Mingming Jia

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.

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.

SPOT5 multi-spectral (MS) and panchromatic (PAN) image fusion using an improved wavelet method based on local algorithm

Remote sensing image fusion is an effective way to extract a large volume of data from multi-source images. However, traditional image fusion methods cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. In this paper, a new wavelet method based on a local algorithm is presented. The proposed method fuses multi-spectral (MS) and panchromatic (PAN) images to improve spatial information and preserve spectral characteristics. The main advantage of the new fusion method is the exploitation of the dependency between neighboring pixels. SPOT5 MS and PAN images were employed to execute the fusion methods. To compare with the new method, the principal component analysis (PCA), wavelet transformation, and PCA-based wavelet (PCA+W) image fusion methods were selected. Qualitative and quantitative analyses and classification accuracy assessment were conducted to evaluate the performance of the fusion methods. The results demonstrate that the new wavelet method based on a local algorithm is better than traditional image fusion methods. The new fusion method can achieve a wide range of balance between high spatial resolution retention and spectral characteristic preservation; thus, the new method is suitable for different applications.

Evaluating the Effectiveness of Conservation on Mangroves: A Remote Sensing-Based Comparison for Two Adjacent Protected Areas in Shenzhen and Hong Kong, China

Mangroves are ecologically important ecosystems and globally protected. The purpose of this study was to evaluate the effectiveness of mangrove conservation efforts in two adjacent protected areas in China that were under the management policies of the Ramsar Convention (Mai Po Marshes Nature Reserve (MPMNR), Hong Kong) and China’s National Nature Reserve System (Futian Mangrove National Nature Reserve (FMNNR), Shenzhen). To achieve this goal, eleven Landsat images were chosen and classified, areal extent and landscape metrics were then calculated. The results showed that: from 1973–2015, the areal extent of mangroves in both reserves increased, but the net change for the MPMNR (281.43 hm2) was much higher than those of the FMNNR (101.97 hm2). In general, the area-weighted centroid of the mangroves in FMNNR moved seaward by approximately 120 m, whereas in the MPMNR, the centroid moved seaward even farther (410 m). Although both reserves saw increased integrality and connectivity of the mangrove patches, the patches in the MPMNR always had higher integrality than those in the FMNNR. We concluded that the mangroves in the MPMNR were more effectively protected than those in the FMNNR. This study may provide assistance to the formulation of generally accepted criteria for remote sensing-based evaluation of conservation effectiveness, and may facilitate the development of appropriate mangrove forest conservation and management strategies in other counties.

Monitoring Loss and Recovery of Salt Marshes in the Liao River Delta, China

ABSTRACT Jia, M.; Wang, Z.; Liu, D.; Ren, C.; Tang, X., and Dong, Z., 2015. Monitoring loss and recovery of salt marsh in the Liao River Delta, China. Coastal salt marsh plays an important role in the aquatic food web and the export of nutrients to coastal waters. The salt marshes in the Liao River Delta of China, dominated by Suaeda heteroptera, experienced a dramatic loss in the 1990s and then recovered in the 2000s. This study investigates these changes of salt marsh using a time series of Landsat Thematic Mapper (TM) images acquired in 1988, 1995, 2000, 2004, 2007, and 2009. The classification tree method was used on these TM images to extract S. heteroptera, and an interactive self-organizing data analysis algorithm was used to determine other land cover types. The conversions between salt marsh and other land cover types were described with conversion matrices. The classification results show that, during 1998–2004, salt marsh decreased dramatically at an average rate of 662.68 ha/y. However, during the period 2004–2009, salt marsh recovered gradually at a rate of 115.51 ha/y. The conversion matrix indicates that, from 1988 to 2004, a large area of former salt marsh was directly replaced by man-made landscape types, such as reed field (5111 ha), aquaculture pond (2655 ha), reservoir (1720 ha), and paddy field (729 ha). In contrast, the result for the period from 2004 to 2009 shows that salt marshes were recovered by the conversion of some areas of former barren beaches and river back to salt marsh. Driving forces analysis suggests that salt marsh dynamics were mainly caused by human activities, with the secondary drivers being climatic warming and dry conditions.

Influence of vegetation phenology on modelling carbon fluxes in temperate deciduous forest by exclusive use of MODIS time-series data

Understanding the influence of vegetation phenology on modelling primary productivity, biomass, and natural carbon dynamics, as well as the underlying mechanisms, is crucial for assessing the vulnerability of terrestrial carbon pools under future changing climate conditions. Considering that the component fluxes of carbon sequestration, gross primary production (GPP) and ecosystem respiration (Re), are dominant alternately during the course of the year, here we propose a new model for estimating the carbon sequestration of temperate deciduous forest exclusively based on Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data, including land-surface temperature (LST), Terra night-time LST (LST′), enhanced vegetation index (EVI), land-surface water index (LSWI), fraction of absorbed photosynthetically active radiation (FPAR), and leaf area index (LAI). This study aims to reveal the main environmental control variables that contribute to the net ecosystem exchange (NEE) variations and to develop an improved model that accurately predicts NEE according to the growing and dormant seasons. The seasonality information was extracted from time series of MODIS NDVI data based on nonlinear least squares fits of asymmetric Gaussian model functions in the computer program, TIMESAT. The results suggest that the improved model could provide substantially better NEE estimates and well reflect the seasonal dynamics of the temperate deciduous forest. In addition, because both ecosystem photosynthesis and respiration are powerful during the growing season, all variables are strongly correlated with NEE at the 0.01 p-level, whereas only some parameters (temperature and water) are significant during the non-growing period due to dominant respiration and limited photosynthesis.

