ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences最新文献_第8页

MEASURING LAND USE CHANGES AND QUANTIFYING URBAN EXPANSION USING REMOTE SENSING AND GIS TECHNIQUES – A CASE STUDY OF QOM 利用遥感和地理信息系统技术测量土地利用变化和量化城市扩张——以库姆为例

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-609-2023

Y. Norouzi

{"title":"MEASURING LAND USE CHANGES AND QUANTIFYING URBAN EXPANSION USING REMOTE SENSING AND GIS TECHNIQUES – A CASE STUDY OF QOM","authors":"Y. Norouzi","doi":"10.5194/isprs-annals-x-4-w1-2022-609-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-609-2023","url":null,"abstract":"Abstract. Rapid urban sprawl necessitates solid urban planning tactics, which requires assessing and quantifying the sustainable or unsustainable encroachment of urban settings towards the urban periphery. Like many cities in developing countries, Iranian cities have witnessed tremendous changes in recent decades. The process of urbanization following economic and social developments has caused the intractable and unrestrained growth of cities with a national and regional role. Remote sensing and geospatial information system technology give urban planners the appropriate and pertinent information they need to guarantee the sustainable management of urban environments. This study explored the changes in Qom metropolis, Iran during four time periods, from 1985, 2000, 2010, and 2021, and assessed how the city expanded using Shannon's entropy model and the Urban Expansion Intensity Index. In this study, Landsat satellite images from the selected years were employed, and three land use/land cover classification types, including agricultural, built-up, and others, were derived using the maximum likelihood classification approach. The relative Shannon’s entropy result for the study years (1985, 2000, 2010, and 2021) are 0.66, 0.68, 0.69, and 0.86 respectively, which demonstrate a dispersed expansion pattern, with the maximum value in 2021. Also, the Urban Expansion Intensity Index, with the values 0.33, 0.33, and 0.51 for three periods (1985–2000, 2000–2010, 2010–2021), indicates that the city's expansion rate was low-speed throughout the chosen periods, despite having reached its peak between 2010 and 2021.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"700 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76854060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

REGISTRATION, GEOREFERENCING AND PROCESSING OF MULTIPLE LASER SCANS ACQUIRED BY TERRESTRIAL LASER SCANNER FOR ESTIMATING TREE MORPHOLOGICAL PARAMETERS 地面激光扫描仪获取的多幅激光扫描图像的配准、地理参考和处理，用于估算树木形态参数

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-737-2023

M. Verma, M. Yadav

引用次数: 1

A FLEXIBLE TRAJECTORY COMPRESSION ALGORITHM FOR MULTI-MODAL TRANSPORTATION 一种多式联运柔性轨迹压缩算法

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-501-2023

S. S. Mirvahabi, R. Ali Abbaspour, C. Claramunt

{"title":"A FLEXIBLE TRAJECTORY COMPRESSION ALGORITHM FOR MULTI-MODAL TRANSPORTATION","authors":"S. S. Mirvahabi, R. Ali Abbaspour, C. Claramunt","doi":"10.5194/isprs-annals-x-4-w1-2022-501-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-501-2023","url":null,"abstract":"Abstract. Continuous progress in navigation, sensor-based, and GPS technologies have made smart devices essential to our daily lives and many location-based applications. However, the trajectory datasets generated by these applications require the management of large data volumes while preserving their main properties and semantics. One of the most popular methods for compressing trajectory data offline is the Douglas–Peucker (DP) algorithm, but its principles should be applied to a diverse range of contexts when considering real-time trajectory data. This paper introduces a Flexible Douglas-Peucker algorithm (FDP) that takes into account the data’s diversity, underlying properties, and semantics. The proposed framework is applied to the Geolife benchmark dataset with a series of different thresholds that reflects different contexts and constraints when performing a trajectory compression process. The results show that the proposed algorithm achieves a significant compression rate while preserving trajectory data points that have a semantic role concerning different modes of transportation.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80922702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IDENTIFICATION AND SEPARATION OF RICE FIELDS USING REMOTE SENSING 稻田的遥感识别与分离

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-509-2023

S. Mirzapour, P. Alemi Safaval, S. Karimi, S. Behzadi, M. K. Kheirkhah Zarkesh, H. Zavar, S. H. Hashemi Ashka

引用次数: 0

WHEAT BIOMASS ESTIMATION FROM UAV IMAGERY USING AN ENSEMBLE LEARNING APPROACH WITH BAYESIAN OPTIMIZATION 基于贝叶斯优化的集成学习方法的无人机图像小麦生物量估算

