scholarly journals Evaluation and Monitoring of Water Quantity and Quality of the Buriganga River in Bangladesh using Multi-temporal Landsat Images

2020 ◽  
Vol 8 (1) ◽  
pp. 61-69
Author(s):  
Romana Afroz ◽  
Md Bodruddoza Mia ◽  
Md Saiful Islam
Keyword(s):  
Surface Water ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Distribution ◽  
Water Bodies ◽  
Water Quantity ◽  
Buriganga River ◽  
Water Quantity And Quality

Buriganga River, the study area, is one of the most polluted and decreasing expeditiously its area in Bangladesh due to rapid urbanization, effluents of industries and factories surrounding the river, sewage disposal from Dhaka City and some anthropogenic activities. The objective of this study is to evaluate and monitor the water quantity and quality of the river using satellite remote sensing techniques. Unsupervised and indices based classification were used to derive and monitor landuse-landcover (LULC), surface water distribution (SWD), land surface temperature(LST) and total suspended material (TSM) using four sets of Landsat TM/ETM+/OLI/TIRS images of the study area from 1989 to 2015. The indices are Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). LULC classification results showed that the water bodies and vegetation decreased and consequently urban as well bared area increased from 1989 to 2015. Results of indices (NDVI and NDWI) analysis are similar to that of unsupervised LULC outputs, that is, the water bodies decreased with increasing urban structures of the study area. The surface water distribution monitoring results from the suitable change detection GIS model indicate that the water bodies have decreased about 31.07% and accretion rate increased rapidly from 1989 to 2015 along the river bank due to urbanization and accretion activity is more prominent in north, northeast, northwest, south, southeast and eastern part. The study also shows that the rate of TSM is sporadically increasing during the study period i.e., the maximum and minimum value of TSM was 56215.53 and 1956 mg/l in 1989 and 14188714.35 mg/l and 333942 mg/l in 2015 respectively; this indicates that the water is harmful for aquatic life. Both the analyzed satellite image outcome and in situ observations reveal that land surface temperature is also increased in some part of the study area. The study results could be used to make policy for upgrading the water quality and to maintain the extent and water quantity for agriculture, navigation and fisheries sectors of the Buriganga River. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 8(1), 2019, P 61-69

scholarly journals Influence of Surface Water Bodies on the Land Surface Temperature of Bangladesh

2019 ◽  
Vol 11 (23) ◽  
pp. 6754 ◽  
Author(s):  
Najeebullah Khan ◽  
Shamsuddin Shahid ◽  
Eun-Sung Chung ◽  
Sungkon Kim ◽  
Rawshan Ali
Keyword(s):  
Surface Water ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Positive Impact ◽  
Water Bodies ◽  
Mk Test ◽  
Recent Climate ◽  
Surface Water Bodies ◽  
The Impact

Recent climate change has resulted in the reduction of several surface water bodies (SWBs) all around the globe. These SWBs, such as streams, rivers, lakes, wetlands, reservoirs, and creeks have a positive impact on the cooling of the surrounding climate and, therefore, reduction in SWBs can contribute to the rise of land surface temperature (LST). This study presents the impact of SWBs on the LST across Bangladesh to quantify their roles in the rapid temperature rise of Bangladesh. The moderate resolution imaging spectroradiometer (MODIS) LST and water mask data of Bangladesh for the period 2000–2015 are used for this purpose. Influences of topography and geography on LST were first removed, and then regression analysis was conducted to quantify the impact of SWBs on the LST. The non-parametric Mann–Kendall (MK) test was used to assess the changes in LST and SWBs. The results revealed that SWBs were reduced from 11,379 km2 in 2000 to 9657 km2 in 2015. The trend analysis showed that changes in SWBs have reduced significantly at a 90% level of confidence, which contributed to the acceleration of LST rise in the country due to global warming. The spatial analysis during the specific years showed that an increase in LST can be seen with the reduction of SWBs. Furthermore, the reduction of 100 m2 of SWBs can reduce the LST of the surrounding regions from −1.2 to −2.2 °C.

