检索结果-内蒙古大学图书馆

Spatiotemporal analysis of land surface temperature trends in Nashik, India: A 30-year study from 1992 to 2022

EARTH SCIENCE INFORMATICS 2024年第3期17卷 2107-2128页

作者： Sharma, Kratika Tiwari, Ritu Wadhwani, Arun Kumar Chaturvedi, Shobhit Indian Inst Informat Technol Comp Sci & Engn Dept Pune Maharashtra India Madhav Inst Sci & Technol Elect Engn Dept Gwalior Madhya Pradesh India Pandit Deendayal Energy Univ Sch Technol Dept Civil Engn Gandhinagar Gujarat India

Over the past thirty years, Nashik, India, witnessed rapid urbanization, elevating Land Surface Temperatures (LSTs). This study presents a comprehensive approach for analyzing the spatiotemporal dynamics of LST in Nashik by utilizing Thermal Infrared Radiation bands from LANDSAT datasets. Regional LST maps from mid-May in 1992, 2003, 2013, and 2022, produced using the single channel algorithm, analyze LST changes and distributions. Land Cover Maps are developed to analyse the LST changes across different Land Classes. Further, statistical relationships are established across LSTs and landscape indicators like Normalized Difference Built-Up Index (NDBI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). A consistent increase in citywide LST is detected as the area coverage for hottest (40-45)degrees C LST band grew from 30.47 km2 in 1992 to 132.16 km2, 141.47 km2 and 174.85 km2 in 2003, 2013 and 2022 respectively. In contrast the cooler (30-40)degrees C band coverages fell from 305.39 km2 in 1992 to 203.12 km2, 194.66 km2and 144.82 km2 in 2003, 2013 and 2022 respectively. In 2022, an unprecedented 16.25 km2 area experienced extreme LST (45-50)degrees C, a trend unseen in prior decades. Noteworthy, Built-up areas and Barelands showed much higher (40-45)degrees C LSTs than vegetated areas and water bodies (30-40)degrees C. Statistical relations also affirm these patterns: Stronger LST corelations (rho = 0.66) to NDBI indicate higher temperatures in densely built-up areas. In comparison, negative LST correlations with NDVI (rho = -0.61) and NDWI (rho = -0.66) signify cooler zones with vegetation and water bodies. These findings emphasize water-rich areas with vegetation moderating temperatures, while built-up areas elevate heat. Thus, municipalities must prioritize awareness, green spaces, water conservation, cooling technologies, and zoning regulations to counteract this warming tr

关键词： Nashik Land Surface Temperature LANDSAT single channel algorithm LST Change Detection Correlation-Regression Analysis

来源：评论

学校读者我要写书评

暂无评论

Long-term monitoring of thermal pollution from Baniyas power plant in the Syrian coastal water using Landsat data

引用

REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT 2024年 36卷

作者： Khatib, Assem Al-Araj, Badr Salhab, Zeina Tishreen Univ Fac Surveying & Geomat Engn Latakia Syria Tishreen Univ Fac Sci Latakia Syria Tishreen Univ High Inst Marine Res Latakia Syria

Thermal Discharge from power plants in coastal waters may significantly influence the aquatic marine environment. Today, remotely sensing data is considered one of the primary sources to monitor the thermal pollution of power plants. This research quantitatively assesses the accuracy of retrieved Landsat/TIRS Sea Surface Temperature (SST) and effectively uses archival Landsat data to monitor the thermal pollution from Baniyas Thermal Power Plant (TTP) in the Syrian coastal water for 40 years from 1984 to 2023. The results show a strong linear correlation between Landsat/TIRS retrieved and in-situ measured SST values with an RMS error of 0.84 degrees C, which indicates the high effectiveness of using Landsat data in monitoring thermal pollution. The results also show that the average area affected by thermal pollution was 34 ha, and the thermal pollution level average was 2.9 degrees C. Thermal pollution changes in the entire period were analyzed according to three phases: formation and growth (1984 - 1992), stability (1993 - 2011), and decline (2012 - 2023). The annual thematic maps of thermal pollution show that the thermal pollution levels gradually decreased from the Baniyas TPP outlet towards open water and did not exceed a distance of 2 km offshore. The operational capacity of Baniyas TPP exhibited an influence on both thermal pollution levels and areas. The thermal pollution spatial pattern was consistent with the surface currents on the eastern coast of the Mediterranean Sea. The methodology produced in this research could be used effectively to monitor thermal pollution using satellite remote sensing data. The thematic maps developed in this study could be used as a basis for sampling to study the effect of thermal pollution levels on aquatic organisms and then develop environmental norms in Syria about the permissible values of thermal pollution.

