China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.
A series of SnO-coated α-Fe solid-solution nanocapsules were fabricated by a modified arc-discharge technique from Fe1−x Sn x targets with x = 0, 2, 3, 4 and 5 at%. The core and shells change with changing Sn concentration (0, 2, 3, 4 and 5 at%) in the Fe1−x Sn x targets used in the preparation. An in-depth study of the complex permittivity and permeability reveals that the SnO-coated α-Fe solid-solution nanocapsules with 3 at% Sn exhibit excellent microwave-absorption properties among the present SnO-coated Fe solid-solution nanocapsules, due to a proper electromagnetic match in the microstructure, the strong natural resonance as well as dipolar polarization mechanisms.
Abstract:The accuracy of different coarse-resolution land cover products is an important consideration for product users at the regional or global scale, and different evaluation methods inevitably result in discrepancies in accuracy for the same land cover product. The remote sensing community has responded to this increased interest by improving methodologies for more accurately evaluating the correctness of land cover information. In this study, a pixel-based hierarchical classification strategy followed by an object-based classification method was applied to compact airborne spectrographic imager (CASI) hyperspectral data in order to produce highly accurate, high spatial resolution classification reference data. Some aspects of the fuzzy/conventional evaluation of MODIS land cover (MODISLC) (500 m) and GlobCover (300 m) data based on sub-pixel class fractions derived from high spatial resolution reference data at different thematic resolutions are also discussed. Relationships between homogeneity and fuzzy accuracy for two land cover products were obtained at different thematic resolutions. Additionally, the influences on the relationship resulting from the thematic resolution were also studied, and these are reported in this paper. Attempts were made to establish fuzzy/conventional evaluation rules for fuzzy classes, and the different performances of the fuzzy and conventional evaluations for hard/fuzzy labels were compared. The adjusted GlobCover accuracy after theoretical removal of the effect caused by spatial resolution was calculated based on the relationship OPEN ACCESSRemote Sens. 2014, 6 2865 between homogeneity and accuracy; the result was a higher accuracy than for MODISLC at the same thematic resolution. In addition, the different performance characteristics of the relationships between homogeneity and adjusted GlobCover accuracy/MODISLC accuracy at different thematic resolutions were compared and analyzed over the area where the CASI transects were obtained.
In this study, variation characteristics of hydrometeorological factors were explored based on observed time-series data between 1957 and 2010 in four subregions of the Yellow River Basin. For each region, precipitation-streamflow models at annual and flood-season scales were developed to quantify the impact of annual precipitation, temperature, percentage of flood-season precipitation, and anthropogenic interference. The sensitivities of annual streamflow to these three climatic factors were then calculated using a modified elasticity coefficient model. The results presented the following:(1) Annual streamflow exhibited a negative trend in all regions; (2) The reduction of annual streamflow was mainly caused by a precipitation decrease and temperature increase for all regions before 2000, whereas the contribution of anthropogenic interference increased significantly-more than 45%, except for Tang-Tou region after 2000. The percentage of flood-season precipitation variation can also be responsible for annual streamflow reduction with a range of 7.36% (Tang-Tou) to 21.88% (Source); (3) Annual streamflow was more sensitive to annual precipitation than temperature in the humid region, and the opposite situation was observed in the arid region. The sensitivities to intra-annual climate variation increased after 2000 for all regions, and the increase was more significant in Tou-Long and Long-Hua regions.importance for a better understanding of the hydrologic mechanisms, which is beneficial for planning suitable adaptation strategies and water management.There are various methods to separate the impacts of climate change and anthropogenic interference on streamflow, mainly including catchment experiments, hydrological models, and statistical methods [9]. Catchment experiments are the most rigorous empirical research design for estimating the effects of land use on aquatic systems [10], but they can be influenced by the variation in experimental conditions and the presentation of results [11]. Most relevant studies indicate that catchment streamflow decreased significantly after afforestation and increased after deforestation [10,12,13]. Hydrological models, both distributed and lumped, have been widely used [7,[14][15][16]. Hu et al. applied the water and energy budget-based distributed hydrological model (WEB-DHM) to diagnose and quantify climate and human impacts on streamflow change [17]. Hundecha et al. applied a conceptual rainfall-runoff model to 95 catchments in the Rhine basin to model the effect of land use change on runoff [18]. Statistical methods such as streamflow elasticity have also been used in regions specifically with available long-term climate and hydrologic data [9,19,20]. Tian et al. used regression analysis to illustrate runoff decline via comparison of precipitation-runoff correlation for the period prior to and after sharp runoff decline [21].The semiarid and arid Yellow River Basin (YRB) is the main source of surface water in the northwest and northern part of China. The annual streamflow is a...
Climate variation and underlying surface dynamics have caused a significant change in the trend of evapotranspiration (ET) in the Yellow River Basin (YRB) over the last two decades. Combined with the measured rainfall, runoff and gravity recovery and climate experiment (GRACE) product, five global ET products were firstly merged using a linear weighting method. Linear slope, “two-step” multiple regression, partial differential, and residual methods were then employed to explore the quantitative impacts of precipitation (PCPN), temperature (Temp), sunshine duration (SD), vapor pressure deficit (VPD), wind speed (WS), leaf area index (LAI), and the residual factors (e.g., microtopography changes, irrigation, etc.) on the ET trend in the YRB. The results show that: (1) The ET estimates were improved by merging five global ET products using the linear weighting method. The sensitivities of climatic factors and LAI on the ET trend can be separately calculated using proposed “two-step” statistical regression method; (2) the overall ET trend in the entire study area during 2000–2018 was 3.82 mm/yr, and the highest ET trend was observed in the Toudaoguai-Longmen subregion. ET trend was dominantly driven by vegetation greening, with an impact of 2.47 mm/yr and a relative impact rate of 51.16%. The results indicated that the relative impact rate of the residual factors (e.g., microtopography, irrigation, etc.) on the ET trend is up to 28.17%. The PCPN and VPD had increasing roles on the ET trend, with impacts of 0.45 mm/yr and 0.05 mm/yr, respectively, whereas the Temp, SD, and WS had decreasing impacts of –0.19 mm/yr, –0.15 mm/yr, and –0.17 mm/yr, respectively. (3) The spatial pattern of impact of specific influencing factor on the ET trend was determined by the spatial pattern of change trend slope of this factor and sensitivity of ET to this factor. ET trends of the source area and the Qingtongxia–Toudaoguai were dominated by the climatic factors, while the residual factors dominated the ET trend in the Tangnaihai–Qingtongxia area. The vegetation restoration was the dominant factor causing the increase in the ET in the middle reaches of the YRB, and the impact rates of the LAI were ranked as follows: Yanhe Rive > Wudinghe River > Fenhe River > Jinghe River > Beiluohe River > Qinhe River > Kuyehe River > Yiluohe River.
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