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Article

Mapping Brick Kilns to Support Environmental Impact Studies around Delhi Using Sentinel-2

1
Research Institute of Humanity and Nature, Kyoto 603-8047, Japan
2
Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-0882, Japan
3
Faculty of Science, Nara Women’s University, Nara 630-8506, Japan
4
Faculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810, Japan
5
Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(9), 544; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090544
Received: 30 June 2020 / Revised: 14 August 2020 / Accepted: 7 September 2020 / Published: 11 September 2020
(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)
Cities lying in the Indo-Gangetic plains of South Asia have the world’s worst anthropogenic air pollution, which is often attributed to urban growth. Brick kilns, facilities for producing fired clay-bricks for construction are often found at peri-urban region of South Asian cities. Although brick kilns are significant air pollutant emitters, their contribution in under-represented in air pollution emission inventories due to unavailability of their distribution. This research overcomes this gap by proposing publicly available remote sensing dataset based approach for mapping brick-kiln locations using object detection and pixel classification. As brick kiln locations are not permanent, an open-dataset based methodology is advantageous for periodically updating their locations. Brick kilns similar to Bull Trench Kilns were identified using the Sentinel-2 imagery around the state of Delhi in India. The unique geometric and spectral features of brick kilns distinguish them from other classes such as built-up, vegetation and fallow-land even in coarse resolution imagery. For object detection, transfer learning was used to overcome the requirement of huge training datasets, while for pixel-classification random forest algorithm was used. The method achieved a recall of 0.72, precision of 0.99 and F1 score of 0.83. Overall 1564 kilns were detected, which are substantially higher than what was reported in an earlier study over the same region. We find that brick kilns are located outside urban areas in proximity to outwardly expanding built-up areas and tall built structures. Duration of brick kiln operation was also estimated by analyzing the time-series of normalized difference vegetation index (NDVI) over the brick kiln locations. The brick kiln locations can be further used for updating land-use emission inventories to assess particulate matter and black carbon emissions. View Full-Text
Keywords: object-detection; transfer learning; open-data; emission inventory; urban growth; land-use; environment impact; soil-degradation; SDG object-detection; transfer learning; open-data; emission inventory; urban growth; land-use; environment impact; soil-degradation; SDG
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MDPI and ACS Style

Misra, P.; Imasu, R.; Hayashida, S.; Arbain, A.A.; Avtar, R.; Takeuchi, W. Mapping Brick Kilns to Support Environmental Impact Studies around Delhi Using Sentinel-2. ISPRS Int. J. Geo-Inf. 2020, 9, 544. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090544

AMA Style

Misra P, Imasu R, Hayashida S, Arbain AA, Avtar R, Takeuchi W. Mapping Brick Kilns to Support Environmental Impact Studies around Delhi Using Sentinel-2. ISPRS International Journal of Geo-Information. 2020; 9(9):544. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090544

Chicago/Turabian Style

Misra, Prakhar, Ryoichi Imasu, Sachiko Hayashida, Ardhi A. Arbain, Ram Avtar, and Wataru Takeuchi. 2020. "Mapping Brick Kilns to Support Environmental Impact Studies around Delhi Using Sentinel-2" ISPRS International Journal of Geo-Information 9, no. 9: 544. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090544

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