Bingfang Wu

A Policy-Driven Large Scale Ecological Restoration: Quantifying Ecosystem Services Changes in the Loess Plateau of China

As one of the key tools for regulating human-ecosystem relations, environmental conservation policies can promote ecological rehabilitation across a variety of spatiotemporal scales. However, quantifying the ecological effects of such policies at the regional level is difficult. A case study was conducted at the regional level in the ecologically vulnerable region of the Loess Plateau, China, through the use of several methods including the Universal Soil Loss Equation (USLE), hydrological modeling and multivariate analysis. An assessment of the changes over the period of 2000-2008 in four key ecosystem services was undertaken to determine the effects of the Chinese governments ecological rehabilitation initiatives implemented in 1999. These ecosystem services included water regulation, soil conservation, carbon sequestration and grain production. Significant conversions of farmland to woodland and grassland were found to have resulted in enhanced soil conservation and carbon sequestration, but decreased regional water yield under a warming and drying climate trend. The total grain production increased in spite of a significant decline in farmland acreage. These trends have been attributed to the strong socioeconomic incentives embedded in the ecological rehabilitation policy. Although some positive policy results have been achieved over the last decade, large uncertainty remains regarding long-term policy effects on the sustainability of ecological rehabilitation performance and ecosystem service enhancement. To reduce such uncertainty, this study calls for an adaptive management approach to regional ecological rehabilitation policy to be adopted, with a focus on the dynamic interactions between people and their environments in a changing world.

Three Gorges Project: Efforts and challenges for the environment

The Three Gorges Project has been subject to intense debates regarding its benefits and costs. The environmental impacts of this huge project have been an important focus of these debates since the project planning stage. After the operation of the Three Gorges Dam at full capacity at the end of 2008, new environmental and ecological issues are emerging. This paper gives a brief description of the Three Gorges Project and its environmental impact assessment process, as well as major efforts to control environmental problems brought about by the project. From the long and complicated evaluation process, it is clear that there are large uncertainties and competing opinions regarding the benefits and costs, especially the ecological and environmental ones, of the project even after great research effort. Emphasis here is given to the environmental challenges including: (1) water quality control; (2) water and sediment regulation; (3) biodiversity conservation in the riparian and aquatic ecosystems; (4) environmentally friendly dam operation and regional sustainable development. Opportunities often grow out of the challenges. The Three Gorges Project provides opportunities for grand-scale experiments on the environmental, ecological, and socio-economic impacts of large dams. Local, national, and international concerted efforts and concrete actions should be directed to the mitigation and control of the negative impacts as well as securing the positive contributions of the project across scales.

How ecological restoration alters ecosystem services: an analysis of carbon sequestration in China's Loess Plateau

Restoring disturbed and over-exploited ecosystems is important to mitigate human pressures on natural ecosystems. China has launched an ambitious national ecosystem restoration program called Grain to Green Program (GTGP) over the last decade. By using remote sensing techniques and ecosystem modelling, we quantitatively evaluated the changes in ecosystem carbon sequestration since Chinas GTGP program during period of 2000–2008. It was found the NPP and NEP in this region had steadily increased after the initiative of the GTGP program, and a total of 96.1 Tg of additional carbon had been sequestered during that period. Changes in soil carbon storage were lagged behind and thus insignificant over the period, but was expected to follow in the coming decades. As a result, the Loess Plateau ecosystem had shifted from a net carbon source in 2000 to a net carbon sink in 2008. The carbon sequestration efficiency was constrained by precipitation, and appropriate choices of restoration types (trees, shrubs, and grasses) in accordance to local climate are critical for achieving the best benefit/cost efficiency.

Water body mapping method with HJ-1A/B satellite imagery

Abstract This paper proposes an integrated water body mapping method with HJ-1A/B satellite imagery, the CCD (charge coupled device) data of the Chinese environmental satellites that were launched on September 6th, 2008. It combines the difference between NDVI and NDWI (NDVI–NDWI) with SLOPE and near-infrared (NIR) band. The NDVI–NDWI index is used to enhance the contrast between water bodies and the surrounding surface features; the topographic SLOPE is used to eliminate the mountain shadow; and the NIR band is used to reduce the effects of artificial construction land. The objectives are evaluating the potential of the HJ-1A/B imagery on water body monitoring, and proposing ideally mapping method. The test study results indicated that the NDVI–NDWI index is superior to the single index of NDVI and NDWI to enhance the contrast between water bodies and the rest of the features. On the basis of the accurately mapped water bodies in the HJ-1A/B CCD images of the study area, we conclude that the HJ-1A/B multi-spectral satellite images is an ideal data source for high spatial and temporal resolution water bodies monitoring. And the integrated water body mapping method is suitable for the applications of HJ-1A/B multi-spectral satellite images in this field.

