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Green tide identification from HY-1C satellite data based on sub-pixel mapping technique
Chen Gong;Zhong Junfei;Xu Ying;Wu Ke;Green algae frequently undergo explosive blooms along the coastal regions of Jiangsu and Shandong Provinces, China, forming green tides that pose a significant risk to marine ecosystems, the ocean environment, and the social economy. Remote sensing has emerged as an effective tool for precise identification of the spatiotemporal dynamics of coastal green tides on a large scale. However, constrained by limited spatial resolution, the mixed pixels problem is ubiquitous in remote sensing imagery, which undermines the ability of traditional hard classification methods to finely resolve green tide distributions, leading to inaccurate area estimations and seriously hindering subsequent green tide prevention and control efforts. To address this challenge, this study leveraged sub-pixel mapping techniques to identify green tides and calculate corresponding green tide areas using low-spatial-resolution(50 m) imagery from the coastal zone imager(CZI) onboard the Haiyang-1C(HY-1C) satellite. The calculated areas were then compared with those derived from classification results of higher-spatial-resolution(16 m) imagery from the charge-coupled device(CCD) camera onboard the Huanjing-2A(HJ-2A) for the same region. The results demonstrate that sub-pixel mapping techniques can effectively achieve green tide identification from low-spatial-resolution ocean satellite data, offering a novel approach for large-scale, fine-grained green tide identification and area estimation via remote sensing.
An unsupervised fast road extraction method based on image feature mining
Ma Hong;Chen Hao;Guangdong Provincial Institute of Land and Resources Surveying and Mapping;Roads constitute a crucial component of fundamental geographic information data, and their automated extraction has long been a key research topic in the field of remote-sensing monitoring. Traditional manual recognition is inefficient and time-consuming. Therefore, this study explored road information detection in remote-sensing images based on cluster analysis technology. First, the image was segmented; then clustering was performed, combined with an edge detection algorithm and a road-search decision rule to rapidly extract road information. The results demonstrate that the proposed method achieves a comprehensive F1-score above 80%, and the processing time for a single image ranges from 2 to 6 s. It effectively and rapidly extracts road edges, making it feasible as an auxiliary tool in surveying and mapping production and capable of substantially improving work efficiency.
A boundary IoU evaluation protocol for remote sensing building extraction
Wang Bozhen;In the extraction of buildings from high-resolution remote-sensing imagery, the prevailing evaluation framework relies mainly on mean average precision(mAP) and mask intersection over union(Mask IoU), which provides limited insight into boundary accuracy. To address this shortcoming, this paper proposed a boundary intersection over union(BIoU) evaluation protocol tailored to the remote-sensing building extraction domain. The protocol comprised two metrics—BIoU and the 95th-percentile Hausdorff distance(HD95)—and adopted a dual-caliber reporting strategy. Based on the Wuhan University(WHU) and Massachusetts building datasets, it systematically compared the performance of eight method configurations under the proposed protocol, including variants of the real-time instance-segmentation model(YOLOv8-seg), the Ushaped encoder-decoder network(U-Net), and the deep semantic segmentation network(DeepLabv3+). The results show that, for in-domain scenarios, the intersection over union(IoU) of all methods is comparable(0.843-0.851), whereas the HD95 reveals a paradigm-level gap. In cross-domain scenarios, the you only look once(YOLO)-series detection algorithms retain an IoU of 0.224-0.279, whereas semantic-segmentation models drop to 0.054-0.095, significantly reversing the indomain ranking. After fine-tuning with only 5% of target-domain samples, the semantic-segmentation models achieve better IoU performance than the zero-shot YOLO. This demonstrates that the proposed BIoU+HD95 protocol effectively exposes the limitations of relying solely on in-domain Mask IoU for evaluation, offering a new tool for method evaluation and selection in remote-sensing building extraction.
