ALBERT

Description: The Yellow River Basin is one of China’s most densely-populated, fastest growing and most dynamic regions, with abundant natural resources and intense agricultural production. Major land policies have recently resulted in remarkable landscape modifications throughout the basin. The availability of precise regional land cover change information is crucial to better understand the prevailing dynamics and underlying factors influencing the current processes in such a complex system and can additionally serve as a valuable component for modeling and decision making. Such comprehensive and detailed information is lacking for the Yellow River Basin so far. In this study, we derived land cover characteristics and dynamics from the complete last decade based on optical high-temporal MODIS Normalized Differenced Vegetation Index (NDVI) time series for the whole Yellow River Basin. After filtering and smoothing for noise reduction with the use of the adaptive Savitzky–Golay filter, the processed time series was used to derive a large variety of phenological and annual metrics. The final classifications for the basin (2003 and 2013) were based on a random forest classifier, trained by reference samples from very high-resolution imagery. The accuracy assessment for all 18 thematic classes, which was based on a 30% reference data split, yielded an overall accuracy of 87% and 84% for 2003 and 2013, respectively. Major land cover and land use changes during the last decade have occurred on the Loess Plateau, where land and conservation reforms triggered large-scale recovery of grassland and shrubland habitat that had been previously covered by agriculture or sparse vegetation. Agricultural encroachment and urban area expansion are other processes influencing the dynamics in the basin. The necessity for regionally-adapted land cover maps becomes obvious when our land cover products are compared to existing global products, where thematic accuracy remains low, particularly in a heterogeneous landscape, such as the Yellow River Basin. The basin-wide novel land cover and land use products of the Yellow River Basin hold a large potential for climate, hydrology and biodiversity modelers, as well as river basin and regional governmental authorities and will be shared upon request.

Description: Forests, Vol. 8, Pages 341: Excessive Accumulation of Chinese Fir Litter Inhibits Its Own Seedling Emergence and Early Growth—A Greenhouse Perspective Forests doi: 10.3390/f8090341 Authors: Bo Liu Stefani Daryanto Lixin Wang Yanjuan Li Qingqing Liu Chong Zhao Zhengning Wang Litter accumulation can strongly influence plants’ natural regeneration via both physical and chemical mechanisms, but the relative influence of each mechanism on seedling establishment remains to be elucidated. Chinese fir (Cunninghamia lanceolata) is one of the most important commercial plantations in southern China, but its natural regeneration is poor, possibly due to its thick leaf litter accumulation. We used natural and plastic litter to study the effects of Chinese fir litter on its own seedling emergence and early growth, as well as to assess whether the effect is physical or chemical in nature. Results showed that high litter amount (800 g·m−2) significantly reduced seedling emergence and the survival rate for both natural and plastic litter. Low litter amount (200 g·m−2) exerted a slightly positive effect on root mass, leaf mass, and total mass, while high litter amount significantly inhibited root mass, leaf mass, and total mass for both natural and plastic litter. Root-mass ratio was significantly lower, and leaf-mass ratio was significantly greater under high litter cover than under control for both natural and plastic litter. Although the root/shoot ratio decreased with increasing litter amount, such effect was only significant for high litter treatment for both natural and plastic litter. Seedling robustness (aboveground biomass divided by seedling height) decreased with increasing litter amount, with high litter treatment generating the least robust seedlings. Because plastic and natural litter did not differ in their effects on seedling emergence and growth, the litter layer’s short-term influence is primarily physical. These data indicated that as litter cover increased, the initial slightly positive effects on seedling emergence and early growth could shift to inhibitory effects. Furthermore, to penetrate the thick litter layer, Chinese fir seedlings allocated more resources towards stems and aboveground growth at the expense of their roots. This study provided experimental evidence of litter amount as a key ecological factor affecting seedling development and subsequent natural regeneration of Chinese fir.

Description: IJERPH, Vol. 15, Pages 855: Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15050855 Authors: Chunsheng Wu Gaohuan Liu Chong Huang Qingsheng Liu Xudong Guan The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures. The aim of this study was to obtain the spatial distribution of the ecological vulnerability (EV) in YRD based on 21 indicators selected from underwater status, soil condition, land use, landform, vegetation cover, meteorological conditions, ocean influence, and social economy. In addition, the fuzzy analytic hierarchy process (FAHP) method was used to obtain the weights of the selected indicators, and a fuzzy logic model was constructed to obtain the result. The result showed that the spatial distribution of the EV grades was regular, while the fuzzy membership of EV decreased gradually from the coastline to inland area, especially around the river crossing, where it had the lowest EV. Along the coastline, the dikes had an obviously protective effect for the inner area, while the EV was higher in the area where no dikes were built. This result also showed that the soil condition and groundwater status were highly related to the EV spatially, with the correlation coefficients −0.55 and −0.74 respectively, and human activities had exerted considerable pressure on the ecological environment.

