scholarly journals Analysis of Peri-Urban Areas Under Durg-Bhilai Development Plan Using Satellite Image: Need of Policy & Challenges to Governance: A Review

2021 ◽  
Vol 10 (1) ◽  
pp. 7-7
Author(s):  
Rustam Sahu ◽  
Sonam Vaidya ◽  
Shubham Yadav
Keyword(s):  
Urban Areas ◽  
Satellite Image ◽  
Development Plan

scholarly journals Agro-ecological landuse transformation in oasis systems of Al Jabal Al Akhdar, northern Oman

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andreas Buerkert ◽  
Bryan Adam Dix ◽  
Mohamed Nasser Al Rawahi ◽  
Eva Schlecht
Keyword(s):  
Water Use ◽  
Urban Areas ◽  
Satellite Image ◽  
Treated Wastewater ◽  
Irrigated Agriculture ◽  
Al Jabal Al Akhdar ◽  
Time Series Approach ◽  
Use Efficiency ◽  
Ground Truthing ◽  
Satellite Image Analysis

AbstractThe millenia-old oasis systems in the Western Hajar Mountains of Northern Oman have received widespread attention as models of sustainable irrigated agriculture in hyperarid Arabia. Given Oman’s rampant urbanization, growing scarcity of water and skilled labour, we quantified chances in water use, land use, and land cover between 2007 and 2018 using a rare time-series approach of detailed GIS-based crop mapping. Results from satellite image analysis and comprehensive ground truthing showed that urban areas grew from 206 ha in 2009 to 230 ha in 2014 and 252 ha in 2018. Throughout this decade, irrigated areas in backyards and front-house gardens of the town, planted largely to tree crops and vegetables, increased from 13.5 to 23.3 ha. Between 2007 and 2018 the actively used area of the studied oasis systems declined by 2.0% and the share of perennial crops without underplanting by 5.1%, while land under agroforestry increased by 2.1% and fallow land by 3.5%. Rising water demand of the sprawling town Sayh Qatanah led to terraces of Al ‘Ayn and Ash Sharayjah now being partly irrigated with treated wastewater which accelerated the abandonment of the old settlement structures. The labour- and water use efficiency-driven transformation of the Al Jabal Al Akhdar oasis agriculture into increasingly market-oriented landuse systems questions its function as example of sustainable, bio-cultural heritage of Arabia.

scholarly journals FLOOD MAPPING USING RANDOM FOREST AND IDENTIFYING THE ESSENTIAL CONDITIONING FACTORS; A CASE STUDY IN FREDERICTON, NEW BRUNSWICK, CANADA

2020 ◽  
Vol V-3-2020 ◽  
pp. 609-615 ◽  
Author(s):  
M. Esfandiari ◽  
S. Jabari ◽  
H. McGrath ◽  
D. Coleman
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
New Brunswick ◽  
Urban Areas ◽  
Learning Algorithm ◽  
Satellite Image ◽  
Machine Learning Algorithms ◽  
Slope Aspect ◽  
Flood Peak ◽  
Conditioning Factors

Abstract. Flood is one of the most damaging natural hazards in urban areas in many places around the world as well as the city of Fredericton, New Brunswick, Canada. Recently, Fredericton has been flooded in two consecutive years in 2018 and 2019. Due to the complicated behaviour of water when a river overflows its bank, estimating the flood extent is challenging. The issue gets even more challenging when several different factors are affecting the water flow, like the land texture or the surface flatness, with varying degrees of intensity. Recently, machine learning algorithms and statistical methods are being used in many research studies for generating flood susceptibility maps using topographical, hydrological, and geological conditioning factors. One of the major issues that researchers have been facing is the complexity and the number of features required to input in a machine-learning algorithm to produce acceptable results. In this research, we used Random Forest to model the 2018 flood in Fredericton and analyzed the effect of several combinations of 12 different flood conditioning factors. The factors were tested against a Sentinel-2 optical satellite image available around the flood peak day. The highest accuracy was obtained using only 5 factors namely, altitude, slope, aspect, distance from the river, and land-use/cover with 97.57% overall accuracy and 95.14% kappa coefficient.

scholarly journals Optical Remote Sensing

2021 ◽  
pp. 315-344
Author(s):  
Man Sing Wong ◽  
Xiaolin Zhu ◽  
Sawaid Abbas ◽  
Coco Yin Tung Kwok ◽  
Meilian Wang
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Information Extraction ◽  
Urban Areas ◽  
Satellite Image ◽  
Background Information ◽  
Optical Remote Sensing ◽  
Basic Operation ◽  
City Development ◽  
Satellite Image Processing

