This paper discuses the necessity of combining remote sensing images with professional maps in respects of the remote sensing imases's application potentialities and its developmental trend as well as the limitations of traditional professional maps, and expounds the guiding ideology and basic demand of making remote sensing professional images, at last, it takes "the satellite imase of trourism plan of Hainan provence"for example to introduce the methods of how to make professional images.

POS (Position and Orientation System) provides position and attitude information during aerial photography. There must be at least one reference GPS base station for traditional differential GPS (DGPS) positioning, and the establishment of a GPS station would be a very costly and difficult task in some areas. GPS Precise Point Positioning (PPP) has been advanced as a way to avoid the use of the GPS base station. This paper describes the approaches to the processing of an actual aerial photographic data by using both kinds of GPS positioning methods. The final results of the POS-supported aerial triangulation from PPP are compared with those from DGPS solution. The empirical results suggest that the accuracy of POS-supported aerial triangulation from PPP can satisfy the 1∶2 000 topographic map specifications for aerophotogrammetric office operation. It is feasible to process the POS data of ADS40 without a GPS Base Station by using Precise Point Positioning.

Texture plays a very important role in image retrieval and classification, and texture feature extraction has been a research hotspot. Most present existing texture extraction algorithms can be only used to calculate texture features of gray image. Texture extraction algorithm for color image is very few. Referring to the analytical method of gray level co-occurrence matrix (GLCM),the authors analyzed the influence law of parameters (direction,distance,grayscale,window size)on GLCM texture features of color image. A color image texture feature extraction method(color GLCM,CGLCM)based on GLCM was realized. Through analyzing the influence law of these parameters on four texture features(ASM(angular second moment),Entropy,Contrast,Correlation),a proper parameter value range was given and the CGLCM method was optimized. The results of comparing CGLCM method with GLCM method show that the four texture features calculated with CGLCM method have better robustness and identification capability. These results can provide reference for image retrieval and classification based on texture information.

The coastal terrain of Zhejiang is complex. It is impossible to use the traditional way to measure the tideland heights of many beaches or offshore islands. With UAV remote sensing technology and tidal observation, the tideland height can be measured, and the difficult problems of artificial measurement can be solved, thus greatly improving the efficiency. Firstly, in combination with existing data, the aerial region and tide information are determined.Secondly,the UAV aerial operations and tidal observations are implemented outside synchronization. Finally, the boundary between tide and coast are interpreted and drawn with high-precision remote sensing image data (DOM), the tidal observation data are interpolated to update tideland height. The results show that this technology can quantitatively describe the tideland height information and is hence a new method of tideland height measurement.

Since the availability of global runoff data decrease year by year, the inversion algorithms, as substitutes for the river discharge measured at hydrological stations, have become increasingly important. With the continuous development of satellite remote sensing technology, the methods for estimating river discharge have increased in number. This study systematically summarized the remote sensing-based inversion methods for river discharge, as well as the inversion methods for hydraulic remote sensing elements that are closely related to the estimation of river discharge and the progress made in them. Moreover, this study reviewed the methods, principles, and application status of two types of algorithms based on hydrological models and empirical regression equations and summarized the applicable conditions and shortcomings of different methods. Finally, this study predicted the worldwide development trends of the river discharge inversion based on the satellite remote sensing technology, including ① actively developing the advanced data assimilation technology for satellite remote sensing data; ② integrating new sensor products; ③ optimizing and innovating algorithms.

Snow proves to be both an important factor in characterizing the surface cryosphere and a critical parameter for weather and hydrological phenomena. Employing remote sensing to conduct long-term and large-scale monitoring of snow morphologies and their changes plays a vital role in research into global climate change, investigations into hydrology and water resources, and geological disaster prevention. After decades of development, significant progress has been made in the field of remote sensing-based snow monitoring technology both in China and abroad. Accordingly, the products for remote sensing-based snow monitoring have become increasingly abundant, and the snow-orientated inversion algorithms have been continuously improved. This paper provides a summary of the existing, widely applied products after categorizing them into three types: snow-cover extent (SEC), snow coverage, and snow depth/snow water equivalent (SWE) products. Furthermore, this study organizes the commercialized remote sensing inversion algorithms used in existing, typical SEC and SWE products. The review of advances in the relevant scientific research reveals that, with the constant presence of sensors with high temporal and spatial resolutions in China and abroad and the support of both novel optical and microwave data sources and new technologies, researchers have gradually improved the accuracy of snow-orientated inversion algorithms by optimizing these algorithms based on regional characteristics. This will provide more support for continuously improving remote sensing-based snow monitoring products in the future.

Inland surface water bodies, including rivers, lakes, and reservoirs, are significant freshwater resources for human beings and ecology, and their monitoring and control are greatly significant. Optical remote sensing provides great convenience for the monitoring of surface water resources, proving to be an important means for the information extraction and dynamic monitoring of inland surface water bodies. This study reviews the basic principles, remote sensing data sources, methods, existing issues, and prospects of the information extraction of water bodies. Owing to the unique characteristics of the remote sensing images of inland surface water bodies, their information can be extracted in an accurate, scientific, and effective manner using remote sensing. Multiple remote sensing data resources can be applied to the information extraction, and the optical remote sensing-based extraction methods include the threshold value method, classifier method, object orientation method, and deep learning method. Given that different methods have unique advantages, disadvantages, and applicable conditions, selecting appropriate multi-source data and varying methods based on the conditions of study areas tend to improve the information extraction accuracy. Nevertheless, there still exist some issues in the optical remote sensing-based water body information extraction, such as the balance of spatiotemporal resolution of remote sensing data, the information mining of water body characteristics, the generalization ability of water body models, and the uniformity of criteria for accuracy evaluation.

