The Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA and several international collaboration agencies, aims to achieve high-resolution two-dimensional observations of global surface water. Equipped with the advanced Ka-band radar interferometer (KaRIn), it significantly enhances the ability to monitor surface water and provides a new data source for obtaining large-scale water surface elevation (WSE) data at high temporal and spatial resolution. However, the accuracy and applicability of its scientific data products for inland water bodies still require validation. This study obtained three scientific data products from the SWOT satellite between August 2023 and December 2024: the Level 2 KaRIn high-rate river single-pass vector product (L2_HR_RiverSP), the Level 2 KaRIn high-rate lake single-pass vector product (L2_HR_LakeSP), and the Level 2 KaRIn high-rate water mask pixel cloud product (L2_HR_PIXC). These were compared with in situ water level data to validate their accuracy in retrieving inland water levels across eight different regions in the middle and lower reaches of the Yangtze River (MLRYR) and to evaluate the applicability of each product. The experimental results show the following: (1) The inversion accuracy of L2_HR_RiverSP and L2_HR_LakeSP varies significantly across different regions. In some areas, the extracted WSE aligns closely with the in situ water level trend, with a coefficient of determination (R2) exceeding 0.9, while in other areas, the R2 is lower (less than 0.8), and the error compared to in situ water levels is larger (with Root Mean Square Error (RMSE) greater than 1.0 m). (2) This study proposes a combined denoising method based on the Interquartile Range (IQR) and Adaptive Statistical Outlier Removal (ASOR). Compared to the L2_HR_RiverSP and L2_HR_LakeSP products, the L2_HR_PIXC product, after denoising, shows significant improvements in all accuracy metrics for water level inversion, with R2 greater than 0.85, Mean Absolute Error (MAE) less than 0.4 m, and RMSE less than 0.5 m. Overall, the SWOT satellite demonstrates the capability to monitor inland water bodies with high precision, especially through the L2_HR_PIXC product, which shows broader application potential and will play an important role in global water dynamics monitoring and refined water resource management research.

土壤侵蚀是内蒙古自治区十大孔兑区域最严重的环境问题之一.为该区域生态环境的健康发展,本研究基于多源数据结合多种土壤侵蚀模型对 2021 年十大孔兑区域的土壤侵蚀做出评估,评估结果显示:2021 年十大孔兑区域土壤侵蚀面积为 4398.85 km2,占区域总土地面积的 40.86%,其中轻度、中度、强烈、极强烈和剧烈等级的土壤侵蚀面积分别为 2614.38 km2、1328.74 km2、276.29 km2、194.45 km2和40.15 km2,区域整体以中度和轻度侵蚀为主.基于评估结果本研究总结了十大孔兑区域土壤侵蚀的空间分布特点,并综合多因素对侵蚀特征进行分析,最终得到如下结论:(1)十大孔兑区域的水力侵蚀离散分布于孔兑上游,这是由地形地貌、植被覆盖等多个因素共合同作用导致的,其中地形地貌对侵蚀分布的影响相对较大;(2)十大孔兑区域的风力侵蚀聚集分布于孔兑中下游,中游的库布齐沙漠是孔兑中风力侵蚀最为严重的区域,风力侵蚀的分布受到土地利用类型和植被覆盖的影响较大;(3)十大孔兑区域的土壤侵蚀集中在达拉特旗、东胜区和杭锦旗境内,但由于各县区部分覆盖的侵蚀地貌不同,各县区在水力和风力侵蚀面积占比上有很大差异.

Rockfall is generally developed in high and steep mountain area, which is difficult to identify by ground surveys. In this study, a method combining UAV photogrammetry, UAV LiDAR and ground-based LiDAR technology is proposed for 3D data collection in the high vegetation coverage canyon areas, which is comprehensively applied to rockfall investigation and evaluation in the area around Yingxiu Hydropower Station. 7 potential rockfalls were identified in the study area. The remote controlling and large range data acquisition of the airborne LiDAR are combined with the high-precision, multi measuring station, multi angle and other characteristics of the ground-based LiDAR to obtain the real condition of the slope surface in the study area, which is conducive to rockfall identification.

Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area.

Surface soil moisture (SM) plays a decisive function during the grassland degradation and restoration process. In this paper, a surface soil moisture retrieval model in desert steppe area with improved spatial resolution is established using diurnal temperature range (DTR) and Normalized Difference Vegetation Index (NDVI). The model integrates land surface temperature (LST) at daytime and nighttime respectively derived from Landsat8 and MODIS images to improve the spatial resolution of soil moisture from 1km to 30m. The results are validated by in situ measurements from Frequency Domain Reflectometry (FDR) in study region, and the root mean square error (RMSE) is 1.3919. Compared with the MODIS-DTR, the Landsat-MODIS DTR improves the accuracy and the spatial resolution of soil moisture retrieval.

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

UAV (unmanned aerial vehicle) remote sensing system has advantages of strong real-time, flexible and convenient, little influence by the external environment, and the ability to work full-time. It can go deep into the places safely and reliably which staff can hardly arrived. The remote sensing system can be in response to emergencies to gain first-hand information as quickly as possible and have produced a unique emergency response to acquire an important basis for overall decision-making. However, UAV remote sensing system was so fast, flexible, low flying to carry on quick response to acquire high-resolution images. In the Wenchuan Earthquake, UAV remote sensing was applied successfully to acquire first-hand earthquake damage information in the short time under cloudy and rainy conditions of Sichuan Province. The system flow of UAV remote sensing to extract information on damaged houses after earthquake was set up successfully. Moreover, UAV remote sensing had an important role in mapping of damaged buildings after earthquake. Rapid identification of mapping of damaged buildings after earthquake with UAV remote sensing techniques can be carried out. UAV remote sensing techniques could have greater potentials for disaster mitigation and management after earthquake.

Remote sensing system fitted on Unmanned Aerial Vehicle (UAV) can obtain clear images and high-resolution aerial photographs. It has advantages of strong real-time, flexibility and convenience, free from influence of external environment, low cost, low-flying under clouds and ability to work full-time. When an earthquake happened, it could go deep into the places safely and reliably which human staff can hardly approach, such as secondary geological disasters hit areas. The system can be timely precise in response to secondary geological disasters monitoring by a way of obtaining first-hand information as quickly as possible, producing a unique emergency response capacity to provide a scientific basis for overall decision-making processes. It can greatly enhance the capability of on-site disaster emergency working team in data collection and transmission. The great advantages of UAV remote sensing system played an irreplaceable role in monitoring secondary geological disaster dynamics and influences. Taking the landslides and barrier lakes for example, the paper explored the basic application and process of UAV remote sensing in the disaster emergency relief. UAV high-resolution remote sensing images had been exploited to estimate the situation of disaster-hit areas and monitor secondary geological disasters rapidly, systematically and continuously. Furthermore, a rapid quantitative assessment on the distribution and size of landslides and barrier lakes was carried out. Monitoring results could support relevant government departments and rescue teams, providing detailed and reliable scientific evidence for disaster relief and decision-making.

Soil moisture (SM) plays a decisive function during the grassland degradation and restoration process. In this paper, SM in desert steppe is measured with various methods at different spatial scale, including point-, field- and regional-scale, and the SM results from FDR, CRS and remote sensing (RS) are verified mutually. The results show that CRS is adaptable to measure desert steppe, of which with FDR R 2 is 0.83 and RMSE is 0.0162kg/kg; substituting CRS SM validated for traditional point measurement to verify RS retrieval, a much stronger correlation is achieved with R 2 of 0.97 much bigger than that of FDR and RS, whose R 2 is only 0.80, proving quantifiably that CRS is obviously a new effective means for verifying SM of RS retrieval.

