scholarly journals Factors affecting the accuracy of forest clear-cut area estimation on medium spatial resolution satellite winter images

2008 ◽  
Vol 48 (1) ◽  
pp. 17-29
Author(s):  
Julia Budenkova
Keyword(s):  
Spatial Resolution ◽  
Satellite Images ◽  
Patch Size ◽  
Landsat Tm ◽  
Habitat Conditions ◽  
Difference Image ◽  
Clear Cut ◽  
Relative Boundary ◽  
Boundary Length ◽  
The Difference

Keskmise ruumilise lahutusega talvistelt satelliidipiltidelt tehtavate lageraiealade pindalahinnangute täpsust mõjutavad faktorid The aim of this paper was to investigate the influence of attributes, describing clear-cut patch size, age, shape, nearest neighbours and habitat conditions on classification results of medium spatial resolution Landsat Thematic Mapper (TM) satellite images. The study area was Võru State Forest District in South-East Estonia and the satellite images used were made in late winter when the ground was covered with snow. Clear-cuts as significantly changed areas in forests were discerned from non-changed areas with thresholding of a two-date difference image. The results of the statistical analysis showed that clear-cut attributes had an influence on image classification results. The most influential variables (presented in decreasing order of significance) are the mean of clear-cut patch pixel values on the difference image, the relative boundary length with forest, the relative boundary length with coniferous forest and the clear-cut area to perimeter ratio. The age of clear-cut and habitat conditions had no statistically significant influence on classification results. The set of influential attributes remained the same when the classifications were performed on two more liberal and on two more conservative thresholding levels. Images in the visible and near infrared spectral region (Landsat TM bands 1-4) revealed appropriate for clear-cut mapping. The difference in the area of a single clear-cut patch represented in the forestry database to that classified from a Landsat TM image was about a sixth of the patch size. This implies the utility of medium resolution satellite images in clear-cut activity assessments in particular areas but not so much the applicability of these images for single patch area estimations.

scholarly journals Change detection from satellite images based on optimal asymmetric thresholding the difference image

2019 ◽  
Vol 7 (1) ◽  
pp. 73-89
Author(s):  
Fahime Youssefi ◽  
Mohammad Javad Valadan Zoej ◽  
Mojtaba Jannati ◽  
◽  
◽  
...  
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Difference Image ◽  
The Difference

Generalized Heterodyne Configurations for Photo-induced Force Microscopy

2019 ◽  
Author(s):  
Le Wang ◽  
Devon Jakob ◽  
Haomin Wang ◽  
Alexis Apostolos ◽  
Marcos M. Pires ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Repetition Rate ◽  
Modulation Frequency ◽  
High Harmonic ◽  
Chemical Imaging ◽  
Heterodyne Detection ◽  
Force Microscopy ◽  
Wide Range ◽  
The Difference ◽  
Afm Cantilever

<div>Infrared chemical microscopy through mechanical probing of light-matter interactions by atomic force microscopy (AFM) bypasses the diffraction limit. One increasingly popular technique is photo-induced force microscopy (PiFM), which utilizes the mechanical heterodyne signal detection between cantilever mechanical resonant oscillations and the photo induced force from light-matter interaction. So far, photo induced force microscopy has been operated in only one heterodyne configuration. In this article, we generalize heterodyne configurations of photoinduced force microscopy by introducing two new schemes: harmonic heterodyne detection and sequential heterodyne detection. In harmonic heterodyne detection, the laser repetition rate matches integer fractions of the difference between the two mechanical resonant modes of the AFM cantilever. The high harmonic of the beating from the photothermal expansion mixes with the AFM cantilever oscillation to provide PiFM signal. In sequential heterodyne detection, the combination of the repetition rate of laser pulses and polarization modulation frequency matches the difference between two AFM mechanical modes, leading to detectable PiFM signals. These two generalized heterodyne configurations for photo induced force microscopy deliver new avenues for chemical imaging and broadband spectroscopy at ~10 nm spatial resolution. They are suitable for a wide range of heterogeneous materials across various disciplines: from structured polymer film, polaritonic boron nitride materials, to isolated bacterial peptidoglycan cell walls. The generalized heterodyne configurations introduce flexibility for the implementation of PiFM and related tapping mode AFM-IR, and provide possibilities for additional modulation channel in PiFM for targeted signal extraction with nanoscale spatial resolution.</div>