In this paper, Wuhan City was selected for case study. Land use information obtained from satellite remote sensing TM image in 2000 and 2005 was used as the main data source, and the GIS technology was employed as the data integration analysis platform. An ecological risk index was constructed based on the varieties of land use, and the systematic sampling method was utilized to make it a spatial variable. After the performance of sampling, the semivariagram analysis and block kriging were conducted to compile the map of ecological risk distribution. The results indicate that the spatial distribution of ecological risk became more uneven in the working area. The level of the ecological risk study area was divided into three levels: the majority of the vegetation and the waters belonged to the low ecological risk area, whereas the urban built-up area and its marginal areas belonged to moderate ecological risk and relatively high risk areas. Spatial distribution of areas of various levels experienced certain extent of changes in the five years.

The energy of electromagnetic radiation which is accepted by most detectors using as Remote Sensing comes mainly from the reflection of the earth surface to solar radiation energy.This reflection is related to the relative positions between the sun and the earth. Then the solar angles which represent the relative positions is quite important in the research of Remote Sensing.This paper gives a detailed and whole method for calculating the solar angles, such as solar right ascension, solar declination, solar hour angle,solar vertical angle, solar zenith angle, and so on.The main idea for the method depends on the theory and method of celestial mechanics. At first, it is neccessary solving six elements of orbit argument of perigee of mean spring equinox (ω), mean anomaly (M), eccentricity (e), major axis of orbit (α), mean obliquity (i) ,and right ascension of ascending node(Ω), Then mean solar right ascension and mean solar declination are gained by solving Kepler eqduation on the basis of the six elements of orbit. True solar right ascension and true solar declination are computed by correcting nutations and precessions of mean solar right ascension and mean solar declination. The calculating of solar hour angle is that the sidereal time is firstly computed, and then the sidereal time minus solar right ascension is solar hour angle. The formula for computing solar vertical angle (h) is sin (h)=sin (δ)×sin+ cos (δ)×cos×cos (t) given solar declination (δ), solar hour angle (t), and the latitude of earth surface . Finally, ninety degrees minus solar vertical angles solar zenith angle.At last in the paper, there are some examples about the application of these solar angles on the research of Remote Sensing.

Algorithms for identifying convexity-concavity of a simple polygon has a very important application in many fields. The authors analyzed the present popular algorithms for identifying convexity-concavity of a simple polygon such as angling method, left-right-point method, vector-area method, vector-product method, raying method, slopping method and extremity-vertices-order method. A detailed derivation of these algorithms has revealed that these algorithms can all use the formula b=p*m as the expression, and are equivalent to each other in nature; nevertheless, the pole-order method still have some problems to be further studied. Based on an analysis of the computation, the authors hold that theoretically the vector-product method, the slopping method and the raying method could be used effectively in programming.

A new approach to the fusion of multifocus images based on wavelet transform is proposed to solve the problem that some parts of the images are blurred because of the different focus points. The images are firstly decomposed by using wavelet transform, and then the low and high frequency coefficients are fused by using different fusion strategies: the low frequency coefficient is fused with a rule weighted average of energy, while the high frequency coefficient is processed with the regional grads. After that the fused image is obtained by inverse wavelet transform. Experiments prove that the fused image obtained by the method has a better subjective visual effect and objective evaluation criteria, thus attaining a better result than other traditional fusion methods.

The vegetation optical depth (VOD) serves as a microwave-based method for estimating vegetation water content and biomass. Compared to optical remote sensing, the satellite-based VOD, exhibiting a lower sensitivity to atmospheric disturbances, can measure the characteristics and information of vegetation in various aspects, thus providing an independent and complementary data source for global vegetation monitoring. It has been extensively applied to investigate the effects of global climate and environmental changes on vegetation. Discerning the research advances of VOD application in the dynamic monitoring of global vegetation is critical for VOD’s further development and application. Hence, this study first presented the primary methods for obtaining the VOD through inversion of passive and active microwave data, comparatively analyzing the principal characteristics of various sensor VOD products. Then, this study generalized the current research advances of VOD in the dynamic monitoring of vegetation in terms of vegetation characteristic monitoring (like vegetation water content and biomass), carbon balance analysis, drought monitoring, and phenological analysis. Finally, this study expounded the advantages, limitations, and improvement approaches of VOD products, envisioning the application prospect of VOD in the dynamic monitoring of vegetation.

Hyperspectral image is a new kind of remote sensing images with the feature of "combining mapping and spectra into one",thus better expressing the subtle differences on the surface of the material through the continuous spectral curve. Hyperspectral images have a wide range of applications in such aspects as classification,unmixing and target detection. With the continuous development of hyperspectral remote sensing technology,anomaly target detection has become one of the most active direction of research because it doesn't need a priori information. Many anomaly target detection algorithms have been proposed. Based on data available both in China and abroad,this paper summarized the research situation and new progress in anomaly detection algorithms. The author first expounded the essence of hyperspectral anomaly target detection and used the basic theory and then analyzed and summed up some representative anomaly detection algorithms in such aspects as the ideas of algorithm,key technology,advantages and disadvantages. On such a basis, the author summarized and described the evaluation method of anomaly detection and discussed the future development trend of anomaly target detection algorithm, with the purpose of finding new breakthroughs in the study of the algorithm of hyperspectral anomaly target detection.

