scholarly journals Assessment of potential locations for evacuation in Depok Municipality using images from UAV

2021 ◽  
Vol 884 (1) ◽  
pp. 012009
Author(s):  
Amrih Halil ◽  
Revi Hernina ◽  
Rokhmatuloh
Keyword(s):  
Image Processing ◽  
Residential Area ◽  
Aerial Images ◽  
Safety Study ◽  
Public Facilities ◽  
Soccer Field

Abstract This study aims to perform assessment of public facilities in Perumnas Depok Utara, Depok Municipality, Indonesia for evacuation locations using images from UAV. A UAV device, a DJI Phantom 4 was flown at 100 metres height to capture seven locations of public facilities located within Perumnas Depok Utara residential area. Raw images from DJI Phantom 4 underwent image processing and georeferencing process to generate smooth aerial images. Public facilities locations were identified from acquired images and later digitized to generate layers of assessment parameters. Each locations were scored based on rating of all criteria’s parameters. Seven criteria serve as foundation layers for evacuation assessment namely size, ownership, availability, capacity, infrastructure, transportation and safety. Study result shows that Jawa Soccer Field is the first rank of potential evacuation location while Balai Rakyat Meeting Place is the least potential evacuation location. Total area for potential evacuation locations around 43,000 m2 and can accommodate 28,961 people or equal to 60.5% of Beji Village’s population.

scholarly journals Implementación de un software para el análisis de imágenes aéreas multiespectrales de caña de azúcar [Implementation of software for the analysis of multispectral aerial images sugarcane]

2013 ◽  
Author(s):  
Gerardo Schneider ◽  
Alejandro Javier Hadad ◽  
Alejandra Kemerer
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Crop Productivity ◽  
Software Implementation ◽  
Aerial Images ◽  
The Status

Resumen En este trabajo se presenta una implementación de software para la determinación del estado de plantaciones de caña de azúcar basado en el análisis de imágenes aéreas multiespectrales. En la actualidad no existen técnicas precisas para estimar objetivamente la superficie de caña caída o volcada, y esta ocasiona importantes pérdidas de productividad en la cosecha y en la industrialización. Para la realización de éste trabajo se confeccionó un dataset referencial de imágenes, y se implementó un software a partir del cual se obtuvieron indicadores propuestos como representativos del fenómeno agronómico, y se realizaron análisis de los datos generados. Además se implementó un software clasificador referencial basado en redes neuronales con el que se estimó la fortaleza de dichos indicadores y se estimó la superficie afectada en forma cuantitativa y espacial. Palabras ClavesCaña de azúcar, cuantificación, volcado, red neuronal, procesamiento de imagen   Abstract In this paper we present a software implementation for determining the status of sugarcane plantations based on the analysis of multispectral aerial images. Currently there are no precise techniques to estimate objectively the cane area fall or overturned, and this causes significant losses in crop productivity and industrialization. For the realization of this work a dataset benchmark images was made, and a software, from which were obtained representative proposed indicators for the agronomic phenomenon was implemented, and analyzes of the data generated were realized. In addition, we implemented a software benchmark classifier based on neural networks with which we estimated the strength of these indicators and the area affected was estimated quantitatively and spatially. Keywords Sugarcane, quantification, fall, neural network, image processing

scholarly journals Rain Gutter Detection in Aerial Images for Aedes aegypti Mosquito Prevention

2020 ◽  
Author(s):  
Lucas Rossi ◽  
André Backes ◽  
Jefferson Souza
Keyword(s):  
Image Processing ◽  
Aedes Aegypti ◽  
Unmanned Aerial Vehicle ◽  
Digital Image Processing ◽  
Yellow Fever ◽  
Automatic System ◽  
Aerial Images ◽  
Aerial Vehicle ◽  
Mosquito Breeding ◽  
Breeding Location

The detection of Aedes aegypti mosquito is essential in the prevention process of serious diseases such as dengue, yellow fever, chikungunya, and Zika virus. Common approaches consist of surveillance agents who need to enter residences to find and eliminate these outbreaks, but often they are unable to do this work due to the absence or resistance of the resident. This paper proposes an automatic system that uses aerial images obtained through a camera coupled from an Unmanned Aerial Vehicle (UAV) to identify rain gutters from a shed that may be mosquitoes’ foci. We use Digital Image Processing (DIP) techniques to differentiate the objects that may or may not be those foci of the mosquito-breeding. The experimental results show that the system is capable of automatically detecting the appropriately mosquito-breeding location.

scholarly journals Fuzzy Similarity Measure and its Application to High Resolution Colour Remote Sensing Image Processing

