scholarly journals Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Timothy Shields ◽  
Jessie Pinchoff ◽  
Jailos Lubinda ◽  
Harry Hamapumbu ◽  
Kelly Searle ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Population Distribution ◽  
Satellite Image ◽  
Public Health Research ◽  
Cluster Detection ◽  
Practical Significance ◽  
Programme Implementation ◽  
Detection Analysis ◽  
High Resolution Satellite Imagery

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

scholarly journals Vehicle Detection and Classification from High Resolution Satellite Images

2014 ◽  
Vol II-1 ◽  
pp. 1-8 ◽  
Author(s):  
L. Abraham ◽  
M. Sasikumar
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Weather Forecasting ◽  
Vehicle Detection ◽  
Satellite Imaging ◽  
Suitable Alternative ◽  
High Resolution Satellite Images ◽  
Technological Developments ◽  
High Resolution Satellite Imagery

In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

scholarly journals Segmentation of Satellite Imagery of Amedi Site Using Chan–Vese Model with Saliency Estimation

2020 ◽  
Vol 1 (4) ◽  
pp. 125-134
Author(s):  
Pawan Rachee
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Object Segmentation ◽  
Satellite Image ◽  
Bilateral Filter ◽  
Histogram Equalization ◽  
Saliency Map ◽  
Enhancement Technique ◽  
Map Segmentation ◽  
Quantitative Manner

The images that have been taken from space satellites are described by satellite imagery. The presence of the earth's surface is detected by remote sensing. Normally the source of the satellite image is barely seen, because many points in the sky are obscured with cloud shadows. Therefore, one of the most important and ubiquitous tasks in image analysis is segmentation. Segmentation is the method of dividing a image into a collection of specific regions that vary in some essential qualitative or quantitative manner. In this paper we will focus on a method for segmenting images that was developed   Three different methods to detect the location of the satellite images have been studied, implemented, and tested; these are based on Chan-Vese and saliency map segmentation, and multi-resolution segmentation to obtain a proper object segmentation. In this study, the combination of the proposed segmentation automatic detection and image enhancement technique has been performed to reduce the noise of the original image. In addition, the Bilateral filter, and histogram equalization are used in these proposed techniques. Experimental results demonstrate that the suggested method can precisely extract the objective of Amedi site from the satellite images with difficult backgrounds and overlapping regions.

A Novel Region-Based Approach for Automatic Road Extraction from High Resolution Satellite Images

2013 ◽  
Vol 284-287 ◽  
pp. 2998-3003
Author(s):  
Young Gi Byun
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Image ◽  
Road Surface ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Road Extraction ◽  
High Resolution Satellite Images ◽  
High Resolution Satellite Imagery ◽  
One Class Classification

With the constantly increasing public availability of high resolution satellite imagery, interest in automatic road extraction from this imagery has recently increased. Road extraction from high resolution satellite imagery refers to reliable road surface extraction instead of road line extraction because roads in the imagery mostly correspond to an elongated region with a locally constant spectral signature rather than traditional thin lines. This paper proposes a novel automatic road extraction approach that is based on a combination of image segmentation and one-class classification and consists of two main steps. First, the image is segmented using a modified previous segmentation algorithm to achieve more reliable segmentation for road extraction. The key road objects are then automatically extracted from the segmented image to obtain road training samples. Then one-class classification, based on a support vector data description classifier, is carried out to extract the road surface area from the image. The experimental results from a pan-sharpened KOMPSAT-2 satellite image demonstrate the correctness and efficiency of the proposed method for its application to road extraction from high resolution satellite image.

scholarly journals ALGORITHM AND APPLICATION OF GCP-INDEPENDENT BLOCK ADJUSTMENT FOR SUPER LARGE-SCALE DOMESTIC HIGH RESOLUTION OPTICAL SATELLITE IMAGERY

2018 ◽  
Vol XLII-3 ◽  
pp. 1607-1615
Author(s):  
Y. S. Sun ◽  
L. Zhang ◽  
B. Xu ◽  
Y. Zhang
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Satellite Images ◽  
Satellite Image ◽  
Optimization Method ◽  
Adjustment Process ◽  
Large Area ◽  
Rank Defect ◽  
And Performance

The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image – GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

scholarly journals Adaptive digital technique for discriminating between shadow and water bodies in the high resolution satellite imagery

2019 ◽  
Vol 14 (31) ◽  
pp. 81-88
Author(s):  
Anaam Kadhim Hadi
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Google Earth ◽  
Experimental Results ◽  
Water Bodies ◽  
Digital Technique ◽  
Matlab Program ◽  
High Resolution Satellite Images ◽  
High Resolution Satellite Imagery

This research presents a new algorithm for classification theshadow and water bodies for high-resolution satellite images (4-meter) of Baghdad city, have been modulated the equations of thecolor space components C1-C2-C3. Have been using the color spacecomponent C3 (blue) for discriminating the shadow, and has beenused C1 (red) to detect the water bodies (river). The new techniquewas successfully tested on many images of the Google earth andIkonos. Experimental results show that this algorithm effective todetect all the types of the shadows with color, and also detects thewater bodies in another color. The benefit of this new technique todiscriminate between the shadows and water in fast Matlab program.

