Long-Term Changes of Open-Surface Water Bodies in the Yangtze River Basin Based on the Google Earth Engine Cloud Platform

Abstract

The spatiotemporal changes of open-surface water bodies in the Yangtze River Basin (YRB) have profound influences on sustainable economic development, and are also closely relevant to water scarcity in China. However, long-term changes of open-surface water bodies in the YRB have remained poorly characterized. Taking advantage of the Google Earth Engine (GEE) cloud platform, this study processed 75,593 scenes of Landsat images to investigate the long-term changes of open-surface water bodies in the YRB from 1984 to 2018. In this study, we adopted the percentile-based image composite method to collect training samples and proposed a multiple index water detection rule (MIWDR) to quickly extract the open-surface water bodies. The results indicated that (1) the MIWDR is suitable for the long-term and large-scale Landsat water bodies mapping, especially in the urban regions. (2) The areas of permanent water bodies and seasonal water bodies were 29,076.70 km2 and 21,526.24 km2, accounting for 57.46% and 42.54% of the total open-surface water bodies in the YRB, respectively. (3) The permanent water bodies in the YRB increased along with the decreases in the seasonal water bodies from 1984 to 2018. In general, the total open-surface surface water bodies in the YRB experienced an increasing trend, with an obvious spatial heterogeneity. (4) The changes of open-surface water bodies were associated with the climate changes and intense human activities in the YRB, however, the influences varied among different regions and need to be further investigated in the future.

Open-Surface Water Bodies Dynamics Analysis in the Tarim River Basin (North-Western China), Based on Google Earth Engine Cloud Platform

“…Each image was then processed using ARWDR to obtain a preliminary water body distribution map. Mountain shadows and other classification errors were finally removed from the JRC global surface water bodies distribution dataset [8,36]. The flow chart of this study is shown in Figure 4.…”

“…The percentage of the number of times a pixel is identified as water in all good observations of the pixel can be defined as the water inundation frequency (WIF) [36], which is calculated as follows:…”

“…WIF is taken in the range of [0%, 100%]. In previous studies [22,36,52], 75% and 25% were used as thresholds for classifying permanent and seasonal water bodies: the pixel was considered a permanent water bodies when WIF > 75%, a seasonal water bodies when 75% ≥ WIF > 25%, and an invalid water bodies when WIF < 25%. In this way, the uncertainty of image data quality flags and other small probability problems in image preprocessing are reduced.…”

Google Earth Engine e sua aplicabilidade na gestão de recursos hídricos

“…Os recursos e serviços hídricos desempenham um papel crítico no crescimento econômico e na sustentabilidade ambiental [Deng et al 2019]. Como componentes essenciais dos recursos hídricos, os corpos d'água de superfície aberta, incluindo lagoas, rios, córregos e reservatórios fornecem uma série de serviços proporcionados pelo ecossistema, como abastecimento de água e alimentos e regulação climática [Kumar and Mutanga 2018].…”

Awareness of Children about Rational Use of Water: An Approach Based on Serious Game and Data Mining

“…In addition, this water is not well distributed to the population, and many countries have water crises. The water shortage expectation in the near future proves that the world population must be mobilized, as soon as possible, to face the problem of water waste in daily activities (DENG et al, 2019;POORTINGA et al, 2018).…”