关键词： Mediterranean sea Baniyas power plant Thermal pollution Remote sensing Sea surface temperature single channel algorithm

来源：评论

学校读者我要写书评

暂无评论

Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval algorithms and Emissivity Models and Toolbox Implementation

引用

REMOTE SENSING 2020年第2期12卷 294-294页

作者： Sekertekin, Aliihsan Bonafoni, Stefania Cukurova Univ Dept Geomat Engn TR-01950 Ceyhan Adana Turkey Univ Perugia Dept Engn Via G Duranti 93 I-06125 Perugia Italy

Land Surface Temperature (LST) is an important parameter for many scientific disciplines since it affects the interaction between the land and the atmosphere. Many LST retrieval algorithms based on remotely sensed images have been introduced so far, where the Land Surface Emissivity (LSE) is one of the main factors affecting the accuracy of the LST estimation. The aim of this study is to evaluate the performance of LST retrieval methods using different LSE models and data of old and current Landsat missions. Mono Window algorithm (MWA), Radiative Transfer Equation (RTE) method, single channel algorithm (SCA) and Split Window algorithm (SWA) were assessed as LST retrieval methods processing data of Landsat missions (Landsat 5, 7 and 8) over rural pixels. Considering the LSE models introduced in the literature, different Normalized Difference Vegetation Index (NDVI)-based LSE models were investigated in this study. Specifically, three LSE models were considered for the LST estimation from Landsat 5 Thematic Mapper (TM) and seven Enhanced Thematic Mapper Plus (ETM+), and six for Landsat 8. For the accurate evaluation of the estimated LST, in-situ LST data were obtained from the Surface Radiation Budget Network (SURFRAD) stations. In total, forty-five daytime Landsat images;fifteen images for each Landsat mission, acquired in the Spring-Summer-Autumn period in the mid-latitude region in the Northern Hemisphere were acquired over five SURFRAD rural sites. After determining the best LSE model for the study case, firstly, the LST retrieval accuracy was evaluated considering the sensor type: when using Landsat 5 TM, 7 ETM+, and 8 Operational Land Imager (OLI), and Thermal Infrared Sensor (TIRS) data separately, RTE, MWA, and MWA presented the best results, respectively. Then, the performance was evaluated independently of the sensor types. In this case, all LST methods provided satisfying results, with MWA having a slightly better accuracy with a Root Mean Square Error (RMS

关键词： land surface temperature (LST) land surface emissivity (LSE) performance evaluation Mono window algorithm radiative transfer equation single channel algorithm Split window algorithm Landsat SURFRAD data

来源：评论

学校读者我要写书评

暂无评论

Comparison of soil dielectric mixing models for soil moisture retrieval using SMAP brightness temperature over croplands in India

引用

JOURNAL OF HYDROLOGY 2021年 602卷 126673-126673页

作者： Suman, Swati Srivastava, Prashant K. Pandey, Dharmendra K. Prasad, Rajendra Mall, R. K. O'Neill, Peggy Banaras Hindu Univ Inst Environm & Sustainable Dev Remote Sensing Lab Varanasi 221005 Uttar Pradesh India Banaras Hindu Univ DST Mahamana Ctr Excellence Climate Change Res Inst Environm & Sustainable Dev Varanasi Uttar Pradesh India Indian Space Res Org Space Applicat Ctr Ahmadabad Gujarat India Indian Inst Technol BHU Dept Phys Varanasi Uttar Pradesh India NASA Goddard Space Flight Ctr Hydrol Sci Lab Greenbelt MD USA