Recent ecological transitions in China: greening, browning, and influential factors

Ecological conservation and restoration are necessary to mitigate environmental degradation problems. China has taken great efforts in such actions. To understand the ecological transition during 2000–2010 in China, this study analysed trends in vegetation change using remote sensing and linear regression. Climate and socioeconomic factors were included to screen the driving forces for vegetation change using correlation or comparative analyses. Our results indicated that China experienced both vegetation greening (restoration) and browning (degradation) with great spatial heterogeneity. Socioeconomic factors, such as human populations and economic production, were the most significant factors for vegetation change. Nature reserves have contributed slightly to the deceleration of vegetation browning and the promotion of greening; however, a large-scale conservation approach beyond nature reserves was more effective. The effectiveness of the Three-North Shelter Forest Program lay between the two above approaches. The findings of this study highlighted that vegetation trend detection is a practical approach for large-scale ecological transition assessments, which can inform decision-making that promotes vegetation greening via proper socioeconomic development and ecosystem management.

Remote sensing-based global crop monitoring: experiences with China's CropWatch system

Monitoring the production of main agricultural crops is important to predict and prepare for disruptions in food supply and fluctuations in global crop market prices. Chinas global crop-monitoring system (CropWatch) uses remote sensing data combined with selected field data to determine key crop production indicators: crop acreage, yield and production, crop condition, cropping intensity, crop-planting proportion, total food availability, and the status and severity of droughts. Results are combined to analyze the balance between supply and demand for various food crops and if needed provide early warning about possible food shortages. CropWatch data processing is highly automated and the resulting products provide new kinds of inputs for food security assessments. This paper presents a comprehensive overview of CropWatch as a remote sensing-based system, describing its structure, components, and monitoring approaches. The paper also presents examples of monitoring results and discusses the strengths and limitations of the CropWatch approach, as well as a comparison with other global crop-monitoring systems.

Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation

Abstract While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties, the temporal resolution of the data is rather low, which can be easily made worse by cloud contamination. In contrast, although Moderate Resolution Imaging Spectroradiometer (MODIS) can only achieve a spatial resolution of 250 m in its normalised difference vegetation index (NDVI) product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution and high temporal resolution of different data sources, a new method (Spatial and Temporal Adaptive Vegetation index Fusion Model [STAVFM]) for blending NDVI of different spatial and temporal resolutions to produce high spatial–temporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). STAVFM defines a time window according to the temporal variation of crops, takes crop phenophase into consideration and improves the temporal weighting algorithm. The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of HJ-1 CCD NDVI to generate an NDVI dataset with both high spatial and high temporal resolution. An application of the generated NDVI dataset in crop biomass estimation was provided. An average absolute error of 17.2% was achieved. The estimated winter wheat biomass correlated well with observed biomass (R 2 of 0.876). We conclude that the new dataset will improve the application of crop biomass estimation by describing the crop biomass accumulation in detail. There is potential to apply the approach in many other studies, including crop production estimation, crop growth monitoring and agricultural ecosystem carbon cycle research, which will contribute to the implementation of Digital Earth by describing land surface processes in detail.

Estimation and Validation of Land Surface Evaporation Using Remote Sensing and Meteorological Data in North China

There is a growing interest in quantifying regional scale actual evapotranspiration (ET) for water resource management. Using moderate-resolution Imaging spectroradiometer (MODIS) data, in combination with meteorological records, an integrated approach is proposed to estimate daily ET over 1-km grid covering North China. The Surface Energy Balance System (SEBS) is adapted to partition the sensible heat from latent heat. A gap-filling method for ET estimation during cloudy intervals is accomplished by a combination of SEBS outputs and Penman-Monteith equation. The proposed scheme, named ETWatch, is calibrated and evaluated using measurements from four flux sites in the semi-humid regions with different soil types, land cover, and climate conditions in North China. The gap-filling method reproduces observed fluxes with satisfied correlation, yielding about a 22% MAPD in Yucheng agriculture site. The improved method could be used to study the impact of different agricultural water consuming patterns in North China.

Crop classification using HJ satellite multispectral data in the North China Plain

Abstract The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multitemporal multispectral charge-coupled device (CCD) data on board HJ-1-A and HJ-1-B for crop classification in the North China Plain. Support vector machine classifier is selected for the classification using different combinations of multitemporal HJ multispectral data. The results indicate that multitemporal HJ CCD data could effectively identify wheat fields with an overall classification accuracy of 91.7%. Considering only single temporal data, 88.2% is the best classification accuracy achieved using the data acquired at the flowering time of wheat. The performance of the combination of two temporal data acquired at the jointing and flowering times of wheat is almost as well as using all three temporal data, indicating that two appropriate temporal data are enough for wheat classification, and much more data have little effect on improving the classification accuracy. Moreover, two temporal data acquired over a larger time interval achieves better results than that over a smaller interval. However, the field borders and smaller cotton fields cannot be identified effectively by HJ multispectral data, and misclassification phenomenon exists because of the relatively coarse spatial resolution.

Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity

ABSTRACT Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.