Zutao Ouyang

Using hyperspectral vegetation indices as a proxy to monitor soil salinity

For monitoring soil salinity, the potential of various hyperspectral vegetation indices were investigated. Furthermore, the most sensitive band combinations to salt-stress were identified and developed into a satisfied and specific salinity index for heterogeneous vegetation.

A comparison of pixel-based and object-oriented approaches to VHR imagery for mapping saltmarsh plants

article i nfo Article history: Object-oriented classification (OOC) has shown many significant advantages over other methods for classification of urban or forest ecosystems. However, it remains unclear if this technology could exhibit these advantages on mapping monospecific plant stands in herbaceous plant dominated ecosystems (e.g. saltmarshes). In this study, we compared the effectiveness of OOC and pixel-based classification (PBC) methods for mapping plants in a saltmarsh ecosystem. QuickBird was selected for very high resolution (VHR) imagery. Eleven models defined by classification types, feature spaces, classifiers, and hierarchical approaches with multi-scale segmentation were built for comparison. The results showed that the QuickBird imagery efficiently discriminated saltmarsh monospecific vegetation stands and that OOC performed better than PBC in terms of accuracy. We also found that the improvement of OOC was primarily due to employing membership functions and a hierarchical approach with multi-scale segmentation. Although texture and shape features have been deemed as two major advantages of OOC, enhanced performance was not observed in this study. The results of this study demonstrated that OOC would be superior to PBC for classifying herbaceous plant species in terms of accuracy. To improve the classification accuracy, greater concern should be given to exploration of the relationships between features of both objects and classes and to combining information from different object scales, while shape and texture features can be a minor consideration due to their intricately high spatial variability.

Vegetation response to extreme climate events on the Mongolian Plateau from 2000 to 2010

Climate change has led to more frequent extreme winters (aka, dzud) and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000?2002 combined summer drought?dzud and 2010 dzud were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000?2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000?2001, 2005 and 2009) were characterized by negative anomalies with peak values between ?1.5 and ?0.5 and were statistically different (P?<?0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (p?<?0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI?<??1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (R2?=?65 and 60, p?<?0.05) than for the IM grassland biome (R2?=?53, p?<?0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and dzud) between the desert and grassland biomes on the Plateau.

Net ecosystem methane and carbon dioxide exchanges in a Lake Erie coastal marsh and a nearby cropland

Net ecosystem carbon dioxide (FCO2) and methane (FCH4) exchanges were measured by using the eddy covariance method to quantify the atmospheric carbon budget at a Typha- and Nymphaea-dominated freshwater marsh (March 2011 to March 2013) and a soybean cropland (May 2011 to May 2012) in northwestern Ohio, USA. Two year average annual FCH4 (49.7 g C-CH4 m−2 yr−1) from the marsh was high and compatible with its net annual CO2 uptake (FCO2: −21.0 g C-CO2 m−2 yr−1). In contrast, FCH4 was small (2.3 g C-CH4 m−2 yr−1) and accounted for a minor portion of the atmospheric carbon budget (FCO2: −151.8 g C-CO2 m−2 yr−1) at the cropland. At the seasonal scale, soil temperature associated with methane (CH4) production provided the dominant regulator of FCH4 at the marsh (R2 = 0.86). At the diurnal scale, plant-modulated gas flow was the major pathway for CH4 outgassing in the growing season at the marsh. Diffusion and ebullition became the major pathways in the nongrowing season and were regulated by friction velocity. Our findings highlight the importance of freshwater marshes for their efficiency in turning over and releasing newly fixed carbon as CH4. Despite marshes accounting for only ~4% of area in the agriculture-dominated landscape, their high FCH4 should be carefully addressed in the regional carbon budget.