In order to research the adaptability of cosmic-ray neutron method in soil moisture measurement and serve the management and decision of animal husbandry, continuous monitoring was conducted by the Cosmic-Ray Sensing probe (CRS) in desert steppe. By comparing with measuring results of the Time Domain Reflectometry (TDR), the consistency of soil moisture measured by CRS and TDR and the sensitivity in response of soil moisture with both methods to rainfall were researched. Results show that a good consistency of soil moisture measured by CRS and TDR is achieved and that TDR isn’t sensitive to rainfall, while CRS can not only respond quickly to rainfall but also reveal clearly corresponding changes of soil moisture led by different rainfalls. It’s concluded that cosmic-ray neutron method can measure soil moisture and reflect its dynamic change accurately in desert steppe and provide decision basis for the modern animal husbandry management.

Regional river basins, transboundary rivers in particular, are shared water resources among multiple users. The tempospatial distribution and utilization potentials of water resources in these river basins have a great influence on the economic layout and the social development of all the interested parties in these basins. However, due to the characteristics of cross borders and multi-users in these regions, especially across border regions, basic data is relatively scarce and inconsistent, which bring difficulties in basin water resources management. Facing the basic data requirements in regional river management, the overall technical framework for remote sensing monitoring and data service system in China's regional river basins was designed in the paper, with a remote sensing driven distributed basin hydrologic model developed and integrated within the frame. This prototype system is able to extract most of the model required land surface data by multi-sources and multi-temporal remote sensing images, to run a distributed basin hydrological simulation model, to carry out various scenario analysis, and to provide data services to decision makers.

Floods disaster is a kind of common natural disasters and it has great destructive power for people's lives and property.The study of floods affected areas is significant for disaster damage assessment,reconstruction,etc.For the analysis of floods disaster,this paper proposed a method to analyze floods based on local autocorrelation statistics according to the study of spatial autocorrelation.First,masking the images and removing the interferences of clouds on the images.Next,using the local autocorrelation statistics to analyze three images.Then,extracting water by density segmentation method and dividing every image into two bodies of water and land.Finally,overlaying the three classification results and analyzing the disaster situations of floods.An experiment was designed by using the three period images of Nenjiang basin in 2013.Experimental results showed that this method could analyze the large affected areas relatively and accurately.

Drought occurs frequently in recent years with a lot of economic and social losses. The build of drought risk index frame, which is one of the effective ways assisting drought risk management of agriculture, helps to quantify and standardize drought risk evaluations. Based on a series of data related with drought on northwest Liaoning province, drought characteristic is analyzed. Depending on the form mechanism of drought risk, hazard, exposure, vulnerability, ability of preventing and decreasing drought disaster are considered to select typical indicators which describe the influences to drought well. Index frame of agricultural drought risk is then set up to supply scientific solutions for decreasing, rescuing and preventing drought disasters.

The purpose of this study is to make an attempt on establishing a method to assess water management for larger irrigated area using remote sensed information. Firstly, we analyzed the crop water consumption rule during the whole growing stage taking winter wheat as an example. Then the remote sensed assessment method of water use efficiency was established, which took remote sensed ET, biomass and observed precipitation as input data. Finally, the method was applied for the assessment of irrigation water use efficiency in Beijing Tongzhou district over the three growing seasons of 2003-2004, 2004-2005, 2005-2006 of winter wheat. In the end, the feasibility of this method is validated by comparison the results with year-to-year variation of statistical yields. The assessing results can be used for water managers and policy makers in improving irrigation water use efficiency.

The relationship between crop ET(Evapotranspiration) and yield is the theory base of agricultural irrigation management. Research on the interval amount of suitable crop ET is the most important headline of irrigation planning and water resources allocation. This paper, on the basis of previous field research works, taking winter wheat as an example, firstly analyzed the rule of crop water consumption during the whole growing stage and the relationship between ET and biomass, water productivity. Then, the relationship models of ET-biomass and ET-water productivity at the whole growing stage were established in Beijing by using remote-sensing ET and biomass, and the suitable water consumption interval for the winter wheat under the condition of non-sufficient irrigation was deduced[300mm,408mm]. At the last, the application characteristics and the main influences on the models were discussed. The paper provides scientific basis and reference for further research on improving crop water productivity and yield under the condition of non-sufficient irrigation in Northern semi-arid region.

