Browsing by Author "Jia, Mingming"
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Item Invasion of Spartina alterniflora in the coastal zone of mainland China: Control achievements from 2015 to 2020 towards the Sustainable Development Goals(Elsevier, 2022-12-01) Li, Huiying; Mao, Dehua; Wang, Zongming; Huang, Xiao; Li, Lin; Jia, Mingming; Earth and Environmental Sciences, School of ScienceThe Sustainable Development Goals (SDGs) and the Convention on Biological Diversity's 15th Conference of the Parties (CBD COP15) both emphasized the urgency of protecting biological diversity. Spartina alterniflora (S. alterniflora), as an invasive species in China, has posed severe biodiversity challenges, demanding nationwide control and management. This study aims to assess the effectiveness of S. alterniflora management during China's SDGs implementation from 2015 to 2020. Landsat images acquired in 2015 (the beginning year of SDGs), 2018, and 2020 (the end year of SDGs' targets 6.6, 14.2, 14.5, and 15.8 related to alien invasion) were applied to quantify the spatiotemporal dynamics of S. alterniflora extent. The results revealed a consistent shrinkage of S. alterniflora, with a net areal reduction of 2610 ha from 2015 to 2020, implying the effectiveness of control measures on S. alterniflora invasion. Provinces including Zhejiang, Jiangsu, and Shanghai have succeeded in controlling S. alterniflora, evidenced by the sharp reduction in S. alterniflora area by 4908 ha, 2176 ha, and 1034 ha, respectively, from 2015 to 2020. However, better management of S. alterniflora is needed in regions with more severe S. alterniflora invasion, e.g., Shandong, Fujian, and Guangdong provinces. Our results suggest that relevant policies, regulations, and ecological restoration projects implemented by national or local governments in China received satisfactory results in S. alterniflora control. Nevertheless, S. alterniflora potential utilities and its governance effectiveness should be objectively evaluated and weighed to obtain the greatest ecological benefits and promote sustainable coastal ecosystems. The results of this study are expected to provide important baseline information benefitting the formulation of coastal protection and restoration strategies in China.Item Mapping Forest Cover in Northeast China from Chinese HJ-1 Satellite Data Using an Object-Based Algorithm(MDPI, 2018-12-16) Ren, Chunying; Zhang, Bai; Wang, Zongming; Li, Lin; Jia, Mingming; Earth Sciences, School of ScienceForest plays a significant role in the global carbon budget and ecological processes. The precise mapping of forest cover can help significantly reduce uncertainties in the estimation of terrestrial carbon balance. A reliable and operational method is necessary for a rapid regional forest mapping. In this study, the goal relies on mapping forest and subcategories in Northeast China through the use of high spatio-temporal resolution HJ-1 imagery and time series vegetation indices within the context of an object-based image analysis and decision tree classification. Multi-temporal HJ-1 images obtained in a single year provide an opportunity to acquire phenology information. By analyzing the difference of spectral and phenology information between forest and non-forest, forest subcategories, decision trees using threshold values were finally proposed. The resultant forest map has a high overall accuracy of 0.91 ± 0.01 with a 95% confidence interval, based on the validation using ground truth data from field surveys. The forest map extracted from HJ-1 imagery was compared with two existing global land cover datasets: GlobCover 2009 and MCD12Q1 2009. The HJ-1-based forest area is larger than that of MCD12Q1 and GlobCover and more closely resembles the national statistics data on forest area, which accounts for more than 40% of the total area of the Northeast China. The spatial disagreement primarily occurs in the northern part of the Daxing'an Mountains, Sanjiang Plain and the southwestern part of the Songliao Plain. The compared result also indicated that the forest subcategories information from global land cover products may introduce large uncertainties for ecological modeling and these should be cautiously used in various ecological models. Given the higher spatial and temporal resolution, HJ-1-based forest products could be very useful as input to biogeochemical models (particularly carbon cycle models) that require accurate and updated estimates of forest area and type.Item Monitoring the Invasion of Spartina alterniflora Using Multi-source High-resolution Imagery in the Zhangjiang Estuary, China(MDPI, 2017-06) Liu, Mingyue; Li, Huiying; Li, Lin; Man, Weidong; Jia, Mingming; Wang, Zongming; Lu, Chunyan; Earth Science, School of ScienceSpartina 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. View Full-TextItem National wetland mapping in China: a new product resulting from object-based and hierarchical classification of Landsat 8 OLI images(Elsevier, 2020-06) Mao, Dehua; Wang, Zongming; Du, Baojia; Li, Lin; Tian, Yanlin; Jia, Mingming; Zeng, Yuan; Song, Kaishan; Jiang, Ming; Wang, Yeqiao; Earth Sciences, School of ScienceSpatially and thematically explicit information of wetlands is important to understanding ecosystem functions and services, as well as for establishment of management policy and implementation. However, accurate wetland mapping is limited due to lacking an operational classification system and an effective classification approach at a large scale. This