scholarly journals Geomorphological Mapping of Razzaza–Habbaria Area using Remote Sensing Techniques

2018 ◽  
Vol 13 (1) ◽  
pp. 155-166
Author(s):  
Baghdad Science Journal
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Image Data ◽  
Unsupervised Classification ◽  
Multispectral Data ◽  
Geomorphological Mapping ◽  
The Earth ◽  
Sensing Application ◽  
Remote Sensing Techniques ◽  
Spatial Entities

Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razzaza Lake shows the different geomorphologic units and the land use maps that were delineated from Landsat ETM+ Image. Digital Image unsupervised classification was adopted to delineate the different classes by applying ERDAS 8.4 software. According to this classification five classes were selected and delineated in different colors.

scholarly journals Multimedia Detection and Processing of Remote-Sensing Image of Small Target Combined with Variable Neighborhood Search Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yaqin Wang ◽  
Maolong Qiu
Keyword(s):  
Remote Sensing ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Image Data ◽  
Unsupervised Classification ◽  
Neighborhood Search ◽  
Remote Sensing Images ◽  
The Earth ◽  
Small Targets ◽  
Neighborhood Search Algorithm

The development of scientific satellites has made it a reality for people to view the Earth from the sky. However, due to the resolution of the image obtained, the effective and accurate interpretation of remote-sensing images has always been one of the goals pursued by the industry. In this paper, we merge the variable neighborhood search algorithm, reduce the accuracy of remote-sensing images, clean the invalid information of the data, use unsupervised classification methods to quickly locate small targets, use it as verification information, compare and select the image data through sample information, distinguish the background and target results, and get stable detection results. Practice shows that this method can effectively detect small targets in remote-sensing images.

scholarly journals Estimation of flooded area in the Bahr El-Jebel basin using remote sensing techniques

2006 ◽  
Vol 3 (4) ◽  
pp. 1851-1877 ◽  
Author(s):  
M. A. H. Shamseddin ◽  
T. Hata ◽  
A. Tada ◽  
M. A. Bashir ◽  
T. Tanakamaru
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Lake Victoria ◽  
Open Water ◽  
Unsupervised Classification ◽  
Water Balance Model ◽  
Balance Model ◽  
Water Evaporation ◽  
Flooded Area ◽  
Remote Sensing Techniques

Abstract. In spite of the importance of Sudd (swamp) area estimation for any hydrological project in the southern Sudan, yet, no abroad agreement on its size, due to the inaccessibility and civil war. In this study, remote sensing techniques are used to estimate the Bahr El-Jebel flooded area. MODIS-Terra (Moderate Resolution Imaging Spectroradiometer) level 1B satellite images are analyzed on basis of the unsupervised classification method. The annual mean of Bahr El-Jebel flooded area has been estimated at 20 400 km2, which is 96% of Sutcliffe and Park (1999) estimation on basis of water balance model prediction. And only, 53% of SEBAL (Surface Energy Balance Algorithm for Land) model estimation. The accuracy of the classification is 71%. The study also found the swelling and shrinkage pattern of Sudd area throughout the year is following the trends of Lake Victoria outflow patterns. The study has used two evaporation methods (open water evaporation and SEBAL model) to estimate the annual storage volume of Bahr El-Jebel River by using a water balance model. Also the storage changes due time is generated throughout the study years.

scholarly journals Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World

2021 ◽  
Vol 13 (19) ◽  
pp. 3865
Author(s):  
Yongqiang Zhang ◽  
Dongryeol Ryu ◽  
Donghai Zheng
Keyword(s):  
Remote Sensing ◽  
Anthropogenic Impacts ◽  
The Earth ◽  
Wide Range ◽  
Important Challenge ◽  
Flood Simulations ◽  
Remote Sensing Techniques ◽  
Evapotranspiration Estimation ◽  
Ecohydrological Processes ◽  
Changing World

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions, on how to make the most out of the state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world.

scholarly journals Special Issue on Remote Sensing of Snow and Its Applications

Geosciences ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 277 ◽  
Author(s):  
Ali Nadir Arslan ◽  
Zuhal Akyürek
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Land Surface ◽  
Climate Models ◽  
Weather Forecasting ◽  
Special Issue ◽  
Carbon Cycles ◽  
Wide Range ◽  
Remote Sensing Techniques

Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water, and carbon cycles. Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological, and climate models for predicting snowmelt runoff, snow water resources, and to warn about snow-related natural hazards. The main objectives of this Special Issue, “Remote Sensing of Snow and Its Applications” in Geosciences are to present a wide range of topics such as (1) remote sensing techniques and methods for snow, (2) modeling, retrieval algorithms, and in-situ measurements of snow parameters, (3) multi-source and multi-sensor remote sensing of snow, (4) remote sensing and model integrated approaches of snow, and (5) applications where remotely sensed snow information is used for weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc. It is very important to understand (a) differences and similarities, (b) representativeness and applicability, (c) accuracy and sources of error in measuring of snow both in-situ and remote sensing and assimilating snow into hydrological, land surface, meteorological, and climate models. This Special Issue contains nine articles and covers some of the topics we listed above.