scholarly journals Lake Phenology of Freeze-Thaw Cycles Using Random Forest: A Case Study of Qinghai Lake

2020 ◽  
Vol 12 (24) ◽  
pp. 4098
Author(s):  
Weixiao Han ◽  
Chunlin Huang ◽  
Hongtao Duan ◽  
Juan Gu ◽  
Jinliang Hou
Keyword(s):  
Surface Water ◽  
Random Forest ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Qinghai Lake ◽  
Water Index ◽  
Freeze Thaw ◽  
Normalized Difference Water Index ◽  
Break Up

Lake phenology is essential for understanding the lake freeze-thaw cycle effects on terrestrial hydrological processes. The Qinghai-Tibetan Plateau (QTP) has the most extensive ice reserve outside of the Arctic and Antarctic poles and is a sensitive indicator of global climate changes. Qinghai Lake, the largest lake in the QTP, plays a critical role in climate change. The freeze-thaw cycles of lakes were studied using daily Moderate Resolution Imaging Spectroradiometer (MODIS) data ranging from 2000–2018 in the Google Earth Engine (GEE) platform. Surface water/ice area, coverage, critical dates, surface water, and ice cover duration were extracted. Random forest (RF) was applied with a classifier accuracy of 0.9965 and a validation accuracy of 0.8072. Compared with six common water indexes (tasseled cap wetness (TCW), normalized difference water index (NDWI), modified normalized difference water index (MNDWI), automated water extraction index (AWEI), water index 2015 (WI2015) and multiband water index (MBWI)) and ice threshold value methods, the critical freeze-up start (FUS), freeze-up end (FUE), break-up start (BUS), and break-up end (BUE) dates were extracted by RF and validated by visual interpretation. The results showed an R2 of 0.99, RMSE of 3.81 days, FUS and BUS overestimations of 2.50 days, and FUE and BUE underestimations of 0.85 days. RF performed well for lake freeze-thaw cycles. From 2000 to 2018, the FUS and FUE dates were delayed by 11.21 and 8.21 days, respectively, and the BUS and BUE dates were 8.59 and 1.26 days early, respectively. Two novel key indicators, namely date of the first negative land surface temperature (DFNLST) and date of the first positive land surface temperature (DFPLST), were proposed to comprehensively delineate lake phenology: DFNLST was approximately 37 days before FUS, and DFPLST was approximately 20 days before BUS, revealing that the first negative and first positive land surface temperatures occur increasingly earlier.

scholarly journals Estimating malaria burden in Nigeria: a geostatistical modelling approach

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Nnadozie Onyiri
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Model ◽  
Vegetation Index ◽  
Malaria Prevalence ◽  
Malaria Risk ◽  
Water Bodies ◽  
Area Index ◽  
Environmental Covariates

This study has produced a map of malaria prevalence in Nigeria based on available data from the Mapping Malaria Risk in Africa (MARA) database, including all malaria prevalence surveys in Nigeria that could be geolocated, as well as data collected during fieldwork in Nigeria between March and June 2007. Logistic regression was fitted to malaria prevalence to identify significant demographic (age) and environmental covariates in STATA. The following environmental covariates were included in the spatial model: the normalized difference vegetation index, the enhanced vegetation index, the leaf area index, the land surface temperature for day and night, land use/landcover (LULC), distance to water bodies, and rainfall. The spatial model created suggests that the two main environmental covariates correlating with malaria presence were land surface temperature for day and rainfall. It was also found that malaria prevalence increased with distance to water bodies up to 4 km. The malaria risk map estimated from the spatial model shows that malaria prevalence in Nigeria varies from 20% in certain areas to 70% in others. The highest prevalence rates were found in the Niger Delta states of Rivers and Bayelsa, the areas surrounding the confluence of the rivers Niger and Benue, and also isolated parts of the north-eastern and north-western parts of the country. Isolated patches of low malaria prevalence were found to be scattered around the country with northern Nigeria having more such areas than the rest of the country. Nigeria’s belt of middle regions generally has malaria prevalence of 40% and above.