Single-image super-resolution reconstruction for GF-1 wide-swath imagery
Li Jue;Shen Peng;Gao Luxiong;To further enhance the spatial resolution of Gaofen-1(GF-1) wide-swath imagery and expand its applicability in national condition monitoring—particularly hydrology and water resources—this study investigated the single-image superresolution(SISR) problem for GF-1 wide-swath data. Six representative algorithms were selected from two broad categories—interpolation-based methods and adversarial neural-network approaches—and implemented. A test set was constructed that spanned resolutions from 16 m down to 2 m, to validate the super-resolution performance and effectiveness of the six algorithms under low, medium, and high scaling(up-sampling) factors. Assessment metrics included mean-square error(MSE) and visual-fidelity indices. The experiments show that, for the medium-and low-factor SISR requirements of GF-1 wide-swath imagery, all six methods can meet the task; deep-learning-based algorithms achieve the highest reconstruction quality, whereas interpolation-based techniques provide a clear advantage in computational efficiency. Consequently, when efficiency is a priority, interpolation methods are recommended for medium-and low-factor super-resolution tasks; when sufficient computing resources are available, deep-learning algorithms should be adopted to achieve optimal results. For high-factor superresolution, deep-learning methods remain the preferred choice, but attention should be paid to the artifacts they may introduce.
Spatial differentiation characteristics of multi-scale road networks in Beijing based on GIS
Zeng Xiaoying;Taking Beijing as the study area, this research first assigned differentiated weights to roads of varying hierarchical levels using line density and kernel density estimation methods to develop four distinct road network density calculation methods. Hot spot analysis and spatial autocorrelation analysis were then applied to examine both the spatial differentiation characteristics of Beijing's road network across multiple scales and the comparative performance of the four density calculation methods. Results demonstrate that Beijing's road network exhibits pronounced spatial differentiation: road network density decreases gradually from the central urban area towards the urban periphery, and the southeastern region has a markedly higher density than the northwestern region. Hot spot areas are clustered in the central urban area, while cold spot areas are distributed along the city's northwestern boundary; the overall clustering pattern remains largely insensitive to variations in study scale. The global Moran's I value is above 0.970, indicating significant positive spatial autocorrelation. Three agglomeration patterns are identified: high-high agglomeration, low-low agglomeration, and non-significant agglomeration. Furthermore, the spatial agglomeration effect intensifies as the study scale becomes smaller. Comparative analysis of the four road network density metrics demonstrates that the weighted road network kernel density provides a more refined characterization of the fine-grained spatial distribution of Beijing's road network.
Analysis of Land Use Conflicts and Driving Factors at County Scale in the Yellow River Basin Based on GIS
XIE Minghang;HU Qiliang;ZHOU Xiaoxiang;Exploring the spatiotemporal evolution and driving factors of land use conflicts is of great significance for the harmonious development of the regional human-land system. In this study， methods including the land use transfer matrix and the construction of a comprehensive land use conflict index were adopted to systematically analyze the dynamic characteristics of land use change and the spatiotemporal evolution of land use conflicts in Xin'an County from 2000 to 2020. The main driving factors of land use conflicts were identified using a geographic detector. The results show that: 1) Cultivated land and forestland were the dominant land use types in Xin'an County during 2000–2020. The areas of cultivated land and grassland continued to decrease， while forestland， water area and construction land generally showed an increasing trend. The mutual conversion intensity between cultivated land and forestland was the highest. 2) Over the 20 years， the areas of stable and controllable， slightly out-of-control and severely out-of-control land use conflict grades in Xin'an County showed a decreasing trend， whereas the area of basically controllable grade increased overall. The overall spatial distribution of land use conflict grades presented a pattern of "high in the middle and low at both ends". The out-of-control areas of cultivated land， forestland， grassland and construction land continued to decline， and the severely out-of-control area of water area decreased significantly. 3) Relief amplitude， normalized difference vegetation index (NDVI)， regional gross domestic product (GDP) and population density were the main driving factors for the evolution of land use conflicts in Xin'an County. The findings can provide a useful reference for territorial spatial optimization， ecological protection and restoration， and high-quality development in Xin'an County.
