Estimation and verification of green tide biomass based on UAV remote sensing

Since 2007,the Yellow Sea green tide has broken out every summer,causing great harm to the environment and society.Although satellite remote sensing(RS)has been used in biomass research,there are several shortcomings,such as mixed pixels,atmospheric interference,and difficult field validation.The biomass of green tide has been lacking a high-precision estimation method.In this study,high-resolution unmanned aerial vehicle(UAV)RS was used to quantitatively map the biomass of green tides.By utilizing experimental data from previous studies,a robust relationship was established to link biomass to the red-green-blue floating algae index(RGB-FAI).Then,the lab-based model for green tide biomass from visible images taken by the UAV camera was developed and validated by field measurements.Re sults show that the accurate and cost-effective method is able to estimate the green tide biomass and its changes in given local waters of the near and far seas.The study provided an effective complement to the traditional satellite RS,as well as high-precision quantitative techniques for decision-making in disaster management.

Framework of SAGI Agriculture Remote Sensing and Its Perspectives in Supporting National Food Security

Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful within large scale agriculture applications （such as on a national or provincial scale）, it may not supply sufifcient information with adequate resolution, accurate geo-referencing, and specialized biological parameters for use in relation to the rapid developments being made in modern agriculture. Information that is more sophisticated and accurate is required to support reliable decision-making, thereby guaranteeing agricultural sustainability and national food security. To achieve this, strong integration of information is needed from multi-sources, multi-sensors, and multi-scales. In this paper, we propose a new framework of satellite, aerial, and ground-integrated （SAGI） agricultural remote sensing for use in comprehensive agricultural monitoring, modeling, and management. The prototypes of SAGI agriculture remote sensing are ifrst described, followed by a discussion of the key techniques used in joint data processing, image sequence registration and data assimilation. Finally, the possible applications of the SAGI system in supporting national food security are discussed.

Application of Remote Sensing and Geographic Information System in Land Use and Land Cover Change

The integration and application of remote sensing （RS） and geographic in-formation system （GIS） in the study of the Land Use and Land Cover Change （LUCC） were summarized, as wel as researches on the monitoring dynamic changes in LUCC, driving force and application examples of the integration and the application of RS and GIS in simulation research. The methods and technical ap-proaches of RS and GIS in LUCC research were discussed. Views on the existing problems of the integration and the application of RS and GIS were put forward, and the future developing direction of LUCC technology was forecasted.

Technical foundation research on high resolution remote sensing system of China's coastal zone

China's coastal zone is a region with a highly developed economy that contrasts clearly with the slow paced regular investigation on its natural environment,which cannot keep pace with the requirement of economic development and modern management.Laying a theoretical foundation for the modern management of China's costal zone is aimed at. This research focuses on the following processing and analyzing technologies for coastal zone high-resolution remote sensing data: organization and management of large amounts of high-resolution remote sensing data, quick and precise spatial positioning system,algorithms for image fusion in feature level and coastal zone feature extraction. They will form a technical foundation of the system. And, if combined with other research results such as coastal zone remote sensing classification system and its mapping subsystem, an advanced technical frame for remote sensing investigation of coastal zone resource will be constructed.

Regionalization for Rice Yield Estimation by Remote Sensing in Zhejiang Province

In order to provide a scientific basis for rice yield estimation and improve the accuracy of yield estimation in Zhejiang Province, regionalization indices for rice yield estimation by remote sensing (RS) in the province were determined by considering the special features of yield estimation by RS, and based on analysis of the natural conditions of Zhejiang Province. The indices determined included rice cropping system, agroclimate, landform, surface feature structure and rice yield level, where rice planting system was considered as the main one. Then regionalization for rice yield estimation by RS was completed by spatial neighboring analysis with the Geographical information System (GIS) technology combined with using of tree algorithm. The province was divided into two regions, i. e., the single-cropping rice region which was subdivided into 3 regions including those in mountains of northwest Zhejiang, water network area of north Zhejiang and mountains of south Zhejiang, and double-cropping rice region which was subdivided into 5 regions including those on plain of north Zhejiang, coastal plains and hills of southeast Zhejiang, Jin-Qu Basin of middle Zhejiang, hills of east Zhejiang, and hills and mountains of northwest Zhejiang. This regionalization took the county borders as the region boundaries, kept the regions connective and made the administrative regions integrity and, then, could meet the requirements of rice yield estimation by RS, showing that the results were quite satisfying.

Evaluation of Eco-Environmental Frangibility Based on Remote Sensing and Geographic Information System

The eco-environmental frangibility is studied by choosing the factors of land use class change and vegetation cover rate, and the equation of eco-environmental frangibility and its evaluation system are established based on remote sensing （RS） and geographic information system technology （GIS）. Four different years of TM images are selected to calculate land use change grads and vegetation cover rate, and the relationship between the two factors and eco-environment frangibility index are build, taking Fuzhou as an example. The character of times change and space distribution of eco-environment frangibility are described. The result indicates the area of eco-environment frangibility increased 2.6% in Fuzhou during twelve years, and expands from the region between infield and forest land to forest land in space distribution.

Urban Expansion of China from the 1970s to 2020 Based on Remote Sensing Technology

Based on Remote Sensing (RS) and Geographical Information System (GIS) technology,urban expansion of 75 cities in China from the 1970s to 2020 was reconstructed by visual-interpretation method,which described the growing process of urban lands and its influences on local land use structures synchronously.By employing annual expansion area per city and urban expansion density,spatial-temporal characteristics and macro patterns of urban expansion were analyzed from the aspects of regional-distributions,administrative-levels and population-sizes comprehensively.Results indicate that:1) urban expansion in China was universal,distinct,persistent,periodic and fluctuating.In the past five decades,urban lands of 75 monitored cities in China expanded dramatically from 3606.26 km2 to 30 521.13 km2.2) Though urban expansion presented significant differences from the aspects of regional distribution,administrative levels,and population sizes,it exhibited a deceleration trend in the 13th Five-Year Plan among all kinds of cities.3) Cultivated lands were the first land resource for urban expansion,and 55.17% of newly-expanded urban lands appeared by encroaching this land use type.China’s urban expansion has caused sustained pressure on cultivated land protection,especially in super megacities,and the contradiction between urban expansion and cultivated land protection will always exist.4) The compactness of urban lands in China increased before 1987 and reduced in the next three decades,which was consistent with the implementation of major policies and the deployment of national strategies,and is expected to become compact with a stopping declining or even rebounding after the 13th Five-Year Plan.

A STUDY ON DESERTIFICATION OF WEST JILIN PROVINCE BASED ON REMOTE SENSING AND GIS TECHNIQUES

'West Jilin Province' in this paper means Zhenlai, Baicheng, Taonan, Da'an,Tongyu, Fuyu, Songyuan, Qian'an, Changling, also includes Gongzhuling, Shuangliao, Lishu, Siping andNong' an which have been suffered from desertification. In west Jilin Province there are three sandzones passing through, they are Xiang (Xianghai) -Wu (Ulan Tug) sand zone, Hai-Feng sand zone, andTao'er River right bank sand zone. The desertification area of west Jilin Province is 819 100 ha,making up 12. 5% of the total land area. Among desertification types, in Jilin Province lightdesertification is the major, then is medium decertification, hevey desertification is the least.According to the comparison of the interpretation results of the Landsat images of the 1980s and the1990s by remote sensing and GIS techniques, it can be seen that the desertification area in westJilin Province basically didn't change on the whole, only increased 6130 ha, making up 0. 8% of thedesertification area, change scale is less than 1%. Evidently, desertification is controlled mostly,but some areas are continuing deterioration. The desertification process of China can be dividedinto three types according to origin nature, they are sandy steppe desertification, fixed sandarea(sand land) activation and dunes transfer invasion. Reasons of desertification of West JilinProvince are analyzed, they include natural factors (such as material source factors, chimatefactors) and artificial factors (such as destroying grass to reclaim, steppe decreasing greatly,illegally feeling shelter forest stands, constructing reservoir to influence eco-environment etc. ).Some suggestions are put forward as follows: establishing the social project for ecologicalreconstruction of degenerated land; intensifying planning and management of land use, revertingfarmland into forestland or pasture in a planned way. The key desertification control is to dependmainly on policy and management, then control techniques.

Integrated Evaluation Model for Eco-Environmental Quality in Mountainous Region Based on Remote Sensing and GIS

Based on Remote Sensing （RS）, Geographic Information System （GIS）, and combining Principal Component Analysis, this paper designed a numerical integrated evaluation model for mountain eco-environment on the base of grid scale. Using this model, we evaluated the mountain eco-environmental quality in a case study area-the upper reaches of Minjiang River, and achieved a good result, which accorded well with the real condition. The study indicates that, the integrated evaluation model is suitable for multi-layer spatial factor computation, effectively lowing man＇s subjective influence in the evaluation process; treating the whole river basin as a system, the model shows full respect to the circulation of material and energy, synthetically embodies the determining impact of such natural condition as water-heat and landform, as well as human interference in natural eco-system; the evaluation result not only clearly presents mountainous vertical distribution features of input factors, but also provides a scientific and reliable thought for quantitatively evaluating mountain eco-environment.

AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION

In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection.

Reservoir Inflow Estimation Using Remote Sensing, GIS and Geosimulation

RS （remote sensing） applications to hydrological problem solving have successfully transitioned from being experimental to operational in the last couple of years, and information gathered through these technologies can facilitate water resource procedures. Patterns from RS imagery can be translated into a deterministic distribution of input data over a wide area on a pixel-by-pixel basis. This paper presents the implementation of different methodologies of integrating satellite-derived information from RS, and GIS （geographic information system） visualization and simulation capabilities in improving hydrologic estimation processes.

Investigation on Saline Wetland Resources in Shandong Province Based on Remote Sensing and Geographic Information System

Based on the remote sensing data of Landsat, the information of saline wetlands in Shandong Province was extracted and classified by the interaction of computer automatic classification and visual interpretation. The results showed that the tidal wetland was the largest saline wetland type, with an area accounted for 33.88% of the total; the brine pan came at the second, accounting for 20.3% of the total area; followed by the severe saline wetland, accounting for 18.5%. Natural wetland is the main saline wetland type in Shandong Province, accounting for 60.1% of the total saline wetland area. The biodiversity, ecological function and value of natu- ral wetlands are higher than that of constructed wetland. However, the amount of natural wetlands is decreasing, and their functions are deteriorating, thus, the protection of the limited natural wetland resources is urgent.

Approaches to Detecting Gene-Environment Interactions in Human Variation Using Genetic Engineering, Remote Sensing and GIS

Elucidation of the relationships between genetic polymorphisms and environmental exposures can provide insights into the pathways and mechanisms underlying complex traits. A new approach was used to detect G×E （gene-environment） interactions involved in human skin pigmentation variation to better understand the adaptive evolution of skin pigmentation. Specifically, we used genetic engineering, remote UVR （ultraviolet radiation） sensing and GIS （geographic information systems） to integrate the analysis of genetic and environmental factors into a coherent biological framework. Since we expected to generate large datasets for this multidimensional analysis, we used PCA （principal components analysis） as a spatial statistical analysis technique for analyzing the G×E interactions. The results suggest that skin pigmentation may be affected by mutations induced by UVR and support the hypothesis that global variation in skin pigmentation may be the result of localized adaptation to different UVR conditions via natural selection. Analyzing the relationships between heterozygous frequencies for SNP （single nucleotide polymorphism） loci and seasonal UVR levels as the environment changes will help elucidate the selective mechanisms involved in the UVR-induced evolution of skin pigmentation. Skin pigmentation fulfills the criteria for a successful evolutionary G×E interactions model.

基于YOLOv7-RS的遥感图像目标检测研究

针对遥感图像目标检测过程中存在的背景复杂、目标特征不明显、小目标排列密集的问题,基于YOLOv7算法,提出了一种改进的遥感图像目标检测算法YOLOv7-RS(YOLOv7-Remote Sensing),提高了遥感图像的目标检测精度。首先,向特征提取网络中融合SimAM减少背景噪声的干扰;其次,提出了D-ELAN网络增强遥感目标的特征提取能力;再次,利用SIOU损失函数以提高算法模型的收敛速度;最后,优化了正负样本分配策略,改善了遥感图像中小目标密集排列时的漏检问题。实验结果表明,YOLOv7-RS在NWPU VHR-10和DOTA数据集上的mAP达到95.4%和74.1%,相较于其他主流算法有了明显提升。

Interpreting the Shortwave Infrared &Thermal Infrared Regions of Remote Sensed Electromagnetic Spectrum with Application for Mineral-Deposits Exploration

The ASTER (Advanced Space-borne Thermal Emission and Reflection radiometer) data, including all the 3 parts: VNIR (Visible and Near-Infrared), SWIR (Short Wave Infrared), TIR (Thermal Infrared), were applied for extraction of mineral deposits, such as the Ni-Cu deposit in eastern Tianshan, the gypsum in western Tianshan, and the borax in Tibetan. This paper discusses the extraction methodology using the ASTER remote sensing data and reveals the good extraction results. This paper bravely represents the summary of the main achievement for this field by the scientists in other countries and gives a comparison with the works by others. The new achievements, described in this paper, comprise the extraction of anomalies for Ni-Cu deposit, gypsum, and borax.

水利遥感智能云平台HydrSAI建设及应用

水利行业对于整合“天-空-地”一体化遥感监测技术的应用需求越来越高,然而传统的遥感影像分析模型往往难以适应日益多样化的行业应用需求。因此,通过集成分布式存储、虚拟化管理、自动化运维和云安全等技术,以PaaS和SaaS方式提供云服务,构建了一个融合先进人工智能技术、面向行业应用的智能化遥感影像数据处理云平台HydrSAI。该平台集成了影像预处理、样本采集与建库、模型构建与优化、高性能矢量切片以及云计算服务技术,并配备可扩展的影像库、样本库和模型库。该平台在深圳市人为扰动图斑识别以及大藤峡库区开展了试验应用,其识别效率相较于目视识别得到显著提升。HydrSAI可为水利部门提供高效、便捷、智能化的遥感解译支持。

Data quality evaluation and calibration of on-road remote sensing systems based on exhaust plumes

In recent years,with rapid increases in the number of vehicles in China,the contribution of vehicle exhaust emissions to air pollution has become increasingly prominent.To achieve the precise control of emissions,on-road remote sensing(RS)technology has been developed and applied for law enforcement and supervision.However,data quality is still an existing issue affecting the development and application of RS.In this study,the RS data from a cross-road RS system used at a single site(from 2012 to 2015)were collected,the data screening process was reviewed,the issues with data quality were summarized,a new method of data screening and calibration was proposed,and the effectiveness of the improved data quality control methods was finally evaluated.The results showed that this method reduces the skewness and kurtosis of the data distribution by up to nearly 67%,which restores the actual characteristics of exhaust diffusion and is conducive to the identification of actual clean and high-emission vehicles.The annual variability of emission factors of nitric oxide decreases by 60%-on average-eliminating the annual drift of fleet emissions and improving data reliability.

GMTS: GNN-based multi-scale transformer siamese network for remote sensing building change detection

With the remarkable success of change detection(CD)in remote sensing images in the context of deep learning,many convolutional neural network(CNN)based methods have been proposed.In the current research,to obtain a better context modeling method for remote sensing images and to capture more spatiotemporal characteristics,several attention-based methods and transformer(TR)-based methods have been proposed.Recent research has also continued to innovate on TR-based methods,and many new methods have been proposed.Most of them require a huge number of calculation to achieve good results.Therefore,using the TR-based mehtod while maintaining the overhead low is a problem to be solved.Here,we propose a GNN-based multi-scale transformer siamese network for remote sensing image change detection(GMTS)that maintains a low network overhead while effectively modeling context in the spatiotemporal domain.We also design a novel hybrid backbone to extract features.Compared with the current CNN backbone,our backbone network has a lower overhead and achieves better results.Further,we use high/low frequency(HiLo)attention to extract more detailed local features and the multi-scale pooling pyramid transformer(MPPT)module to focus on more global features respectively.Finally,we leverage the context modeling capabilities of TR in the spatiotemporal domain to optimize the extracted features.We have a relatively low number of parameters compared to that required by current TR-based methods and achieve a good effect improvement,which provides a good balance between efficiency and performance.

从单星观测到体系协同:风云卫星智慧协同观测体系的技术特征与发展展望

风云卫星是我国民用遥感卫星中应用范围最广泛、成效最为显著的卫星系列之一,在推动国民经济发展和加强装备自主建设等方面发挥了重要作用。面向气象高质量发展、防灾减灾、应对气候变化、生态文明建设和国家安全等多重挑战,风云卫星将坚持创新驱动发展战略,以体系化、智能化为主要发展方向,突破平台和载荷关键技术,构建智慧协同观测体系。本文探讨了风云卫星智慧协同观测体系在气象综合观测效能提升、体系化智能化网络赋能及全方位环境保障等方面的必要性,在分析国内外气象卫星发展历程的基础上,提出了新一代风云气象卫星构建智慧协同观测体系的建设思路和初步方案,并对体系构建中的关键技术进行了分析。最后,展望了风云卫星智慧协同观测体系的应用前景。

安徽省自然资源遥感影像综合应用服务平台设计与实现

针对自然资源省级卫星应用技术中心的核心业务场景和服务对象的需求,设计了省级遥感影像综合应用服务平台的总体架构、平台数据库、功能架构与技术架构。在平台建设的过程中,利用混合数据库管理模式与脚本化建库技术实现了卫星遥感数据库的高效检索与维护,运用影像数据服务动态渲染技术,解决了影像地图服务发布预处理流程复杂、更新周期长等问题,采用微服务架构搭建了省级遥感影像综合应用服务平台,在保证平台“7×24 h”稳定高效运行的前提下,为后续平台的功能更新与版本升级奠定了良好的基础。