中部崛起与环鄱阳湖城市群的发展战略

城市群是区域经济的重要增长极。要在中部崛起中加快江西的发展,就必须构建以南昌为中心,九江、景德镇、鹰潭为次中心,涵盖22个县（市）的环鄱阳湖城市群,整合区域内经济、文化、科技和资源优势,加快区域交通、产业、商贸、产权、金融、技术、人才、信息市场一体化进程,使之成为中部地区最具竞争力的经济区。     

The use of MODIS 250 m bands to improve the MODIS 1 km ocean color atmospheric correction algorithm in turbid water

“Clear water” is a scale-dependent concept, so it is more likely to successfully find the “clear water” from images with smaller scale than that with larger scale data. In this study, an optimal spectral relationship of moderate-resolution imaging spectroradiometer (MODIS) 250 m and 1 km resolution data at near-infrared bands (OSRLM) is constructed for converting pseudo “clear water” reflectance at 859 nm to those at 748 and 869 nm. According to scale effects, the satellite-observed pseudo “clear water” reflectance is greater than 5.18%, larger than that derived from OSRLM model. An atmospheric correction model for MODIS 1km data using pseudo “clear water” reflectance of MODIS 250 m data (ACMM) was developed for improving the performance of traditional “clear water” atmospheric correction model (CWAC). The model validation results indicate that ACMM model has a better performance than CWAC model. By comparison, the uncertainty decreases by 19.18% in the use of ACMM model over CWAC model for deriving water-leaving reflectance in Taihu Lake, China. This uncertainty is significantly reduced in water-leaving reflectance estimation due to partial removal of scale effects on “clear water”. These findings imply that satellite-derived aerosol scattering contribution at smaller scale usually has a better performance than that at larger scale.     

SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data

An accurate and continuous monitoring of lakes and inland seas is available since 1993 thanks to the satellite altimetry missions (Topex–Poseidon, GFO, ERS-2, Jason-1, Jason-2 and Envisat). Global data processing of these satellites provides temporal and spatial time series of lakes surface height with a decimetre precision on the whole Earth. The response of water level to regional hydrology is particularly marked for lakes and inland seas in semi-arid regions. A lake data centre is under development at by LEGOS (Laboratoire d’Etude en Géophysique et Océanographie Spatiale) in Toulouse, in coordination with the HYDROLARE project (Headed by SHI: State Hydrological Institute of the Russian Academy of Science). It already provides level variations for about 150 lakes and reservoirs, freely available on the web site (HYDROWEB: http://www.LEGOS.obs-mip.fr/soa/hydrologie/HYDROWEB), and surface-volume variations of about 50 big lakes are also calculated through a combination of various satellite images (Modis, Asar, Landsat, Cbers) and radar altimetry. The final objective is to achieve in 2011 a fully operating data centre based on remote sensing technique and controlled by the in situ infrastructure for the Global Terrestrial Network for Lakes (GTN-L) under the supervision of WMO (World Meteorological Organization) and GCOS (Global Climate Observing System).     

Synergetic retrieval of terrestrial AOD from MODIS images of twin satellites Terra and Aqua

Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first.     

Snow-covered lake ice in GPS multipath reception – Theory and measurement

Speculary reflected signals from the ground can significantly affect the performance of Global Positioning System receivers. For this type of multipath condition, the received powers are primarily the sum of the speculary reflected and direct signals. These reflected signals can provide useful information about the land-surface composition. In this paper, we discuss the special case of a snow-covered frozen lake, with incident energy at 1.57542 GHz with right-hand circularly polarization at elevation angles between 2° and 40°. The relative received powers are computed and measured for various thicknesses of lake ice. The received powers for both theory and measurement have the same behavior throughout a range of elevation angles. The potential for inferring lake ice thickness is explored for a snow-covered lake ice case study.     

Calibration of Envisat radar altimeter over Lake Issykkul

This study presents the results of calibration/validation (C/V) of Envisat satellite radar altimeter over Lake Issykkul located in Kyrgyzstan, which was chosen as a dedicated radar altimetry C/V site in 2004. The objectives are to estimate the absolute altimeter bias of Envisat and its orbit based on cross-over analysis with TOPEX/Poseidon (T/P), Jason-1 and Jason-2 over the ocean. We have used a new method of GPS data processing in a kinematic mode, developed at the Groupe de Recherche de Geodesie Spatiale (GRGS), which allows us to calculate the position of the GPS antenna without needing a GPS reference station. The C/V is conducted using various equipments: a local GPS network, a moving GPS antenna along the satellites tracks over Lake Issykkul, In Situ level gauges and weather stations. The absolute bias obtained for Envisat from field campaigns conducted in 2009 and 2010 is between 62.1 and 63.4 ± 3.7 cm, using the Ice-1 retracking algorithm, and between 46.9 and 51.2 cm with the ocean retracking algorithm. These results differ by about 10 cm from previous studies, principally due to improvement of the C/V procedure. Apart from the new algorithm for GPS data processing and the orbit error reduction, more attention has been paid to the GPS antenna height calculation, and we have reduced the errors induced by seiche over Lake Issykkul. This has been assured using cruise data along the Envisat satellite track at the exact date of the pass of the satellite for the two campaigns. The calculation of the Envisat radar altimeter bias with respect to the GPS levelling is essential to allow the continuity of multi-mission data on the same orbit, with the expected launch of SARAL/Altika mission in 2012. Implications for hydrology in particular, will be to produce long term homogeneous and reliable time series of lake levels worldwide.     

Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m²·yr¹ during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions.