scholarly journals Spatial Video Health Risk Mapping in Informal Settlements: Correcting GPS Error

2018 ◽  
Vol 16 (1) ◽  
pp. 33 ◽  
Author(s):  
Andrew Curtis ◽  
Sandra Bempah ◽  
Jayakrishnan Ajayakumar ◽  
Dania Mofleh ◽  
Lorriane Odhiambo
Keyword(s):  
Global Positioning System ◽  
Informal Settlement ◽  
Informal Settlements ◽  
Risk Mapping ◽  
Health Interventions ◽  
Health Concern ◽  
Original Video ◽  
Global Positioning ◽  
Spatial Video ◽  
Coordinate Error

Informal settlements pose a continuing health concern. While spatial methodologies have proven to be valuable tools to support health interventions, several factors limit their widespread use in these challenging environments. One such technology, spatial video, has been used for fine-scale contextualized mapping. In this paper, we address one of the limitations of the technique: the global positioning system (GPS) coordinate error. More specifically, we show how spatial video coordinate streams can be corrected and synced back to the original video to facilitate risk mapping. Past spatial video collections for the Mathare informal settlement of Kenya are used as an illustration as these data had been previously discarded because of excessive GPS error. This paper will describe the bespoke software that makes these corrections possible, and then will go on to investigate patterns in the coordinate error.

Enabling participatory planning with GIS: a case study of settlement mapping in Cuttack, India

2012 ◽  
Vol 24 (1) ◽  
pp. 77-97 ◽  
Author(s):  
Avery Livengood ◽  
Keya Kunte
Keyword(s):  
Planning Process ◽  
Central Government ◽  
Informal Settlement ◽  
Informal Settlements ◽  
City Government ◽  
Global Positioning ◽  
Slum Upgrading ◽  
Government Fund ◽  
Gps Devices

This paper describes the use of Global Positioning System (GPS) devices to map informal settlements in Cuttack, India in ways that enhance and support residents’ participation in the data collection and planning process. Rather than relying on remote sensing to identify informal settlement locations, each settlement is visited individually by a mapping team comprised of community leaders and NGO staff. The mapping team meets with settlement residents to develop a detailed settlement profile and map the settlement boundary using a GPS device. This process has helped to open and sustain a dialogue between the residents of informal settlements and city government around “slum” upgrading, and has influenced the use of a central government fund to support local upgrading plans.

scholarly journals Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jayakrishnan Ajayakumar ◽  
Andrew J. Curtis ◽  
Vanessa Rouzier ◽  
Jean William Pape ◽  
Sandra Bempah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Health Risk ◽  
Spatial Data ◽  
Model Performance ◽  
Informal Settlements ◽  
Environmental Risks ◽  
Image Resolution ◽  
Risk Mapping ◽  
Spatial Video

Abstract Background The health burden in developing world informal settlements often coincides with a lack of spatial data that could be used to guide intervention strategies. Spatial video (SV) has proven to be a useful tool to collect environmental and social data at a granular scale, though the effort required to turn these spatially encoded video frames into maps limits sustainability and scalability. In this paper we explore the use of convolution neural networks (CNN) to solve this problem by automatically identifying disease related environmental risks in a series of SV collected from Haiti. Our objective is to determine the potential of machine learning in health risk mapping for these environments by assessing the challenges faced in adequately training the required classification models. Results We show that SV can be a suitable source for automatically identifying and extracting health risk features using machine learning. While well-defined objects such as drains, buckets, tires and animals can be efficiently classified, more amorphous masses such as trash or standing water are difficult to classify. Our results further show that variations in the number of image frames selected, the image resolution, and combinations of these can be used to improve the overall model performance. Conclusion Machine learning in combination with spatial video can be used to automatically identify environmental risks associated with common health problems in informal settlements, though there are likely to be variations in the type of data needed for training based on location. Success based on the risk type being identified are also likely to vary geographically. However, we are confident in identifying a series of best practices for data collection, model training and performance in these settings. We also discuss the next step of testing these findings in other environments, and how adding in the simultaneously collected geographic data could be used to create an automatic health risk mapping tool.