[Downloads: 62 ] [Citations: 0 ] [Reads: 5 ] HTML PDF Cite this article
Ground terrain underground pipeline mapping based on 3D LIDAR point cloud feature selection
Xu Renfeng;The complex surface coverage of overlapping features and the concealment of underground pipelines often result in severe occlusion and large measurement errors in the point clouds obtained by a single LiDAR platform. To improve the accuracy of real-world mapping of ground topography and underground pipelines， a real-world mapping method for ground topography and underground pipelines based on feature selection of 3D LiDAR point clouds was studied. By synchronously scanning with airborne LiDAR and ground LiDAR， point cloud scanning data of ground topography and underground pipelines were obtained， avoiding occlusion from a single perspective; a feature point selection algorithm based on local normal vector consistency was designed to identify the key mapping points of ground topography and underground pipelines， suppressing the redundancy and noise of multi-end perspective point clouds; a kd-tree was used to accelerate neighborhood search to construct a local projection coordinate system， and multiple source point clouds were fused in a unified coordinate system to achieve real-world mapping of ground topography and underground pipelines. Experimental results show that the measurement error of the plane position of ground topography and underground pipelines in severely occluded areas is less than ±5 cm in height measurement error， improving the accuracy of real-world mapping.
[Downloads: 20 ] [Citations: 0 ] [Reads: 5 ] HTML PDF Cite this article
Spatio-Temporal Differentiation and Coupling Coordination Analysis of Landscape Ecological Risk in Counties Along the Yellow River in Southwestern Shandong Based on GIS
WANG Yujie;XING Xiaolu;To reveal the spatio-temporal evolution and coupling coordination characteristics of landscape ecological risk at the county level in southwestern Shandong， and support territorial space optimization and ecological protection， this study takes Dongping County as the research area. Based on land use data from 2000 to 2020， it divides territorial spaces into production， living and ecological spaces. With the adoption of GIS technology， landscape ecological risk model and coupling coordination degree model， this paper systematically analyzes the evolution of three functional spaces， as well as the spatio-temporal changes and coupling coordination of regional landscape ecological risk. The results show that during the study period， production space remained the dominant type in Dongping County， living space expanded continuously， and ecological space decreased significantly in the later stage. The overall landscape ecological risk gradually declined， with high-risk areas shrinking steadily and low-risk areas expanding outward. The coupling coordination level between the three functional spaces and landscape ecological risk kept improving， the area of uncoordinated regions decreased， and all types of coordinated areas expanded steadily. The research findings can provide a scientific reference for the optimization of territorial space pattern and ecological protection and restoration in Dongping County and other counties along the Yellow River.
[Downloads: 111 ] [Citations: 0 ] [Reads: 8 ] HTML PDF Cite this article
Study on Land Use Pattern and Carbon Storage Change in Mountainous Areas of Western Henan Based on GIS
XING Lei;SHEN Xinkai;JING Xiang;Exploring the impacts of land use evolution on carbon storage in mountainous western Henan is of great significance for regional ecological restoration and the realization of the "Dual Carbon" goals. Taking Sanmenxia City as the research area， this paper comprehensively adopts spatial analysis tools of Geographic Information System (GIS)， land use transfer matrix and the InVEST model to systematically investigate the spatiotemporal evolution of land use patterns and the differentiation characteristics of carbon storage from 2005 to 2025， and quantitatively calculate carbon gains and losses caused by transitions of various land use types. The results show that from 2005 to 2025， forest land in Sanmenxia City expanded continuously， grassland decreased drastically， and construction land continuously encroached on cultivated land. The total regional carbon storage presented a trend of an initial decline followed by a rebound， with southern forest lands as high carbon sink zones and towns in northern river valleys as low carbon sink zones. The conversion of cultivated land and grassland to forest land constitutes the major carbon sink pathway， while the conversion of cultivated land to non-agricultural land and the reclamation of forest land are the primary sources of carbon loss. Carbon sinks generated by ecological restoration projects can partially offset carbon losses resulting from urban development. The research results can provide a scientific basis for ecological restoration and the achievement of the dual‑carbon goals in the mountainous areas of western Henan.