AbstractApplications of Earth-observational remote sensing are rapidly increasing over urban areas. The latest regime shift from conventional urban development to smart-city development has triggered a rise in smart innovative technologies to complement spatial and temporal information in new urban design models. Remote sensing-based Earth-observations provide critical information to close the gaps between real and virtual models of urban developments. Remote sensing, itself, has rapidly evolved since the launch of the first Earth-observation satellite, Landsat, in 1972. Technological advancements over the years have gradually improved the ground resolution of satellite images, from 80 m in the 1970s to 0.3 m in the 2020s. Apart from the ground resolution, improvements have been made in many other aspects of satellite remote sensing. Also, the method and techniques of information extraction have advanced. However, to understand the latest developments and scope of information extraction, it is important to understand background information and major techniques of image processing. This chapter briefly describes the history of optical remote sensing, the basic operation of satellite image processing, advanced methods of object extraction for modern urban designs, various applications of remote sensing in urban or peri-urban settings, and future satellite missions and directions of urban remote sensing.

scholarly journals USO DO SOLO E DEGRADAÇÃO AMBIENTAL: estudo de caso da bacia do Mata Fome em Belém, Pará

2017 ◽  
Vol 2 (7) ◽  
pp. 162
Author(s):  
Marcos Jonatas Damasceno da Silva ◽  
Luziane Mesquita da Luz
Keyword(s):  
Urban Space ◽  
Environmental Degradation ◽  
Health Risks ◽  
Urban Areas ◽  
Satellite Image ◽  
Land Uses ◽  
Vegetation Water ◽  
The Relationship ◽  
Soil Changes

São diversos os problemas presentes nos espaços das cidades brasileiras, principalmente nos grandes espaços urbanos. Um desses problemas é a degradação do meio ambiente decorrente de intervenções não planejadas nesses espaços. Nesse sentido, este trabalho tem o propósito de analisar a relação entre a produção do espaço urbano, que atribui diferentes usos ao solo e a degradação do meio ambiente na Bacia do Mata Fome em Belém, Pará. Além disso, foi realizado um mapeamento do uso do solo da área de estudo, onde foi utilizada a imagem do satélite Ikonos de 2006. Os resultados deste trabalho evidenciaram que a produção do espaço urbano na Bacia do Mata Fome e os diversos usos do solo, provocaram degradação ambiental, por desencadearem a destruição da cobertura vegetal, poluição da água e do solo, mudanças na topografia dos terrenos, inundações, riscos à saúde, entre outros danos.Palavras-chave: Meio ambiente; Urbanização; Bacia hidrográfica; Poluição.USE OF SOIL AND ENVIRONMENTAL DEGRADATION: a case study of Mata Fome basin in Belém, ParáABSTRACTThere are several problems present in the spaces of brazilian cities, especially in large urban areas. One such problem is the degradation of the environment due to unplanned interventions in these spaces. In this sense, this work aims to analyze the relationship between the production of urban space that assigns different uses to soil and environmental degradation in the Mata Fome Watershed in Belém, Pará. In addition, we carried out a mapping of the use of soil of the study area where the satellite image Ikonos 2006. The results of this study indicated that the production of urban space in Mata Fome Watershed and various land uses, caused environmental degradation was used to trigger the destruction of vegetation, water pollution and soil changes in the topography of the land, floods, health risks and other damage.Keywords: Environment; Urbanization; Hydrographic watershed; Pollution.USO DEL SUELO Y DEGRADACIÓN AMBIENTAL: estudio del caso de la cuenca del Mata Fome en Belém, ParáRESUMEN Hay varios problemas presentes en los espacios de las ciudades brasileñas, especialmente en las grandes áreas urbanas. Uno de estos problemas es la degradación del medio ambiente debido a las intervenciones no planificadas en estos espacios. En este sentido, este trabajo tiene como objetivo analizar la relación entre la producción del espacio urbano, que asigna a los diferentes usos del suelo y la degradación del medio ambiente en la Cuenca del Mata Fome en Belém, Pará. Además, se realizó un mapeo del uso del suelo de la zona de estudio, donde la imagen de satélite Ikonos 2006. Los resultados de este estudio indicaron que la producción del espacio urbano en la Cuenca del Mata Fome y diversos usos de la tierra causado la degradación ambiental se utilizó para desencadenar la destrucción de la vegetación, la contaminación del agua y los cambios de suelo en la topografía del terreno, inundaciones, riesgos para la salud, y otros daños.Palabras clave: Medio ambiente; Urbanización; Cuenca hidrográfica; Contaminación.