Hydropower project may bring with it social-economic profits as well as side effects. The built dam and reservoir often cause some problems to the surrounding areas, among which the ecological and environmental effects caused by hydropower projects are always concerned by the public. In this article, we take the Ertan reservoir catchment as the research area and try to quantitatively analyze the variation of vegetation cover and soil erosion by remote sensing technique, and to comprehensively assess the evolvement and development trend of reservoir catchment. Soil erosion, land use/cover are used as ecological and environmental indicators which reflect the changes before, after and in the period of the construction of Ertan hydropower station. Supported by the multi-source remote sensing data (from satellite Landsat and CBERS) and DEM data, the land use/cover is interpreted through RS images which are classified both by unsupervised and supervised method, and the driving factors of the ecological changes are also analyzed. At the same time, the changes of soil loss are also monitored and analyzed during flood seasons of Ertan reservoir area before and after reservoir impoundment (1995, 2000 and 2005) using the revised universal soil loss equation (RUSLE). The results show that during the recent 13 years the arable land area has decreased obviously, and construction area and water surface have increased slightly. The increase of vegetation cover has some relations with the implementation of local ecological projects, i.e., de-farming to forestry and de-farming to pasture projects. At the same time, changes may also be caused by the climate adjustment in the reservoir area. In the ten years from 1995 to 2005, the high soil loss classes were transforming to lowly level classes continuously. All of these show that the soil loss of Ertan reservoir area is getting better.

Groundwater is not only an essential component of water resources,but also an extremely sensitive factor of the environment in Northwestern inner land basin.The groundwater dynamic could affect the evolvement of oasis,vegetation growth and development.The remote sensing technique,for its large-scale covering and cost-effective feature,may pay an important role in obtaining information of groundwater level in inner land basin where there is a paucity of basic hydrological data for backward developed monitoring systems.Ground surface reflection is significantly related to the depth of groundwater level for the very few precipitations in arid region.This paper aims to develop the groundwater level monitoring model for in arid region based support vector machine(SVM) regression method by using remote sensing.The spatial distribution and changes of ground-water level in time-series can be monitored and analyzed with vegetation and surface temperature information from the image radiation.The inputs of the model are the Normal Differential Vegetation Index(NDVI) and Land Surface Temperature(LST) data extracted from the MODIS images products,as well as the field observations of wells.Various kernel functions including the one-order polynomial,cubic polynomial and RBF function for SVM regression method are tested and simulated to find appropriate one for modeling.The research results in Shule River basin of Hexi corridor,Gansu Province illustrate that the model approach proposed is effective especially for the shallow groundwater level monitoring in arid region.The shallow groundwater levels with depth less than 3 meters fit the one-order polynomial kernel function better,and for greater groundwater depth more than 5 meters,it is even more suitable for selection of RBF kernel function or a cubic polynomial nuclear function method to simulate groundwater level.The research results could provide the basic approaches for the water cycle module and hydrology research,as well as support the sustainable water resources development and management in Northwest regions of China.

Drought is one of the major natural disasters which causes very severe impacts on economy and society in China and has become a bottleneck to sustainble development in the country.It is critical important to detect large area drought events timely and provide accurate early warnings for drought relief.Starting with a brief introduction to the general development of remote sensing technology home and abroad,this article provides with an overall summary of the current status on remote sensing for drough monitoring and remote sensing data-sources availability.Several main drought monitoring methods under use are discussed,such as thermal inertia method,canpoy temperature method,vegetation index method,microwave remote sensing method,etc.Some recommendations on imrpoving drought monitoring using remote sensing are put forward.This review article would be of help to facilitate the real operation of drough moitoring using remote sensing in China.

Since distributed spatial database will be the main data source of Internet CIS, we have to cope with the intercommunication between heterogeneous databases and systems. At fust, the paper analyses three means of dada sharing and the limitation of each means, then introduces the concept and specialties of CML. Based on the above, we design a mode for spatial data intercommunication between heterogeneous databases using GML.