scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Assessment of land consumption rate with urban dynamics change using geospatial techniques

01 Jun 2012-Journal of Land Use Science (Taylor & Francis)-Vol. 7, Iss: 2, pp 135-148
TL;DR: In this article, a study was conducted using satellite remote sensing data Landsat MSS (Multi-spectral Scanner), ETM+(Enhanced Thematic Mapper), IRS P-6 (Indian Remote Sensing Satellite), LISS IV (Linear Imaging Self-Scanner), and IRSP-5 Cartosat-1 for the assessment of urban area change dynamics between years 1976 and 2008 in Bhagalpur city in the state of Bihar in India.
Abstract: Land consumption is increasing rapidly with the exponential growth of population. The built-up environment configuration influences the management processes for development and other municipality works. Population growth also affects the availability of land for different purposes in its spatial distribution. The present study was conducted using satellite remote sensing data Landsat MSS (Multi-spectral Scanner), ETM+ (Enhanced Thematic Mapper), IRS P-6 (Indian Remote Sensing Satellite), LISS IV (Linear Imaging Self-Scanner), and IRS P-5 Cartosat-1 for the assessment of urban area change dynamics between years 1976 and 2008 in Bhagalpur city in the state of Bihar in India. The ground truth and coordinate points were collected using a Global Positioning System (GPS) for the location of the built-up themes prepared in the Geographic Information System (GIS). Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were introduced to aid in the quantitative assessment changes. The results show a rap...
Citations
More filters
Journal ArticleDOI
TL;DR: In this article, the authors highlighted the importance of digital change detection techniques for nature and location of change of the Hawalbagh block in district Almora, Uttarakhand, India.

544 citations


Cites background from "Assessment of land consumption rate..."

  • ...Sharma et al. (2012) introduced land consumption rate (LCR) and Land Absorption Coefficient (LAC) to aid in the quantitative assessment changes between the years 1976 and 2008 in Bhagalpur city in the state of Bihar in India....

    [...]

Journal ArticleDOI
TL;DR: The main objective of this study focuses on the comparison of three classification tools for Landsat images, which are maximum likelihood classification (MLC), support vector machine and artificial neural network (ANN), in order to select the best method among them.

298 citations

Journal ArticleDOI
TL;DR: In this article, the authors used remote sensing and GIS tools for studying land use/land cover change and integrating the associated driving factors for deriving useful outputs. And they used the CA-Markov Chain Model (CAMCM) to identify the spatial and temporal changes that have occurred in LULC in this area.
Abstract: Remote sensing and GIS are important tools for studying land use/land cover (LULC) change and integrating the associated driving factors for deriving useful outputs. This study is based on utilization of Earth observation datasets over the highly urbanized Allahabad district in India. Allahabad district has experienced intense change in LULC in the last few decades. To monitor the changes, advanced techniques in remote sensing and GIS, such as Cellular Automata (CA)-Markov Chain Model (CAMCM) were used to identify the spatial and temporal changes that have occurred in LULC in this area. Two images, 1990 and 2000, were used for calibration and optimization of the Markovian algorithm, while 2010 was used for validating the predictions of CA-Markov using the ground based land cover image. After validating the model, plausible future LULC changes for 2020 were predicted using the CAMCM. Analysis of the LULC pattern maps, achieved through classification of multi-temporal satellite datasets, indicated that the socio-economic and biophysical factors have greatly influenced the growth of agricultural lands and settlements in the area. The two urbanization indicators calculated in this study viz. Land Consumption Ratio (LCR) and Land Absorption Coefficient (LAC) were also used, which indicated a drastic change in the area in terms of urbanization. The predicted LULC scenario for year 2020 provides useful inputs to the LULC planners for effective and pragmatic management of the district and a direction for an effective land use policy making. Further suggestions for an effective policy making are also provided which can be used by government officials to protect this important land resource.

235 citations

Journal ArticleDOI
TL;DR: In this article, the processing of data on urban land conversion along the Italian Adriatic coast in the last 50 years has been studied and the results obtained show different aspects of the phenomenon: values were obtained for the average annual speed of transformation of the coastal strip; clustering, dispersion and statistical concentration of the data obtained were studied, which has made it possible to show unparalleled threshold values in the present levels of urbanization; geostatistical surveys were conducted to determine the distribution changes of urban concentration over time; analyses were developed to point out what landscape and morphological

110 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluated the dynamics and spatial pattern of Mekelle City's expansion in the past three decades 1984-2014, and showed that in the periods 1984-1994, 1994-2004, and 2004-2014 the built-up area increased annually by 10%, 9%, and 8%, respectively, with an average annual increment of 19% 100-ha year−1, from 531-ha in 1984 to 3524 -ha in 2014.
Abstract: Information on the rate and pattern of urban expansion is required by urban planners to devise proper urban planning and management policy directions. This study evaluated the dynamics and spatial pattern of Mekelle City’s expansion in the past three decades 1984–2014. Multi-temporal Landsat images and Maximum Likelihood Classifier were used to produce decadal land use/land cover LULC maps. Changes in LULC and spatial pattern of urban expansion were analysed by post-classification change detection and spatial metrics, respectively. The results showed that in the periods 1984–1994, 1994–2004, and 2004–2014, the built-up area increased annually by 10%, 9%, and 8%, respectively; with an average annual increment of 19% 100 ha year−1, from 531 ha in 1984 to 3524 ha in 2014. Between 1984 and 2014, about 88% of the gain in built-up area was from conversion of agricultural lands, which decreased by 39%. Extension of existing urban areas was the dominant growth type, which accounted for 54%, 75%, and 81% of the total new development during 1984–1994, 1994–2004, and 2004–2014, respectively. The spatial metrics analyses revealed urban sprawl, with increased heterogeneity and gradual dispersion in the outskirts of the city. The per capita land consumption rate ha per person increased from 0.009 in 1984 to 0.014 in 2014, indicating low density urban growth. Based on the prediction result, the current 2014 built-up area will double by 2035, and this is likely to have multiple socioeconomic and environmental consequences unless sustainable urban planning and development policies are devised.