On the basis of a detailed discussion on the principle of GB InSAR, the main data processing and analysis stages for estimating deformations starting with the GB InSAR observations are described. This paper gives a review of the main types and development trend of ground-based radar system, the main application domain and some existent problems of GB InSAR, and then summarizes the pros and cons of ground-based and space-borne InSAR for deformation monitoring.

A comparison with traditional soil moisture monitoring methods shows that the remote sensing method has great superiority. This paper presents a review of the remote sensing methods currently used both in China and abroad for monitoring soil moisture, which include the reflectivity method, the vegetation index method, the surface temperature, temperature-vegetation index method, the crop water stress index method, the thermal inertia method and the microwave method, with a detailed comparative description of the advantages and disadvantages of these methods. Based on summarizing researches on remote sensing monitoring methods for soil water, this paper evaluated the focal points, difficulties and development trend of this research field. It is held that the thermal inertia method and the vegetation temperature index method are relatively mature methods for soil moisture monitoring. With the wide application of geographic information system, the microwave remote sensing will become the key research direction in this field because of its unique advantages.

Soil salinization is identified as a major cause of decreased soil fertility, productivity, vegetation coverage, and crop yield. Optical remote sensing monitoring enjoys advantages such as macro-scale, timeliness, dynamics, and low costs, rendering this technology significant for the dynamic monitoring of soil salinization. However, there is a lack of reviews of the systematic organization of multi-scale remote sensing data, multi-type remote sensing feature parameters, and inversion models. This study first organized the optical remote sensing data sources and summarized the remote sensing data sources and scale platforms utilized in current studies on saline soil monitoring. Accordingly, this study categorized multi-source remote sensing data into three different platforms: satellite, aerial, and ground. Second, this study organized the mainstream characteristic parameters for modeling and two typical inversion methods, i.e., statistical regression and machine learning, and analyzed the current status of research on both methods. Finally, this study explored the fusion of remote sensing data sources and compared the pros and cons of various modeling methods. Furthermore, in combination with current hot research topics, this study discussed the prospects for the application of data assimilation and deep learning to soil salinization monitoring.

Cloud cover is the main factor affecting the quality of remote sensing image. Cloud detection for remote sensing images is one of the principal problems that must be solved in remote sensing data restoration processing. On the basis of extensive investigation of existing articles, the research status of cloud detection is analyzed, and then a classification and comprehensive overview of cloud detection methods is presented, the cloud detection methods for several kinds of commonly used satellite data are also given. By comparing the cloud detection methods, the existing problems and development trend of cloud detection method are discussed.

Oil spill is one of the main sources of pollution to the marine environment. Early monitoring of oil spill is very important for marine environment protecting. In this paper, the calculation of radar backscattering based on the wave spectrum was carried out, and a review of the study of the damping ratio of wave spectrum in consideration of the films characteristics, water molecular tension, elastic model and surface tension was carried out. The problem of insufficient research on the damping of the oil spill remote sensing monitoring with the wave spectrum and the quantitative calculation of the damping was discussed. The research on the damping of the oil spill for remote sensing monitoring in the future may be based on the backscattering characteristics of the real ocean wave spectrum under the cover with oil slicks. The research on radar coefficient calculation can provide support for quantitative analysis of the damping characteristics of oil spills, thus improving the accuracy of oil spill remote sensing monitoring.

In the context of achieving peak carbon dioxide emissions and carbon neutrality, conducting a remote sensing-based ecological assessment and monitoring analysis is greatly significant for ascertaining the ecological condition in time and formulating scientific and reasonable ecological protection policies. The early remote sensing-based ecological assessment indices, simple and involving complex processes, are difficult to find wide applications. In contrast, the remote sensing ecological index (RSEI), contributing to elevated assessment efficiency, has been extensively used. To gain a deeper understanding of RSEI, this study describes its background, calculation method, and research status and provides a summary of the current issues and regional adjustments. Furthermore, it analyzes the main application directions of RSEI, namely the in-depth analyses of regional ecological assessment and change monitoring. Finally, the study proposes that despite a broad space for RSEI development, it is necessary to conduct research into the spatiotemporal scales of images, storage and batch processing capabilities, model adaption, and intelligentization.

Guizhous Karst rocky desertification is most serious in China. The analysis of the evolution features could provide the objective basis for the tackling and transformation of rocky desertification. The survey of the rocky desertification was based on the three phases of remote sensing images spanning 20 years (at the end of the 1980s, the end of the 1990s and the year of 2008). On the basis of geometric correction, image registration, image mosaic, radiometric correction, and information enhancement and in combination with the field examination and artificial interpretation, researchers obtained the limestone distribution map, the rocky desertification distribution map, the rocky desertification evolution map and the data base. Comparison and analysis show that, from 1988 to 1999, the rocky desertification of Guizhou Province became more and more serious, and the annual average degradation area increased by 744 km²; nevertheless, from 1999 to 2008, the area of degradation became smaller and smaller, and the degradation area was reduced by 1 153.3 km² per year. In combination with the evolution features of rocky desertification in Guizhou Province, this paper deals with the relationship of decrease of agricultural population, the development and utilization of marsh gas, the increase of per head income and the policy of conversion of cropland into forest to the evolution regularity of rocky desertification, with the purpose of providing objective grounds for the further tackling and transformation of rocky desertification.

