Geologic Hazard Assessment of Slopeland Villages Using Remote Sensing Techniques

2015 ◽  
Vol 764-765 ◽  
pp. 1095-1099
Author(s):  
Shu Rong Yang ◽  
Yi Lung Yeh
Keyword(s):  
Remote Sensing ◽  
Hazard Assessment ◽  
Image Interpretation ◽  
Remote Sensing Image ◽  
Assessment Method ◽  
Geologic Hazard ◽  
Susceptibility Maps ◽  
Hazard Zone ◽  
Geologic Maps ◽  
Remote Sensing Techniques

This study focuses on 53 villages located in the slopelands of Pingtung County. Remote sensing image interpretation techniques are used to identify geologic hazard areas. GIS map overlay analysis of environmental geologic maps, landslide susceptibility maps and potential debris flow torrent maps provided by local and regional governments are used to further interpret and correctly identify the extent of the geologic hazard zone. This study successfully combines both GIS and GPS techniques, and according to data analysis results, constructs a slopeland village geologic hazard assessment method.

scholarly journals PCAN—Part-Based Context Attention Network for Thermal Power Plant Detection in Remote Sensing Imagery

2021 ◽  
Vol 13 (7) ◽  
pp. 1243
Author(s):  
Wenxin Yin ◽  
Wenhui Diao ◽  
Peijin Wang ◽  
Xin Gao ◽  
Ya Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Power Plants ◽  
State Of The Art ◽  
Thermal Power ◽  
Image Interpretation ◽  
Remote Sensing Image ◽  
Thermal Power Plants ◽  
Average Precision ◽  
Deep Convolutional Neural Networks ◽  
Multi Scale

The detection of Thermal Power Plants (TPPs) is a meaningful task for remote sensing image interpretation. It is a challenging task, because as facility objects TPPs are composed of various distinctive and irregular components. In this paper, we propose a novel end-to-end detection framework for TPPs based on deep convolutional neural networks. Specifically, based on the RetinaNet one-stage detector, a context attention multi-scale feature extraction network is proposed to fuse global spatial attention to strengthen the ability in representing irregular objects. In addition, we design a part-based attention module to adapt to TPPs containing distinctive components. Experiments show that the proposed method outperforms the state-of-the-art methods and can achieve 68.15% mean average precision.

Active fusion - A new method applied to remote sensing image interpretation

1996 ◽  
Vol 17 (13) ◽  
pp. 1349-1359 ◽  
Author(s):  
Axel Pinz ◽  
Manfred Prantl ◽  
Harald Ganster ◽  
Hermann Kopp-Borotschnig
Keyword(s):  
Remote Sensing ◽  
Image Interpretation ◽  
Remote Sensing Image ◽  
New Method

Study on Macroscopically Dynamic Monitoring of Newly Increased Construction Land in Northwestern Plains Based on Middle Resolution Remote Sensing Data

2013 ◽  
Vol 333-335 ◽  
pp. 1475-1478
Author(s):  
Zhi Hong Liu ◽  
Xing Ke Yang ◽  
Qian Zhu ◽  
Hu Jun He ◽  
San You Cheng
Keyword(s):  
Remote Sensing ◽  
Image Interpretation ◽  
Remote Sensing Data ◽  
Remote Sensing Image ◽  
Dynamic Monitoring ◽  
Remote Sensing Images ◽  
Construction Land ◽  
Multi Temporal ◽  
Northwestern Region ◽  
Northwestern Plains

Analyzing the significance of macroscopically dynamic monitoring of newly increased construction land, and considering the influence of various factors, this paper selects central Shaanxi Plain in Northwestern region for a typical experimental zone, setting up knowledge base of remote sensing images interpretation, using multi-temporal remote sensing images, carrying through interactive interpretation of change patterns spots of newly increased construction land and field validation. Results of middle resolution remote sensing image interpretation are compared, analyzed. Additionally, interpretation accuracy of different scales are studied, especially between middle resolution 10 ms ALOS remote sensing image and panchromatic high resolution remote sensing, on newly increased construction land in northwestern plains, to find out the remote sensing images which can not only quickly extract new construction land change patterns spots, but also can satisfy precision requirement of the business.

scholarly journals Study on spatial distribution of coral reefs in Nam Yet island by using GIS and remote sensing techniques

