scholarly journals Assessment of Urban Dynamics to Understand Spatiotemporal Differentiation at Various Scales Using Remote Sensing and Geospatial Tools

2020 ◽  
Vol 12 (8) ◽  
pp. 1306 ◽  
Author(s):  
Mangalasseril Mohammad Anees ◽  
Deepika Mann ◽  
Mani Sharma ◽  
Ellen Banzhaf ◽  
Pawan K Joshi
Keyword(s):  
Remote Sensing ◽  
Urban Planning ◽  
Multiple Scales ◽  
Urban Expansion ◽  
Spatial Association ◽  
Spatial Differentiation ◽  
Integrated Analysis ◽  
Growth Type ◽  
Local Conditions ◽  
Urban Dynamics

Analysis of urban dynamics is a pivotal step towards understanding landscape changes and developing scientifically sound urban management strategies. Delineating the patterns and processes shaping the evolution of urban regions is an essential part of this step. Utilizing remote-sensing techniques and Geographic Information System (GIS) tools, we performed an integrated analysis on urban expansion in Srinagar city and surrounding areas from 1999 to 2017 at multiple scales in order to assist urban planning initiatives. To capture various spatial indicators of expansion, we analysed (i) land use/land cover (LULC) changes, (ii) rate and intensity of changes to built-up areas, (iii) spatial differentiation in landscape metrics (at 500, 1000 and 2000 m cell-size), and (iv) growth type of the urban expansion. Global Moran’s I statistics and local indicators of spatial association (LISA) were also employed to identify hotspots of change in landscape structure. Our methodology utilizes a range of geovisualization tools which are capable of appropriately addressing various elements required for strategic planning in growing cities. The results highlight aggregation and homogenization of the urban core as well as irregularity and fragmentation in its periphery. A combination of spatial metrics and growth type analysis supports the supposition that there is a continuum in the diffusion-coalescence process. This allows us to extend our understanding of urban growth theory and to report deviations from accepted stages of growth. As our results show, each dominating growth phase of the city—both diffusion (1999) and coalescence (2009 and 2017)—is interspersed with features from the other type. An improved understanding of spatial differentiation and the identification of hotspots can serve to make urban planning more tailored to such local conditions. An important insight derived from the results is the applicability of remote-sensing data in urban planning measures and the usefulness of freely available medium resolution data in gaining a comprehensive understanding of the evolution of cities.

Urban Expansion and Loss of Agricultural Land: A Remote Sensing Based Study of Shirpur City, Maharashtra

2017 ◽  
Vol 6 (1) ◽  
pp. 2097-2102
Author(s):  
Yogesh Mahajan ◽  
◽  
Shrikant Mahajan ◽  
Bharat Patil ◽  
Sanjay Kumar Patil ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Agricultural Land ◽  
Urban Expansion

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Mapping 20 Years of Urban Expansion in 45 Urban Areas of Sub-Saharan Africa

2021 ◽  
Vol 13 (3) ◽  
pp. 525
Author(s):  
Yann Forget ◽  
Michal Shimoni ◽  
Marius Gilbert ◽  
Catherine Linard
Keyword(s):  
Case Studies ◽  
Urban Areas ◽  
Urban Expansion ◽  
Local Population ◽  
Sub Saharan Africa ◽  
Annual Growth Rate ◽  
Urban Dynamics ◽  
Mapping Approach ◽  
Sub Saharan ◽  
The Impact

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.

scholarly journals Improved YOLO Network for Free-Angle Remote Sensing Target Detection

2021 ◽  
Vol 13 (11) ◽  
pp. 2171
Author(s):  
Yuhao Qing ◽  
Wenyi Liu ◽  
Liuyan Feng ◽  
Wanjia Gao
Keyword(s):  
Remote Sensing ◽  
Feature Extraction ◽  
Target Detection ◽  
Multiple Scales ◽  
Classification Problem ◽  
Input Image ◽  
Detection Accuracy ◽  
Feature Maps ◽  
Regression Problem ◽  
Public Datasets

Despite significant progress in object detection tasks, remote sensing image target detection is still challenging owing to complex backgrounds, large differences in target sizes, and uneven distribution of rotating objects. In this study, we consider model accuracy, inference speed, and detection of objects at any angle. We also propose a RepVGG-YOLO network using an improved RepVGG model as the backbone feature extraction network, which performs the initial feature extraction from the input image and considers network training accuracy and inference speed. We use an improved feature pyramid network (FPN) and path aggregation network (PANet) to reprocess feature output by the backbone network. The FPN and PANet module integrates feature maps of different layers, combines context information on multiple scales, accumulates multiple features, and strengthens feature information extraction. Finally, to maximize the detection accuracy of objects of all sizes, we use four target detection scales at the network output to enhance feature extraction from small remote sensing target pixels. To solve the angle problem of any object, we improved the loss function for classification using circular smooth label technology, turning the angle regression problem into a classification problem, and increasing the detection accuracy of objects at any angle. We conducted experiments on two public datasets, DOTA and HRSC2016. Our results show the proposed method performs better than previous methods.

scholarly journals Study on the Urban Fringe Based on the Expansion–Shrinking Dynamic Pattern

2021 ◽  
Vol 13 (10) ◽  
pp. 5718
Author(s):  
Changqing Sui ◽  
Wei Lu
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Land Use Planning ◽  
Urban Landscape ◽  
Rapid Development ◽  
Urban Expansion ◽  
Urban Fringe ◽  
Spatial Form ◽  
Architectural Form ◽  
Ecological Protection

The urban fringe, as a part of an urban spatial form, plays a considerably major role in urban expansion and shrinking. After decades of rapid development, Chinese cities have advanced from a simple expansion stage to an expansion–shrinking-coexistence stage. In urban shrinking and expansion, the urban fringe shows different characteristics and requirements for specific aspects such as urban planning, land use, urban landscape, ecological protection, and architectural form, thereby forming expanding and shrinking urban fringes. A comprehensive study of expanding and shrinking urban fringes and their patterns is theoretically significant for urban planning, land use, planning management, and ecological civilisation construction.

Applications and Trends of Remote Sensing in Professional Urban Planning

2011 ◽  
Vol 5 (5) ◽  
pp. 249-261 ◽  
Author(s):  
Nancy Hoalst-Pullen ◽  
Mark W. Patterson
Keyword(s):  
Remote Sensing ◽  
Urban Planning

Detecting forest damage after a low-severity fire using remote sensing at multiple scales

2015 ◽  
Vol 35 ◽  
pp. 239-246 ◽  
Author(s):  
John T.T.R. Arnett ◽  
Nicholas C. Coops ◽  
Lori D. Daniels ◽  
Robert W. Falls
Keyword(s):  
Remote Sensing ◽  
Multiple Scales ◽  
Forest Damage

Overview of the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08): A field experiment evaluating methods for quantifying ET at multiple scales

2012 ◽  
Vol 50 ◽  
pp. 4-19 ◽  
Author(s):  
Steven R. Evett ◽  
William P. Kustas ◽  
Prasanna H. Gowda ◽  
Martha C. Anderson ◽  
John H. Prueger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Field Experiment ◽  
Multiple Scales ◽  
Evaluating Methods
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