Land-use mapping and change detection in a coal mining area - a case study in the Jharia coalfield, India

Prakash, Anupma; Gupta, Ravi P.

doi:10.1080/014311698216053

Cited by 244 publications

(109 citation statements)

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“…While a few land use/cover change studies used remotely sensed data from sources with a relatively similar scale [38,39], differences in the scales of the input data were not taken into consideration by many authors that have used satellite images, mainly Landsat images for land use/land cover studies in different parts of the world like in Tanzania [40,41], in Uganda [42,43]; in Ghana [44], in Nepal [45,46], in Kenya [47][48][49] in Nigeria [50][51][52][53], in Zimbabwe [54], in India [55][56][57], in Turkey [58][59][60], in Iran [61,62], and in Bangladesh [63][64][65]. Similarly, differences in the scales of the remotely sensed input data were not considered in most of the land use/cover studies that have been done in Ethiopia [12,[66][67][68].…”

Section: Discussionmentioning

confidence: 99%

Identifying Land Use/Cover Dynamics in the Koga Catchment, Ethiopia, from Multi-Scale Data, and Implications for Environmental Change

Yeshaneh

Wagner

Exner-Kittridge

et al. 2013

IJGI

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This study analyzed more than 50 years of land cover and land use changes in the 260 km 2 Koga catchment in North Western Ethiopia. The data used includes 1:50,000 scale aerial photographs, Landsat MSS, TM and ETM images, and ASTER images together with ground truth data collected through field surveys and community elders' interviews. Aerial photographs have high spatial resolution but provide lower spectral resolution than satellite data. While most land use/cover change studies compare changes from different spatial scales, this study applied land use/cover classification techniques to bring the data to a relatively similar scale. The data revealed that woody vegetation decreased from 5,576 ha to 3,012 ha from the 1950s to 2010. Most of the deforestation took place between the 1970s and 1980s, but there is an increasing trend since then. No significant changes were observed in the area used for agriculture that comprises the pastures and crop fields since the 1950s, while there is an enormous increase in the area used for settlement, due to a tremendous increase in population from one point in time to another. The bare lands that used to exist in previous years were found to be totally covered with other land cover/use classes and no bare lands were observed in the study area in the year 2010. Population pressure and land use policies were found to be reasons for the changes in land use/cover while soil degradation,

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Section: Discussionmentioning

confidence: 99%

Identifying Land Use/Cover Dynamics in the Koga Catchment, Ethiopia, from Multi-Scale Data, and Implications for Environmental Change

Yeshaneh

Wagner

Exner-Kittridge

et al. 2013

IJGI

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“…In India, several works have been carried out to study the deforestation rates and changes in LULC (Prakash and Gupta, 1998 Keeping these perspectives in view, an attempt was made to provide opportunities to realize a strategic assessment to determine the LULC change during the past years , assessment of the impact on forest cover by using integrate field and image analysis. This study has been undertaken with a hope to meet the challenges in planning and management especially to control the deforestation of Kamrup district of Assam.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Kumar¹

2017

Appl Ecol Env Res

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“…Satellite data and automatic classification methods can be used for the described tasks as an alternative to the captured aerial images. However, digital image processing techniques dedicated to high resolution data, such as multi-temporal Landsat TM [10], have limited potential because very high resolution images are needed to provide more detailed information at the level of individual trees and plant communities. As an alternative to selected classification methods for vegetation mapping, object-based image analysis can efficiently process a large volume of very high-resolution image data, but requires advanced software tools and time-consuming testing [11].…”

Section: Methodsmentioning

confidence: 99%

Computer Based Modeling of Vegetation Propagation across a Disturbed Space Linked to GIS

Matějı́ček¹,

Kovář²

2015

JEASE

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Abstract:The paper is focused on computer simulation of natural vegetation propagation across two selected disturbed sites. Two sites located in the different environments, the abandoned sedimentation basin of a former pyrite ore mine and the ash deposits of a power station, were selected to illustrate the proposed spatio-temporal model. Aerial images assisted in identifying and monitoring the progress in the propagation of vegetation. Analysis of the aerial images was based on varying vegetation coverage explored by classification algorithms. A new approach is proposed entailing coupling of a local dynamic model and a spatial model for vegetation propagation. The local dynamic model describes vegetation growth using a logistic growth approach based on delayed variables. Vegetation propagation is described by rules related to seed and its dispersal phenomena on a local scale and on the scale of outlying spreading. The disturbed sites are divided into a grid of microsites. Each microsite is represented by a 5 m  5 m square. A state variable in each microsite indicates the relative vegetation density on a scale from 0 (no vegetation) to 1 (long-term maximum of vegetation density). Growth, local vegetation propagation and the effects of outlying vegetation propagation in each cell are described by an ordinary differential equation with delayed state variables. The grid of cells forms a set of ordinary differential equations. The abandoned sedimentation basin and the ash deposits are represented by grids of 185  345 and 212  266 cells, respectively. A few case-oriented studies are provided to show various predictions of vegetation propagation across two selected disturbed sites. The first case study simulates vegetation growing without spatial propagations and delayed variables in the spatio-temporal model. The second and the third case studies extend the previous study by including local and outlying vegetation propagation, respectively. The fourth case study explores delayed impacts in the logistic growth term and the delayed outcome by vegetation propagation across the disturbed space. The performed case-oriented studies confirm the applicability of the proposed spatio-temporal model to predict vegetation propagation in short-term successions and to estimate approximate vegetation changes in long-term development. As a result, it can be concluded that remotely sensed data are a valuable source of information for estimates of model parameters and provide an effective method for monitoring the progress of vegetation propagation across the selected sites, spaces disturbed by human activities.

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Land-use mapping and change detection in a coal mining area - a case study in the Jharia coalfield, India

Cited by 244 publications

References 0 publications

Identifying Land Use/Cover Dynamics in the Koga Catchment, Ethiopia, from Multi-Scale Data, and Implications for Environmental Change

Identifying Land Use/Cover Dynamics in the Koga Catchment, Ethiopia, from Multi-Scale Data, and Implications for Environmental Change

Monitoring and Assessment of Land Use and Land Cover Changes (1977 - 2010) in Kamrup District of Assam, India Using Remote Sensing and Gis Techniques

Computer Based Modeling of Vegetation Propagation across a Disturbed Space Linked to GIS

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