Mapping and Monitoring of the Land Use/Cover Changes in the Wider Area of ltanos, Crete, Using Very High Resolution EO Imagery With Specific Interest in Archaeological Sites

2019 ◽  
Author(s):  
Sawyer Reid stippa ◽  
George Petropoulos ◽  
Leonidas Toulios ◽  
Prashant K. Srivastava
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Archaeological Site ◽  
Digital Photography ◽  
Archaeological Sites ◽  
Large Area ◽  
High Resolution Imagery ◽  
Site Mapping ◽  
Rule Sets

Archaeological site mapping is important for both understanding the history as well as protecting them from excavation during the developmental activities. As archaeological sites generally spread over a large area, use of high spatial resolution remote sensing imagery is becoming increasingly applicable in the world. The main objective of this study was to map the land cover of the Itanos area of Crete and of its changes, with specific focus on the detection of the landscape’s archaeological features. Six satellite images were acquired from the Pleiades and WorldView-2 satellites over a period of 3 years. In addition, digital photography of two known archaeological sites was used for validation. An Object Based Image Analysis (OBIA) classification was subsequently developed using the five acquired satellite images. Two rule-sets were created, one using the standard four bands which both satellites have and another for the two WorldView-2 images their four extra bands included. Validation of the thematic maps produced from the classification scenarios confirmed a difference in accuracy amongst the five images. Comparing the results of a 4-band rule-set versus the 8-band showed a slight increase in classification accuracy using extra bands. The resultant classifications showed a good level of accuracy exceeding 70%. Yet, separating the archaeological sites from the open spaces with little or no vegetation proved challenging. This was mainly due to the high spectral similarity between rocks and the archaeological ruins. The satellite data spatial resolution allowed for the accuracy in defining larger archaeological sites, but still was a difficulty in distinguishing smaller areas of interest. The digital photography data provided a very good 3D representation for the archaeological sites, assisting as well in validating the satellite-derived classification maps. All in all, our study provided further evidence that use of high resolution imagery may allow for archaeological sites to be located, but only where they are of a suitable size archaeological features.

Mapping and verification of the snow cover timing in the Baikal region by remote sensing data MODIS “snow cover”

2021 ◽  
Vol 973 (7) ◽  
pp. 21-31
Author(s):  
Е.А. Rasputina ◽  
A.S. Korepova
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Baikal Region ◽  
Remote Sensing Data ◽  
Meteorological Station ◽  
Sensing Data ◽  
Modis Data ◽  
Weather Stations ◽  
The Difference

The mapping and analysis of the dates of onset and melting the snow cover in the Baikal region for 2000–2010 based on eight-day MODIS “snow cover” composites with a spatial resolution of 500 m, as well as their verification based on the data of 17 meteorological stations was carried out. For each year of the decennary under study, for each meteorological station, the difference in dates determined from the MODIS data and that of weather stations was calculated. Modulus of deviations vary from 0 to 36 days for onset dates and from 0 to 47 days – for those of stable snow cover melting, the average of the deviation modules for all meteorological stations and years is 9–10 days. It is assumed that 83 % of the cases for the onset dates can be considered admissible (with deviations up to 16 days), and 79 % of them for the end dates. Possible causes of deviations are analyzed. It was revealed that the largest deviations correspond to coastal meteorological stations and are associated with the inhomogeneity of the characteristics of the snow cover inside the pixels containing water and land. The dates of onset and melting of a stable snow cover from the images turned out to be later than those of weather stations for about 10 days. First of all (from the end of August to the middle of September), the snow is established on the tops of the ranges Barguzinsky, Baikalsky, Khamar-Daban, and later (in late November–December) a stable cover appears in the Barguzin valley, in the Selenga lowland, and in Priolkhonye. The predominant part of the Baikal region territory is covered with snow in October, and is released from it in the end of April till the middle of May.

