Surface water bodies mapping in Zimbabwe using landsat 8 OLI multispectral imagery: A comparison of multiple water indices

Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.

Download Full-text

Combining Water Indices to Detect Water Bodies using Landsat 8 OLI

Journal of Institute of Control Robotics and Systems ◽

10.5302/j.icros.2019.18.0220 ◽

2019 ◽

Vol 25 (5) ◽

pp. 470-475

Author(s):

Michelle V. Japitana ◽

Chul-Soo Ye ◽

Marlowe Edgar C. Burce

Keyword(s):

Water Bodies ◽

Landsat 8 ◽

Landsat 8 Oli ◽

Water Indices

Download Full-text

Identifying Most Influential Land Use Parameters Contributing Reduction of Surface Water Bodies in Rajshahi City, Bangladesh: A Remote Sensing Approach

Remote Sensing of Land ◽

10.21523/gcj1.18020202 ◽

2019 ◽

Vol 2 (2) ◽

pp. 87-95 ◽

Cited By ~ 3

Author(s):

Abdulla-Al Kafy ◽

Muhaiminul Islam ◽

Abdur Rouf Khan ◽

Lamia Ferdous ◽

Md. Mamun Hossain ◽

...

Keyword(s):

Land Use ◽

Surface Water ◽

Environmental Sustainability ◽

Water Bodies ◽

Landsat 8 ◽

World Population ◽

Land Use Land Cover ◽

Rapid Urbanization ◽

Surface Water Bodies ◽

Rajshahi City

Surface water bodies are one of the irreplaceable natural resources for human survival, and it extensively reduces with increasing the world population. This study modeled the spatiotemporal changes of land use / land cover (LULC) and identified the most influential LULC parameters, which contributes in the reduction of surface water bodies using the Landsat 4 and 5 TM and Landsat 8 OLI images (1992-2017). Rajshahi City Corporation is situated in the Northern piece of Bangladesh. A maximum likelihood supervised images classification algorithm was used for detection of changes in LULC. Matrix union technique was used for identifying the prominent LULC parameters. About 14% of water bodies were filled up in twenty-five year (1992-2017) due to rapid urbanization in Rajshahi City Corporation area. This study can provide an essential move towards necessary actions for preservation of surface water bodies to maintain the ecological balance and environmental sustainability.

Download Full-text

ASSESSMENT OF SURFACE WATER DYNAMICS USING MULTIPLE WATER INDICES AROUND ADAMA WOREDA, ETHIOPIA

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-5-181-2018 ◽

2018 ◽

Vol IV-5 ◽

pp. 181-188

Author(s):

M. Sathianarayanan

Keyword(s):

Surface Water ◽

Surface Area ◽

Rapid Change ◽

Water Bodies ◽

Water Dynamics ◽

Landsat 8 ◽

Water Index ◽

Surface Water Resources ◽

Normalized Difference Water Index ◽

Water Indices

Abstract. Rapid change of Adama wereda during the last three decades has posed a serious threat to the existence of ecological systems, specifically water bodies which play a crucial part in supporting life. Role of Satellite images in Remote Sensing could be more important in investigation, monitoring dynamically and planning of natural surface water resources. Landsat-5(TM) &amp; Landsat 8 (OLI) has high spatial, temporal and multispectral resolution and therefore provides consistent and perfect data to detect changes in surface changes of water bodies. In this paper, a study was conducted to detect the changes in water body extent during the period of 1984, 2000 and 2017 using various water indices such as namely Water Ratio Index (WRI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), supervised classification and wetness component of K-T transformation and the results are Presented. NDWI has been adopted for this study as compared with other indices through ground survey. The results showed an intense decreasing trend in the lakes of chelekleka, kiroftu, lake 1 and lake 3 of surface area in the period 1984–2017, especially between 2000 and 2017 when the lake lost about 1.309km2 (one third) of its surface area compared to the year 2000, which is equivalent to 76%, 18%, 0.03% and 96%. Interestingly koka lake has shown very erratic changes in its area coverage by losing almost 3.5km2 between 1984 and 2000 and then climbing back up by 14.8km2 in 2017. Percentage of increment was observed that 10.6% as compared with previous year.

Download Full-text