The target motion information extraction technology described in this paper uses satellite remote sensing to detect ground moving targets and estimate its motion parameters. It is one of the important application directions of remote sensing images and has been widely used in traffic monitoring and military remote sensing. As an excellent tool for the study of large-scale target motion characteristics, the high-resolution optical satellite image has more obvious texture features and richer information. After summarizing the research progress of moving targets in optical satellite imagery, this paper describes the methods of moving target detection and motion parameter estimation according to the process of target motion information extraction from high-resolution optical satellite image. Meanwhile, the principle and ideas of a novel method which is based on sequence panchromatic satellite images to detect moving target are introduced. In the end, based on analyzing the weaknesses of existing target motion information extraction research in data source and algorithm, it is pointed out that the target motion information extraction is developing towards automation, intellectualization and real-time.

In order to evaluate the white roof plan for quantitative alleviation of the urban heat island effect, the authors, adopting Shanghai as a study area and based on remote sensing, obtained the data of roof reflectance. By using Hottel model, the sun sunny hourly irradiance was simulated, and the city's rooftops in the absorption of solar radiation were employed to simulate the process under different values of reflectance. According to the "white roof plan", the authors estimated that the temperature of island intensity in the study area can reduce 1.32 ℃ during the lunch period in summer. In combination with the white roof heat transfer model, the authors also estimated that, in the house with white rooftop in summer, the air conditioning energy efficiency can be up to 12.60%.

Leave water reflectance is an important parameter in the study of water optical characteristics. To better interpret the effect of cyanophytes contamination on water optical characteristics, the authors conducted in situ measurement of spectral reflectance and water sampling in the Taihu Lake on 10 and 11, November 2008. Remarkable effects were observed in leave water reflectance of the cyanobacterial water, leading to an obvious absorption peak in the red region and an increase in the near-infrared region. Equivalent leave water reflectance based on FY-3A and MODIS band settings was derived by using the spectral response functions. Furthermore, the authors used the Ration Index (RI) model for the estimation of chlorophyll-a on 12, November 2008, and observed high determination coefficients R2=0.72, which were further used to map the chlorophyll-a distribution. The results obtained will be helpful to the further evaluation of optical characteristics and water quality.

Acquiring the number of building floors can provide data support and decision-making services for urban safety and disaster hazards. The number is primarily acquired through manual investigation and statistics currently. Furthermore, the automatic inversion of building heights based on remote sensing images suffers from low algorithmic efficiency, incomplete extraction, and a low automation degree. To acquire the number of building floors quickly and extensively, this study designed an identification algorithm based on GF-7 satellite images. First, shadow lines were automatically extracted using the fishing net method based on preprocessing such as principal component analysis. Then, the building height was calculated based on the geometric relationship formed by the shadow, and the building height was then converted into the number of building floors. Finally, the error in the extraction results was corrected through support vector machine regression, aiming to eliminate the influence of the measurement error of the shadow length. With Chaoyang District in Beijing as the study area, this study conducted model training and testing of the identification algorithm. As shown by the experimental results with Zhengzhou City in Henan Province as the verification area, the overall identification accuracy was 90.21%, with an identification error of three floors at most for buildings with 6~50 floors. This study provides novel technical support and application service for automatically acquiring the number of building floors rapidly and extensively based on satellite data.

With the in-depth development of the national fitness movement in China, the public’s health awareness has significantly increased, but sports and fitness facilities have gradually been unable to meet the people’s growing need for fitness. Based on the review and summary of the historical development, application scope, and application means of the geographic information system (GIS) technology in national fitness, this paper concludes that the GIS is primarily applied to the spatial data analysis, the resource allocation of fitness facilities, and the query and retrieval of fitness information in the field of national fitness by means of the spatial distribution characteristics analysis, accessibility assessment, and correlation verification of national fitness facilities. The GIS technology can efficiently address the issues concerning the layout of sports and fitness facilities, thus facilitating physical exercise activities of the public and significantly improving the effects of national fitness activities. Furthermore, the GIS technology will provide more effective technical support for national fitness activities in the scientific and technological progress and the development of multidisciplinary research.

Taking the interaction between spatial and temporal resolution of remote sensing data into consideration, the authors hold that there is no satellite sensor that can produce images with both high spatial and temporal resolution, and spatiotemporal fusion of remote sensing data is an effective method to solve this problem. This paper introduces main research achievements of spatiotemporal fusion model obtained both in China and abroad. Based on the comparative analysis of the mainstream fusion models, these models can be divided into two categories, i.e., the transformation-based model and the pixel-reconstruction-based model. Furthermore, the authors divide the pixel-reconstruction-based model into mixed linear model and spatial and temporal adaptive reflectance model, and then introduce the basic principles, methods of these models. This paper makes a comparative analysis of the advantages and disadvantages of various aspects of the model. At last, the data, application and scale prospect of spatiotemporal fusion models are put forward.

The composition of the low-altitude unmanned aerial system is described, and then the single image correction method,the after stitching correction method and the aerial triangulation method of mapping by using the UAV images are proposed according to their small scene and high resolution of the UAV images. The key points of the three different mapping methods are emphatically discussed, and the three methods are jointly analyzed and tested according to their mapping effect, accuracy and efficiency. The results demonstrate that the after stitching correction method has higher efficiency, and the aerial triangulation method has better accuracy, with the single image correction method in between, as evidenced by judging the efficiency and accuracy.

 The extraction of road from the high resolution remote sensing image remains an open question in spite of the fact that lots of efforts have been made in this area. This paper describes the road feature, road model and the basic idea, analyses the methods for road extraction. The thought and the plans of further research on this subject are also presented.