scholarly journals Mapeamento e identificação de vetores responsáveis pela supressão do manguezal na Zona Costeira do Baixo Sul da Bahia, Brasil (Mapping and identification of vectors responsible for mangrove suppression in the Southern Bahia Lowlands, Brazil)

2020 ◽  
Vol 12 (7) ◽  
pp. 2503
Author(s):  
Ana Paula Sena de Souza ◽  
Ivonice Sena de Souza ◽  
George Olavo ◽  
Jocimara Souza Britto Lobão ◽  
Rafael Vinícius de São José
Keyword(s):  
Urban Areas ◽  
Satellite Image ◽  
Mangrove Ecosystem ◽  
Shrimp Farming ◽  
Mangrove Forests ◽  
Coverage Area ◽  
Southern Bahia ◽  
Global Accuracy ◽  
Landsat Satellite ◽  
Accuracy Indices

O ecossistema manguezal representa 8% de toda a linha de costa do planeta ocupando uma área total de 181.077 km2. O Brasil é o segundo país em extensão de áreas de manguezal, ficando atrás apenas da Indonésia. O objetivo do presente estudo foi mapear e identificar os principais vetores responsáveis pela supressão da cobertura das áreas de manguezal na região do Baixo Sul da Bahia, Brasil, a partir de imagens de satélite Landsat disponíveis para o período entre 1994 e 2017. Os mapeamentos foram realizados a partir de classificação supervisionada, utilizando o método Maxver. A acurácia da classificação obtida foi verificada através da verdade de campo, de índices de Exatidão Global, e dos coeficientes de concordância kappa e Tau. As classes que apresentaram maior área de cobertura no período analisado foram: vegetação ombrófila densa, agropecuária, solo exposto e manguezal. Foram identificados dois vetores principais responsáveis pela supressão dos bosques de mangue: a expansão desordenada das áreas urbanas (com destaque para o município de Valença) e o avanço da atividade de carcinicultura clandestina, devido a instalação de tanques de cultivo de camarão sem o devido processo de licenciamento ambiental (sobretudo no município de Nilo Peçanha). O uso das geotecnologias, em especial o Sensoriamento Remoto e os Sistemas de Informações Geográficas, foram ferramentas fundamentais na identificação destes vetores responsáveis pela supressão das áreas de manguezal na área de estudo região do Baixo Sul da Bahia.  Mapping and identification of vectors responsible for mangrove suppression in the Southern Bahia Lowlands, BrazilA B S T R A C TThe mangrove ecosystem represents 8% of the entire coastline of the planet and occupies a total area of 181,077 km2. Brazil is the second largest country in terms of mangrove areas, second only to Indonesia. The aim of the present study was to map and identify the main vectors responsible for the suppression of mangrove cover in the Southern Lowlands of Bahia, Brazil, from Landsat satellite images available for the period 1994-2017. based on supervised classification using the Maxver method. The accuracy of the classification obtained was verified through field truth, Global Accuracy indices, and kappa and Tau agreement coefficients. The classes that presented larger coverage area in the analyzed period were: dense ombrophilous vegetation, agriculture, exposed soil and mangrove. Two main vectors responsible for the suppression of mangrove forests were identified: the disorderly expansion of urban areas (especially the municipality of Valença) and the advance of clandestine shrimp farming due to the installation of shrimp farms without due environmental licensing process (mainly in the municipality of Nilo Peçanha). The use of geotechnologies, especially Remote Sensing and Geographic Information Systems, were fundamental tools in the identification of these vectors responsible for the suppression of mangrove areas in the study area of the Southern Bahia Lowlands.Key-words: environmental impacts, satellite image, shrimp farming.

scholarly journals Towards Sub-Pixel Automatic Geometric Corrections of Very-High Resolution Panchromatic Satellite Data of Urban Areas

2019 ◽  
Vol 11 (9) ◽  
pp. 1097 ◽  
Author(s):  
Aleš Marsetič ◽  
Peter Pehani
Keyword(s):  
Feature Extraction ◽  
High Resolution ◽  
Urban Areas ◽  
Satellite Images ◽  
Reference Data ◽  
Geometric Model ◽  
Control Point ◽  
Satellite Image ◽  
Extraction Algorithm ◽  
Very High

