检索结果-内蒙古大学图书馆

Modeling Land Surface Temperature with a mono-window algorithm to Estimate Urban Heat Island Intensity in an Expanding Urban Area

引用

ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL 2022年第1期9卷 1-21页

作者： Abdullah, Shahriar Barua, Dhrubo Noakhali Sci & Technol Univ Dept Environm Sci & Disaster Management Noakhali 3814 Bangladesh

We have estimated the amplitude and impact of urbanization on Chittagong metropolitan area (CMA), and investigated the correlation between land cover features and land surface temperature (LST). We have also located the urban heat island (UHI) and calculated the UHI intensity. Support vector machine (SVM) for land cover classification and mono-window algorithm (MWA) for LST estimation were applied to Landsat images of years 1990, 2000, 2010 and 2020. Validation of classification and temperature was also done by various statistical parameters giving credible results. The findings reveal that in Chittagong, between 1990 and 2020, the urban area has raised by almost 12%, whereas vegetative areas have decreased by about 14%. With the rise of the urban area, the temperature has also shifted from 19.8 degrees C to 23.7 degrees C. Moreover, the UHI intensity has also raised from 1 degrees C to 2.3 degrees C, which is the indication of an unplanned and unsustainable urban development. Evidently, the whole city can turn into a UHI if proper steps are not taken immediately.

关键词： Urban heat island Land surface temperature mono-window algorithm Support vector machine Urbanization Chittagong

来源：评论

学校读者我要写书评

暂无评论

Improvement of mono-window algorithm for Land Surface Temperature Retrieval Integrated with Sub-pixel Mapping for Landsat Imagery 4

Improvement of Mono-window Algorithm for Land Surface Temper...

引用

4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA)

作者： Dai, Xiaoyan Guo, Zhongyang Chen, Chen Fudan Univ Dept Environm Sci & Engn Shanghai Peoples R China East China Normal Univ Minist Educ Key Lab Geog Informat Sci Shanghai Peoples R China

ISBN: (纸本)9781509014798

Since a large proportion of pixels are often composed of mixed land cover types within remote sensing images, how to eliminate the impact of the error resulting from pixel mixing effect in the estimation of land surface emissivity on the accuracy of land surface temperature (LST) retrieval from remote sensing data is a key problem to resolve firstly in process of LST retrieval. Based on the local relationship between the thermal radiance of one pixel and that of its components satisfying the Planck's radiance function, in this paper, the mono-window algorithm was improved by integrating with mixed-pixel classification and sub-pixel mapping for Landsat imagery. Validation indicates that the improved mono-window algorithm is able to provide more accurate LST than the original algorithm for Landsat TM/ETM+ imagery. By applying the improved algorithm to the Landsat image of Shanghai, the result revealed the spatial heterogeneity characteristics of UHI effect in Shanghai city.

关键词： land surface temperature mono-window algorithm sub-pixel mapping Landsat imagery remote sensing

来源：评论

学校读者我要写书评

暂无评论

An Improved mono-window algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

引用

REMOTE SENSING 2015年第4期7卷 4268-4289页

作者： Wang, Fei Qin, Zhihao Song, Caiying Tu, Lili Karnieli, Arnon Zhao, Shuhe Chinese Acad Agr Sci Inst Agroresources & Reg Planning Beijing 100081 Peoples R China Nanjing Univ Sch Geog & Oceanog Sci Nanjing 210093 Jiangsu Peoples R China Ben Gurion Univ Negev J Blaustein Inst Desert Res Dept Environm Phys Remote Sensing Lab IL-84990 Midreshet Ben Gurion Ben Gurion Israel Jiangsu Ctr Collaborat Innovat Geog Informat Reso Nanjing 210023 Jiangsu Peoples R China

The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST). However, calibration notices issued by the United States Geological Survey (USGS) indicated that data from the Landsat 8 Thermal Infrared Sensor (TIRS) Band 11 have large uncertainty and suggested using TIRS Band 10 data as a single spectral band for LST estimation. In this study, we presented an improved mono-window (IMW) algorithm for LST retrieval from the Landsat 8 TIRS Band 10 data. Three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature) were required for the IMW algorithm to retrieve LST. A new method was proposed to estimate the parameter of effective mean atmospheric temperature from local meteorological data. The other two essential parameters could be both estimated through the so-called land cover approach. Sensitivity analysis conducted for the IMW algorithm revealed that the possible error in estimating the required atmospheric water vapor content has the most significant impact on the probable LST estimation error. Under moderate errors in both water vapor content and ground emissivity, the algorithm had an accuracy of similar to 1.4 K for LST retrieval. Validation of the IMW algorithm using the simulated datasets for various situations indicated that the LST difference between the retrieved and the simulated ones was 0.67 K on average, with an RMSE of 0.43 K. Comparison of our IMW algorithm with the single-channel (SC) algorithm for three main atmosphere profiles indicated that the average error and RMSE of the IMW algorithm were -0.05 K and 0.84 K, respectively, which were less than the -2.86 K and 1.05 K of the SC algorithm. Application of the IMW algorithm to Nanjing and its vicinity in east China resulted in a reasonable LST estimation for the region. Spatial variation of

