scholarly journals Past and Future Trajectories of Farmland Loss Due to Rapid Urbanization Using Landsat Imagery and the Markov-CA Model: A Case Study of Delhi, India

2019 ◽  
Vol 11 (2) ◽  
pp. 180 ◽  
Author(s):  
Junmei Tang ◽  
Liping Di

This study integrated multi-temporal Landsat images, the Markov-Cellular Automation (CA) model, and socioeconomic factors to analyze the historical and future farmland loss in the Delhi metropolitan area, one of the most rapidly urbanized areas in the world. Accordingly, the major objectives of this study were: (1) to classify the land use and land cover (LULC) map using multi-temporal Landsat images from 1994 to 2014; (2) to develop and calibrate the Markov-CA model based on the Markov transition probabilities of LULC classes, the CA diffusion factor, and other ancillary factors; and (3) to analyze and compare the past loss of farmland and predict the future loss of farmland in relation to rapid urban expansion from the year 1995 to 2030. The predicted results indicated the high accuracy of the Markov-CA model, with an overall accuracy of 0.75 and Kappa value of 0.59. The predicted results showed that urban expansion is likely to continue to the year of 2030, though the rate of increase will slow down from the year 2020. The area of farmland has decreased and will continue to decrease at a relatively stable rate. The Markov-CA model provided a better understanding of the past, current, and future trends of LULC change, with farmland loss being a typical change in this region. The predicted result will help planners to develop suitable government policies to guide sustainable urban development in Delhi, India.

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 359
Author(s):  
Zhouqiao Ren ◽  
Jianhua He ◽  
Qiaobing Yue

Landscape connectivity is important for all organisms as it directly affects population dynamics. Yet, rapid urbanization has caused serious landscape fragmentation, which is the primary contributor of species extinctions worldwide. Previous studies have mostly used spatial snap-shots to evaluate the impact of urban expansion on landscape connectivity. However, the interactions among habitats over time in dynamic landscapes have been largely ignored. Here, we demonstrated that overlooking temporal connectivity can lead to the overestimation of the impact of urban expansion. How much greater the overestimation is depends on the amount of net habitat loss. Moreover, we showed that landscape connectivity may have a delayed response to urban expansion. Our analysis shifts the way to understand the ecological consequences of urban expansion. Our framework can guide sustainable urban development and can be inspiring to conservation practices under other contexts (e.g., climate change).


2019 ◽  
Vol 4 (1) ◽  
pp. 61-63
Author(s):  
Alhaji Mustapha Isa

Deforestation and climate change have become global environmental issues. The detection of forest changes in association with climate change can be successfully carried out by the use of multi-temporal remote sensing and modelling. This study undertook analysis of the past and present condition of the forest from the pattern changes of the Kota tinggi district johor state Malaysia, using landsat images of three different periods. These are thematic mapper (TM) data of 1998; enhanced thematic mapper (ETM+) image of 2008 and the operation land imager (OLI) of 2018 were collectively used. The images were geometrically and atmospherically pre-processed then classified, using maximum likelihood (M/C) algorithm to produce thematic land use/cover maps of the district. The accuracy of the classification was assessed through ground truthing and confusion matrices which revealed an accuracy of above 90% and kappa coefficient at 0.9 respectively.


2019 ◽  
pp. 1624-1644
Author(s):  
Gabriele Nolè ◽  
Rosa Lasaponara ◽  
Antonio Lanorte ◽  
Beniamino Murgante

This study deals with the use of satellite TM multi-temporal data coupled with statistical analyses to quantitatively estimate urban expansion and soil consumption for small towns in southern Italy. The investigated area is close to Bari and was selected because highly representative for Italian urban areas. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and geospatial data analysis to reveal spatial patterns. Analyses have been carried out using global and local spatial autocorrelation, applied to multi-date NASA Landsat images acquired in 1999 and 2009 and available free of charge. Moreover, in this paper each step of data processing has been carried out using free or open source software tools, such as, operating system (Linux Ubuntu), GIS software (GRASS GIS and Quantum GIS) and software for statistical analysis of data (R). This aspect is very important, since it puts no limits and allows everybody to carry out spatial analyses on remote sensing data. This approach can be very useful to assess and map land cover change and soil degradation, even for small urbanized areas, as in the case of Italy, where recently an increasing number of devastating flash floods have been recorded. These events have been mainly linked to urban expansion and soil consumption and have caused loss of human lives along with enormous damages to urban settlements, bridges, roads, agricultural activities, etc. In these cases, remote sensing can provide reliable operational low cost tools to assess, quantify and map risk areas.