2021 ◽  
Author(s):  
Yu Li
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
High Resolution ◽  
Similarity Measure ◽  
Remote Sensing Image ◽  
Aerial Images ◽  
Fuzzy Similarity ◽  
Short Range Ordering ◽  
Remote Sensing Image Processing ◽  
The Relationship

The focus for the study in this thesis is placed on developing basic algorithms and tools for high-resolution colour remote sensing image processing tasks such as colour morphology, multivariate clustering, and multivariate filtering. First, the fuzzy similarity measure (FSM) among vectors in a vector space is introduced. This measure is based on two assumptions for the relationship among vectors: short-range ordering and fuzzification. Second, based on the FSM, the colour morphology, multivariate fuzzy clustering, and multivariate filtering are defined. The performances of all proposed methods will be evaluated numerically and subjectively. Third, this study also places more emphases on solving some applied problems related to recognizing colour edges, detecting and extracting complex road network and building rooftops, and reducing noise in high-resolution remote sensing images such as QuickBird, Ikonos, and aerial images. The results obtained in the study demonstrate the effectiveness and efficacy of the FMS and the proposed methods.

scholarly journals AUTOMATIC SEA BIRD DETECTION FROM HIGH RESOLUTION AERIAL IMAGERY

2016 ◽  
Vol XLI-B7 ◽  
pp. 299-303
Author(s):  
S. Mader ◽  
G. J. Grenzdörffer
Keyword(s):  
Image Processing ◽  
Marine Mammals ◽  
Feature Detection ◽  
Bird Species ◽  
Automatic Monitoring ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Processing Methods ◽  
Bird Detection ◽  
Global Operations

Great efforts are presently taken in the scientific community to develop computerized and (fully) automated image processing methods allowing for an efficient and automatic monitoring of sea birds and marine mammals in ever-growing amounts of aerial imagery. Currently the major part of the processing, however, is still conducted by especially trained professionals, visually examining the images and detecting and classifying the requested subjects. This is a very tedious task, particularly when the rate of void images regularly exceeds the mark of 90%. In the content of this contribution we will present our work aiming to support the processing of aerial images by modern methods from the field of image processing. We will especially focus on the combination of local, region-based feature detection and piecewise global image segmentation for automatic detection of different sea bird species. Large image dimensions resulting from the use of medium and large-format digital cameras in aerial surveys inhibit the applicability of image processing methods based on global operations. In order to efficiently handle those image sizes and to nevertheless take advantage of globally operating segmentation algorithms, we will describe the combined usage of a simple performant feature detector based on local operations on the original image with a complex global segmentation algorithm operating on extracted sub-images. The resulting exact segmentation of possible candidates then serves as a basis for the determination of feature vectors for subsequent elimination of false candidates and for classification tasks.

scholarly journals Fuzzy Similarity Measure and its Application to High Resolution Colour Remote Sensing Image Processing

2021 ◽  
Author(s):  
Yu Li
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
High Resolution ◽  
Similarity Measure ◽  
Remote Sensing Image ◽  
Aerial Images ◽  
Fuzzy Similarity ◽  
Short Range Ordering ◽  
Remote Sensing Image Processing ◽  
The Relationship

The focus for the study in this thesis is placed on developing basic algorithms and tools for high-resolution colour remote sensing image processing tasks such as colour morphology, multivariate clustering, and multivariate filtering. First, the fuzzy similarity measure (FSM) among vectors in a vector space is introduced. This measure is based on two assumptions for the relationship among vectors: short-range ordering and fuzzification. Second, based on the FSM, the colour morphology, multivariate fuzzy clustering, and multivariate filtering are defined. The performances of all proposed methods will be evaluated numerically and subjectively. Third, this study also places more emphases on solving some applied problems related to recognizing colour edges, detecting and extracting complex road network and building rooftops, and reducing noise in high-resolution remote sensing images such as QuickBird, Ikonos, and aerial images. The results obtained in the study demonstrate the effectiveness and efficacy of the FMS and the proposed methods.

Discussion on the Supplying Merchanism of the Supporting Public Facilities of the Urban Edges Residential Area

2011 ◽  
Vol 368-373 ◽  
pp. 3074-3077
Author(s):  
Yan Peng ◽  
Yi Chen
Keyword(s):  
Residential Area ◽  
Urban Fringe ◽  
Slow Start ◽  
The Public ◽  
Public Facilities ◽  
Public Products ◽  
Set Up

The construction of the new urban fringe residential area is developing very fast during the urban process, but the construction and management of the public products and service in this area are relatively slow. Start with the supply classify, we hope to set up a new, perfect supplying mechanism of the public products and service from the planning, construction, and the management.

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