Research on Geothermal Energy Using RS Land Surface Material with Temperature Inversion Technology

2013 ◽  
Vol 644 ◽  
pp. 33-36
Author(s):  
Jian Feng Li ◽  
Jian Ping Chen
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Geothermal Energy ◽  
Yunnan Province ◽  
Temperature Inversion ◽  
Inversion Method ◽  
Surface Material ◽  
Remote Sensing Images ◽  
Proper Method ◽  
Material Temperature

Taking Tengchong area in Yunnan Province as a study area and ASTER and ETM remote sensing images as research object, authors selected the proper method for the study area by Comparing the results of the Land Surface Material Temperature Inversion. The result shows that the ETM inversion method is more precise than the ASTER method. Both methods can meet the demand of temperature classification.

Rapid dehazing algorithm based on large-scale median filtering for high-resolution visible near-infrared remote sensing images

2014 ◽  
Vol 12 (05) ◽  
pp. 1461010 ◽  
Author(s):  
Changmiao Hu ◽  
Ping Tang
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Near Infrared ◽  
Low Frequency ◽  
Median Filtering ◽  
Remote Sensing Images ◽  
Infrared Band ◽  
Remote Sensing Image Processing

In recent years, China's demand for satellite remote sensing images increased. Thus, the country launched a series of satellites equipped with high-resolution sensors. The resolutions of these satellites range from 30 m to a few meters, and the spectral range covers the visible to the near-infrared band. These satellite images are mainly used for environmental monitoring, mapping, land surface classification and other fields. However, haze is an important factor that often affects image quality. Thus, dehazing technology is becoming a critical step in high-resolution remote sensing image processing. This paper presents a rapid algorithm for dehazing based on a semi-physical haze model. Large-scale median filtering technique is used to extract large areas of bright, low-frequency information from images to estimate the distribution and thickness of the haze. Four images from different satellites are used for experiment. Results show that the algorithm is valid, fast, and suitable for the rapid dehazing of numerous large-sized high-resolution remote sensing images in engineering applications.

scholarly journals Inversion and Analysis of Land Surface Temperature based on Landsat - a case study of BeiBei District in Chongqing

2020 ◽  
Vol 165 ◽  
pp. 03006
Author(s):  
Zhou Yang ◽  
Liu Na-na
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Exchange Process ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Temperature Inversion ◽  
Correction Method ◽  
Inversion Method ◽  
Temperature Area

Land surface temperature is the surface of the earth’s energy change and the exchange process, which is an important index for a lot of scientific research. In this paper, the surface temperature changes of BeiBei district in Chongqing in the past 20 years were inverted in 6 time phases. The surface temperature inversion method of Landsat remote sensing data was studied, and the atmospheric correction method was adopted to conduct the inversion by using Landsat5TM and landsat8OLI-TIRS image data. The results showed that from 2004 to 2014, the area of high temperature area increased year by year, and the area of low temperature area also increased year by year.

scholarly journals Road Detection from Remote Sensing Images using Impervious Surface Characteristics: Review and Implication

2014 ◽  
Vol XL-8 ◽  
pp. 955-959 ◽  
Author(s):  
P. P. Singh ◽  
R. D. Garg
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Road Network ◽  
Satellite Images ◽  
Hybrid Approach ◽  
Surface Characteristics ◽  
Road Detection ◽  
Remote Sensing Images ◽  
High Resolution Satellite Images ◽  
Road Segments

The extraction of road network is an emerging area in information extraction from high-resolution satellite images (HRSI). It is also an interesting field that incorporates various tactics to achieve road network. The process of road detection from remote sensing images is quite complex, due to the presence of various noises. These noises could be the vehicles, crossing lines and toll bridges. Few small and large false road segments interrupt the extraction of road segments that happens due to the similar spectral behavior in heterogeneous objects. To achieve a better level of accuracy, numerous factors play their important role, such as spectral data of satellite sensor and the information related to land surface area. Therefore the interpretation varies on processing of images with different heuristic parameters. These parameters have tuned according to the road characteristics of the terrain in satellite images. There are several approaches proposed and implemented to extract the roads from HRSI comprising a single or hybrid method. This kind of hybrid approach has also improved the accuracy of road extraction in comparison to a single approach. Some characteristics related to impervious and non-impervious surfaces are used as salient features that help to improve the extraction of road area only in the correct manner. These characteristics also used to utilize the spatial, spectral and texture features to increase the accuracy of classified results. Therefore, aforesaid characteristics have been utilized in combination of road spectral properties to extract road network only with improved accuracy. This evaluated road network is quite accurate with the help of these defined methodologies.

scholarly journals Criteria for the optimal selection of remote sensing optical images to map event landslides

2018 ◽  
Vol 18 (1) ◽  
pp. 405-417 ◽  
Author(s):  
Federica Fiorucci ◽  
Daniele Giordan ◽  
Michele Santangelo ◽  
Furio Dutto ◽  
Mauro Rossi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Central Italy ◽  
Morphological Characteristics ◽  
Visual Interpretation ◽  
Remote Sensing Images ◽  
Optical Images ◽  
Image Characteristics ◽  
Landslide Mapping ◽  
Error Index

Abstract. Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.

Research on 3mm Band Radiometric Brightness Temperature Inversion

2012 ◽  
Vol 239-240 ◽  
pp. 320-323
Author(s):  
Guang Feng Zhang ◽  
Qi Wang ◽  
Guo Wei Lou
Keyword(s):  
Remote Sensing ◽  
Integral Equation ◽  
Temperature Distribution ◽  
Brightness Temperature ◽  
Fredholm Integral Equation ◽  
Error Compensation ◽  
Water Surface ◽  
Temperature Inversion ◽  
Calculation Model ◽  
Inversion Method

A MMW radiometer is widely used in remote sensing and guidance. In order to obtain the real brightness temperature distribution of the target, we need to solve the first kind of ill Fredholm integral equation of radiometric antenna temperature. The paper presents a kind of inversion method for modifying antenna pattern and the approach of error compensation. Compared with the theoretical calculation model of 3mm smooth water surface, the results show this algorithm has a higher accuracy for the measurement application.

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