scholarly journals THE LAND SURFACE TEMPERATURE IMPACT TO LAND COVER TYPES

2016 ◽  
Vol XLI-B3 ◽  
pp. 871-876 ◽  
Author(s):  
I. Ibrahim ◽  
A. Abu Samah ◽  
R. Fauzi ◽  
N. M. Noor
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Temperature Variation ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Bodies ◽  
Land Cover Types ◽  
Tukey Test ◽  
Bare Land ◽  
Post Hoc

Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

Quantitative Estimation of Land Surface Temperature and Its Relationship with Land Use/Cover around Sonipat District, Haryana, India

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Diksha Rana ◽  
Maya Kumari ◽  
Rina Kumari
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Environmental Influence ◽  
Quantitative Estimation ◽  
Inverse Correlation ◽  
Urban Ecosystem ◽  
Water Bodies

Urbanization is a human activity that changes the surface of the earth and degrades the surroundings of major cities all over the world. The problem is more acute in many developing cities with a high population and rapid economic growth. The present study focuses on the effect of land use/land cover (LULC) on the land surface temperature (LST) in Sonipat district, Haryana India. The LULC derived from multispectral satellite data of two periods, 2011 and 2021, indicated a significant increase in urban areas by (3%) and barren and fallow land by (7%), whereas crop land has decreased by (11%) and water bodies have remained the same, in comparison with 2011. The LST, derived from a thermal infrared sensor, showed an overall increase in LST by 5 °C from 2011 to 2021. The results also showed that there was a significant LST difference across the LULC units. Pearson’s correlation analysis results showed an inverse correlation between LST and NDVI across urban areas and other land use classes, whereas a positive correlation over water bodies were observed in the study area. Therefore, LST and its relationship with NDVI via LULC, is a key parameter to investigate the thermal glitches in an urban ecosystem. This can be adopted as a useful tool for analyzing the environmental influence on the ecological unit.

scholarly journals Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing

2021 ◽  
Vol 13 (8) ◽  
pp. 1526
Author(s):  
Yaoyao Zheng ◽  
Yao Li ◽  
Hao Hou ◽  
Yuji Murayama ◽  
Ruci Wang ◽  
...  
Keyword(s):  
Inner City ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Landscape Patterns ◽  
Water Bodies ◽  
Cooling Effect ◽  
Landsat 8 ◽  
West Lake

The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands.

scholarly journals Urban Land Surface Temperature Monitoring and Surface Thermal Runoff Pollution Evaluation Using UAV Thermal Remote Sensing Technology

2021 ◽  
Vol 13 (20) ◽  
pp. 11203
Author(s):  
Shanshan Xu ◽  
Kun Yang ◽  
Yuanting Xu ◽  
Yanhui Zhu ◽  
Yi Luo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Surface Temperature ◽  
Water Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Surface ◽  
Surface Water Temperature ◽  
Before And After

With the continuous advancement of urbanization, the impervious surface expands. Urbanization has changed the structure of the natural land surface and led to the intensification of the urban heat island (UHI) effect. This will affect the surface runoff temperature, which, in turn, will affect the surface water temperature of urban lakes. This study will use UAS TIR (un-manned aerial system thermal infrared radiance) remote sensing and in situ observation technology to monitor the urban space surface temperature and thermal runoff in Kunming, Yunnan, in summer; explore the feasibility of UAS TIR remote sensing to continuously observe urban surface temperature during day and night; and analyze thermal runoff pollution. The results of the study show that the difference between UAS TIR LSTs and in situ LSTs (in situ air temperature 10 cm above the ground.) varies with the type of land covers. Urban surface thermal runoff has varying degrees of impact on water bodies. Based on the influence of physical factors such as vegetation and buildings and meteorological factors such as solar radiation, the RMSE between UAS LSTs and in situ LSTs varies from 1 to 5 °C. Land cover types such as pervious bricks, asphalt, and cement usually show higher RMSE values. Before and after rainfall, the in situ data of the lake surface water temperature (LSWT) showed a phenomenon of first falling and then rising. The linear regression analysis results show that the R2 of the daytime model is 0.92, which has high consistency; the average R2 at night is 0.38; the averages R2 before and after rainfall are 0.50 and 0.83, respectively; and the average RMSE is 1.94 °C. Observational data shows that thermal runoff quickly reaches thermal equilibrium with the land surface temperature about 30 min after rainfall. The thermal runoff around the lake has a certain warming effect on LSWT.

