Detection of land subsidence and its relationship with land cover types using ESA Sentinel satellite data: a case study of Quetta Valley, Pakistan. Issue 24 (17th December 2019)

• Record Type: Journal Article
• Authors: Ahmad, Waqas; Choi, Minha; Kim, Soohyun; Kim, Dongkyun
• Is Part Of: International journal of remote sensing. Volume 40:Issue 24(2019)
• Page Start: 9572
• Page End: 9603
• Publication Date: 2019-12-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2019.1633704
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: This paper presents the analysis of land subsidence as a result of excessive groundwater abstraction for irrigation and domestic supply in Quetta valley, Pakistan. The European Space Agency (ESA) Sentinel–1 and Sentinel–2 satellite data is used to identify and categorize the spatial distribution of land subsidence. The aquifer geology and observed groundwater table are used to establish the relationship between land subsidence and groundwater abstraction. For this, we performed Persistent Scattering Interferometry (PSIn) analysis using the Sentinel–1 Synthetic Aperture Radar (SAR) imagery to develop 28 maps of land subsidence covering a period of 16 October 2014 to 22 November 2016. The interferometry results matched well with the land subsidence values measured at the Global Positioning System (GPS) ground station with a mean absolute error of 5.7 mm and coefficient of determination of 0.94. The land subsidence values at each pixel of the map were classified according to the land cover types of the study area. Here, the map of land cover types was developed using the multispectral image of Sentinel–2A satellite. The results revealed that, during the 2–year period, the entire study area has suffered from varying degree of accumulated land subsidence ranging between 10 and 280 mm in magnitude, which was linearly proportional to the depth and drawdown of groundwater table observed at four piezometers located in the study area. The magnitude of land subsidence across the study area showed a strong correlation with land covers. The urban area and orchard vegetation with a large amount of groundwater abstraction showed an excessive amount of cumulative land subsidence, while the seasonally cultivated and barren land are slightly affected by land subsidence.