The accurate estimation of soil moisture (SM) using microwave remote sensing depends mostly on careful selection of retrieval parameters among which the soil dielectric mixing model is the important one. These models are often categorized into empirical, semi-empirical or volumetric based on their methodologies and input data requirements. To study in detail, the comparative performance of four dielectric mixing models - Wang & Schmugge model, Hallikainen model, Dobson model and Mironov model were used with Soil Moisture Active Passive (SMAP) L-band brightness temperature and single channel algorithm for SM retrieval over agricultural landscapes in India. The highest performance statistics combination in terms of Root Mean Square Error (RMSE), correlation coefficient (R-2) and percentage bias (PBIAS) against the concurrent in-situ SM measurements were calculated at the selected validation sites. The overall results indicate that the best performance was given by the Mironov model (RMSE = 0.07 m(3)/m(3)), followed by Wang & Schmugge model (RMSE = 0.08 m(3)/m(3)), Halli-kainen model (RMSE = 0.09 m(3)/m(3)), Dobson model (RMSE = 0.10 m(3)/m(3)) and original SMAP radiometer SM (RMSE = 0.12 m(3)/m(3)). Findings of this study provides important insights into application and performance of dielectric mixing models in mapping surface SM variations. This study also underlines the pivotal role of local conditions for SM retrieval which should be carefully included in the algorithms.

关键词： Dielectric mixing models single channel algorithm Soil Moisture Active Passive Soil Moisture

来源：评论

学校读者我要写书评

暂无评论

Comparison of the accuracy of daytime land surface temperature retrieval methods using Landsat 8 images in arid regions

引用

INFRARED PHYSICS & TECHNOLOGY 2021年 115卷 103692-103692页

作者： Aliabad, Fahime Arabi Zare, Mohammad Malamiri, Hamidreza Ghafarian Yazd Univ Fac Nat Resources & Desert Stud Dept Arid Lands Management Yazd Iran Yazd Univ Dept Geog Yazd Iran

Land surface temperature (LST) is a significant parameter in surface and atmospheric systems which can be used to describe the physical processes of energy and water exchange. There are several ways to retrieve land surface temperature using satellite imagery. The purpose of the current study is to compare the accuracy of different LST retrieval algorithms, including 11 types of split-window algorithms, two mono-window algorithms, and three single-channel algorithms. The validation of LST retrieval algorithms was done using temperature-based and cross-validation methods. In this study, 20 images from Landsat 8 satellite related to 2017 and 2018 were used to retrieve LST in different ways. The temperatures obtained from different methods were compared in one day, and the average of LST of the different methods was about 5. different, which indicates the importance of the existing validation methods. Using Sentinel-2 image classification, 20 points in homogeneous areas with pure pixels were selected to measure the LST using a thermometer for land validation. Results showed that in a split window algorithm which was applied on the water vapor image, the RMSE error has been reduced by 2 degrees C. In cross-validation, MODIS LST images were used, and RMSE temporal image was prepared, and classified into five groups including less than 2, 2-3, 3-4 and more than 5 degrees C Comparing the area of each of these groups in different methods showed that MW2 and SW1 methods have less accuracy than the other methods. The SW9 algorithm can retrieve temperature with an error of less than 2. in 80% of the area. The results of cross-validation showed that the SC2 algorithm had the highest accuracy among the algorithms that use a thermal band for LST retrieval with a RMSE spatial of 5.3 degrees C and the SW10 and SW11 have shown the highest accuracy among the algorithms that use two thermal bands with RMSE less than 5 degrees C In general, the algorithms that use atmospheric transmitt

关键词： Mono window algorithm single channel algorithm Split window algorithm Validation

来源：评论

学校读者我要写书评

暂无评论

Evaluation of the urban heat island over Abha-Khamis Mushait tourist resort due to rapid urbanisation in Asir, Saudi Arabia

引用

URBAN CLIMATE 2021年 36卷

作者： Arshad, Muhammad Khedher, Khaled M. Eid, Ebrahem M. Aina, Yusuf A. King Khalid Univ Coll Engn Dept Chem Engn Abha Saudi Arabia King Khalid Univ Dept Civil Engn Coll Engn Abha Saudi Arabia Mrezgua Univ Campus Dept Civil Engn High Inst Technol Studies Nabeul Tunisia King Khalid Univ Coll Sci Dept Biol Abha Saudi Arabia Kafrelsheikh Univ Fac Sci Dept Bot Kafr Al Sheikh Egypt Yanbu Ind Coll Dept Geomat Engn Technol Yanbu Saudi Arabia

