Landscape Planning and Design Based on E Cognition High-resolution Remote Sensing Image
Author: 
Yan WuAuthors Info & Claims
Yan WuAuthors Info & ClaimsArticle No.: 9, Pages 1 - 5
Abstract
High resolution remote sensing image resource is a very important geographic information recording medium. It has great utilization value and can be digitized, informationized and transmitted through network in space. This paper mainly introduces the idea and implementation process of forming a high resolution remote sensing image resource classification system based on the combination of E-Cognition high resolution remote sensing image receiving technology and blind area recognition theory. And it also briefly analyzes the application status of this method. In addition, the landscape planning platform is designed later, and the performance of the platform is tested. The test results show that the landscape planning platform based on eCognition high-resolution remote sensing images can accurately locate user needs, with user accuracy of more than 80%.
References
[1]
Guangqi Wen, Peng Cao, Haonan Wang, Hanlin Chen, Xiaoli Liu, Jinghui Xu, Osmar R. Zaïane:MS-SSD: multi-scale single shot detector for ship detection in remote sensing images. Appl. Intell. 53(2): 1586-1604 (2023).
[2]
Imran Ali, Zohaib Mushtaq, Saad Arif, Abeer D. Algarni, Naglaa F. Soliman, Walid El Shafai:Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing. Comput. Syst. Sci. Eng. 46(1): 303-319 (2023).
[3]
S. Rajalakshmi, S. Nalini, Ahmed Alkhayyat, Rami Qays Malik:Hyperspectral Remote Sensing Image Classification Using Improved Metaheuristic with Deep Learning. Comput. Syst. Sci. Eng. 46(2): 1673-1688 (2023).
[4]
Pradeep Kumar Ladi, Murali Gopal Kakita, Ratnakar Dash, Sandeep Kumar Ladi:PKNNet: a novel feature learning architecture for vegetation mapping using remote sensing hyperspectral image classification. Earth Sci. Informatics 16(1): 1091-1107 (2023).
[5]
Rubeena Vohra, K. C. Tiwari:Land cover classification using multi-fusion based dense transpose convolution in fully convolutional network with feature alignment for remote sensing images. Earth Sci. Informatics 16(1): 983-1003 (2023).
[6]
N. A. Lawrance, T. S. Shiny Angel:Performance evaluation of image fusion techniques and implementation of new fusion technique for remote sensing satellite data. J. Intell. Fuzzy Syst. 44(2): 3353-3367 (2023).
[7]
Meera Ramadas, Ajith Abraham:Segmentation on remote sensing imagery for atmospheric air pollution using divergent differential evolution algorithm. Neural Comput. Appl. 35(5): 3977-3990 (2023).
[8]
Wei Lu, LiJun Zhao, Rong Xu:Remote sensing image processing technology based on mobile augmented reality technology in surveying and mapping engineering. Soft Comput. 27(1): 423-433 (2023).
[9]
Bhuwan Bhattarai, Yagya Raj Pandeya, Jie You, Arjun Kumar Lamichhane, Joonwhoan Lee:High-Resolution Representation Learning and Recurrent Neural Network for Singing Voice Separation. Circuits Syst. Signal Process. 42(2): 1083-1104 (2023).
[10]
Gongyang Li, Zhi Liu, Dan Zeng, Weisi Lin, Haibin Ling:Adjacent Context Coordination Network for Salient Object Detection in Optical Remote Sensing Images. IEEE Trans. Cybern. 53(1): 526-538 (2023).
[11]
Wahidya Nurkarim, Arie Wahyu Wijayanto:Building footprint extraction and counting on very high-resolution satellite imagery using object detection deep learning framework. Earth Sci. Informatics 16(1): 515-532 (2023).
[12]
Madan Parajuli, Mohamed Shaban, Thuy L. Phung:Automated differentiation of skin melanocytes from keratinocytes in high-resolution histopathology images using a weakly-supervised deep-learning framework. Int. J. Imaging Syst. Technol. 33(1): 262-275 (2023).
Index Terms
- Landscape Planning and Design Based on E Cognition High-resolution Remote Sensing Image
Recommendations
An Agglomerative Hierarchical Clustering Based High-Resolution Remote Sensing Image Segmentation Algorithm
CSSE '08: Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 04Remote sensing image segmentation is the basis of image pattern recognition. It is significant for the application and analysis of remote sensing images. Clustering analysis as a non-supervised learning method is widely used in the segmentation of ...
Multilevel similarity model for high-resolution remote sensing image registration
AbstractImage registration is a prerequisite and the basis for many important applications of remote sensing images. Compared with medium-/low-resolution images, high-resolution (HR) remote sensing images exhibit considerable resolution ...
A Shadow Detection Method from Urban High Resolution Remote Sensing Image Based on Color Features of Shadow
ISISE '12: Proceedings of the 2012 Fourth International Symposium on Information Science and EngineeringWhile high resolution remote sensing images have clearer landscape detail and richer spatial information than low and moderate resolution remote sensing images, high-resolution imagery contains more shadows in the urban areas. First, four color features ...
Comments
Information & Contributors
Information
Published In
December 2023
292 pages
ISBN:9798400709401
DOI:10.1145/3632314
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 09 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ISIA 2023
ISIA 2023: 2023 International Conference on Intelligent Sensing and Industrial Automation
December 9 - 10, 2023
Virtual Event, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 19Total Downloads
- Downloads (Last 12 months)11
- Downloads (Last 6 weeks)0
Reflects downloads up to 03 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format