study was aimed to map wetlands in China by developing a hybrid object-based and hierarchical classification approach (HOHC) and a new wetland classification system for remote sensing. Application of the hybrid approach and the wetland classification system to Landsat 8 Operational Land Imager data resulted in a wetland map of China with an overall classification accuracy of 95.1%. This national scale wetland map, so named CAS_Wetlands, reveals that China’s wetland area is estimated to be 451,084 ± 2014 km2, of which 70.5% is accounted by inland wetlands. Of the 14 sub-categories, inland marsh has the largest area (152,429 ± 373 km2), while coastal swamp has the smallest coverage (259 ± 15 km2). Geospatial variations in wetland areas at multiple scales indicate that China’s wetlands mostly present in Tibet, Qinghai, Inner Mongolia, Heilongjiang, and Xinjiang Provinces. This new map provides a new baseline data to establish multi-temporal and continuous datasets for China’s wetlands and biodiversity conservation.Item Rapid Invasion of Spartina alterniflora in the Coastal Zone of Mainland China: New Observations from Landsat OLI Images(MDPI, 2018-12) Liu, Mingyue; Mao, Dehua; Wang, Zongming; Li, Lin; Man, Weidong; Jia, Mingming; Ren, Chunying; Zhang, Yuanzhi; Earth Sciences, School of SciencePlant invasion imposes significant threats to biodiversity and ecosystem function. Thus, monitoring the spatial pattern of invasive plants is vital for effective ecosystem management. Spartina alterniflora (S. alterniflora) has been one of the most prevalent invasive plants along the China coast, and its spread has had severe ecological consequences. Here, we provide new observation from Landsat operational land imager (OLI) images. Specifically, 43 Landsat-8 OLI images from 2014 to 2016, a combination of object-based image analysis (OBIA) and support vector machine (SVM) methods, and field surveys covering the whole coast were used to construct an up-to-date dataset for 2015 and investigate the spatial variability of S. alterniflora in the coastal zone of mainland China. The classification results achieved good estimation, with a kappa coefficient of 0.86 and 96% overall accuracy. Our results revealed that there was approximately 545.80 km2 of S. alterniflora distributed in the coastal zone of mainland China in 2015, from Hebei to Guangxi provinces. Nearly 92% of the total area of S. alterniflora was distributed within four provinces: Jiangsu, Shanghai, Zhejiang, and Fujian. Seven national nature reserves invaded by S. alterniflora encompassed approximately one-third (174.35 km2) of the total area of S. alterniflora over mainland China. The Yancheng National Nature Reserve exhibited the largest area of S. alterniflora (115.62 km2) among the reserves. Given the rapid and extensive expansion of S. alterniflora in the 40 years since its introduction and its various ecological effects, geospatially varied responding decisions are needed to promote sustainable coastal ecosystems.Item Rapid Invasion of Spartina Alterniflora in the Coastal Zone of Mainland China: Spatiotemporal Patterns and Human Prevention(MDPI, 2019-05-19) Mao, Dehua; Liu, Mingyue; Wang, Zongming; Li, Lin; Man, Weidong; Jia, Mingming; Zhang, Yuanzhi; Earth Sciences, School of ScienceGiven the extensive spread and ecological consequences of exotic Spartina alterniflora (S. alterniflora) over the coast of mainland China, monitoring its spatiotemporal invasion patterns is important for the sake of coastal ecosystem management and ecological security. In this study, Landsat series images from 1990 to 2015 were used to establish multi-temporal datasets for documenting the temporal dynamics of S. alterniflora invasion. Our observations revealed that S. alterniflora had a continuous expansion with the area increasing by 50,204 ha during the considered 25 years. The largest expansion was identified in Jiangsu Province during the period of 1990-2000, and in Zhejiang Province during the periods 2000-2010 and 2010-2015. Three noticeable hotspots for S. alterniflora invasion were Yancheng of Jiangsu, Chongming of Shanghai, and Ningbo of Zhejiang, and each had a net area increase larger than 5000 ha. Moreover, an obvious shrinkage of S. alterniflora was identified in three coastal cities including the city of Cangzhou of Hebei, Dongguan, and Jiangmen of Guangdong. S. alterniflora invaded mostly into mudflats (>93%) and shrank primarily due to aquaculture (55.5%). This study sheds light on the historical spatial patterns in S. alterniflora distribution and thus is helpful for understanding its invasion mechanism and invasive species management.Item Remote Observation in Habitat Suitability Changes for Waterbirds in the West Songnen Plain, China(MDPI, 2019-01) Tian, Yanlin; Wang, Zongming; Mao, Dehua; Li, Lin; Liu, Mingyue; Jia, Mingming; Man, Weidong; Lu, Chunyan; Earth Sciences, School of ScienceBeing one of the most important habitats for waterbirds, China’s West Songnen Plain has experienced substantial damage to its ecosystem, especially the loss and degradation of wetlands and grasslands due to anthropogenic disturbances and climate change. These occurrences have led to an obvious decrease in waterbird species and overall population size. Periodic and timely monitoring of changes in habitat suitability and understanding the potential driving factors for waterbirds are essential for maintaining regional ecological security. In this study, land cover changes from 2000 to 2015 in this eco-sensitive