Increased knowledge of heat island surfaces (HIS) and intense heat island surfaces (IHIS) in urban environments is critical for the mitigation of excess urban heat and the associated burden on power grids. In this study, we propose a robust thermal remote sensing solution for the delineation of HIS and IHIS areas in Abha and Khamis, a tourist resort in southern Saudi Arabia. Land surface temperature (LST) classification images were retrieved by applying the single channel algorithm (SCA) to thermal band 10 of Landsat 08 data. The pixels of the LST images were grouped based on temperature ranges using ENVI 5.5 software, and were then delineated into classification images of HIS and IHIS areas. Analysis of these images revealed that the overall area of HIS dynamics in both Abha and Khamis ranged from 562 to 826 km(2), with temperature variations between 36.0 degrees C and 41.0 degrees C, while IHIS ranged from under 1 to 14 km(2) , with temperature fluctuations ranging between 40 and 46 degrees C. The city of Khamis had larger summer HIS and IHIS areas than the city of Abha. This study has a strong potential to support local stakeholders, including urban planners, in tracking and offsetting the negative urban heat island (UHI) effects that result from population growth and an increase in impervious surfaces.

关键词： Urban planning Heat island surfaces Urban growth Geospatial techniques Thermal infrared remote sensing single channel algorithm

来源：评论

学校读者我要写书评

暂无评论

Studying the coal fire dynamics in Jharia coalfield, India using time-series analysis of satellite data

引用

REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT 2021年 23卷

作者： Biswal, Shanti Swarup Gorai, Amit Kumar NIT Rourkela Dept Min Engn Sundargarh 769008 India

Coal fires in Jharia coal field (JCF) leads to significant loss of coal and pollutes the environment through emission of toxic gases. The present study aims to analyze the coal-fire dynamics in JCF during 1989-2019 through timeseries analysis. The study used thermal band data of Landsat-5 and Landsat-8 along with the radiosonde data for estimating the land surface temperature (LST) using single channel algorithm. The year-wise coal fire maps were overlapped for analysing the trends of coal fire. The results indicated that coverage area of coal fire zones has been continuously increased from 1989 to 2019. The new fire zones established at every five-year interval from 1989 to 2019 were mapped for understating the fire dynamics. The results indicated that the fire propagation was not in any specific direction. That is, new fire zones developed pocket-wise due to multiple factors and not due to continuous burning of in-situ coals. It has been observed that production level in the mines during this period also been increased possibly through more number of mines. Thus, more number of coal blocks exposed to atmosphere, which leads to catches of fire due to spontaneous heating.

关键词： Coal fire dynamics Landsat data Time-series single channel algorithm

来源：评论

学校读者我要写书评

暂无评论

Sensitivity Analysis and Validation of Daytime and Nighttime Land Surface Temperature Retrievals from Landsat 8 Using Different algorithms and Emissivity Models

引用

REMOTE SENSING 2020年第17期12卷 2776-2776页

作者： Sekertekin, Aliihsan Bonafoni, Stefania Cukurova Univ Dept Geomat Engn TR-01950 Ceyhan Adana Turkey Univ Perugia Dept Engn Via G Duranti 93 I-06125 Perugia Italy

Land Surface Temperature (LST) is a substantial element indicating the relationship between the atmosphere and the land. This study aims to examine the efficiency of different LST algorithms, namely, single channel algorithm (SCA), Mono Window algorithm (MWA), and Radiative Transfer Equation (RTE), using both daytime and nighttime Landsat 8 data and in-situ measurements. Although many researchers conducted validation studies of daytime LST retrieved from Landsat 8 data, none of them considered nighttime LST retrieval and validation because of the lack of Land Surface Emissivity (LSE) data in the nighttime. Thus, in this paper, we propose using a daytime LSE image, whose acquisition is close to nighttime Thermal Infrared (TIR) data (the difference ranges from one day to four days), as an input in the algorithm for the nighttime LST retrieval. In addition to evaluating the three LST methods, we also investigated the effect of six Normalized Difference Vegetation Index (NDVI)-based LSE models in this study. Furthermore, sensitivity analyses were carried out for both in-situ measurements and LST methods for satellite data. Simultaneous ground-based LST measurements were collected from Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) stations, located at different rural environments of the United States. Concerning the in-situ sensitivity results, the effect on LST of the uncertainty of the downwelling and upwelling radiance was almost identical in daytime and nighttime. Instead, the uncertainty effect of the broadband emissivity in the nighttime was half of the daytime. Concerning the satellite observations, the sensitivity of the LST methods to LSE proved that the variation of the LST error was smaller than daytime. The accuracy of the LST retrieval methods for daytime Landsat 8 data varied between 2.17 K Root Mean Square Error (RMSE) and 5.47 K RMSE considering all LST methods and LSE models. MWA with two different LSE models pres

