services during 1992–2012 in the Sanjiang Plain of China

Rapid and periodic assessment of the impact of land cover changes on ecosystem services at regional levels is essential to understanding services and sustainability of ecosystems. This study focused on quantifying and assessing changes of multiple ecosystem services in the Sanjiang Plain of China as a result of land cover changes over the period of 1992-2012. This region is important for its large area of natural wetlands and intensive agriculture. The ecosystem services that were assessed for this region included its regulating services (water yield and ecosystem carbon stocks), supporting services (suitable waterbird habitats), and provisioning services (food production), and the approach to the assessment was composed of the surface energy balance algorithms for land (SEBAL), soil survey re-sampling method and an empirical waterbird habitat suitability model. This large scale and integrated investigation represents the first systematic evaluation on the status of ecosystem carbon stocks in the Sanjiang Plain in addition to the development of an effective model for analysis of waterbird habitat suitability with the use of both remote sensing and geographic information systems (GIS). More importantly, the result from this study has confirmed trade-offs between ecosystem services and negative consequences to environment in this region. The trade-offs were typically manifested by increased water yield and significantly grown food production, which is in contrast with significant losses in ecosystem carbon stocks (-14%) and suitable waterbird habitats (-23%) mainly due to the conversion of land cover from wetland to farmland. This finding implies that land use planning and policy making for this economically important region should take ecosystem service losses into account in order to preserve its natural ecosystems in the best interest of society.

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.

Water quality monitoring using Landsat Themate Mapper data with empirical algorithms in Chagan Lake, China

Lake Chagan represents a complex situation of major optical constituents and emergent spectral signals for remote sensing analysis of water quality in the Songnen Plain. As such it provides a good test of the combined radiometric correction methods developed for optical remote sensing data to monitor water quality. Landsat thematic mapper (TM) data and in situ water samples collected concurrently with satellite overpass were used for the analysis, in which four important water quality parameters are considered: chlorophyll-a, turbidity, total dissolved organic matter, and total phosphorus in surface water. Both empirical regressions and neural networks were established to analyze the relationship between the concentrations of these four water parameters and the satellite radiance signals. It is found that the neural network model performed at better accuracy than empirical regressions with TM visible and near-infrared bands as spectral variables. The relative root mean square error (RMSE) for the neural network was < 10%, while the RMSE for the regressions was less than 25% in general. Future work is needed on establishing the dynamic characteristic of Chagan Lake water quality with TM or other optical remote sensing data. The algorithms developed in this study need to be further tested and refined with multidate imagery data

China's Wetlands: conservation plans and policy impacts.

Since the Ramsar Convention on Wetlands in 1971, wetland conservation (maintenance and sustainable use) and restoration (recovery of degraded natural wetlands) have been high priorities for many countries. China has the world’s fourth largest wetland area, which exceeds the whole territory of Great Britain. While the Chinese government has increasingly recognized the importance of wetland protection, particularly after joining the Ramsar Convention in 1992, natural wetlands in China have suffered great loss and degradation. To address this problem, China has implemented the National Wetland Conservation Program (NWCP)—one of the largest of its kind in the world—with ambitious goals, massive investments, and potentially enormous impacts. Furthermore, NWCP has global implications because it aims to rehabilitate habitats for water birds of international importance, enhance carbon sequestration, conserve soil and water, and protect important headwaters of international rivers and lakes.

Spatial variability of soil organic carbon under maize monoculture in the Song-Nen Plain, Northeast China.

Abstract Soil organic carbon (SOC) and its relationship with landscape attributes are important for evaluating current regional, continental, and global carbon stores. Data of SOC in surface soils (0–20 cm) of four main soils, Cambisol, Arenosol, Phaeozem, and Chernozem, were collected at 451 locations in Nongan County under maize monoculture in the Song-Nen Plain, Northeast China. The spatial characteristics of soil organic carbon were studied, using geographic information systems (GIS) and geostatistics. Effects of other soil physical and chemical properties, elevation, slope, and soil type on SOC were explored. SOC concentrations followed a normal distribution, with an arithmetic mean of 14.91 g kg −1 . The experimental variogram of SOC was fitted with a spherical model. There were significant correlations between soil organic carbon and bulk density ( r = −0.374**), pH ( r = 0.549**), total nitrogen ( r = 0.781**), extractable phosphorus ( r = −0.109*), exchangeable potassium ( r = 0.565**), and cation exchange capacity ( r = 0.313**). Generally, lower SOC concentrations were significantly associated with high elevation ( r = −0.429**). Soil organic carbon was significantly negatively correlated with slope gradient ( r = −0.195**). Samples of the Cambisol statistically had the highest SOC concentrations, and samples of the Arenosol had the lowest SOC value.

Landsat-Based Estimation of Mangrove Forest Loss and Restoration in Guangxi Province, China, Influenced by Human and Natural Factors

Mangrove forest dynamics are undergoing constant changes because of both natural and anthropogenic factors. However, the rates and causes of loss and restoration remain largely unknown. This study aims to respond to this concern by analyzing the dynamics of mangrove forests and surrounding land covers in Guangxi Province, China. We analyzed Landsat images on a decadal scale between 1973 and 2010 using an object-oriented classification method. Temporal analysis results indicated that the areal extent of mangrove forests showed the following changes: a sharp decrease from 5305 ha in 1973 to 2306 ha in 1981; a remarkable increase from 2306 ha in 1981 to 5937 ha in 2000; and a slight degradation from 5937 ha in 2000 to 5759 ha in 2010. Reclamation and natural factors resulted in the loss of mangrove forests. By comparison, protection and reforestation efforts contributed to mangrove forest restoration. During the past 40 years, mangrove forests in Guangxi were fragmented. In contrast to the movement of other mangrove forests in the world, mangroves in the coasts of Guangxi were moved seaward because the rates of change in relative sea level were exceeded by the rates of change in the elevation of sedimentation in mangrove mudflats. Simultaneously, man-made land cover prevented landward migration. These results provide valuable information for better understanding mangrove forest dynamics in developing countries. These results can also be used as guidelines in the creation and implementation of reasonable mangrove forest management policies.

Using CropSyst to Simulate Spring Wheat Growth in Black Soil Zone of Northeast China

ABSTRACT Available water and fertilizer have been the main limiting factors for yields of spring wheat, which occupies a large area of the black soil zone in northeast China; thus, the need to set up appropriate models for scenario analysis of cropping system models has been increasing. The capability of CropSyst, a cropping system simulation model, to simulate spring wheat growth of a widely grown spring cultivar, ‘Longmai 19’, in the black soil zone in northeast China under different water and nitrogen regimes was evaluated. Field data collected from a rotation experiment of three growing seasons (1992–1994) were used to calibrate and validate the model. The model was run for 3 years by providing initial conditions at the beginning of the rotation without reinitializing the model in later years in the rotation sequence. Crop input parameters were set based on measured data or taken from CropSyst manual. A few cultivar-specific parameters were adjusted within a reasonable range of fluctuation. The results demonstrated the robustness of CropSyst for simulating evapotranspiration, aboveground biomass, and grain yield of ‘Longmai 19’ spring wheat with the root mean square errors being 7%, 13% and 13% of the observed means for evapotranspiration (ET), grain yield and aboveground biomass, respectively. Although CropSyst was able to simulate spring production reasonably well, further evaluation and improvement of the model with a more detailed field database was desirable for agricultural systems in northeast China.