This study aims to evaluate and analyze the geology of mines in Ili Valley and investigate the countermeasures for ecological restoration therein. Utilizing the mining development status derived from remote sensing data and the remote sensing survey results of geological environment, as well as multi-source geological, socio-economic, and meteorological data, this study built a hierarchy structural model using analytic hierarchy process (AHP) and assessed the geological environment of mines in the Ili Valley, The results indicate that the severely affected areas are relatively concentrated, accounting for 4.61% of the total area of Ili Valley. The moderately severely affected areas present a continuous distribution. These areas overlap with each other, exhibiting indistinct boundaries. The generally affected areas are primarily distributed in extremely high mountain areas, medium to high mountain areas, and low mountain and hilly areas. The unaffected areas are primarily distributed in the alluvial plain area in the central part Ili River Valley and the plain area of the Zhaosu Basin. The areas with high ecological carrying capacity are mainly concentrated in the central region except for the south of Zhaosu County and Tekes County, the eastern edge of Nilka County, and the northern area of Khorgos. This study proposed corresponding ecological restoration and management measures and countermeasures against major geological issues. The findings of this study can provide basic data and technical support for the sustainable development of the ecology and the rational exploitation of mine resources in the Ili Valley. Additionally, these findings can serve as a case study for monitoring and assessing the geology of mines in arid and semi-arid areas.

Determining the present distribution of historically abandoned mines nationwide and carrying out orderly ecological rehabilitation of these mines are important parts in the preparation of mine ecological rehabilitation planning and serve as the main bases for the deployment of ecological rehabilitation engineering. This study proposed the technical process and method for determining the historically abandoned mines according to the definition of historically abandoned mines and the public management requirements. This technical method was proven effective through tests.

 This paper has dealt with the evaluation indices and factors of urban gardening and greening, analyzed the requirements of the system, designed the function and structure of Kunming gardening and greening management information system based on GIS, explained the reasons for the appearance of polygon fragments in the urban gardening and greening data, proposed the solution of the polygon merger and achieved the automatic merger of polygon fragment. According to the classification criteria of urban greening and China's urban gardening and greening indices, the authors have realized the calculation of three indices of Kunming greening programming, urban gardening and greening classification and the data updating.

In order to realize the refined line inspection management of transmission lines, improve its operation and maintenance efficiency, realize satellite intelligent inspection, and accurately find the defects and hidden dangers of towers and transmission lines, the paper took the coordinates of transmission line towers in Kunming City, Yunnan Province as an example and proposed a method to calibrate the coordinates of transmission towers using satellite images. The method first uses the reference base-map data as the basis to match the control points and uses the digital elevation model (DEM) to perform geometric correction on the original remote sensing image. Then combined with such technologies as shadow detection and edge detection and visual interpretation, the calibrated tower coordinates are obtained. The experiment verified the geometric correction accuracy of the SuperView-1 (SV1) and Gaofen-2(GF2) satellite images in the Kunming area, and the errors in the plane after correction were 0.931 and 1.387 m, respectively. In addition, the experiment verified the calibration accuracy of the old tower coordinates on the two lines. The results show that the plane accuracy of the tower has increased from 13.811 m and 8.256 m to 5.970 m and 5.104 m, respectively, which meets the basic power grid requirements. This method can realize the calibration of the tower coordinates, reduce the workload of manual inspection, and improve the efficiency of line inspection. With the explosive growth of remote sensing image data, multi-source images from the space and ground will continue to be combined, and the technology for the positioning of transmission towers based on satellite remote sensing images will have a broader development prospect.

Crop seeds are the most basic and original means of production in the planting industry. The selection of high-quality seeds directly determines the economic and production benefits in the agricultural production process. Hyperspectral imaging technology emerged in the 1980s, which has the characteristics of non-destruction, rapid imaging and “integration of atlas”. Previous studies of crop seeds using hyperspectral imaging technology mainly focused on the variety identification, vigor detection, and seed quality of crop seeds. In this paper, based on the previous research, the authors summarize and refine the data processing models, which include such methods as partial least square method, Ada-Boost algorithm, limit learning machine (ELM), random forest (RF), support vector machine (SVM), and artificial neural network (ANN). To sum up, the purpose of this paper is to provide the best spectral range, sample types, noise reduction methods, feature band extraction, model building and other aspects as the basis for various types of crop seed research, and to provide suggestions for future research direction.

To obtain the fundamental data of mine environments objectively, this study monitored the damaged mining land and the ecological restoration land in abandoned open-pit mines in China by combining remote sensing data with multi-source data, computer automated information extraction with human-computer interactive interpretation, and comprehensive laboratory research with field investigation. The remote sensing monitoring in 2022 shows that the mining land of abandoned open-pit mines in China covered an area of 82.74×10⁴ hm², representing 0.86‰ of the national land area, primarily distributed in Inner Mongolia and Xinjiang Uygur autonomous regions as well as Hebei, Shandong, and Heilongjiang provinces. Among them, the damaged mining land and the ecological restoration land accounted for 50.74×10⁴ hm² and 32.00×10⁴ hm², respectively, with an ecological restoration rate of 38.68%. The mining land of abandoned open-pit mines occupied primary farmland of 2.63×10⁴ hm², representing 3.18% of the total mining area. The mining land of nationwide abandoned open-pit mines within the ecological red line accounted for 8.09×10⁴ hm², representing 9.77% of the total mining area. The mining land of nationwide abandoned open-pit mines, coinciding with the result of the third national land resource survey (mining land), totaled 30.13×10⁴ hm², representing 36.42% of the total mining area. This study preliminarily analyzed the present situation and existing problems of remote sensing work involving the mining land of nationwide abandoned open-pit mines, the occupation of primary farmland, the mining land of such mines within the ecological red line, and corresponding environmental restoration and governance. Finally, this study proposed countermeasures and suggestions in this regard.

