Estimation Model of Environmental Leakage of Plastic Waste along the Yangtze River Based on Remote Sensing Data and UAV Data

2021 ◽  
Author(s):  
Jingwen Liu
Keyword(s):  
Remote Sensing ◽  
Yangtze River ◽  
Remote Sensing Data ◽  
Plastic Waste ◽  
The Yangtze River ◽  
Estimation Model ◽  
Sensing Data

Evapotranspiration variations in the Yangtze River Basin from multi-satellite remote sensing data

2018 ◽  
Vol 11 (2) ◽  
pp. 451-467
Author(s):  
Xiaojuan Tian ◽  
Shuanggen Jin
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Remote Sensing Data ◽  
Optical Remote Sensing ◽  
The Yangtze River ◽  
Sensing Data ◽  
The Yangtze River Basin ◽  
Precipitation And Temperature

Abstract Evapotranspiration (ET) variations in the Yangtze River Basin (YRB) are influenced by environmental and climate changes related to planting of crops, forest vegetation, water use and other human activities. However, it is difficult to measure ET variations and analyse influencing factors in the YRB due to lack of in-situ measurements. In the present study, the ET variations were estimated and investigated in the whole, the upper, middle and lower reaches of the YRB using the Gravity Recovery and Climate Experiment (GRACE), optical remote sensing data and hydrological models based on a water balance method, which was validated by MODerate Resolution Imaging Spectroradiometer (MODIS) observations and models. Furthermore, GRACE-ET verified the drought events in 2006 and 2011. The long-term variation rate of GRACE-ET is 0.79 mm/yr. The spatial distribution of seasonal ET variations indicates that ET is highest in summer and lowest in autumn-winter. It also shows that the completion of the Three Gorges Project has certainly increased ET. Precipitation and temperature have the largest impact on the ET variations; radiation and soil moisture have moderate effects. ET variations in the middle and lower reaches are greatly affected by precipitation, and temperature plays a more important role in the upper YRB reaches.

scholarly journals Evolution of Surge-Type Glaciers in the Yangtze River Headwater Using Multi-Source Remote Sensing Data

2019 ◽  
Vol 11 (24) ◽  
pp. 2991 ◽  
Author(s):  
Jin Yan ◽  
Mingyang Lv ◽  
Zhixing Ruan ◽  
Shiyong Yan ◽  
Guang Liu
Keyword(s):  
Remote Sensing ◽  
Flow Velocity ◽  
Yangtze River ◽  
Stable State ◽  
Remote Sensing Data ◽  
Radar Data ◽  
Series Data ◽  
The Yangtze River ◽  
Glacier Surges ◽  
Short Time

A surge-type glacier is a special and dangerous type of glacier, which can advance quickly in a short-time with cycles. Glaciers in the Yangtze River headwater are generally acknowledged to be in a stable state. However, not all of those glaciers are stable. In this paper, five glaciers from the Yangtze River headwater glacier were selected as the experimental subjects, and multi-source remote sensing images were used to study and analyze the surge behavior over the past 30 years. Based on the Landsat series data, ERS-2, and ENVISAT radar data, this paper extracts the glacier centerline information, glacial area information, and glacial flow velocity during different time periods from 1988 to 2018, which are used to monitor the active periods of glacier surges. We found three surge-type glaciers in the study area. The glacial characteristics of the three glaciers showed some drastic changes, they can advance quickly nearly 800 m in active periods, their area change can reach 2.0 × 106 m2, and their flow velocity can suddenly increase by dozens of times. Surging periods and the initiated time of the three glaciers are different, which are locked in 1997, 2003, and 1997–1998. All those surges ended within one to two years. We suggest that the surges in this paper are dominated by hydrological conditions.

scholarly journals Modeling regional evaporation through ANFIS incorporated solely with remote sensing data

2013 ◽  
Vol 10 (5) ◽  
pp. 6153-6192
Author(s):  
F.-J. Chang ◽  
W. Sun
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Data Allocation ◽  
Remotely Sensed Data ◽  
Estimation Model ◽  
Landsat Images ◽  
Inference System ◽  
Sensing Data

Abstract. The study aims to model regional evaporation that possesses the ability to present the spatial distribution of evaporation across the whole Taiwan by the adaptive network-based fuzzy inference system (ANFIS) based solely on remote sensing data. The remote sensing data used in this study consist of Landsat image products including Enhanced Vegetation Index (EVI) and land surface temperature (LST). The model construction is designed through two types of data allocation (temporal and spatial) driven with the same ten-year data of EVI and LST derived from Landsat images. Evidences indicate the estimation model based solely on remotely sensed data can effectively detect the spatial variation of evaporation and appropriately capture the evaporation trend with acceptable errors of about 1 mm day−1. The results also demonstrate the composite of EVI and LST input to the proposed estimation model improves the accuracy of estimated evaporation values as compared with the model using LST as the only input, which reveals EVI indeed benefits the estimation process. The results suggest Model-T (temporal input allocation) is suitable for making island-wide evaporation estimation while Model-S (spatial input allocation) is suitable for making evaporation estimation at ungauged sites. An island-wide evaporation map for the whole study area (Taiwan Island) is then derived. It concludes the proposed ANFIS model incorporated solely with remote sensing data can reasonably well generate evaporation estimation and is reliable as well as easily applicable for operational estimation of evaporation over large areas where the network of ground-based meteorological gauging stations is not dense enough or readily available.

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