[Downloads: 81 ] [Citations: 0 ] [Reads: 7 ] HTML PDF Cite this article
Extraction of Tree Diameter at Breast Height Based on Mobile 3D Laser Scanning Technology
Xu Yanbo;Cao Ning;Aiming at the problems that station-based scanning is easily limited by trunk and leaf occlusion， terrain undulation， and requires long time for point cloud collection and post-processing， this paper proposes a method for tree diameter at breast height (DBH) extraction based on mobile 3D laser scanning technology. This method adopts mobile 3D laser scanning for data collection， which can maximally overcome the complex forest environment， reduce the impact of various occlusions， ensure data integrity， and efficiently acquire 3D spatial data of forest land. The process and key algorithms of tree DBH extraction， including point cloud elevation normalization， filtering， clustering and cylinder fitting， are studied， and a DBH extraction and statistics software is developed to realize rapid extraction and automatic statistics of tree DBH information， significantly improving operation efficiency. Comparative experiments with traditional tree DBH measurement methods show that the proposed method is feasible and reliable， can effectively meet the needs of forest land investigation， and provide technical support and reference for large-scale forest investigation.
[Downloads: 13 ] [Citations: 0 ] [Reads: 9 ] HTML PDF Cite this article
Study of Texture Images Extraction Based on Gray Level Co-Occurence Matrix
FENG Jian-hui,YANG Yu-jing (Faculty of Land Resource Engineering of Kuming University of Science and Technology, Kuming,Yunnan,650093)The non-spectral characteristics play an important role in assisting the image classification in remote sensing, as these characteristics can avoid the mistake classification maken by the "the same object with different spectrum" phenomenons. The texture ch aracteristic is one kind of non-spectral characteristics. It is also helpful to improve the classification precision. In this paper, co-occurrence matrix applied to extract the texture images based on pixel level is discussed and experiments are carried out to analyze this method.
[Downloads: 6,325 ] [Citations: 423 ] [Reads: 10 ] HTML PDF Cite this article
Measuring Principle and Developmental Prospect of 3D Laser Scanner
ZHANG Qi-fu1,2 SUN Xian-shen1(1.Institute of Surveying and Mapping,Information Engineering University,Zhengzhou Henan 450052, China;2.95972 Troops,Jiuquan Gansu 735018,China)Firstly,this article sums up some methods about measuring distances,angles,scanning and scanner's orientation.Secondly,it detailedly introduces developing conditions nowadays,and gets the relationships among measuring bound,precision and scanning speed which are based on contrasting and analyzing of scanner's technical parameter.Finally,because of scanner's disadvantages,the article forecasts the future development of the accurate orientation,integrating many function,localization and common software.
[Downloads: 4,242 ] [Citations: 274 ] [Reads: 11 ] HTML PDF Cite this article
Comparing SIFT、SURF、BRISK、ORB and FREAK in Some Different Perspectives
SUO Chun-bao;YANG Dong-qing;LIU Yun-peng;SIFT,SURF,BRISK,ORB,FREAK and other image feature matching algorithm have different robustness,in this paper,we compare these algorithms from the viewpoint of matching speed,and the robustness of image rotation,image blur,different illumination,different scale and different viewing angle.The evaluation index in this paper is the number of feature point pairs that matched correct in two images.Through comparison and analysis,we found that,the SURF and FREAK have the more comprehensive robustness.
[Downloads: 4,449 ] [Citations: 233 ] [Reads: 10 ] HTML PDF Cite this article
The Comparative Study of Remote Sensing Image Supervised Classification Methods Based on ENVI
YAN Yan DONG Xiu-lan LI Yan (Anhui University of science and technology,Huainan,Anhui,232001,China)This paper describes four commonly used methods of supervised classification ENVI provides,based on the universal application of supervised classification in remote sensing image classification.The same TM image is classified using four methods,the result was analyzed essentially.Therefore,the paper analyzes the difference between the classification accuracy of these four methods.