High-resolution remote sensing images have been widely applied to classification of ore deposits. However, there is a lack of studies on the information extraction and dynamic monitoring of open-pit lateritic nickel deposits. Using high-resolution remote sensing images from the Pleiades and GF-2 satellites, this study investigated the famous open-pit Tagaung Taung nickel deposit in Myanmar. First, information about surface features was extracted using object-oriented classification based on hierarchical multi-scale segmentation. Then, the dynamic changes in the nickel deposit were analyzed. Finally, qualitative and quantitative assessments of the classification accuracy were carried out. The results indicate that the hierarchical multi-scale segmentation technology exhibited encouraging classification and identification effects, with overall classification accuracy of 94.24% and 89.02% and the Kappa coefficients of 0.889 and 0.816, respectively for images from the Pleiades and GF-2 satellites. Therefore, the proposed method is suitable for the information extraction of open-pit lateritic nickel deposits. The dynamic change analysis reveals that the Tagaung Taung nickel deposit experienced continuous expansion of mining at high mining speeds from 2015 to 2017. It can be inferred that this deposit has great potential and broad prospects for resource development. The results of this study can provide technical support for the dynamic monitoring of the Tagaung Taung nickel deposit in Myanmar.

Remote sensing technology can play an important role in metallogenic prognosis. The study of foundational geology and ore-forming theory is the basis of metallogenic prognosis. The theoretical innovation of metallogenesis will expand the scope and direction of ore prediction, and can change the traditional prospecting thoughts. Remote sensing technology has much superiority over conventional geological investigation in such aspects as the ore-control factor interpretation, the extension of the mineralization belt, the tone anomaly caused by mineralization, the annular imagery controlled by mineralization，the geomorphic feature for prospecting, the mineralization information extraction and the comprehensive analysis of multi-source geoscience information. According to the results of ore prediction conducted in western China, this paper sums up a set of metallogenic prognosis methods and procedures based on remote sensing technology.

 

In data processing, data are usually obtained through coordinate conversion. The cadastral parcel is one of the most important objects, and the area of a parcel is the key attribute with legal authorization. However, the parcel area based on the conversion data is different from the original area. In this paper, the authors have developed a relational equation of area computation with coordinate conversion parameters, which is a simple and convenient method for area computation. Theoretical analysis and case studies show the correctness of the equation of area calculation with coordinate conversion parameters. It is concluded that the area conversion parameters in area adjustment are easier to be detected and hence the scheme of the coordinate conversion can be selected correctly.

Combined with the positioning and orientation system (POS), the airborne LiDAR system acquires the three dimensional coordinate information of ground objects, and has the capability of fast generation of high-precision digital elevation model (DEM). DEM is a basic map for landslide investigation and monitoring. Its precision can reflect the small ground surface changes directly. The DEM can be used to quantitatively analyze landslide characteristics accurately. There are several advantages of airborne LiDAR technology: it is affected little by weather, it can penetrate the vegetation layer to obtain the ground surface information and its data-processing process is relatively simple. In this paper, the LiDAR technology was applied in Zhangjiawan Village, Zigui County, Hubei Province. The results show that, based on LiDAR technology, landslides can be recognized clearly with slide mountain shadow maps made with high precision DEM and, what is more, quantitative analysis can be carried out to measure landslides characteristics.

The remote sensing-based feature extraction of opencast mining areas is a hot topic in research on the monitoring of mining activities. However, there is a lack of systematic reviews and summaries of relevant studies. Therefore, this study first defined the features of an opencast mining area, divided the feature extraction into single- and multi-feature extractions according to feature types, and briefly described the differences between the feature extraction of opencast mining areas and general surface feature extraction and land use classification. Then, this study briefly summarized the sources and data processing platforms of remote sensing images available in relevant studies. Subsequently, this study divided the remote sensing-based methods for the feature extraction of opencast mining areas into three categories, namely visual interpretation, traditional feature-based approach, and deep learning. Then, it summarized the research status of these methods and analyzed their advantages, disadvantages, and applicability. Finally, this study proposed the future research direction of the remote sensing-based feature extraction of opencast mining areas, holding that the future developmental trend is to further promote the intelligent, fine-scale, and robust feature extraction of mining areas by effectively utilizing multi-source and multi-temporal data, networks with a stronger feature extraction capacity, and methods for the optimization of complex scenes. The results of this study can be used as a reference for the study and application of remote sensing-based feature extraction of opencast mining areas.

Soil salinization is one of the important factors that affect the soil health in the arid area, so it is very important to obtain the information of soil salinity and monitor the change of soil salinity for the rational use of land resources and soil restoration in the arid area. Based on 52 soil samples collected in the field and Landsat 8 OLI remote sensing images obtained at the same time, the correlation and curve regression analysis were used to quantitatively analyze the correlation and fitting degree between the soil salinization evaluation index based on multispectral remote sensing data and the measured soil Electrical Conductivity (EC). The results are as follows: ① The soil salinity in the study area is relatively light, and the total proportion of non-salinized and slightly salinized soil samples is 82.68%; ② The correlation between salinity index and soil EC is higher than that of vegetation index. The correlation between salinity index S₃ (S₃), salinity index S₅ (S₅), salinity index S₆ (salinity index, S₆) and salinity index Si (salinity index, SI) is above 0.50; ③ Salinity indexes S₂ (S₂), S3, S5 and Si have the highest fitting degree with soil EC in the whole sample, among which S5 has the best performance (R² = 0.41). The fitting degree of index and soil EC increases significantly with the increase of soil salinity under different salinity levels. The highest fitting degree of salinity index and soil EC is S₁ (R² = 0.73) and S₂ (R² = 0.72); ④ In the fitting model, the evaluation index and soil EC calculated based on cubic model, quadratic model and S model has a high fitting degree. This study has analyzed the applicability of various soil salinization evaluation indexes in soil salinity monitoring of Yinbei irrigation area, and the preliminary conclusions can provide reference for remote sensing monitoring of soil salinity in Yinbei irrigation area of Ningxia.