SOME RESULTS OF CROP STRESS MONITORING BY REMOTE SENSING IN NORTHERN MONGOLIA

2018 ◽  
Vol 21 (02) ◽  
pp. 59-63 ◽  
Author(s):  
Tuvshinbayar D ◽  
Erdenetuya B ◽  
Erkhembayar E ◽  
Batbileg B ◽  
Sarangerel J
Keyword(s):  
Remote Sensing ◽  
Stress Field ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Satellite Image ◽  
Stress Monitoring ◽  
Wheat Growth ◽  
Northern Mongolia ◽  
Middle Period ◽  
Farming Industry

This paper presents the spatiotemporal monitoring crop stress in the first period of wheat phenology by satellite image in northern Mongolia. We used 2 satellite images Landsat8 that are dated June 23rd and July 12th of this year. Also calculated are same ratio-based indices such as NDVI, LAI and GNDVI of 2 images in the middle period of wheat phrenology, which are indicated crop stress field reports. NDVI and LAI, derived from satellite imagery are the most important characteristics of wheat stress monitoring. According to our result, as shown satellite image, wheat growth is critical and fuzzily, which is predicted necessary some management for farming. Our results show the ability of pre-processing image to analyze and visualize agricultural environments and workflows has proven to be beneficial to those involved in the farming industry.

scholarly journals Penggunaan Citra Satelit untuk Mengetahui Persebaran Dacrycarpus imbricatus (Blume) de Laub. di Bukit Tapak, Cagar Alam Batukahu Bali

2017 ◽  
Vol 11 (2) ◽  
pp. 130
Author(s):  
Rajif Iryadi ◽  
Arief Priyadi ◽  
I Dewa Putu Darma
Keyword(s):  
Satellite Imagery ◽  
Spatial Data ◽  
Satellite Image ◽  
Visual Interpretation ◽  
Site Characteristics ◽  
Natural Reserve ◽  
High Resolution Satellite Imagery ◽  
The One ◽  
Total Accuracy

Citra Pleaides merupakan aset penting untuk memperoleh data dan informasi tentang struktur vegetasi di hutan yang sulit untuk diukur langsung karena wilayah yang tidak dapat diakses dan memiliki cakupan luas. Dacrycarpus imbricatus (Blume) de Laub. merupakan salah satu tanaman khas di Bukit Tapak yang memiliki nilai konservasi dan nilai ekonomi. Penelitian ini bertujuan untuk mengetahui persebaran D. imbricatus menggunakan data citra satelit Pleaides yang memiliki resolusi spasial tinggi. Penelitian dilakukan dengan interpretasi visual pada citra satelit Pleaides tahun 2014 dan data spasial elevasi. Akurasi citra Pleaides dalam identifikasi tutupan D. imbricatus mencapai 96,83% dan ketelitian total pemetaan mencapai 93,38% dengan koefisien kappa 88,64%. Persebaran D. imbricatus di Bukit Tapak memiliki range habitat aktual lebih sempit dibandingkan dengan range potensialnya yakni pada elevasi 1.321-1.800 mdpl dengan persentase tutupan 89,52% dari total tutupannya. Lereng Bukit Tapak dengan kemiringan 25,1-55% memiliki lingkup tutupan D. imbricatus sebesar 79,29% dari total tutupannya dan sisanya pada lereng>25%. Informasi tersebut penting terkait dengan kelestarian dan usaha konservasi salah satu jenis tumbuhan berbiji terbuka ini di Bukit Tapak.Kata kunci: akurasi; interpretasi; kanopi; konservasi; pleaides Usage of Satellite Imagery to Determine Distribution of Dacrycarpus imbricatus (Blume) De Laub. on The Tapak Hill, Batukahu Natural Reserve BaliAbstractPleaides image is an important asset to obtain data and information with regard to the structure of the vegetation in the forest that are difficult to measure directly as the area is inaccessible and has a large coverage. Dacrycarpus imbricatus (Blume) de Laub. is the one of typical plants on the Tapak Hill which has the conservation and economic values. This study aimed to determine the location and distribution of D. imbricatus using Pleaides satellite image that had a high spatial resolution. The determination of site characteristics was conducted by visual interpretation of high resolution satellite imagery Pleiades 2014 and elevation spatial data. Pleaides accuracy in the identification cover of D. imbricatus reached 96.83% and total accuracy mapping reached 93.38% with kappa coefficient of 88.64%. The distribution of D. imbricatus in Tapak Hill showed actual habitat range narrower than of its potential, which was distributed on the elevation of 1,321 – 1,800 m asl with a percentage of 89,52% from its total cover. About 79.29% of the coverage laid on the slope of 25.1 to 55%, whereas the rest on the slope of >25%. This information is important related to sustainability and conservation efforts for this gymnosperm plant in Tapak Hill. 