GEOMATICA ◽  
2020 ◽  
Author(s):  
Liyuan Qing ◽  
Hasti A. Petrosian ◽  
Sarah N. Fatholahi ◽  
Michael A. Chapman ◽  
Jonathan Li

Urbanization is considered as one of the main factors affecting global change. The Halton Region as part of the Great Toronto Area (GTA), is regarded as one of the fastest growing regions in Canada, generating 20% of national GDP. It is also one of the most desirable places for living and thriving business. This research attempts to assess the urban expansion in the Halton Region, Ontario, Canada from 1989 to 2019 using satellite images, analysis approaches and landscape metrics. Multi-temporal Landsat images, and the supervised learning algorithms in GIS software were used to explore the dynamic changes, and to classify the urban and non-urban areas. The temporal urban expansion in the Halton Region experienced a dramatic rise, and mainly occurred from the centre of the area. The analysis of landscape metrics based on different methods, including Land Use in Central Indiana (LUCI) model, Vegetation-Impervious Surface-soil (V-I-S) model, and the census data of Canada was carried out to understand the transition mode of the urbanization in the Halton Region. Also, the population growth in the centre of the Halton Region was considered as one of driven forces affecting urban expansion. The results showed that most of the landscape metrics rose between 1989 and 2019, indicating leapfrog pattern of urbanization occurred over the entire period. The contribution of this research is to evaluate the urbanization in the Halton Region, and give the city managers a clear mind to make appropriate decisions in further urban planning.


2018 ◽  
Vol 10 (9) ◽  
pp. 3116 ◽  
Author(s):  
Xiuquan Li ◽  
Meizhen Wang ◽  
Xuejun Liu ◽  
Zhuan Chen ◽  
Xiaojian Wei ◽  
...  

Ecosystem balance is an important factor that affects healthy and sustainable urban development. The traditional cellular automata (CA) model considers only a few ecological factors, however, the MCR model can account for ecological factors. In previous studies, few ecological factors were added to the CA model. Thus, the minimal cumulative resistance (MCR) model is combined with the CA and Markov models for the simulation of urban expansion. To verify the reliability of the method, the Wuhan metropolitan area was selected as a representative urban area, and its expansion in the past and future was simulated. Firstly, seven influential factors were selected from the perspective of location theory. The transformation rules of the comprehensive resistance surface followed by the modified CA–Markov model were constructed on the basis of the MCR model. The expansion of the Wuhan metropolitan area in 2013 was simulated on the basis of the 1996 and 2006 maps of land-use status, and the kappa coefficient was used as an index to evaluate the accuracy of the proposed method. Then, the expansion of the Wuhan metropolitan area in 2020 was simulated. Finally, the simulation results obtained with and without the MCR model were compared and analysed from the macro- and micro levels. Results show that the prediction accuracy of the two models differed for ecological regions, such as woodlands and water bodies. The similarities between the regions that were overestimated and underestimated by the MCR-modified CA–Markov model and non-MCR model may be attributed to solution of the land-use transfer matrix with the Markov model. The accuracy of the MCR-modified CA–Markov model for predicting forests, water and other ecological regions was higher than that of the Markov model. Therefore, the proposed MCR-modified CA–Markov model has potential applications in environmentally-conscious urban expansion.


2012 ◽  
Vol 468-471 ◽  
pp. 2155-2164
Author(s):  
Jing Dong Jiang ◽  
Jing Nan Huang ◽  
Ling Tian ◽  
Yong Liu

Urbanization in Southwest China, an extensive mountainous region, has been unprecedentedly rapid in the past two decades, particularly with the implementation of “Great West Development”. However, most present studies on urbanization of Chinese cities are limited to coastal area. Little is known about the urbanization pattern and underlying mechanism in this region. The main purpose of this research is to analyze the process of rapid urbanization and its impact on mountain environment, using Chongqing, the well known “mountain city” in China, as an example. Four time-series satellite images were employed to extract the landscape data. The result was assessed by several “landscape metrics”. The research also investigated how complex natural factors as well as socio-economic factors exerted influence on the urbanization. Based on examination of present landscape, a planning model which was believed suitable for mountain urban development was proposed.