This paper presents an automatic procedure for the geometric corrections of very-high resolution (VHR) optical panchromatic satellite images. The procedure is composed of three steps: an automatic ground control point (GCP) extraction algorithm that matches the linear features that were extracted from the satellite image and reference data; a geometric model that applies a rational function model; and, the orthorectification procedure. Accurate geometric corrections can only be achieved if GCPs are employed to precisely correct the geometric biases of images. Due to the high resolution and the varied acquisition geometry of images, we propose a fast, segmentation based method for feature extraction. The research focuses on densely populated urban areas, which are very challenging in terms of feature extraction and matching. The proposed algorithm is capable of achieving results with a root mean square error of approximately one pixel or better, on a test set of 14 panchromatic Pléiades images. The procedure is robust and it performs well in urban areas, even for images with high off-nadir angles.

scholarly journals Detection of Urban Areas using Genetic Algorithms and Kohonen Maps on Multispectral images

2018 ◽  
Vol 8 (1) ◽  
pp. 46-62 ◽  
Author(s):  
Djelloul Mokadem ◽  
Abdelmalek Amine ◽  
Zakaria Elberrichi ◽  
David Helbert
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithms ◽  
Urban Areas ◽  
Satellite Image ◽  
Initial Population ◽  
Landsat Images ◽  
Kohonen Maps ◽  
Multispectral Satellite Image

In this article, the detection of urban areas on satellite multispectral Landsat images. The goal is to improve the visual interpretations of images from remote sensing experts who often remain subjective. Interpretations depend deeply on the quality of segmentation which itself depends on the quality of samples. A remote sensing expert must actually prepare these samples. To enhance the segmentation process, this article proposes to use genetic algorithms to evolve the initial population of samples picked manually and get the most optimal samples. These samples will be used to train the Kohonen maps for further classification of a multispectral satellite image. Results are obtained by injecting genetic algorithms in sampling phase and this paper proves the effectiveness of the proposed approach.

Post-Disaster Urban Recovery Monitoring in Pisco After the 2007 Peru Earthquake Using Satellite Image

2014 ◽  
Vol 9 (6) ◽  
pp. 1059-1068 ◽  
Author(s):  
Tomoyo Hoshi ◽  
◽  
Osamu Murao ◽  
Kunihiko Yoshino ◽  
Fumio Yamazaki ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Urban Areas ◽  
Satellite Image ◽  
Recovery Process ◽  
Visual Interpretation ◽  
Field Surveys ◽  
Recovery Processes ◽  
The City ◽  
Post Disaster

Pisco was the area most damaged by the 2007 Peru earthquake. The purpose of this research is to develop possibilities of using satellite imagery to monitor postdisaster urban recovery processes, focusing on the urban change in Pisco between 2007 and 2011. To this end, the authors carried out field surveys in the city in 2012 and 2013 and also examined previous surveys to determine that building reconstruction peaked between 2008 and 2009. After analyzing the five-year recovery process, the authors compared its reconstruction conditions by visual interpretation with those by image analysis using satellite image. An accuracy of 71.2% was achieved for the visual interpretation results in congested urban areas, and that for developed districts was about 60%. The result shows that satellite imagery can be a useful tool for monitoring and understanding post-disaster urban recovery processes in the areas in which conducting long-term field survey is difficult.

scholarly journals Implementing area-based approaches (ABAs) in urban post-disaster contexts

2017 ◽  
Vol 29 (2) ◽  
pp. 349-364 ◽  
Author(s):  
David Sanderson
Keyword(s):  
Project Management ◽  
Urban Development ◽  
Urban Areas ◽  
Current Practice ◽  
Scale Up ◽  
Development Plan ◽  
Humanitarian Response ◽  
Management Cycle ◽  
Post Disaster

This paper examines area-based approaches (ABAs) in urban post-disaster contexts. After introducing the main features of ABAs, the paper discusses current practice in humanitarian response, and the need within urban areas to draw lessons from urban development approaches, from which ABAs have emerged. The paper then presents lessons from research concerning the application of ABAs in relation to phases of the project management cycle: assessment and design, implementation, and monitoring, evaluation and learning. The paper ends with a brief discussion. Overall, it argues that for ABAs to be effective, they need to draw on longstanding lessons from urban development, plan for a longer timeframe for their actions than is otherwise often the case in recovery operations, and consider the need to scale up actions for wider city application.

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