Salting our freshwater lakes

Significance In lakes, chloride is a relatively benign ion at low concentrations but begins to have ecological impacts as concentrations rise into the 100s and 1,000s of mg L−1. In this study, we investigate long-term chloride trends in 371 freshwater lakes in North America. We find that in Midwest and Northeast North America, most urban lakes and rural lakes that are surrounded by >1% impervious land cover show increasing chloride trends. Expanding on this finding, thousands of lakes in these regions are at risk of long-term salinization. Keeping lakes “fresh” is critically important for protecting the ecosystem services freshwater lakes provide, such as drinking water, fisheries, recreation, irrigation, and aquatic habitat. The highest densities of lakes on Earth are in north temperate ecosystems, where increasing urbanization and associated chloride runoff can salinize freshwaters and threaten lake water quality and the many ecosystem services lakes provide. However, the extent to which lake salinity may be changing at broad spatial scales remains unknown, leading us to first identify spatial patterns and then investigate the drivers of these patterns. Significant decadal trends in lake salinization were identified using a dataset of long-term chloride concentrations from 371 North American lakes. Landscape and climate metrics calculated for each site demonstrated that impervious land cover was a strong predictor of chloride trends in Northeast and Midwest North American lakes. As little as 1% impervious land cover surrounding a lake increased the likelihood of long-term salinization. Considering that 27% of large lakes in the United States have >1% impervious land cover around their perimeters, the potential for steady and long-term salinization of these aquatic systems is high. This study predicts that many lakes will exceed the aquatic life threshold criterion for chronic chloride exposure (230 mg L−1), stipulated by the US Environmental Protection Agency (EPA), in the next 50 y if current trends continue.

Spectral Discrimination of the Invasive Plant Spartina alterniflora at Multiple Phenological Stages in a Saltmarsh Wetland

Spartina alterniflora has widely invaded the saltmarshes of the Yangtze River Estuary and brought negative effects to the ecosystem. Remote sensing technique has recently been used to monitor its distribution, but the similar morphology and canopy structure among S. alterniflora and its neighbor species make it difficult even with high-resolution images. Nevertheless, these species have divergence on phenological stages throughout the year, which cause distinguishing spectral characteristics among them and provide opportunities for discrimination. The field spectra of the S. alterniflora community as well as its major victims, native Phragmites australis and Scirpus mariqueter, were measured in 2009 and 2010 at multi-phenological stages in the Yangtze River Estuary, aiming to find the most appropriate periods for mapping S. alterniflora. Collected spectral data were analyzed separately for every stage firstly by re-sampling reflectance curves into continued 5-nm-wide hyper-spectral bands and then by re-sampling into broad multi-spectral bands – the same as the band ranges of the TM sensor, as well as calculating commonly used vegetation indices. The results showed that differences among saltmarsh communities’ spectral characteristics were affected by their phenological stages. The germination and early vegetative growth stage and the flowering stage were probably the best timings to identify S. alterniflora. Vegetation indices like NDVI, ANVI, VNVI, and RVI are likely to enhance spectral separability and also make it possible to discriminate S. alterniflora at its withering stage.

Linear spectral mixture analysis of Landsat TM data for monitoring invasive exotic plants in estuarine wetlands

This study assessed the feasibility of spectral mixture analysis (SMA) of Landsat thematic mapper (TM) data for monitoring estuarine vegetation at species level. SMA modelling was evaluated, using χ2 test, by comparing SMA fraction images with a precisely classified QuickBird image that has a higher spatial resolution. To clearly understand the strengths and weaknesses of SMA, eight SMA models with different endmember combinations were assessed. When the TM data dimension for SMA and the endmember number required were balanced, a model with three endmembers representing water and two vegetation types was most accurate, whereas a model with five endmembers approximated the actual surface situation and generated a relatively accurate result. Our results indicate that an SMA model with appropriate endmembers had relatively satisfactory accuracy in monitoring vegetation. However, errors might occur in SMA fraction images, especially in models with an inappropriate endmember combination, and the errors were mainly distributed in areas filled with water or near water. Therefore, short vegetation usually submerged during high tide tended to be poorly predicted by SMA models. These results strongly suggest that tide water has a great influence on SMA modelling, especially for short vegetation.