Monitoring the Invasion of Spartina alterniflora Using Multi-source High-resolution Imagery in the Zhangjiang Estuary, China

Spartina alterniflora (S. alterniflora) is one of the most harmful invasive plants in China. Google Earth (GE), as a free software, hosts high-resolution imagery for many areas of the world. To explore the use of GE imagery for monitoring S. alterniflora invasion and developing an understanding of the invasion process of S. alterniflora in the Zhangjiang Estuary, the object-oriented method and visual interpretation were applied to GE, SPOT-5, and Gaofen-1 (GF-1) images. In addition, landscape metrics of S. alterniflora patches adjacent to mangrove forests were calculated and mangrove gaps were recorded by checking whether S. alterniflora exists. The results showed that from 2003–2015, the areal extent of S. alterniflora in the Zhangjiang Estuary increased from 57.94 ha to 116.11 ha, which was mainly converted from mudflats and moved seaward significantly. Analyses of the S. alterniflora expansion patterns in the six subzones indicated that the expansion trends varied with different environmental circumstances and human activities. Land reclamation, mangrove replantation, and mudflat aquaculture caused significant losses of S. alterniflora. The number of invaded gaps increased and S. alterniflora patches adjacent to mangrove forests became much larger and more aggregated during 2003–2015 (the class area increased from 12.13 ha to 49.76 ha and the aggregation index increased from 91.15 to 94.65). We thus concluded that S. alterniflora invasion in the Zhangjiang Estuary had seriously increased and that measures should be taken considering the characteristics shown in different subzones. This study provides an example of applying GE imagery to monitor invasive plants and illustrates that this approach can aid in the development of governmental policies employed to control S. alterniflora invasion.

Land use/cover characterizaitoin with MODIS time series data with hybrid classification mothed over Australia for 2001 and 2003

Improved and up-to-date land use/land cover (LULC) data sets are needed over the whole country of Australia to support science and policy applications focused on understanding the role and response of the LULC to environmental change. The main goal of this study was to map LULC in Australia using MODIS 250 m Normalized Difference Vegetation Index (NDVI), Land Surface Vegetation Index (LSWI) and reflectance time series data of 2000 and 2003. NDVI time-series were filtered by the Savitzky-Golay algorithm in the present study to smooth out noise. A combination of unsupervised ISODATA and a hierarchical decision tree classification were performed on 2 years 12-month time-series MODIS data. Also, Australian Vegetation Map and other land use/land cover data set were used as labeling reference during the classification process. The MODIS land cover products were evaluated using existing land use/cover data derived from Landsat TM as reference data (AUS-2000), also LULC information derived from 11 scenes of Landsat-5 TM data were used as validation data source. The overall classification accuracy was 76.4%. It turned out that our result is acceptable because the relative high resolution of MODIS data and more prior knowledge was applied.

Remote Monitoring of Expansion of Aquaculture Ponds Along Coastal Region of the Yellow River Delta from 1983 to 2015

Aquaculture ponds are one of the fastest-growing land use types in valuable and fertile coastal areas and have caused serious environmental problems. Quantitative assessment of the extent, spatial distribution, and dynamics of aquaculture ponds is of utmost importance for sustainable economic development and scientific management of land and water resources in the coastal area. An object- oriented classification approach was applied to Landsat images acquired over three decades to investigate the long-term change of aquaculture ponds in the coastal region of the Yellow River Delta. The results indicated that the aquaculture ponds in the study area undergone a sharp expansion from 40.38 km2 in 1983 to 1406.89 km2 in 2015, and the fast expansion occurred during the period of 2010–2015 and 1990–2000. Natural wetlands, especially mudflat, and cropland were main land use types contributing to the increase of aquaculture ponds. The patches of aquaculture ponds were consequently prevalence in the north of the Yellow River Estuary and landscape metrics indicated an increase of the aquaculture ponds of the study area in the quantity and complexity. The expansion of aquaculture ponds inevitably had negative effects on the coastal environment, including loss of natural wetlands, water pollution and land subsidence, etc. The results from this study provide baseline data and valuable information for efficiently planning and managing aquaculture practices and for effectively implementing adequate regulations and protection measures.

Mapping biomes of Australia based on the Holdridge Life Zone Model

In this paper a new biome map of Australia with one million scale was produced based on the Holdridge Life Zone (HLZ) model. Climate data over the whole Australia from 1983 to 2007 were disposed in order to processed HLZ model and get a biome map. Australia is an extremely dry land, in this study we obtained the area of arid biome was 3 561 674.31 km2, occupy 46.35 percent of the continent. When analyzing the effect of climatic variability, we found that in the period of 1983 to 2007, the mean annual temperature has an increasing trend, at the same time the annual precipitation was decreasing. This result reflected to the badly drought in these years.