关键词： Landsat 8 TIRS data land surface temperature thermal infrared mono-window algorithm split-window algorithm

来源：评论

学校读者我要写书评

暂无评论

Enhancing landsat 8 land surface temperature retrieval in coastal regions using MODIS atmospheric water vapor data

引用

INTERNATIONAL JOURNAL OF REMOTE SENSING 2025年第8期46卷 3137-3161页

作者： Wang, Tianyi Gao, Zhiqiang Ning, Jicai Tian, Xinpeng Wang, De Wang, Yueqi Jiang, Xiaopeng Luan, Xianyi Chinese Acad Sci Yantai Inst Coastal Zone Res CAS Key Lab Coastal Environm Proc & Ecol Remediat Yantai 264003 Shandong Peoples R China Chinese Acad Sci Yantai Inst Coastal Zone Res Shandong Key Lab Coastal Environm Proc Yantai Shandong Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

The Landsat series has long served as a critical data source for remote sensing-based land surface temperature (LST) retrieval. Accurate LST estimation requires parameters like emissivity and atmospheric transmittance, whose uncertainties can introduce significant errors. This study presents the MODIS three-channel weighted algorithm, which offers robust atmospheric water vapour retrieval capabilities, particularly in regions with high spatial variability such as coastal areas. By analysing variations in atmospheric water vapour across different land cover types, we incorporate these values into Qin's mono-window algorithm for LST calculation and validate the results through two approaches: UAV-based validation and cross-validation. The UAV-based measurements were used to directly compare observed and modelled LST, achieving a high accuracy with an RMSE of 1.01. Cross-validation against existing satellite-derived LST products further confirmed the model's reliability, demonstrating robust consistency with an RMSE of 1.259 K. This integration provides a reliable solution for addressing atmospheric variability in heterogeneous landscapes, with potential applications in climate monitoring and land management.

关键词： Land surface temperature MODIS mono-window algorithm atmospheric water vapour retrieval coastal zone

来源：评论

学校读者我要写书评

暂无评论

Dynamic trends in land surface temperature and land use/land cover transitions in semi-arid metropolitan city, Jaipur

引用

ENVIRONMENTAL MONITORING AND ASSESSMENT 2024年第1期197卷 1-38页

作者： Khajuria, Neha Kaushik, S. P. Kurukshetra Univ Dept Geog Kurukshetra 136119 India

The increasing surface heat in metropolitan areas is one of the biggest issues, especially as natural surfaces are being replaced by impermeable concrete surfaces. This study uses Landsat data (1991-2022) to examine the spatio-temporal dynamics of LST and LULC in Jaipur, highlighting the impact of urban expansion and the city's semi-arid nature on the thermal landscape. We have used the maximum likelihood classifier for supervised LULC classification and the mono-window algorithm for retrieving LST. The evaluation is done using buffer analysis. Furthermore, to assess the interrelationship between LST and LULC indices (NDVI & NDBI), regression analysis is used. The CA-ANN model is employed to project LSTs of 2032 and 2042. The findings indicate that the built-up land in the study area grew by 52.80% from 1991-2022. Most of this expansion has come at the expense of agriculture/open land, and vegetation cover. The mean LST in the city has risen by 5.9 degrees C, with the inner zone (B1) increasing from 35.44 degrees C to 41.93 degrees C, indicating urbanisation-induced heat stress. In the outer zones (B5-B6), dry sandy and rocky soils contribute to elevated temperatures. Water bodies show the lowest LST, while open and barren lands have the highest. LST exhibit a positive correlation with NDBI and a weak negative correlation with NDVI. Predictions indicate that by 2042, about 99% of the urban landscape will encounter surface temperatures above 40 degrees C, with 28.79% exceeding 45 degrees C. Raised temperatures could exacerbate the UHI effect, leading to serious health and environmental concerns.

