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Identifying hotspots in land use land cover change and the drivers in a semi-arid region of India

Overview of attention for article published in Environmental Monitoring and Assessment, August 2018
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Citations

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41 Dimensions

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143 Mendeley
Title
Identifying hotspots in land use land cover change and the drivers in a semi-arid region of India
Published in
Environmental Monitoring and Assessment, August 2018
DOI 10.1007/s10661-018-6919-5
Pubmed ID
Authors

Vijayasekaran Duraisamy, Ramkumar Bendapudi, Ajit Jadhav

Abstract

The study examines long-term land use/land cover change (LUCC) at a finer scale in a semi-arid region of India. The objectives were to study and quantify the spatiotemporal LUCC and uncover the major drivers causing the change in the Mula Pravara river basin, which is located in a semi-arid region of Maharashtra state, India. Advanced very high-resolution radiometer (AVHRR)-Normalized Difference Vegetation Index (NDVI) 3g data for the years 1982-2015 were used to identify the 'hotspot' with significant positive and negative LUCC. Multi-temporal Landsat imagery was used to produce finer scale land use maps. From 1991 to 2016, the agricultural land area increased by approximately 98% due to the conversion of uncultivable and fallow lands to agriculture. The built-up area increased by 195%, and in recent years, an urban expansion has occurred in agricultural lands close to the urban fringe areas. There has been a shift from food crops to commercial crops, as observed from the steep increase in the amount of land under horticultural plantations, by 1601% from 2001 to 2016. In addition, the area under forest canopy was reduced in the protected regions. Institutional factors that improved access to water resources were the major drivers of change in hotspots, especially in the context of agriculture. Technological and economic factors were the other supporting factors that contributed to the change. This study demonstrates the advantages of using satellite remote sensing techniques to monitor the LUCC, which is useful for predicting future land changes and aids in planning adaptation strategies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 143 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 22%
Researcher 14 10%
Student > Master 14 10%
Student > Bachelor 8 6%
Student > Doctoral Student 6 4%
Other 17 12%
Unknown 52 36%
Readers by discipline Count As %
Environmental Science 24 17%
Agricultural and Biological Sciences 15 10%
Social Sciences 14 10%
Earth and Planetary Sciences 12 8%
Engineering 10 7%
Other 6 4%
Unknown 62 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 September 2018.
All research outputs
#6,507,541
of 23,854,458 outputs
Outputs from Environmental Monitoring and Assessment
#421
of 2,748 outputs
Outputs of similar age
#110,200
of 336,479 outputs
Outputs of similar age from Environmental Monitoring and Assessment
#11
of 44 outputs
Altmetric has tracked 23,854,458 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,748 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,479 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.