Conventional remote sensing monitoring techniques, constrained by data availability and computational capacity, often fall short of the research requirements of extensive landslide disaster monitoring. This study established a dynamic assessment model for landslide hazards in the Three Gorges Reservoir area based on cloud computing platform Google Earth Engine (GEE), achieving dynamic assessment of landslide hazards in the area under the support of the massive data storage and robust computational capabilities of GEE. First, based on factors such as slope, slope aspect, normalized difference vegetation index (NDVI), normalized differential water index (NDWI), and geological structures, a landslide susceptibility zone map was established using a weighted gradient boosting decision tree (WGBDT) model. Then, the rainfall threshold inducing landslides in the Three Gorges Reservoir area was determined based on the Global Precipitation Measurement (GPM) data from the National Aeronautics and Space Administration (NASA). Subsequently, the rainfall classification criteria and a landslide hazard assessment model were established by combining rainfall and landslide susceptibility. Finally, focusing on the rainfall on August 31 in the Three Gorges Reservoir area, the daily distribution maps of landslide hazards in the Three Gorges Reservoir area were plotted, yielding the spatio-temporal variation trend of landslide hazards. In sum, the data processing and analysis tools of GEE allow for the analysis of landslide-related data of the Three Gorges Reservoir area, thus providing nearly real-time monitoring and early warning information for landslide hazards and offering a basis for the formulation of disaster prevention and mitigation policies.

With the rapid socio-economic development and the increasing demand for natural resources in China, the protection of natural reserves is facing increasing difficulties. The remote sensing-based research on monitoring the disturbance and the restoration of mangrove forests through time series analysis is still in its initial stage. Moreover, time series algorithms are highly complex. Based on the LandTrendr time segmentation algorithm of Google Earth Engine (GEE) and the Landsat image time-series data, this study investigated the disturbance to mangrove forests in the Dongzhaigang Mangrove Nature Reserve during 1990—2020. The results are as follows: ① A total of 42.39 hm² of mangrove forests were disturbed during 1990—2020, among which the largest disturbance area of 12.78 hm² occurred in 2014; ② During 1990—2020, minor, moderate, and severe disturbances accounted for 65.39%, 30.78%, and 3.83%, respectively; ③ The overall identification accuracy of the pixels of mangrove forests subject to changes was 89.50%, and the overall detection accuracy of years witnessing disturbance was 88%, with a Kappa coefficient of 0.79. This study analyzed the years and areas of the disturbance to mangrove forests in the Dongzhaigang Mangrove Nature Reserve over 30 years based on LandTrendr. Moreover, this study analyzed the disturbance factors according to the actual situation and concluded that human activities are the main disturbance factor, followed by natural factors, such as diseases, pests, and extreme weather events. This study will provide a scientific basis and a decision reference for the management of the mangrove forest reserve.

Based on an analysis of remote sensing data sources, the authors classify the methods into five categories, i.e., visual interpretation, ratio of index analysis, correspondence analysis, spatial structure analysis, and object-oriented information extraction, and summarize their characteristics and application fields. The research direction and development trends are also predicted, which include such application fields as hyper-spectral remote sensing data, artificial intelligence, expert systems and non-linear theory.

Water is a very important resource, and it is an important material basis for the survival and development of all human beings and organisms. Water extraction can result to easily understand the general situation of existing water resources, thus being conducive to the rational planning and management of water resources and having a significant impact on human life and social activities. Traditional artificial methods are time-consuming and laborious, and therefore satellite remote sensing data is now used to extract water parameters such as water position, area, shape and river width, which has become an effective method and means to obtain water parameters quickly. On the basis of extensive literature research, this paper illustrates the basic ideas of water extraction of remote sensing image and its development course as well as the basic method and current situation of water extraction performed by experts, and makes a comprehensive review and analysis of the advantages and disadvantages of various methods so as to explain the problems of water extraction and research prospect, make the readers understand the situation of this field and provide some ideas for the study in this field.

Timely and accurate detection and statistical analysis of the spatial distributions and time-series variations of water bodies like rivers and lakes holds critical significance and application value. It has become a significant interest in current remote sensing surface observation research. Conventional water body extraction methods rely on empirically designed index models for threshold-based segmentation or classification of water bodies. They are susceptible to shadows of surface features like vegetation and buildings, and physicochemical characteristics like sediment content and saline-alkali concentration in water bodies, thus failing to maintain robustness under different spatio-temporal scales. With the rapid acquisition of massive multi-source and multi-resolution remote sensing images, deep learning algorithms have gradually exhibited prominent advantages in water body extraction, garnering considerable attention both domestically and internationally. Thanks to the powerful learning abilities and flexible convolutional structure design schemes of deep neural network models, researchers have successively proposed various models and learning strategies to enhance the robustness and accuracy of water body extraction. However, there lacks a comprehensive review and problem analysis of research advances in this regard. Therefore, this study summarized the relevant research results published domestically and internationally in recent years, especially the advantages, limitations, and existing problems of different algorithms in the water body extraction from remote sensing images. Moreover, this study proposed suggestions and prospects for the advancement of deep learning-based methods for extracting water bodies from remote sensing images.