scholarly journals A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images

2020 ◽  
Vol 12 (11) ◽  
pp. 1746
Author(s):  
Salman Ahmadi ◽  
Saeid Homayouni
Keyword(s):  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Active Contours ◽  
Training Data ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Difference Image ◽  
Proposed Model ◽  
The Difference ◽  
Aperture Radar

In this paper, we propose a novel approach based on the active contours model for change detection from synthetic aperture radar (SAR) images. In order to increase the accuracy of the proposed approach, a new operator was introduced to generate a difference image from the before and after change images. Then, a new model of active contours was developed for accurately detecting changed regions from the difference image. The proposed model extracts the changed areas as a target feature from the difference image based on training data from changed and unchanged regions. In this research, we used the Otsu histogram thresholding method to produce the training data automatically. In addition, the training data were updated in the process of minimizing the energy function of the model. To evaluate the accuracy of the model, we applied the proposed method to three benchmark SAR data sets. The proposed model obtains 84.65%, 87.07%, and 96.26% of the Kappa coefficient for Yellow River Estuary, Bern, and Ottawa sample data sets, respectively. These results demonstrated the effectiveness of the proposed approach compared to other methods. Another advantage of the proposed model is its high speed in comparison to the conventional methods.

The Design of Real-Time Face Detection System Based on FPGA

2013 ◽  
Vol 473 ◽  
pp. 231-234
Author(s):  
Su Hua Chen ◽  
Xu Fang ◽  
Yong Guang Liu ◽  
Jun Wang
Keyword(s):  
Processing Speed ◽  
Detection System ◽  
Main Body ◽  
Infrared Source ◽  
Difference Image ◽  
Small Influence ◽  
The Face ◽  
The Difference ◽  
Locating System ◽  
Image Difference

The design attempts for thefirst time to realize face locating system on the FPGA platform using themethod combined initiative infrared source with image difference. Through imagedifference process, the system obtains a difference image without backgroundinterference which takes the face as the main body. It can obtain the personface boundary by projecting the difference image in the horizontal and verticaldirection. The system processing speed amount s to the video source frequency25 frame per second, satisfying the timely request; the method of initiativeinfrared source makes the exterior have small influence on the image andguarantees the robustness of the system.

scholarly journals Hyperspectral and Multispectral Remote Sensing Image Fusion Based on Endmember Spatial Information

2020 ◽  
Vol 12 (6) ◽  
pp. 1009
Author(s):  
Xiaoxiao Feng ◽  
Luxiao He ◽  
Qimin Cheng ◽  
Xiaoyi Long ◽  
Yuxin Yuan
Keyword(s):  
Image Fusion ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Spectral Unmixing ◽  
High Spectral Resolution ◽  
Remote Sensing Image Fusion ◽  
Fusion Methods ◽  
Invariant Regions ◽  
The Difference

Hyperspectral (HS) images usually have high spectral resolution and low spatial resolution (LSR). However, multispectral (MS) images have high spatial resolution (HSR) and low spectral resolution. HS–MS image fusion technology can combine both advantages, which is beneficial for accurate feature classification. Nevertheless, heterogeneous sensors always have temporal differences between LSR-HS and HSR-MS images in the real cases, which means that the classical fusion methods cannot get effective results. For this problem, we present a fusion method via spectral unmixing and image mask. Considering the difference between the two images, we firstly extracted the endmembers and their corresponding positions from the invariant regions of LSR-HS images. Then we can get the endmembers of HSR-MS images based on the theory that HSR-MS images and LSR-HS images are the spectral and spatial degradation from HSR-HS images, respectively. The fusion image is obtained by two result matrices. Series experimental results on simulated and real datasets substantiated the effectiveness of our method both quantitatively and visually.

Sign in / Sign up

Export Citation Format

Share Document