2020 ◽  
Author(s):  
Georg Veh ◽  
Daniel Garcia-Castellano ◽  
Oliver Korup

<p>The ongoing retreat of glaciers has formed several thousands of meltwater lakes in the Himalayas. Hundreds of these lakes have grown rapidly in area and volume in past decades, raising widely publicised concerns of an increasing hazard from sudden glacier lake outburst floods (GLOFs). Some 40 catastrophic lake outbursts have claimed thousands of fatalities and high losses in the Himalayas, mostly as a consequence of moraine-dam failures. Human and public safety along densely populated river reaches may thus be prone to changes in the lake size-distribution and the frequency of outburst floods. Yet multi-temporal inventories of Himalayan glacier lakes and associated outburst floods that we need for hazard appraisals have been collated only for selected basins with few standardised rules. Objectively tracing changes in regional GLOF hazard through time has thus remained elusive.</p><p>Here we meet this urgent demand for an improved GLOF hazard assessment. We estimate changes in the 100-year GLOF peak discharge from the late 1980s towards a scenario of completely ice-free Himalayas. We use a Random Forest model to predict land cover from seasonal Landsat images, and automatically extract glacier lakes for four time intervals. We obtain credible lake depths and volumes for each interval from a linear model learned from published bathymetric surveys. We further project possible sites for future Himalayan meltwater lakes from three published models of subglacial topography. We assume that these presently ice-covered depressions could fill completely with water though sediment and debris could decrease the storage space for future lakes. We simulate distributions of peak discharge for historic, present, and future lakes, accounting for different combinations of lake area, breach depth, and dam lithology. Most barrier types are unknown and could range from intact metamorphic bedrock to unconsolidated moraine debris. These two end members help to constrain the physically possible boundaries of GLOF peak discharges, which is supported by data from 82 natural dam breaks with known values of erodibility. To estimate the return periods of outburst floods, we used an extreme-value model to couple our simulations of peak discharge with mean annual rates of outburst floods, which remained unchanged in the Himalayas in the past three decades.</p><p>Given this constant rate of outburst floods, we report how hazard—expressed as the 100-year GLOF discharge—varied with regionally changing lake-size distributions in the past decades. We show that the southern Himalayas of Nepal and Bhutan had the largest increase of lake area, feeding notions of a rising GLOF hazard in this region. Hazard in the Western Himalaya, Karakoram, and Hindu Kush increased marginally, in line with the smallest historic abundance of glacier lakes and outburst floods. Future lake abundance and volumes may increase at least six-fold, with the largest lakes appearing in regions that have large glaciers today such as the Western Himalaya and the Karakoram. All other controls held constant, we find that hazard from these future lakes will largely rest on the erodibility of the barrier type, which needs to be acknowledged better in hazard appraisals.</p>


Author(s):  
Le Van Trung ◽  
Nguyen Nguyen Vu

This paper presents the method of integrating remote sensing and GIS to analyze the urbanization trend through the impervious surface change in Can Tho City. The impervious surface maps were created from the multi-temporal LandSat images in 1997, 2005, 2010, 2016 and were overlaid in GIS to extract the urban expansion from 1997 to 2016. The results showed the urban area of Can Tho increased from 1506,638 ha in 1997 to 5611,114 ha in 2016, average growth rate of 14,3%/year. The integration of remote sensing and GIS was found to be effective in monitoring and analyzing urban growth patterns.


2020 ◽  
Vol 52 (3) ◽  
pp. 306
Author(s):  
Murtala Dangulla ◽  
Latifah Abd Manaf ◽  
Firuz Ramli Mohammad

Urbanization is currently one of the most pressing environmental issues which cuts across all countries at unprecedented rates and intensities, with far reaching consequences on ecosystems, biodiversity and human wellbeing. This paper assessed urban expansion and land use/land cover changes in Sokoto metropolis, North-western Nigeria using Remote Sensing and GIS. Landsat images of 1990, 1999 and 2015 were processed for LULC classification and change detection using the Maximum Likelihood Classification, Post Classification Comparison techniques and the Land Change Modeler. The classification revealed five broad land cover classes which include Built-up Area, Farmland, Green Area, Open Space and Wetland/Water. The Built-up and Green areas continuously increased while Farmland and Open space decreased throughout the study period. The metropolis expanded radially at a faster rate between 1999 and 2015 with the highest rate of increase (1890.5ha per annum) recorded in the Built-up Area. This implies a doubling time of approximately 30 years at the expense of Farmland and Open space which may be completely exhausted in 40 and 29 years respectively. Infrastructural provision should thus align with the rate and direction of growth and where the Green Area is converted, replacement should be made to ensure continued supply and stability of the numerous ecosystem services green areas provide.


Author(s):  
W. Zhang ◽  
X. Kong ◽  
G. Tan ◽  
S. Zheng

Urban lakes are important natural, scenic and pattern attractions of the city, and they are potential development resources as well. However, lots of urban lakes in China have been shrunk significantly or disappeared due to rapid urbanization. In this study, four Landsat images were used to perform a case study for lake change detection in downtown Wuhan, China, which were acquired on 1991, 2002, 2011 and 2017, respectively. Modified NDWI (MNDWI) was adopted to extract water bodies of urban areas from all these images, and OTSU was used to optimize the threshold selection. Furthermore, the variation of lake shrinkage was analysed in detail according to SVM classification and post-classification comparison, and the coverage of urban lakes in central area of Wuhan has decreased by 47.37&amp;thinsp;km<sup>2</sup> between 1991 and 2017. The experimental results revealed that there were significant changes in the surface area of urban lakes over the 27 years, and it also indicated that rapid urbanization has a strong impact on the losses of urban water resources.


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