107 citations


Cites background or methods from "Assessment of land consumption rate..."

  • ...…classification (Schneider and Woodcock 2008), supervised classification (Bhatta 2009; Mundia and Murayama 2010; Tewolde and Cabral 2011; Sharma, Pandey, and Nathawat 2012), normalized difference vegetation index (Banzhaf, Grescho, and Kindler 2009; Soffianian et al. 2010) and image…...

    [...]

  • ...…which was used as an index to measure the progressive spatial expansion of the city vis-à-vis its population, was computed by using Equation (6) (Sharma, Pandey, and Nathawat 2012): Land consumption rate ¼ Built-up area Population : (6) Projecting future built-up area demand is important to…...

    [...]

References
More filters
Journal ArticleDOI
Robert M. Haralick1
01 Jan 1979
TL;DR: This survey reviews the image processing literature on the various approaches and models investigators have used for texture, including statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models.
Abstract: In this survey we review the image processing literature on the various approaches and models investigators have used for texture. These include statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models. We discuss and generalize some structural approaches to texture based on more complex primitives than gray tone. We conclude with some structural-statistical generalizations which apply the statistical techniques to the structural primitives.

5,112 citations

Journal ArticleDOI
TL;DR: An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.
Abstract: A variety of procedures for change detection based on comparison of multitemporal digital remote sensing data have been developed. An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.

3,361 citations


"Assessment of land consumption rate..." refers background in this paper

  • ...Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different time points (Singh 1989)....

    [...]

  • ...Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different time points (Singh 1989 )....

    [...]

Journal ArticleDOI
TL;DR: This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature and summarizes and reviews these techniques.
Abstract: Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature.

2,785 citations


"Assessment of land consumption rate..." refers methods in this paper

  • ...In practice, different techniques are often compared to find the most useful change detection results for a specific application (Lu, Mausel, Brondi´zio, and Moran 2004 )....

    [...]

Journal Article
TL;DR: In this paper, a change detection method was used to determine the fluctuation in eel-grass meadows over time, and the results showed that eelgrass is important in our estuarine ecosystems because it is utilized also increase water quality by filtering sediments and nutrias habitat.
Abstract: nent of coastal and estuarine ecosystems (Milne and Milne, The eelgrass (Zostera marina L.) population in Great Bay, 1951; Ackleson and Klemas, 1987; Short, 1989; Ferguson et New Hampshire has recently undergone dramatic changes. A 1993). It grows in bays, and coastal Oceans reoccurrence of the 1930s wasting disease and decreasing throughout the northern temperate regi0ns the and water quality due to pollution led to a reduction in the eel- Can rival the productivity of agricultural crops (~ha~er et al., grass population during the late 1980s. Currently, the eel- 1984). In addition, eelgrass meadows ~rovide habitat for nugrass populations in ~~~~t B~~ have a remark- merous organisms, including coastal fish, lobsters, crabs and able recovery from the decline in the late 1980~. Eelgrass is scallops, and a food source for waterfowl. Eelgrass meadows important in our estuarine ecosystems because it is utilized also increase water quality by filtering sediments and nutrias habitat by many and non-commercial ents within the water (Short, 1989). It is therefore important isms and is a food source for wateqfowl. In order to monitor to maintain healthy ~o~ulations of eelgrass in to enthe eelgrass populations in Great Bay, a change detection Sure the continuing ~rosperit~ of coastal and estuarine ecoanalysis was performed to determine the fluctuation in eel- systems. grass meadows over time.

450 citations


"Assessment of land consumption rate..." refers background in this paper

  • ...Four aspects of change detection that are important when monitoring natural resources are as follows: detecting that changes have occurred, identifying the nature of the changes, measuring the areal extent of the change, and assessing the spatial pattern of the change (Macleod and Congalton 1998)....

    [...]

Journal ArticleDOI
TL;DR: For example, Ojima et al. as discussed by the authors pointed out that water quality and soil fertility in many regions of the world have been severely degraded, and the biotic system has been dissected, depleted and endangered by increasing human demands.
Abstract: creased by 25% to greater than 350 ppm. Water quality and soil fertility in many regions of the world have been severely degraded, and the biotic system has been dissected, depleted, and endangered by increasing human demands (Ojima et al. 1991). To understand the cause and the effect of global change, the scientific community must focus greater attention on the social context (i.e., cultural, political, demographic, and economic factors) influencing human impact on the global environ-

345 citations


"Assessment of land consumption rate..." refers background in this paper

  • ...These conditions often vary and have a direct impact on land use and land cover (Ojima, Glavin, and Turner 1994 )....

    [...]