[Downloads: 5,065 ] [Citations: 184 ] [Reads: 12 ] HTML PDF Cite this article
Research on the Exploration and Application of Unmanned Aerial Vehicle Photogrammetric Technique
LI Bing YUE Jing-xian LI He-jun Beijing Institute of Surveying and Mapping,Beijing,100038The key technologies and methods of constructing the aerial photogrammetric system using Unmanned Aerial Vehicles(UAV) photogrammetric technique are introduced in this paper. The design and development flow of UAV platform are presented,the feasibility of aerial photogrammetric technique based on the UAV is validated by accuracy analysis of the experimental results.
[Downloads: 2,540 ] [Citations: 142 ] [Reads: 11 ] HTML PDF Cite this article
Study of Texture Images Extraction Based on Gray Level Co-Occurence Matrix
FENG Jian-hui,YANG Yu-jing (Faculty of Land Resource Engineering of Kuming University of Science and Technology, Kuming,Yunnan,650093)The non-spectral characteristics play an important role in assisting the image classification in remote sensing, as these characteristics can avoid the mistake classification maken by the "the same object with different spectrum" phenomenons. The texture ch aracteristic is one kind of non-spectral characteristics. It is also helpful to improve the classification precision. In this paper, co-occurrence matrix applied to extract the texture images based on pixel level is discussed and experiments are carried out to analyze this method.
[Downloads: 6,325 ] [Citations: 423 ] [Reads: 10 ] HTML PDF Cite this article
The Comparative Study of Remote Sensing Image Supervised Classification Methods Based on ENVI
YAN Yan DONG Xiu-lan LI Yan (Anhui University of science and technology,Huainan,Anhui,232001,China)This paper describes four commonly used methods of supervised classification ENVI provides,based on the universal application of supervised classification in remote sensing image classification.The same TM image is classified using four methods,the result was analyzed essentially.Therefore,the paper analyzes the difference between the classification accuracy of these four methods.
[Downloads: 5,065 ] [Citations: 184 ] [Reads: 12 ] HTML PDF Cite this article
Comparing SIFT、SURF、BRISK、ORB and FREAK in Some Different Perspectives
SUO Chun-bao;YANG Dong-qing;LIU Yun-peng;SIFT,SURF,BRISK,ORB,FREAK and other image feature matching algorithm have different robustness,in this paper,we compare these algorithms from the viewpoint of matching speed,and the robustness of image rotation,image blur,different illumination,different scale and different viewing angle.The evaluation index in this paper is the number of feature point pairs that matched correct in two images.Through comparison and analysis,we found that,the SURF and FREAK have the more comprehensive robustness.
[Downloads: 4,449 ] [Citations: 233 ] [Reads: 10 ] HTML PDF Cite this article
Measuring Principle and Developmental Prospect of 3D Laser Scanner
ZHANG Qi-fu1,2 SUN Xian-shen1(1.Institute of Surveying and Mapping,Information Engineering University,Zhengzhou Henan 450052, China;2.95972 Troops,Jiuquan Gansu 735018,China)Firstly,this article sums up some methods about measuring distances,angles,scanning and scanner's orientation.Secondly,it detailedly introduces developing conditions nowadays,and gets the relationships among measuring bound,precision and scanning speed which are based on contrasting and analyzing of scanner's technical parameter.Finally,because of scanner's disadvantages,the article forecasts the future development of the accurate orientation,integrating many function,localization and common software.
[Downloads: 4,242 ] [Citations: 274 ] [Reads: 11 ] HTML PDF Cite this article
Analysis on Digital Image Processing with Python
HAN Xiaodong;WANG Haosen;WANG Shuo;WANG Jianwen;Wang Jie;Python is an object-oriented,literal translation of computer language.Although it has only more than 10 years of development history,because of its rich and powerful library,mature and stable,it has a compilation,and runsall operating system.For the characteristics of digital image processing,the use of Python language,To explore its application in grayscale transformation,image histogram,histogram equalization,image averaging and Gaussian blur,And examples illustrate Python's techniques and methods in image processing.