关键词： mono-window algorithm LST (Land Surface Temperature) LULC (Land use/Land cover) UHI (Urban Heat Island) CA-ANN (Cellular Automata-Artificial Neural Network)

来源：评论

学校读者我要写书评

暂无评论

Modeling the spatiotemporal heterogeneity of land surface temperature and its relationship with land use land cover using geo-statistical techniques and machine learning algorithms

引用

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第49期30卷 106917-106935页

作者： Bindajam, Ahmed Ali Mallick, Javed Talukdar, Swapan Shahfahad Shohan, Ahmed Ali A. Rahman, Atiqur King Khalid Univ Coll Engn Dept Architecture & Planning Abha Saudi Arabia King Khalid Univ Coll Engn Dept Civil Engn POB 394 Abha 61411 Saudi Arabia Jamia Millia Islamia Dept Geog Fac Nat Sci New Delhi India

Rapid changes in land use and land cover (LULC) have ecological and environmental effects in metropolitan areas. Since the 1990s, Saudi Arabia's cities have undergone tremendous urban growth, causing urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, etc. This study evaluates the variance and heterogeneity in land surface temperature (LST) because of LULC changes in Abha-Khamis Mushyet, Saudi Arabia, from 1990 to 2020. The research aims to determine the impact of urban biophysical parameters on the High-High (H-H) LST cluster using geospatial, statistical, and machine learning techniques. The support vector machine (SVM) was used to map LULC. The land surface temperature (LST) has been derived using the mono-window algorithm (MWA). The local indicator of spatial associations (LISA) model was implemented on the spatiotemporal LST maps to identify LST clusters. Also, the parallel coordinate plot (PCP) approach was employed to examine the relationship between LST clusters and urban biophysical variables as a proxy of LULC. LULC maps show that urban areas rose by > 330% between 1990 and 2020. Built-up areas had an 83.6% transitional probability between 1990 and 2020. In addition, vegetation and agricultural land have been transformed into built-up areas by 17.9% and 21.8% respectively between 1990 and 2020. Uneven LULC changes in terms of built-up areas lead to increased LST hotspots. High normalized difference built-up index (NDBI) was linked to LST hotspots but not normalized difference water index (NDWI) or normalized difference vegetation index (NDVI). This research could help policymakers develop mitigation strategies for urban heat islands.

关键词： Support vector machine mono-window algorithm LISA model Parallel coordinate plot Abha-Khamis Mushyet

来源：评论

学校读者我要写书评

暂无评论

Comparative assessment of the accuracies of daytime land surface temperature retrieval methods using Landsat 8 and MODIS imageries in Benin, West Africa

引用

JOURNAL OF APPLIED REMOTE SENSING 2023年第3期17卷

作者： Djikpo, Vignon Adelphe Rosos Teka, Oscar Azihou, Fortune Toko, Ismaila Oumorou, Madjidou Sinsin, Brice Univ Abomey Calavi Fac Agron Sci Lab Appl Ecol Cotonou Benin Univ Abomey Calavi Inst Geog Land Management & Environm Lab Cartog Cotonou Houeyiho Benin Univ Abomey Calavi Ecole Polytech Abomey Calavi Dept Environm Management Cotonou Benin

Land surface temperature (LST) is an important climate variable used to assess the effects of climate change. This research project aims to compare the results of mono-window (MW) and split-window (SW) algorithms against the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 Collection 2 Level-2 surface temperature (L8-C2L2) products and identify the most suitable techniques. In-situ measurements of the earth's surface temperature and relative humidity have been recorded in 2020. LSTs have been validated using root mean square error (RMSE) based on the in-situ meteorological data. Validation analysis has indicated that the SW algorithm combined with in-situ micro-scale atmospheric water vapor content values was more accurate for LST. In the overall study area, the RMSE values of 1.09 degrees C, 3.97 degrees C, 4.36 degrees C, and 6.80 degrees C have been calculated for SW, MODIS, L8-C2L2, and MW LSTs, respectively. These results have demonstrated that the SW algorithm outperformed the other LST products. The maximum difference between the in-situ earth surface temperature and the SW algorithm was 0.79 degrees C. These findings are essential for comparing different data-driven approaches and identifying the most efficient techniques. The study's significance lies in identifying the most appropriate method for LST retrieval, which can aid in climate change studies and inform decision-making processes.(c) 2023 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： land surface temperature Landsat imagery moderate resolution imaging spectroradiometer mono-window algorithm split-window algorithm

来源：评论

学校读者我要写书评

暂无评论

Changing land surface temperature in response to land use changes in Kashmir valley of northwestern Himalayas

引用

GEOCARTO INTERNATIONAL 2022年第27期37卷 18618-18637页

作者： ul Shafiq, Mifta Tali, Javaid Ahmad ul Islam, Zahoor Qadir, Junaid Ahmed, Pervez Govt Degree Coll Bijbehara Dept Geog Anantnag India Govt Degree Coll Tral Dept Geog Pulwama India Univ Kashmir Dept Geog & Disaster Management Srinagar India

LST variability in a region is significantly impacted by changes in LULC. The current study makes use of satellite data to examine the historical link between LULC and LST in Kashmir Valley. Using the mono-window algorithm method, the study area has seen substantial changes in LST owing to the conversion of various LULC classes. Results reveal that in LULC agriculture has been transformed to horticulture and built up area with around 80% of the area of Kashmir valley seeing a consequent shift in LST patterns from low category of LST to medium and high category LST. These rapid changes can mainly be attributed to changing economic structure, population growth, the resultant increase in settlements and infrastructure activities, and vegetation dynamics. Strong policy measures are needed to mitigate the impacts of rapid land system changes on the environment keeping in view the sensitivity of the mountainous Kashmir Himalayan region.