2019 ◽  
Vol 19 (3B) ◽  
pp. 177-187
Author(s):  
Nguyen Xuan Tung ◽  
Do Huy Cuong ◽  
Bui Thi Bao Anh ◽  
Nguyen Thi Nhan ◽  
Nguyen The Luan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Field Survey ◽  
Satellite Image ◽  
Image Interpretation ◽  
Kappa Coefficient ◽  
Distribution Map ◽  
Dead Coral ◽  
Gis And Remote Sensing ◽  
Interpretation Process ◽  
Remote Sensing Techniques

Research and application of GIS and remote sensing techniques combined with field survey in coastal areas of Nam Yet island had been carried out to establish the distribution map of submarine habitats. Depth-invariant index was used to correct water column’s effects on spectral reflectance of each habitat. The results of satellite image classification showed that area with well-developed coral at great depths accounted for 12%, area with well-developed coral at small depths accounted for 9%, area with poorly-developed coral accounted for 13%, dead coral area accounted for 15% and area of sand, grit, pebbles and weathered coral accounted for 51%. The assessment after classification showed that the overall accuracy of the satellite image interpretation process was 94% and the kappa coefficient was 0.93.

scholarly journals Remote-Sensing Image Tile-Level Annotation Based on Discriminative Features and Expressive Visual Word Descriptors

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Jiaming Xue ◽  
Shun Xiong ◽  
Chaoguang Men ◽  
Zhiming Liu ◽  
Yongmei Liu
Keyword(s):  
Remote Sensing ◽  
Expert Knowledge ◽  
Feature Fusion ◽  
Image Interpretation ◽  
Texture Features ◽  
Remote Sensing Image ◽  
Remote Sensing Images ◽  
Visual Words ◽  
Wide Range ◽  
Semantic Concepts

Remote-sensing images play a crucial role in a wide range of applications and have been receiving significant attention. In recent years, great efforts have been made in developing various methods for intelligent interpretation of remote-sensing images. Generally speaking, machine learning-based methods of remote-sensing image interpretation require a large number of labeled samples and there are still not enough annotated datasets in the field of remote sensing. However, manual annotation of remote-sensing images is usually labor-intensive and requires expert knowledge and the accuracy of annotation results is relatively low. The goal of this paper is to propose a novel tile-level annotation method of remote-sensing images to obtain remote-sensing datasets which are well-labeled and contain accurate semantic concepts. Firstly, we use a set of images with defined semantic concepts to represent the training set and divide them into several nonoverlapping regions. Secondly, the color features, texture features, and spatial features of each region are extracted, and discriminative features are obtained by the weight optimization feature fusion method. Then, the features are quantized into visual words by applying a density-based clustering center selection method and an isolated feature point elimination method. And the remote-sensing images can be represented by a series of visual words. Finally, the LDA model is used to calculate the probabilities of semantic categories for each region. The experiments are conducted on remote-sensing images which demonstrate that our proposed method can achieve good performance on remote-sensing image tile-level annotation. The implications of our research can obtain annotated datasets with accurate semantic concepts for intelligent interpretation of remote-sensing images.

scholarly journals Comparison of methods of Humidity Index processing in the Irrigated Perimeter Nilo Coelho, Northeast of Brazil

2018 ◽  
Vol 7 (6) ◽  
pp. 315
Author(s):  
Antonio Celso de Sousa Leite ◽  
Leidjane Maria Maciel De Oliveira ◽  
Ulisses Alencar Bezerra ◽  
Débora Natália O. de Almeida Oliveira De Almeida ◽  
Ana Lucia B. Candeias ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Image ◽  
Comparison Of Methods ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Humidity Index ◽  
Irrigated Perimeter ◽  
Remote Sensing Techniques ◽  
Object Of Study ◽  
Remote Sensing Image Processing

The use of remote sensing techniques in support of hydrological studies became common in recent years, through the application of orbital images that are used the reflectance values of the water, for mapping, delineation of water bodies and moisture monitoring in the internal structure of vegetable biomass. Among the methods and techniques of remote sensing image processing with the hydrological analysis, here the Normalized Difference Water Index (NDWI), object of study in the present work, in order to compare the application of the index through different methods. The present study was developed in the territorial part of the Nilo Coelho Irrigated Perimeter located in the Semiarid Northeastern region and covers the municipalities of Casa Nova-BA, Petrolina-PE and Juazeiro-BA, using TM-Landsat 5 sensor images from 30/07/2006. This comparison of the NDWI provided the best application for each index, as well as evaluate the potentiality of the index according to the applied method. 

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