plain were examined using Landsat images and an object-based classification method. Four groups of environmental factors, including human disturbance, water situation, food availability, and shelter safety, characterized by remote sensing data were selected to develop a habitat suitability index (HSI) for assessing habitat suitability for waterbirds. HSI was further classified into four grades (optimum, good, general, and poor), and their spatiotemporal patterns were documented from 2000 to 2015. Our results revealed that cropland expansion and wetland shrinkage were the dominant land cover changes. Waterbird habitat areas in the optimum grade experienced a sharp decline by 7195 km2. The habitat area in good suitability experienced reduction at a change rate of −8.64%, from 38,672 km2 to 35,331 km2. In addition, waterbird habitats in the general and poor grades increased overall by 10.31%. More specifically, the total habitat areas with optimum suitable grade, in five national nature reserves over the study region, decreased by 12.21%, while habitat areas with poor suitable grade increased by 3.89%. Changes in habitat suitability could be largely attributed to the increase in human disturbance, including agricultural cultivation from wetlands and grasslands and the expansion of built-up lands. Our findings indicate that additional attention should be directed towards reducing human impact on habitat suitability for sustainable ecosystems.Item Spatial Expansion and Soil Organic Carbon Storage Changes of Croplands in the Sanjiang Plain, China(MDPI, 2017-04) Man, Weidong; Yu, Hao; Li, Lin; Liu, Mingyue; Mao, Dehua; Ren, Chunying; Wang, Zongming; Jia, Mingming; Miao, Zhenghong; Lu, Chunyan; Li, Huiying; Earth Sciences, School of ScienceSoil is the largest pool of terrestrial organic carbon in the biosphere and interacts strongly with the atmosphere, climate and land cover. Remote sensing (RS) and geographic information systems (GIS) were used to study the spatio-temporal dynamics of croplands and soil organic carbon density (SOCD) in the Sanjiang Plain, to estimate soil organic carbon (SOC) storage. Results show that croplands increased with 10,600.68 km2 from 1992 to 2012 in the Sanjiang Plain. Area of 13,959.43 km2 of dry farmlands were converted into paddy fields. Cropland SOC storage is estimated to be 1.29 ± 0.27 Pg C (1 Pg = 103 Tg = 1015 g) in 2012. Although the mean value of SOCD for croplands decreased from 1992 to 2012, the SOC storage of croplands in the top 1 m in the Sanjiang Plain increased by 70 Tg C (1220 to 1290). This is attributed to the area increases of cropland. The SOCD of paddy fields was higher and decreased more slowly than that of dry farmlands from 1992 to 2012. Conversion between dry farmlands and paddy fields and the agricultural reclamation from natural land-use types significantly affect the spatio-temporal patterns of cropland SOCD in the Sanjiang Plain. Regions with higher and lower SOCD values move northeast and westward, respectively, which is almost consistent with the movement direction of centroids for paddy fields and dry farmlands in the study area. Therefore, these results were verified. SOC storages in dry farmlands decreased by 17.5 Tg·year−1 from 1992 to 2012, whilst paddy fields increased by 21.0 Tg·C·year−1.Item The national nature reserves in China: Are they effective in conserving mangroves?(Elsevier, 2022) Lu, Chunyan; Li, Lin; Wang, Zili; Su, Yanlin; Su, Yue; Huang, Yufei; Jia, Mingming; Mao, Dehua; Earth and Environmental Sciences, School of ScienceMangroves are high-productive ecosystems and globally protected. Establishing nature reserves aimed at counteracting the negative effects of anthropogenic activities is one of the most pivotal approaches to conserve mangrove ecosystems. Evaluation of the conservation effectiveness for mangrove nature reserves is thus indispensable for making knowledge-based conservation policies and funding-decisions by government and managers. In this study, using composited Landsat images by the Google Earth Engine cloud platform and object-oriented deep learning classification method, the land cover maps of national mangrove nature reserves (NMNRs) in China were obtained from 1987 to 2019. The systematic evaluation of conservation effectiveness for each NMNR was conducted by landscape metrics and an entropy weight model. Combined with the dynamics in mangrove distribution, human interference intensity, and natural environment change, the driving force factors affecting the conservation effectiveness for NMNRs were investigated. The results show that the total mangrove area in all NMNRs increased 968.6 ha during the study period, a 21.8 % rate of increase. Except for one NMNR with a slight decline, the conservation of remaining NMNRs was considered effective with increase varied from 14.8 % to 87.5 % in the level of protective efficacy. The conservation effectiveness of NMNRs was affected by both anthropogenic and natural factors, while the improvement to the conservation effectiveness was largely attributed to the implementation of protection policies, such as reforestation engineering. Further direct or indirect challenges in mangrove conservation effectiveness, e.g., pollution, natural disasters, and exotic species invasion, still require close attention. This study provides an effective and efficient approach to quantify the conservation effectiveness of mangrove nature reserves, which would facilitate mangrove conservation and management in the future.