关键词： LULC mono-window algorithm urbanization Kashmir valley landsat

来源：评论

学校读者我要写书评

暂无评论

RADIATIVE HEAT FLUX ESTIMATION FOR GEOTHERMAL EXPLORATION WITH SATELLITE IMAGERY: A CASE STUDY AT KAMOJANG CRATER

RADIATIVE HEAT FLUX ESTIMATION FOR GEOTHERMAL EXPLORATION WI...

引用

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Badruzzaman, Ahmad Saepuloh, Asep Harto, Agung Budi Univ Indonesia Fac Comp Sci Jakarta Indonesia Bandung Inst Technol Fac Earth Sci & Technol Bandung Indonesia

ISBN: (数字)9781665427920

ISBN: (纸本)9781665427920

Geothermal energy is one of the energies that can achieve the seventh goal of the Sustainable Development Goals, which ensures access to affordable, reliable, sustainable, and modern energy. Supported by the geographical conditions of Indonesia, which is a volcanic arc country, the utilization of geothermal energy can be realized massively. This study aims to identify the location of the geothermal potential by calculating the land surface temperature and radiative heat flux from a geothermal system. We have raised a hypothesis that the heat from the geothermal system will consistently be higher than in surrounding environments. We used satellite images from The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Sentinel 2 MSI, and Terra MODIS MOD11A2. The study was conducted in Kamojang Crater, West Java, Indonesia, by extracting land surface temperature from satellite imagery using a mono-window algorithm. The algorithm applies the concept of simple radiation transfer, which directly relates the measurement to the emissivity and temperature of the study area, and a simulation model that describes the effect of the radiation regime on the measurement. The results indicated that the detected geothermal surface manifestations are located at a higher temperature than the background. Furthermore, the high-temperature anomaly is accompanied consistently by the high temperature of ground measurements. Then, radiative heat flux as part of the heat lost from the surface is applied as a variable to calculate the geothermal reservoir energy.

关键词： geothermal radiative heat flux mono-window algorithm satellite imagery

来源：评论

学校读者我要写书评

暂无评论

Estimation of land surface temperature in response to land use/land cover transformation in Kolkata city and its suburban area, India

引用

INTERNATIONAL JOURNAL OF URBAN SCIENCES 2022年第4期26卷 604-631页

作者： Biswas, Souvik Ghosh, Soumen Forest Survey India Minist Environm Forest & Climate Change Dehra Dun Uttarakhand India Univ Burdwan Dept Geog Bardhaman 713104 W Bengal India

The land transformation in Kolkata city and its suburban area is mainly due to intensive population pressure and rapid urban sprawling. Consequently, the land surface temperature (LST) is continuously increasing and gradually intensifying the effects of the urban heat island. The aim of this study is to assess the spatiotemporal variation of LST in response to land use land cover change (LULC) during 1995-2020. The maximum likelihood classifier was used for the supervised classification of LULC and the accuracy assessment was done using the confusion matrix. Quin's mono-window algorithms for Landsat TM data of 1995 and 2010 and split-window algorithms for Landsat 8 OLI data of 2020 were applied to retrieve LST. Several spectral indices such as Normalized difference built-up index (NDBI), Normalized difference vegetation index (NDVI), and Modified normalized difference water index (MNDWI) were calibrated and pixel-specific overlay analysis was done for correlation study between spectral indices and LST. This work revealed that the rapid urban sprawling causes massive land transformation in the study area. The land conversions from trees outside forests (TOF) and agricultural land to built-up were significantly contributing to an overall increase in the mean LST during 1995-2020. The mean LST was comparatively high over Kolkata city than its suburban area. During 1995-2020, the mean LST was increased by nearly 8.43 degrees C in the summer season and 4.32 degrees C in the winter season. The increasing rate of LST was found relatively high over the built-up (7.06 degrees C), agricultural land without crop (5.55 degrees C), and open land (5.54 degrees C). However, it was comparatively low over TOF (4.66 degrees C) and water bodies (3.68 degrees C). The LST was positively correlated to NDBI and negatively correlated to NDVI and MNDWI. In order to combat urban warming, this study will promote green city initiatives through sustainable land use planning.

关键词： Land-use land-cover land surface temperature mono-window algorithm split-window algorithm spectral indices Kolkata city

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：