Object-based image analysis for the impact of sewage pollution in Malad Creek, Mumbai, India

Shirke, Shivani; Pinto, Shannon Meryl; Kushwaha, Vikash K.; Mardikar, Trupti; Vijay, Ritesh

doi:10.1007/s10661-015-4981-9

Cited by 7 publications

(2 citation statements)

References 23 publications

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“…In aquaculture, the methods of interpreting remote sensing data are consistently evolving towards automation, speed, and intelligence [12][13][14][15][16][17][18][19][20][21][22]. However, our current understanding of the spatial distribution of aquaculture ponds remains scant [23][24][25][26][27]. To address this knowledge gap, numerous scholars have employed remote sensing methods for automated extraction.…”

Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020

Meng,

Zhang,

Yang

et al. 2023

Remote Sensing

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Most current research on aquaculture ponds focuses on coastal areas, leaving a gap in understanding of inland regions, such as the strategically significant Yangtze River Economic Belt in China. This study introduces an intelligent extraction method for extensive monitoring of aquaculture ponds in Yangtze River Economic Belt, using Landsat and Sentinel data from 1985 to 2020 with five-year intervals based on the Google Earth Engine (GEE) platform. Land cover change data were also analyzed to understand the impact of aquaculture-related changes. Results indicate a significant increase in aquaculture ponds in the Yangtze River Economic Belt from 3235.51 km2 to 14,207.08 km2 between 1985 and 2020. Aquaculture activity primarily shifted eastward from 1985 to 2015, then westward from 2015 to 2020. Approximately 2018.36 km2 of aquatic areas underwent conversion, mainly to water bodies or croplands, with fewer transitions to impervious surfaces, grasslands, or forests. This study highlights that inland areas can also experience significant increases in aquaculture ponds, particularly alongside large rivers, and that the environmental impacts of these changes differ from those in coastal areas, warranting specific attention.

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Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020

Meng,

Zhang,

Yang

et al. 2023

Remote Sensing

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“…The spectral and texture properties of a feature are calculated based on the original values of the contained pixels. Once the property values are generated, people will be able to do some object analysis on them, e.g., supervised classification or feature extraction (buildings, rivers, roads, forests, lakes, lawns, planes, etc) [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Two Pixel Reference Algorithm

Sun¹,

Di²,

Fang³

2020

Preprint

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Object based image analysis (OBIA) has a unique process requirement: relate all the pixels in the segmented images to the vectorized polygons (pixel in polygon). The existing solutions are very slow in finding the pixels in a polygon. This paper proposes a novel algorithm called Two-Pixel-Reference to speed up the process. The algorithm is initially designed for segmented remote sensing images. It avoids most multiple-layer loops in existing methods and trims many redundant comparison among pixels. Thus it has literal lower Big O algorithm complexity. We implemented the algorithms in C++ and made more than seventy tests on two different machines to compare the algorithm with three other existing algorithms. The results show that it significantly decreases the time cost of the process. In every single test, the proposed algorithm costs much less time than other algorithms. Specifically, the average duration is reduced from 3.96 seconds to 0.15 second on machine #1 and from 3.647 seconds to 0.073 second on machine #2. This paper makes a good example for researching time-efficient algorithms to accelerate the overall process of OBIA in such a big data era.

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A multi-temporal analysis for change assessment and estimation of algal bloom in Sambhar Lake, Rajasthan, India

Vijay

Pinto

Kushwaha

et al. 2016

Environ Monit Assess

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Sambhar Lake in Rajasthan, India is the major inland salt water lake producing salt for centuries. The present study addresses the monitoring changes in and around the lake and its consequent effect on the lake water ecology. For this, satellite images of the years 1976, 1981, 1997, and 2013 are analyzed for land use land cover classes. Significant reduction in the water body is observed in contrast with the increase in salt pan around the periphery of lake and wetland classes. Further, the extent of water body and algae in the lake are delineated as per normalized difference water index and normalized difference vegetation index. Rainfall data do not indicate any major change in the pattern, but drastic decrease in the extent of water body and significant increase in algal bloom are serious concerns for the lake's existence. This may be due to surrounding anthropogenic activities and construction of check dams and anicuts in the lake catchment which curtail the runoff into the lake and provide favorable growth of algae. Sambhar Lake, being declared as a wetland according to the Ramsar Convention, is necessary to protect and conserve the ecological importance of the lake through sustainable planning and management.

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Object-based image analysis for the impact of sewage pollution in Malad Creek, Mumbai, India

Cited by 7 publications

References 23 publications

Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020

Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020

Two Pixel Reference Algorithm

A multi-temporal analysis for change assessment and estimation of algal bloom in Sambhar Lake, Rajasthan, India

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