Nature-based solutions for urban landscapes under post-industrialization and globalization: Barcelona versus Shanghai

ABSTRACT Using Barcelona and Shanghai as case studies, we examined the nature‐based solutions (NBS) in urban settings—specifically within cities experiencing post‐industrialization and globalization. Our specific research questions are: (1) What are the spatiotemporal changes in urban built‐up land and green space in Barcelona and Shanghai? (2) What are the relationships between economic development, exemplified by post‐industrialization, globalization, and urban green space? Urban land use and green space change were evaluated using data derived from a variety of sources, including satellite images, landscape matrix indicators, and a land conversion matrix. The relationships between economic development, globalization, and environmental quality were analyzed through partial least squares structural equation modeling based on secondary statistical data. Both Barcelona and Shanghai have undergone rapid urbanization, with urban expansion in Barcelona beginning in the 1960s–1970s and in Shanghai in the last decade. While Barcelonas urban green space and green space per capita began declining between the 1950s and 1990s, they increased slightly over the past two decades. Shanghai, however, has consistently and significantly improved urban green space and green space per capita over the past six decades, especially since the economic reform in 1978. Economic development has a direct and significant influence on urban green space for both cities and post‐industrialization had served as the main driving force for urban landscape change in Barcelona and Shanghai. Based on secondary statistical and qualitative data from on‐site observations and interviews with local experts, we highlighted the institutions role in NBS planning. Furthermore, aspiration to become a global or globalizing city motivated both cities to use NBS planning as a place‐making tool to attract global investment, which is reflected in various governing policies and regulations. The cities’ effort to achieve a higher status in the global city hierarchy may have contributed to the increase in total green space and urban green per capita. In addition, various institutional shifts, such as land property rights in a market economy vs. a transitional economy, may also have contributed to the differences in efficiency when expanding urban green space in Barcelona and Shanghai. HighlightsUrban green space for Barcelona first declined then slightly increased.Shanghai had a significant improvement in urban green space.Post‐industrialization and planning have affected urban green space.Globalization and institutions contribute to differences in green space dynamics.

Identification of Land-Cover Characteristics Using MODIS Time Series Data: An Application in the Yangtze River Estuary

Land-cover characteristics have been considered in many ecological studies. Methods to identify these characteristics by using remotely sensed time series data have previously been proposed. However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics. In this study, a method for identifying these characteristics was proposed from the ecological perspective of sustained vegetation growth trend. Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position. Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis. The results show that the extracted parameters can reflect ecosystem growth patterns and portray ecosystem traits such as vegetation growth strategy and ecosystem growth situations.

Impact of Climate Change on Vegetation Growth in Arid Northwest of China from 1982 to 2011

Previous studies have concluded that the increase in vegetation in the arid northwest of China is related to precipitation rather than temperature. However, these studies neglected the effects of climate warming on water availability that arise through changes in the melting characteristics of this snowy and glaciated region. Here, we characterized vegetation changes using the newly improved third-generation Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS-3g NDVI) from 1982 to 2011. We analyzed the temperature and precipitation trends based on data from 51 meteorological stations across Northwest China and investigated changes in the glaciers using Gravity Recovery and Climate Experiment (GRACE) data. Our results indicated an increasing trend in vegetation greenness in Northwest China, and this increasing trend was mostly associated with increasing winter precipitation and summer temperature. We found that the mean annual temperature increased at a rate of 0.04 °C per year over the past 30 years, which induced rapid glacial melting. The total water storage measured by GRACE decreased by up to 8 mm yr−1 and primarily corresponded to the disappearance of glaciers. Considering the absence of any observed increase in precipitation in the growing season, the vegetation growth may have benefited from the melting of glaciers in high-elevation mountains (i.e., the Tianshan Mountains). Multiple regression analysis showed that temperature was positively correlated with NDVI and that gravity was negatively correlated with NDVI; together, these variables explained 84% of the NDVI variation. Our findings suggest that both winter precipitation and warming-induced glacial melting increased water availability to the arid vegetation in this region, resulting in enhanced greenness.