GPS and GSM Based Tracking System for Objects Moving over Wide Geographical Areas

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Fatima Ameen ◽  
Ziad Mohammed ◽  
Abdulrahman Siddiq
Keyword(s):  
Global Positioning System ◽  
Mobile Communications ◽  
Moving Objects ◽  
Tracking System ◽  
Geographical Area ◽  
Tracking Systems ◽  
Acceptable Result ◽  
Internet Service ◽  
Global Positioning ◽  
Tracking Objects

Tracking systems of moving objects provide a useful means to better control, manage and secure them. Tracking systems are used in different scales of applications such as indoors, outdoors and even used to track vehicles, ships and air planes moving over the globe. This paper presents the design and implementation of a system for tracking objects moving over a wide geographical area. The system depends on the Global Positioning System (GPS) and Global System for Mobile Communications (GSM) technologies without requiring the Internet service. The implemented system uses the freely available GPS service to determine the position of the moving objects. The tests of the implemented system in different regions and conditions show that the maximum uncertainty in the obtained positions is a circle with radius of about 16 m, which is an acceptable result for tracking the movement of objects in wide and open environments.

Aplikasi Pemosisi Lokal Berbasis Android Dengan Menggunakan GPS

INTI TALAFA ◽  
2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Yaman Khaeruzzaman
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Database Server ◽  
Global Positioning

Seiring dengan pesatnya kemajuan teknologi saat ini, kebutuhan manusia menjadi lebih beragam, termasuk kebutuhan akan informasi. Tidak hanya media informasinya yang semakin beragam, jenis informasi yang dibutuhkan juga semakin beragam, salah satunya adalah kebutuhan informasi akan posisi kita terhadap lingkungan sekitar. Untuk memenuhi kebutuhan itu sebuah sistem pemosisi diciptakan. Sistem pemosisi yang banyak digunakan saat ini cenderung berfokus pada lingkup ruang yang besar (global) padahal, dalam lingkup ruang yang lebih kecil (lokal) sebuah sistem pemosisi juga diperlukan, seperti di ruang-ruang terbuka umum (taman atau kebun), ataupun dalam sebuah bangunan. Sistem pemosisi lokal yang ada saat ini sering kali membutuhkan infrastruktur yang mahal dalam pembangunannya. Aplikasi Pemosisi Lokal Berbasis Android dengan Menggunakan GPS ini adalah sebuah aplikasi yang dibangun untuk memenuhi kebutuhan pengguna akan informasi lokasi dan posisi mereka terhadap lingkungan di sekitarnya dalam lingkup ruang yang lebih kecil (lokal) dengan memanfaatkan perangkat GPS (Global Positioning System) yang telah tertanam dalam perangkat smartphone Android agar infrastruktur yang dibutuhkan lebih efisien. Dalam implementasinya, Aplikasi Pemosisi Lokal ini bertindak sebagai klien dengan dukungan sebuah Database Server yang berfungsi sebagai media penyimpanan data serta sumber referensi informasi yang dapat diakses melalui jaringan internet sehingga tercipta sebuah sistem yang terintegrasi secara global. Kata kunci: aplikasi, informasi, pemosisi, GPS.

The Distribution of Hospitality Services in Uyo Urban, Nigeria

2018 ◽  
pp. 137-150
Author(s):  
Violet Bassey Eneyo
Keyword(s):  
Data Collection ◽  
Global Positioning System ◽  
Central Area ◽  
Positioning System ◽  
Nearest Neighbour ◽  
Global Positioning ◽  
Neighbour Analysis

This paper examines the distribution of hospitality services in Uyo Urban, Nigeria. GIS method was the primary tool used for data collection. A global positioning system (GPS) Garmin 60 model was used in tracking the location of 102 hospitality services in the study area. One hypothesis was stated and tested using the nearest neighbour analysis. The finding shows evidence of clustering of the various hospitality services. The tested hypothesis further indicated that hospitality services clustered in areas that guarantee a sustainable level of patronage to maximize profit. Thus, the hospitality services clustered in selected streets in the metropolis while limited numbers were found outside the city’s central area.

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