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-515-2023

F. Moradi, A. Zarei, S. Ranjbar, S. Homayouni

{"title":"WHEAT BIOMASS ESTIMATION FROM UAV IMAGERY USING AN ENSEMBLE LEARNING APPROACH WITH BAYESIAN OPTIMIZATION","authors":"F. Moradi, A. Zarei, S. Ranjbar, S. Homayouni","doi":"10.5194/isprs-annals-x-4-w1-2022-515-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-515-2023","url":null,"abstract":"Abstract. Wheat is one of the most important food supply and food security globally, especially in developing countries. Therefore, predicting the performance and determining the factors that affect the production of this product is very important. Biomass is one of the crop’s most important biophysical parameters, and its correct estimation can help improve accurate monitoring of growth and crop performance forecasting. With the recent advances in remote sensing, access to aerial images taken by unmanned aerial vehicles (UAV) for monitoring crops has been provided. This study investigates the potential of visible UAV images and the resulting vegetation indices to estimate the dry biomass of two types of Brazilian wheat. For this purpose, the performance of three regression algorithms, including Random Forest (RF), eXtreme Gradient Boosting (XGB), and Gradient Boosting Machine (GBM), to estimate wheat biomass was evaluated. Also, to improve the performance of regression models, Bayesian optimization (BO) was used to adjust the Hyper-parameters, and random forest feature selection was used to select the optimal subset of features. Based on the results, the XGB algorithm with the Root Mean Square Error (RMSE) of about 911.86 (Kg/ha) and coefficient of determination (R2) of about 0.89% showed better performance in biomass estimation than other algorithms.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85453502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ADVANCED CLUSTERING OF ARCHITECTURAL GEOMETRIC ORNAMENTS USING SMALL SCALE MACHINE LEARNING, CASE STUDY OF ILKHANID GEOMETRIC PATTERNS 使用小规模机器学习的建筑几何装饰的高级聚类，ilkhanid几何图案的案例研究

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-417-2023

A. Mahmudnejad, E. Andaroodi, M. Saadatseresht

{"title":"ADVANCED CLUSTERING OF ARCHITECTURAL GEOMETRIC ORNAMENTS USING SMALL SCALE MACHINE LEARNING, CASE STUDY OF ILKHANID GEOMETRIC PATTERNS","authors":"A. Mahmudnejad, E. Andaroodi, M. Saadatseresht","doi":"10.5194/isprs-annals-x-4-w1-2022-417-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-417-2023","url":null,"abstract":"Abstract. Classification is an essential step for architectural historians for better understanding and typology of cultural heritage. This research aims to automatically cluster geometric ornaments of the Ilkhanid period in Iran through using machine learning It examines the application of advanced computer science tools and methods in analysis of architectural heritage by searching the possibility of clustering ornament images with machine learning into different clusters. After examining case studies of mosques, tombs or other buildings in Iran from the Ilkhanid period (1256–1335 CE), 231 images from 36 existing buildings were chosen, and after editing images, an inventory was created based on characterization of each ornament (image) containing: Buildings’ Name, Region, Construction Date, Functionality, Repetition of Motifs, Material, Ornamental Types, Design Complexity, Dominant Colour, Star-Number, Geometric Shape, Geometric Lines, and Geometric Pieces. Next, these images were analysed with small-scale machine learning with the help of the visual programming toolbox Orange (http://orange.biolab.si). The results containing image groups (machine clustered images) were tested with the characterization table of ornaments, and groups of ornaments that represents a style is introduced.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"47 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90053010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

DETECTING MULTIPATH EFFECTS ON SMARTPHONE GNSS MEASUREMENTS USING CMCD AND ELEVATION-DEPENDENT SNR SELECTION TECHNIQUE 利用CMCD和仰角相关信噪比选择技术检测智能手机GNSS测量中的多径效应

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-595-2023

Samin Nasr-Azadani, M.Mahdi, Harald Schuh

引用次数: 2

EVALUATION OF LONG-TERM OBSERVATION OF OCEANIC CURRENTS IN THE COASTAL AREAS OF THE OMAN SEA (MOKRAN COAST) USING COASTAL HIGH- FREQUENCY RADARS 阿曼海(莫克兰海岸)沿海高频雷达对海流长期观测的评价