The Comparative Study of Remote Sensing Image Classification Method Based on ERDAS

2012 ◽  
Vol 546-547 ◽  
pp. 542-547 ◽  
Author(s):  
Guang Wei Zeng ◽  
Gui Fen Chen ◽  
Chu Nan Li ◽  
Jiao Ye
Keyword(s):  
Remote Sensing ◽  
Supervised Classification ◽  
Arable Land ◽  
Processing System ◽  
Image Data ◽  
Unsupervised Classification ◽  
Remote Sensing Image ◽  
Classification Method ◽  
Remote Sensing Image Classification ◽  
Erdas Imagine

ERDAS IMAGINE is a remote sensing image processing system developed by the United States.The paper using ERDAS to classified the remote sensing of Land-sat TM image data by supervised classification method and unsupervised classification method, Using the Yushu City remote sensing image of Jilin Province as the trial data, and classified the forest, arable land and water from the remote sensing images, compared the test data of the supervised classification and unsupervised classification method, shows that the supervised classification method can be better to solute the questions "with the spectrum of foreign body" and "synonyms spectrum" than unsupervised classification method, and optimize classification images, improved information extraction accuracy. The application shows the classification result is consistent with the actual situation and it laid the foundation for land to have the rational planning and use.

scholarly journals Image data paradox – on the impact of the development of image-based remote sensing on the maps’ content in the Eastern Bloc. The case of Poland

2018 ◽  
Vol 50 (4) ◽  
pp. 211-222
Author(s):  
Beata Konopska ◽  
Mirosław Krukowski
Keyword(s):  
Remote Sensing ◽  
Cold War ◽  
Image Data ◽  
Eastern Bloc ◽  
Geographical Information ◽  
Sensing Systems ◽  
The Earth ◽  
Remote Sensing Systems ◽  
The Cold War ◽  
The Impact

Abstract The authors examine the impact of the development of image-based remote sensing systems on the activities of state administrations in the cartographic production and making of geographical information publicly available in the Eastern Bloc countries. A convergence of cartography, secrecy, and power occurred during the Cold War. Through investigation of facts relevant to the acquisition image data of the Earth surface performed by the USA and the USSR, it aims to examine the key questions of why the logic behind the development of cartography in the Eastern Bloc countries after World War II was distorted. The lack of logic was reflected in the fact that the amount of information actually presented on maps decreased with an increase in the information about the surface of the Earth acquired by the means of remote sensing systems. It was suggested that image data in the member states of the Eastern Bloc, in spite of their restricted use and a drop in the informational value of maps, was the main factor behind the creation, detail, and geometric accuracy of civilian maps. Proving this thesis involved analyzing the correlations between the achievements in the field of remote sensing and the quality of maps developed during the Cold War in the Eastern Bloc states.

scholarly journals Research Bathymetry Mapping of Shallow Water Areas around Islands in the Truong Sa Archipelago by Deep - Remote sensing technology

2017 ◽  
Vol 33 (4) ◽  
Author(s):  
Phan Quoc Yen ◽  
Dao Khanh Hoai ◽  
Dinh Thi Bao Hoa
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Satellite Image ◽  
Image Data ◽  
Landsat 8 ◽  
Military Operations ◽  
Sensing Technology ◽  
Remote Sensing Techniques ◽  
Map Data ◽  
The Military

Satellite image data is being researched and applied effectively in the survey and establishment of bathymetry mapping in shallow water areas in both time and human terms. Remote sensing techniques contribute to rapid updating of topography, timely assurance of civil and military operations such as maritime safety, environmental security and rescue, Warfare in the military, especially the ability to remotely monitor disputed areas. The article experiment with the Stumpf et al algorithm to estimate the shallow water depths on the Spratly Island by Landsat 8 image. The correlation coefficient of the model R2 is 0.924; RMSE is 0.99m. In addition, the results are compared with the map data of C-map and use 12 actual test points scores to evaluate the accuracy of the model.

Sign in / Sign up

Export Citation Format

Share Document