A STUDY OF SOIL CONSERVATION MONITORING INFORMATION SYSTEM BASED ON REMOTELY SENSED DATA FOR A CATCHMENT ON THE LOESS PLATEAU

The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.

Research on Extraction Method of Surface Information Based on Multi-Feature Combination Such as Fractal Texture

Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.

Separate Analysis of Remote Sensing Information of Structures of Different Geological Periods and Quantitative Study of Corresponding Tectonic Stress Fields

The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.

The remote sensing composite information entropy and types of Nansha coral reef atolls

In the viempint that the coral reef atolls' growth index of the Nansha Islands is influenced by many factors, the measured remote sensing comopite information including some mutually related factors is divided into 10 geographic events as N1, N2 ..., N10, and the analysis of the atolls' information entropy is made. From the value of theentropy, the closed related factors with the index of the emerged atolls are shown. In proper order, the factors are reeftop's area(0. 319), lagoon's area(0. 324), open-degree of atoll(0. 336), trend of atoll(0. 551 ). On the basis of thiswork, a new description function of the emerged atoll growth index is proposed. This function can be used to identifythe open my of Nansha atoll growth.

Plotting the Sequential Rock Remote Sensing Information by Optimization Dichotomy Method

The sequential rock remote sensing information is a group of rocks that are correlative in space or in space and time. For the sake of plottiug them, someone had brought forward the optimization segn.entotion metkod. We have ased this method to plot the sequential rock remote sensing information at tbe remote sensing hyperspetral test field of Daqing mountain, Inner Mongolia Autonomous Region, China, and found some disadvantages of this method. Therefore, we put forward the optimization dichotomy to plot them, and get better results. Finally we make a conclusion.

THE CLIMATIC STUDY OF CHANGBAI MOUNTAIN BY INTEGRATION OF REMOTE SENSING INFORMATION AND GEO-CODED IMAGES

Ⅰ. INTRODUCTION Changbai Mountain is situated between E127°54′-128°08′, N40°58′-42°06′ about 2700 meters above sea level. It is the typical area of the mountainous climate in the monsoon area of the temperate zone on the globe. The well reserved primeval vertical distribution of natural landscape belts and the Natural Conservation of Changbai Mountains adopted by the UNESCO′s MAB Program cause the worldwide attention of geographers. Beside the complexity of the climatic structure itself, the mechanical effection of the high mountain body also effect the climate in the eastern part of China. In the mountain area where short of meteorological observation data, the climatic study by remote sensing is favorable for discovery and representation of climatic law in large area.

A New Generation of Intelligent Mapping and Remote Sensing Scientific Test Satellite Luojia-301

With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites,they have become an important support for obtaining global accurate surveying and mapping remote sensing information.At present,optical mapping and remote sensing satellites already have sub-meter spatial resolution capabilities,but there is a serious lag problem in mapping and remote sensing information services.It is urgent to develop intelligent mapping and remote sensing satellites to promote the transformation and upgrading to real-time intelligent services.Firstly,based on the three imaging systems of the optical mapping and remote sensing satellites and their realization methods and application characteristics,this paper analyzes the applicable system of the intelligent mapping and remote sensing satellites.Further,according to the application requirements of real-time,intelligence,and popularization,puts forward the design concept of integrated intelligent remote sensing satellite integrating communication,navigation,and remote sensing and focuses on the service mode and integrated function composition of intelligent remote sensing satellite.Then expounds on the performance and characteristics of the Luojia-301 satellite,a new generation of intelligent surveying and mapping remote sensing scientific test satellite.And finally summarizes and prospects the development and mission of intelligent mapping remote sensing satellites.Luojia-301 satellite integrates remote sensing and communication functions.It explores an efficient and intelligent service mode of mapping and remote sensing information from data acquisition to the application terminal and provides a real service verification platform for on-orbit processing and real-time transmission of remote sensing data based on space-ground internet,which is of great significance to the construction of China’s spatial information network.

A Predictive 6G Network with Environment Sensing Enhancement:From Radio Wave Propagation Perspective

In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.