scholarly journals Recognition of indicative landscape objects within protected areas

2020 ◽  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Satellite Imagery ◽  
Remote Sensing Data ◽  
Practical Significance ◽  
Conservation Areas ◽  
Field Methods ◽  
Sensing Data ◽  
High Resolution Satellite Imagery ◽  
Visual Changes

Formulation of the problem. In this article the author describes monitoring of landscape objects within protected area. We created 'image of landscape' from remote sensing data. The developed methodology allows to obtain remotely information about visual changes, to analyze and predict the further development of landscapes of the facies level. It is difficult to investigate nature conservation areas at the facies level in areas with plant diversity. Field methods are time-consuming and labor-intensive, but changes can occur frequently. We offer a methodology for identifying indicative landscape objects by creating an image and its visualization using high-resolution satellite imagery decoding Sentinel-2 (resolution 10 m) and Planet Scope (resolution 3 m). This method with using satellite imagery of study makes it possible to gain access to the terrain that is accessible in hard-to-reach places, namely in swampy areas, in dense forest impassable territories and others. The purpose of the article. The main goal is creating methodic for recognition indicative objects of landscape within protected territories through the appearance of visual changes by the cameral method. Materials and methods. We have improved the method of processing satellite images to identify indicative objects of changes in landscapes at the facies level. We used the method of controlled classification to obtain "a picture" of the landscape in office conditions, carried out an analysis of comparison on the ground and identified objects of interest. Based on experiments we chosen supervised classification and methods for different resolution of remote sensing data. Results and scientific novelty. We have changed the traditional landscape study process and approach in our work. We created a landscape rendering model and then carried out work directly on the ground, comparing the characteristics. this allows you to explore the territory at a distance, in hard-to-reach places and in protected areas, which allows a person to analyze information at a distance, predict and take further measures to preserve landscapes and individual objects. Practical significance. Identification of indicative objects within protected areas allows monitoring changes in landscapes, analyzing and taking measures to preserve them. Systematization of the entire analysis during processing allows you to identify changes in time even in hard-to-reach regions and quickly receive information remotely. The analyzed data allow designing a successful combination of the normal functioning of nature and human activity.

scholarly journals Penerapan Algoritma LZ77 dan Algoritma Difference Coding Untuk Memperkecil Ukuran pada Citra Satelite Geoeye

2020 ◽  
Vol 7 (2) ◽  
pp. 225
Author(s):  
Amanda Pratama ◽  
Muhammad Syahrizal
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Satellite Image ◽  
Level Of Detail ◽  
The Other ◽  
Earth Surface ◽  
Surface Image

Geoeye satellite imagery is one of the satellite images that has a high resolution and is gaining in popularity in recent years. As one of the global satellite imagery, it is clear that this satellite image offers something that can amaze anyone of its users, this satellite image offers an earth surface image with a level of detail that can be considered extraordinary, and the level of accuracy after compared to satellite imagery that has high resolution the other

scholarly journals shorelines of the Holocene Megalake Chad (Africa, Sahara) investigated with very high resolution satellite imagery (Pléiades) : example of the Goz Kerki paleo-spit

2014 ◽  
pp. 63-68 ◽  
Author(s):  
Mathieu Schuster ◽  
Claude Roquin ◽  
Abderamane Moussa ◽  
Jean-François Ghienne ◽  
Philippe Duringer ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Field Surveys ◽  
Large Size ◽  
High Resolution Satellite Imagery ◽  
Sahel Region ◽  
Lake Deposits ◽  
Humid Period ◽  
Very High

Megalake Chad (350,000 km2), the largest paleo-lake of the Sahara-Sahel area, is one of the most emblematic marker of the hydroclimatic changes that occurred during the African Humid Period (AHP; ca. 11,500 — 5,000 years BP) in subtropical Africa. From field surveys, the existence of Megalake Chad is well demonstrated by widespread typical lake deposits. However, considering the very large size of this paleo-lake, it is best evidenced and understood from space. Conspicuous paleo-littoral features distributed along hundreds of kilometers are clearly visible on second generation satellite images. These features represent major archives of the Megalake Chad and of the climate during the AHP. This paper is the first attempt to investigate the paleo-littoral of Megalake Chad with very high resolution satellite imagery. A Pléiades scene (images and DEM) is used to characterize the fossil sand spit of the Goz Kerki, which is one of the most representative and best preserved littoral features of Megalake Chad. Thanks to Pléiades stereoscopic images the geomorphology and the lithology of this paleo-spit can now be detailed and the evolution of the paleo-bathymetry of Megalake Chad can be reconstructed. This brings new insights into the paleo-environments and paleo-climates of the Sahara-Sahel region.

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