[Ecological security characteristics of main irrigated agricultural areas on the Loess Plateau based on remote sensing information]. / åŸºäºŽé¥æ„Ÿä¿¡æ¯çš„é»„åœŸé«˜åŽŸä¸»è¦çŒæº‰å†œä¸šåˆ†å¸ƒåŒºç”Ÿæ€å®‰å ¨ç‰¹å¾.

Ecological security is an important guarantee for the sustainable development of regional economy and society. We analyzed the change characteristics of fraction vegetation coverage (FVC) and remote sensing ecological index (RSEI) of four irrigated agriculture regions of the Loess Plateau (Yinchuan Plain, Hetao Plain, Fenhe River Valley and Weihe River Plain) based on the remote sensing data from 2000 to 2018. The results showed that the FVC decreased in the study area from 2000 to 2018. The variation trend of FVC differed among the four irrigated agricultural distribution areas. The RSEI of the whole area showed an overall downward trend, the RSEI of Yinchuan Plain (down 0.06) and Weihe River Plain (down 0.07) decreased significantly, and the RSEI of Hetao Plain remained stable. The RSEI of Fenhe River Valley showed an increased trend. The ecological stability of Yinchuan Plain and Fenhe River Valley was relatively low, the ecological environment of Hetao Plain was relatively stable, and the ecological environment of Weihe River Plain continued to degrade. The results were important for regional ecological environment protection and agricultural sustainable development.

An Improved Multi-temporal and Multi-feature Tea Plantation Identification Method Using Sentinel-2 Imagery.

As tea is an important economic crop in many regions, efficient and accurate methods for remotely identifying tea plantations are essential for the implementation of sustainable tea practices and for periodic monitoring. In this study, we developed and tested a method for tea plantation identification based on multi-temporal Sentinel-2 images and a multi-feature Random Forest (RF) algorithm. We used phenological patterns of tea cultivation in China's Shihe District (such as the multiple annual growing, harvest, and pruning stages) to extracted multi-temporal Sentinel-2 MSI bands, their derived first spectral derivative, NDVI and textures, and topographic features. We then assessed feature importance using RF analysis; the optimal combination of features was used as the input variable for RF classification to extract tea plantations in the study area. A comparison of our results with those achieved using the Support Vector Machine method and statistical data from local government departments showed that our method had a higher producer's accuracy (96.57%) and user's accuracy (96.02%). These results demonstrate that: (1) multi-temporal and multi-feature classification can improve the accuracy of tea plantation recognition, (2) RF classification feature importance analysis can effectively reduce feature dimensions and improve classification efficiency, and (3) the combination of multi-temporal Sentinel-2 images and the RF algorithm improves our ability to identify and monitor tea plantations.

Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China.

In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC) was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of COD(Cr) and NH3N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well.

Satellite-derived estimations of spatial and seasonal variation in tropospheric carbon dioxide mass over China.

China has frequently been questioned about the data transparency and accuracy of its energy and emission statistics. Satellite-derived remote sensing data potentially provide a useful tool to study the variation in carbon dioxide (CO2) mass over areas of the earth's surface. In this study, Greenhouse gases Observing SATellite (GOSAT) tropospheric CO2 concentration data and NCEP/NCAR reanalysis tropopause data were integrated to obtain estimates of tropospheric CO2 mass variations over the surface of China. These variations were mapped to show seasonal and spatial patterns with reference to China's provincial areas. The estimates of provincial tropospheric CO2 were related to statistical estimates of CO2 emissions for the provinces and considered with reference to provincial populations and gross regional products (GRP). Tropospheric CO2 masses for the Chinese provinces ranged from 53 ± 1 to 14,470 ± 63 million tonnes were greater for western than for eastern provinces and were primarily a function of provincial land area. Adjusted for land area troposphere CO2 mass was higher for eastern and southern provinces than for western and northern provinces. Tropospheric CO2 mass over China varied with season being highest in July and August and lowest in January and February. The average annual emission from provincial energy statistics of CO2 by China was estimated as 10.3% of the average mass of CO2 in the troposphere over China. The relationship between statistical emissions relative to tropospheric CO2 mass was higher than 20% for developed coastal provinces of China, with Shanghai, Tianjin, and Beijing having exceptionally high percentages. The percentages were generally lower than 10% for western inland provinces. Provincial estimates of emissions of CO2 were significantly positively related to provincial populations and gross regional products (GRP) when the values for the provincial municipalities Shanghai, Tianjin, and Beijing were excluded from the linear regressions. An increase in provincial GRP per person was related to a curvilinear increase in CO2 emissions, this being particularly marked for Beijing, Tianjin, and especially Shanghai. The absence of detection of specific elevation of CO2 mass in the troposphere above these municipalities may relate to the rapid mixing and dispersal of CO2 emissions or the proportion of the depth of the troposphere sensed by GOSAT.