RemotesensingstudiesintheHaikouBayCalculationofthedepositionparameters

By making use of the distinguishing features of repetitive imagery of the same area by satellite remote sens-ing, a method of extracting water areas at different tidal levels from the images of bays at different times was adopted toestablish a calculating model for tidal surface and a method of finding a sum by layers was used to establish a calculatingmodel for the deposition parameter. Moreover, by making use of the calculating models for the deposition parameter andfor tidal level, the deposition parameter for the sea area less than 0 m was calculated for the Haikou Bay at two differentperiods of time: during the period of 1965 ￣ 1984 the total amount of deposits was 4 . 8 x 106 m3, and the sedimentationrate was 2 . 5 x 105 m3/a; during the period from 1984 to 1990, the total amount of deposits was - 8 . 9 x 105 m3 and thesedimentation rate was -1 . 5 x 105 m3/a.

Monitoring of Pinus massoniana spatial pattern changes based on RS and GIS techniques

Our research focused on Pinus massoniana information extracted from remote sensing images based on the knowledge detection and decision tree algorithm and established a spatial pattern model, combining quantitative theoretical ecology with remote sensing （RS） and geometric information system （GIS） techniques. Applying information extraction methods and a spatial pattern model, we studied P. massoniana spatial patterns changes before and after the invasion by pine wood nematode （Bursaphelenchus xylophilus） in Fuyang and Zhoushan counties, Zhejiang Province, east China. The P. massoniana spatial patterns are clustering, whether the invasion happened or not. But the degree of clustering is different. Our results show good agreement with field data. Applying the results, we analyzed the relationship between spatial patterns and the invasion level. Then we drew the elementary conclusion that there are two kinds of patterns for pine wood nematode to spread： continuous and discontinuous diffusion. This approach can help monitor and evaluate the changes in ecological systems.

基于粒计算的广西北部湾经济区遥感生态环境时空变化

Accurate and rapid evaluation of the regional eco-environment is critical to policy formulation.The remote sensing ecological index(RSEI)model of the Guangxi Beibu Gulf Economic Zone(GBGEZ)during 2001-2020 was established and evaluated using four indices:dryness,wetness,greenness,and heat.This paper proposes an information granulation method for remote sensing based on the RSEI index value that uses granular computing.We found that:(1)From 2001 to 2020,the eco-environmental quality(EEQ)of GBGEZ tended to improve,and the spatial difference tended to expand.The regional spatial distribution of the eco-environment is primarily in the second-level and third-level areas,and the EEQ in the east and west is better than that in the middle.The contribution of greenness,wetness,and dryness to the improvement of EEQ in the study region increased year by year.(2)From 2001to 2020,the order of the contribution of the EEQ index in the GBGEZ was dryness,wetness,greenness,and heat.(3)The social and economic activities in the study region had a certain inhibitory effect on the improvement of the EEQ.

Sensorless Sensing with WiFi

Can WiFi signals be used for sensing purpose？ The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world＇s largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications.

Data Secure Transmission Model Based on Compressed Sensing and Digital Watermarking Technology

Since the Internet of Things（IoT） secret information is easy to leak in data transfer,a data secure transmission model based on compressed sensing（CS） and digital watermarking technology is proposed here. Firstly, for node coding end, the digital watermarking technology is used to embed secret information in the conventional data carrier. Secondly, these data are reused to build the target transfer data by the CS algorithm which are called observed signals. Thirdly, these signals are transmitted to the base station through the wireless channel. After obtaining these observed signals, the decoder reconstructs the data carrier containing privacy information. Finally, the privacy information is obtained by digital watermark extraction algorithm to achieve the secret transmission of signals. By adopting the watermarking and compression sensing to hide secret information in the end of node code, the algorithm complexity and energy consumption are reduced. Meanwhile, the security of secret information is increased.The simulation results show that the method is able to accurately reconstruct the original signal and the energy consumption of the sensor node is also reduced significantly in consideration of the packet loss.