scholarly journals Analysis of Land Use Land Cover Changes with Land Surface Temperature Using Spatial-Temporal Data for Nagpur City, India

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Farhan Khan ◽  
Bhumika Das ◽  
R. K. Mishra ◽  
Brijesh Patel
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Spatial Data ◽  
Land Surface ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Barren Land

Abstract Remote sensing and Geographic Information System (GIS) are the most efficient tools for spatial data processing. This Spatial technique helps in generating data on natural resources such as land, forests, water, and their management with planning. The study focuses on assessing land change and surface temperature for Nagpur city, Maharashtra, for two decades. Land surface temperature and land use land cover (LULC) are determined using Landsat 8 and Landsat 7 imageries for the years 2000 and 2020. The supervised classification technique is used with a maximum likelihood algorithm for performing land classification. Four significant classes are determined for classification, i.e., barren land, built-up, vegetation and water bodies. Thermal bands are used for the calculation of land surface temperature. The land use land cover map reveals that the built-up and water bodies are increasing with a decrease in vegetation and barren land. Likewise, the land surface temperature map showed increased temperature for all classes from 2000 to 2020. The overall accuracy of classification is 98 %, and the kappa coefficients are 0.98 and 0.9 for the years 2000 and 2020, respectively. Due to urban sprawl and changes in land use patterns, the increase in land surface temperature is documented, which is a global issue that needs to be addressed.

scholarly journals Remote Sensing Based Land Surface Temperature Analysis in Diverse Environment of Lalgudi Block

2019 ◽  
pp. 142-149
Author(s):  
J. Ramachandran ◽  
R. Lalitha ◽  
K. Sivasubramanian
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Forest Area ◽  
Water Bodies ◽  
Spatial And Temporal Variation ◽  
Landsat 8 ◽  
River Sand ◽  
Barren Land ◽  
Diverse Environment

Introduction: Land Surface Temperature (LST) is a significant climatic variable and defined as how hot the "surface" of the Earth would feel to the physical touch in a particular location. A spatial analysis of the land surface temperature with respect to different land use/cover changes is vital to evaluate the hydrological processes. Methods: The objective of this paper is to assess the spatial variation of land surface temperature derived from thermal bands of the Landsat 8 Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) by using split window algorithm. Place and Data: The study was conducted in Lalgudi block of Trichy District, Tamil Nadu, India. The block has diverse environment like forest area, barren land, river sand bed, water bodies, dry vegetation, cultivated areas (paddy, sugarcane, banana etc.) and settlements. Landsat 8 satellite images for four selected scenes (December 2014 & January 2015 and December 2017 & January 2018) were used to estimate the LST. Results: The spatial and temporal variation of Normalized Difference Vegetation Index (NDVI) and LST were estimated. The average NDVI values of cropped fields varied from 0.3 to 0.5 in all the scenes. The maximum value of LST ranging from 35 to 40°C was recorded in river sand bed. Subsequently, semi-urban settlements in the central part of Lalgudi block exhibited higher temperature ranging from 28 – 30°C. The LST of paddy crop and sugarcane was in the range of 23 to 25°C. The water bodies exhibited LST around 20°C. The coconut plantations, forest area and Prosopis juliflora showed LST value ranging from 24 – 29°C. This kind of block level monitoring studies helps in adopting suitable policies to overcome or minimize the problems triggered by increase in land surface temperature.

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