Description: IJGI, Vol. 7, Pages 75: An Open-Boundary Locally Weighted Dynamic Time Warping Method for Cropland Mapping ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7020075 Authors: Xudong Guan Gaohuan Liu Chong Huang Xuelian Meng Qingsheng Liu Chunsheng Wu Xarapat Ablat Zhuoran Chen Qiang Wang This paper proposes an open-boundary locally weighted dynamic time warping (OLWDTW) method using MODIS Normalized Difference Vegetation Index (NDVI) time-series data for cropland recognition. The method solves the problem of flexible planting times for crops in Southeast Asia, which has sufficient thermal and water conditions. For NDVI time series starting at the beginning of the year and terminating at the end of the year, the method can separate the non-growing season cycle and growing season cycle for crops. The non-growing season cycle may provide some useful information for crop recognition, such as soil conditions. However, the shape of the growing season’s NDVI time series for crops is the key to separating cropland from other land cover types because the shape contains all of the crop growth information. The principle of the OLWDTW method is to enhance the effects of the growing season cycle on the NDVI time series by adding a local weight to the growing season when comparing the similarity of time series based on the open-boundary dynamic time warping (DTW) method. Experiments with two satellite datasets located near the Khorat Plateau in the Lower Mekong Basin validate that OLWDTW effectively improves the precision of cropland recognition compared to a non-weighted open-boundary DTW method in terms of overall accuracy. The method’s classification accuracy on cropland exceeds the non-weighted open-boundary DTW by 5–7%. In future studies, an open-boundary self-adaption locally weighted DTW and a more effective combination rule for different crop types should be explored for the method’s best performance and highest extraction accuracy for cropland.

Description: Sensors, Vol. 18, Pages 2733: Comparison of CBERS-04, GF-1, and GF-2 Satellite Panchromatic Images for Mapping Quasi-Circular Vegetation Patches in the Yellow River Delta, China Sensors doi: 10.3390/s18082733 Authors: Qingsheng Liu Chong Huang Gaohuan Liu Bowei Yu Vegetation in arid and semi-arid regions frequently exists in patches, which can be effectively mapped by remote sensing. However, not all satellite images are suitable to detect the decametric-scale vegetation patches because of low spatial resolution. This study compared the capability of the first Gaofen Satellite (GF-1), the second Gaofen Satellite (GF-2), and China-Brazil Earth Resource Satellite 4 (CBERS-04) panchromatic images for mapping quasi-circular vegetation patches (QVPs) with K-Means (KM) and object-based example-based feature extraction with support vector machine classification (OEFE) in the Yellow River Delta, China. Both approaches provide relatively high classification accuracy with GF-2. For all five images, the root mean square errors (RMSEs) for area, perimeter, and perimeter/area ratio were smaller using the KM than the OEFE, indicating that the results from the KM are more similar to ground truth. Although the mapped results of the QVPs from finer-spatial resolution images appeared more accurate, accuracy improvement in terms of QVP area, perimeter, and perimeter/area ratio was limited, and most of the QVPs detected only by finer-spatial resolution imagery had a more than 40% difference with the actual QVPs in these three parameters. Compared with the KM approach, the OEFE approach performed better for vegetation patch shape description. Coupling the CBERS-04 with the OEFE approach could suitably map the QVPs (overall accuracy 75.3%). This is important for ecological protection managers concerned about cost-effectiveness between image spatial resolution and mapping the QVPs.

Description: IJERPH, Vol. 15, Pages 1818: Distribution Characteristics and Seasonal Variation of Soil Nutrients in the Mun River Basin, Thailand International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15091818 Authors: Zhonghe Zhao Gaohuan Liu Qingsheng Liu Chong Huang He Li Chunsheng Wu Based on soil sampling data from the dry season and the rainy season, the spatial heterogeneity and spatial pattern of soil nutrients in the Mun River Basin, Thailand, were studied and the seasonal variation in soil nutrients was analyzed using classical statistical methods and geostatistical methods. The soil nutrient content in the Mun Basin showed moderate and strong variations, and the descending order of soil variability was as follows: available phosphorous (AP) > electric conductivity (EC) > soil organic matter (SOM) > total nitrogen (TN) > pH value in the dry season, with AP showing strong variation, and EC > AP > SOM > TN > pH in the rainy season, with EC showing strong variation. Different soil nutrients and different soil properties had different spatial variation characteristics, and their corresponding best-fitting models were also different. Based on the nugget (C0), sill (C0 + C), and range (A), spatial analysis was performed for the soil nutrients, pH, and EC in the dry season and in the rainy season. Analysis based on kriging spatial interpolation data showed that pH, SOM, TN, and EC had convex or concave distributions, whereas AP had a patchy distribution. Terrain, vegetation, and human disturbance are the main factors that contribute to the differences in the soil nutrient pattern of the Mun River Basin.