With continuously accelerated urbanization, urban expansion-induced farmland occupation and rural hollowing have gradually aggravated arable land abandonment, posing challenges to China’s food security. Hence, accurately determining the distribution of abandoned arable land is critical to arable land protection and food security. This study investigated a county in the major crop production area in a hilly region in southern China. Based on the phenological characteristics of local rice planting, this study adopted six phases of satellite remote sensing images and aerial images acquired in 2020 and 2021 were used as the data source and selected paddy fields determined based on the Third National Land Survey and field ridges in 1∶2 000 digital line graphics (DLGs) as the minimum information extraction unit. Then, the rice planting patches were extracted through time-series normalized difference vegetation index (NDVI) analysis and the improved SVM method. Suspected abandoned areas were screened out through the difference calculation for two consecutive years and then further identified in the unmanned aerial vehicle (UAV)-based sampling aerial survey. Consequently, the abandoned arable land areas were determined, with monitoring accuracy exceeding 85%, as revealed by on-site verification. The results of this study show that the space-air-ground integrated remote sensing monitoring method can provide scientific and effective data support for agricultural management departments to control and manage cultivated land abandonment.

Lake water reserves are often estimated according to water level observation and manually-measured underwater topography data. As for the lakes which lack data, it is really difficult to obtain the information of lake water reserves. In order to explore the solution of this problem, the authors chose the Nam Co Lake in Tibet as a study case. Based on the features of topography similarities between the above lake level and the under lake level, the authors made use of SRTM DEM of above the lake level to construct the relationship between the elevation and the area, the area and the volume increment. In turn, the elevation-area-volume increment of the lake's underwater was recalculated. Finally, the authors constructed the area-volume model to calculate the lake water reserves. The result shows that the calculation is of high relative accuracy. According to the area of the lake by using the DEM of the Nam Co Lake basin,the authors calculated the lake water reserves, which reach 111.570 billion m ³. This result is compared with the calculated water reserves of 101.950 billion m ³ in the Nam Co Lake underwater terrain digital elevation model established based on measured water depth data, and its absolute error is 9.620 billion m ³ whereas its relative error is 9.40%. The results obtained by the authors provide a reference for the estimation of natural lake water reserves with consistent water and underwater topographic parameters in data-absent areas.

Smart city is the inevitable choice for the development of China’s new urbanization. As a product of informatization and urban integration, smart city is gradually realized as an efficient and fine tool for managing people, money, material and things intelligently. The study of influence of UAV remote sensing technology in the construction of intelligent city plays an important role in accelerating the construction of smart cities. In this paper, the authors first reviewed the definition and development status of smart city, and then introduced the applications of unmanned aerial vehicle (UAV) from urban planning, illegal construction supervision, engineering environmental management, waste management, intelligent transportation, and other aspects.Finally, the development tendency was discussed.

During coastal resource monitoring, it is an effective way to extract aquaculture region using remote sensing data, whereas the water color in coastal region is complexly influenced by the distribution difference of chlorophyll-a and total suspended sediment concentration. And it would be difficult to accurately extract the aquaculture region with complex background using traditional methods. In view of the above problem, the authors proposed an algorithm for automatic coastal aquaculture area extraction combined with spectral and spatial information of aquaculture. Firstly, orthogonal subspace projection-weighted constrained energy minization method (OWCEM) was used to enhance the information of coastal aquaculture area. Secondly, by using the spatial texture information of the coastal aquaculture area, standard deviation adaptive segmentation (SDAS) method was used to automatically extract the cultivation area. In order to verify the accuracy of the proposed algorithm, the authors selected Sanggou Bay in Shandong and Sanduao Bay in Fujian as test regions and conducted the area extraction using Landsat8 data. The experimental results show that the proposed method can rapidly and accurately identify the distribution of coastal aquaculture area in complex background color and can reach about 93% accuracy rate with a low missing rate. The method could provide a new and effective means for automatic extraction of offshore aquaculture area.

In order to further understand the glacier change in Ulugh Muztagh under the background of climate change, historical topographic map data, Landsat TM, SRTM DEM and TerraSAR-X/TanDEM-X data with bi-static mode were employed to obtain the detail change of the glacier area and mass balance between 1972 and 2011 around Muztagh peak. The results indicated that reduction rate of annual glacier area was 0.02±0.06% between 1972 and 2011. Among all glaciers, 47 glaciers showed retreat while 2 glaciers advanced for some distance. And the mass change showed a slight negative balance (-0.06±0.01 m w.e./a) for the whole region. From 1972 to 1999, the mass balance was -0.11±0.02 m w.e./a, caused probably by the temperature rising; From 1999 to 2011, the mass change was close to balance (0.02±0.04 m w.e./a), caused by the precipitation increasing. Glacier advance in Muztagh was different from that of normal advanced glacier. For this kind of Polar type glaciers, it was probably caused by the inner melting or liquid water occurrence due to more precipitation that made some glaciers moving forward or surging. In the background of the current climate, most glaciers showed retreat but two glaciers advanced and one glacier surged (avalanche); overall, the glaciers in the region showed slightly negative mass balance.