关键词： land surface temperature (LST) daytime LST nighttime LST validation land surface emissivity (LSE) single channel algorithm radiative transfer equation mono window algorithm SURFRAD data Landsat 8

来源：评论

学校读者我要写书评

暂无评论

Discovering the Changes in Land Surface Temperature Caused by the Conversion of Agricultural Lands to Residential and Urban Use 9

Discovering the Changes in Land Surface Temperature Caused b...

引用

9th International Conference on Recent Advances in Space Technologies (RAST)

作者： Sekertekin, Aliihsan Arslan, Niyazi Cukurova Univ Dept Geomat Engn Adana Turkey

ISBN: (纸本)9781538694480

The aim of this study is to understand the changes in Land Surface Temperature (LST) caused by the conversion of agricultural lands to residential and urban use. Landsat-5 and Landsat-8 satellite data acquired on 30.09.1996 and 27.09.2018, respectively, were utilized to obtain LST images. single channel algorithm was used as LST retrieval method. The study was conducted in eight test sites where farmlands converted to residential and urban areas. These test sites are located in Ceyhan city, which is one of the districts of Adana province in Southern Turkey, and the total area size not only test sites of the study area is 28.51 km(2). LST images were cross-validated with MODIS LST products and RMSEs were calculated as 2.5 K and 2.2 K for 1996 and 2018 LST images, respectively. Considering long term variations, the conversion of farmlands to residential and urban areas caused a distinctive increase in LST, which may lead to the changes in the regional climate patterns. This study showed that decision makers and city planners can consider LST images for a sustainable environment.

关键词： land surface temperature agriculture single channel algorithm Landsat farmland conversion to residential

来源：评论

学校读者我要写书评

暂无评论

Land Surface Temperature Estimation from Remote Sensing Data - A Case Study in Kun Ming City 23

Land Surface Temperature Estimation from Remote Sensing Data...

引用

23rd International Conference on Geoinformatics (Geoinformatics)

作者： Li, Yanfang Yang, Kun Yang, Rong Yunnan Normal Univ Sch Tourism & Geog Sci Cartog & Geog Informat Syst Kunming Peoples R China Yunnan Normal Univ Informat Yunnan Normal Univ Sch Kunming Peoples R China GIS Technol Res Ctr Resource & Environm Western C Minist Educ Kunming Peoples R China

ISBN: (纸本)9781467376631

Land surface temperature is an important indicator of the earth's environmental analysis. Land surface emissivity is one of the key factors of remote sensing retrieving land surface temperature. In this paper, using the Landsat5 TM6 band data acquired in March24, 2009 and taking Kunming city as the study area, we use NDVI threshold method and empirical formula model to calculate the land surface emissivity of Kunming city. In this paper, we apply universal single-channel algorithms to invert the surface temperature of Kunming. The results showed that: The results of land surface emissivity were calculated by NDVI threshold and empirical formula model are significantly related with MODIS surface emissivity products. The real temperature and the surface temperature inverted by two surface emissivity are little difference and they are in the accuracy of the control range. By empirical formula model calculated surface emissivity of the surface temperature anomalies in urban areas, exceeding the real temperature 2 degrees C- 4 degrees C, does not accurately reflect the surface temperature. And the surface temperature inverted by the result of NDVI threshold is closer to the real surface temperature. This method could reflect the temperature under different land covers more accurately. Therefore, land cover such good in Kunming city area, with NDVI threshold method calculated surface emissivity to invert surface temperature is more appropriately.

关键词： land surface emissivity mixed pixel model NDVI empirical formula model method single channel algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：