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-467-2023

M. Maleknezhad, A. Tayfehrostami, A. Abedini, B. Tajfirooz

{"title":"EVALUATION OF LONG-TERM OBSERVATION OF OCEANIC CURRENTS IN THE COASTAL AREAS OF THE OMAN SEA (MOKRAN COAST) USING COASTAL HIGH- FREQUENCY RADARS","authors":"M. Maleknezhad, A. Tayfehrostami, A. Abedini, B. Tajfirooz","doi":"10.5194/isprs-annals-x-4-w1-2022-467-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-467-2023","url":null,"abstract":"Abstract. Ocean currents are of interest to all who deal with marine affairs. Since they can be predicted, as a result, they are essential as renewable energy for us. We can use it in many applications like navigation, generating electricity, and port constructions. So, studying them and discovering the factors that create and influence them is significant. Using the instrumentation that we can use continuously and do not have many problems is preferred. Therefore, using new technologies instead of old traditional methods is crucial. In this study, we discuss ocean currents in the Oman Sea, suggest high-frequency radars (HFR) as new technology, and represent its advantages instead of ADCP. We use Mike 21 to get tidal current constituents and compare them with other data. The results show that values of two components, Mm and MSF, are more respective to astronomical-driven currents. Therefore, the amount of tidal current on the coast of Mokran is low, and other factors cause the current, which short-term observations in this region cannot be achieved. Thus, we need data in a more extended period to find present generating forces and predict them. HFR can be an efficient and valuable tool in such areas.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"273 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75943062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BUILDING RECONSTRUCTION BASED ON A SMALL NUMBER OF TRACKS USING NONPARAMETRIC SAR TOMOGRAPHIC METHODS 基于少量轨迹的非参数SAR层析成像方法的建筑物重建

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-617-2023

M. Omati, M. Omati, M. Bastani

{"title":"BUILDING RECONSTRUCTION BASED ON A SMALL NUMBER OF TRACKS USING NONPARAMETRIC SAR TOMOGRAPHIC METHODS","authors":"M. Omati, M. Omati, M. Bastani","doi":"10.5194/isprs-annals-x-4-w1-2022-617-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-617-2023","url":null,"abstract":"Abstract. Nowadays, the synthetic aperture radar (SAR) tomography (TomoSAR) technique plays a notable role in the 3D reconstruction of urban buildings through several SAR acquisitions with slightly different positions. Nonparametric-based TomoSAR spectral estimation algorithms usually work well when a large number of SAR observations. In this study, with a limited number of SAR images, we have assessed the efficiency of the nonparametric spectral estimation methods, including maximum entropy (ME), singular value decomposition (SVD), linear prediction (LP), Capon, minimum norm (MN), and beamforming (BF) in the reconstruction of the third dimension of urban buildings. The experiments are conducted on both simulated and TerraSAR-X stripmap images to indicate the effectiveness of the LP proposed estimation algorithm. The analysis of the results proves that by minimizing the average output signal power over the antenna array elements, the LP spectral estimation achieves the discrimination of distinct scatterers inside an image pixel. In addition, this low computational estimator improves the sidelobe suppression and the height estimates of the scatterers in the complex multiple-scattering urban environment. Compared to SVD, maximum entropy, Capon, minimum norm, and beamforming, the height of the Eskan tower in Tehran, Iran, obtained with the LP technique, is considerably near to field-based measurement.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86022618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IMPROVED INDOOR POSITIONING USING FINGERPRINT TECHNIQUE AND WEIGHTED K-NEAREST NEIGHBOUR 利用指纹技术和加权k近邻改进室内定位

ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-01-14 DOI: 10.5194/isprs-annals-x-4-w1-2022-575-2023

Sh. Naderi Salim, M. M. Alizadeh, S. Chamankar, H. Schuh

{"title":"IMPROVED INDOOR POSITIONING USING FINGERPRINT TECHNIQUE AND WEIGHTED K-NEAREST NEIGHBOUR","authors":"Sh. Naderi Salim, M. M. Alizadeh, S. Chamankar, H. Schuh","doi":"10.5194/isprs-annals-x-4-w1-2022-575-2023","DOIUrl":"https://doi.org/10.5194/isprs-annals-x-4-w1-2022-575-2023","url":null,"abstract":"Abstract. Global Navigation Satellite Systems are not effective when there is no direct line of sight between the user and the satellites, such as indoor environments and dense urban areas. Today, location-based services are used significantly due to their utility and ease of access. The fingerprint method is one of the common methods of determining the location in indoor environments. In this research, the indoor positioning system based on the fingerprint algorithm with a wireless network has been implemented. The positioning system based on the method of nearest neighbour and weighted K-nearest neighbour with two access points has been implemented in two different scenarios. The output accuracy of each technique has been compared to each other. The main goal of this article is to compare the accuracy of positioning with the fingerprint method using the mentioned algorithms and to find the most suitable mode and algorithm for determining the indoor position in most places. The improved weighted nearest neighbour method will have an almost acceptable result in all scenarios and also in the first scenario with dense and regular reference points the weighted K-nearest neighbour method with RMSE=0.2812(m) has provided the best result. In the second scenario with scattered and irregular reference points the weighted K-nearest neighbour with RMSE=0.6735(m) has given lower accuracy result.\u0000","PeriodicalId":30633,"journal":{"name":"ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78164638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0