scholarly journals Carbon stock estimation by dual-polarized synthetic aperture radar (SAR) and forest inventory data in a Mediterranean forest landscape

2021 ◽  
Author(s):  
Can Vatandaşlar ◽  
Saygin Abdikan
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Forest Inventory ◽  
Carbon Stock ◽  
Forest Ecosystems ◽  
Remote Sensing Data ◽  
Carbon Stocks ◽  
Total Carbon ◽  
Synthetic Aperture ◽  
Sar Images

AbstractForest ecosystems play a crucial role in mitigating global climate change by forming massive carbon sinks. Their carbon stocks and stock changes need to be quantified for carbon budget balancing and international reporting schemes. However, direct sampling and biomass weighing may not always be possible for quantification studies conducted in large forests. In these cases, indirect methods that use forest inventory information combined with remote sensing data can be beneficial. Synthetic aperture radar (SAR) images offer numerous opportunities to researchers as freely distributed remote sensing data. This study aims to estimate the amount of total carbon stock (TCS) in forested lands of the Kizildag Forest Enterprise. To this end, the actual storage capacities of five carbon pools, i.e. above- and below-ground, deadwood, litter, and soil, were calculated using the indirect method based on ground measurements of 264 forest inventory plots. They were then associated with the backscattered values from Sentinel-1 and ALOS-2 PALSAR-2 data in a Geographical Information System (GIS). Finally, TCS was separately modelled and mapped. The best regression model was developed using the HH polarization of ALOS-2 PALSAR-2 with an adjusted R2 of 0.78 (p < 0.05). According to the model, the estimated TCS was about 2 Mt for the entire forest, with an average carbon storage of 133 t ha−1. The map showed that the distribution of TCS was heterogenic across the study area. Carbon hotspots were mostly composed of pure stands of Anatolian black pine and mixed, over-mature stands of Lebanese cedar and Taurus fir. It was concluded that the total carbon stocks of forest ecosystems could be estimated using appropriate SAR images at acceptable accuracy levels for forestry purposes. The use of additional ancillary data may provide more delicate and reliable estimations in the future. Given the implications of this study, the spatiotemporal dynamics of carbon can be effectively controlled by forest management when coupled with easily accessible space-borne radar data.

scholarly journals A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3580 ◽  
Author(s):  
Jie Wang ◽  
Ke-Hong Zhu ◽  
Li-Na Wang ◽  
Xing-Dong Liang ◽  
Long-Yong Chen
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Synthetic Aperture Radar ◽  
3D Imaging ◽  
Synthetic Aperture ◽  
Separation Scheme ◽  
Sar Images ◽  
Wide Swath ◽  
Aperture Radar

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

scholarly journals CARBON STOCK ESTIMATION OF MANGROVE VEGETATION USING REMOTE SENSING IN PERANCAK ESTUARY, JEMBRANA DISTRICT, BALI

2018 ◽  
Vol 14 (2) ◽  
pp. 137
Author(s):  
Amandangi Wahyuning Hastuti ◽  
Komang Iwan Suniada ◽  
Fikrul Islamy
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Remote Sensing Data ◽  
Total Carbon ◽  
Total Biomass ◽  
Sensing Data ◽  
Ground Biomass ◽  
Study Results ◽  
Mangrove Vegetation ◽  
Total Carbon Stock

Mangrove vegetation is one of the forest ecosystems that offers a potential of substantial greenhouse gases (GHG) emission mitigation, due to its ability to sink the amount of CO2 in the atmosphere through the photosynthesis process. Mangroves have been providing multiple benefits either as the source of food, the habitat of wildlife, the coastline protectors as well as the CO2 absorber, higher than other forest types. To explore the role of mangrove vegetation in sequestering the carbon stock, the study on the use of remotely sensed data in estimating carbon stock was applied. This paper describes an examination of the use of remote sensing data particularly Landsat-data with the main objective to estimate carbon stock of mangrove vegetation in Perancak Estuary, Jembrana, Bali. The carbon stock was estimated by analyzing the relationship between NDVI, Above Ground Biomass (AGB) and Below Ground Biomass (BGB). The total carbon stock was obtained by multiplying the total biomass with the carbon organic value of 0.47. The study results show that the total accumulated biomass obtained from remote sensing data in Perancak Estuary in 2015 is about 47.20±25.03 ton ha-1 with total carbon stock of about 22.18±11.76 tonC ha-1and CO2 sequestration 81.41±43.18 tonC ha-1.

scholarly journals GOLD MINERAL PROSPECTING USING PHASED ARRAY TYPE L-BAND SYNTHETIC APERTURE RADAR (PALSAR) SATELLITE REMOTE SENSING DATA, CENTRAL GOLD BELT, MALAYSIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 409-412 ◽  
Author(s):  
Amin Beiranvand Pour ◽  
Mazlan Hashim
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Peninsular Malaysia ◽  
Suture Zone ◽  
Synthetic Aperture ◽  
Sensing Data ◽  
Tropical Environments ◽  
Aperture Radar

The Bentong-Raub Suture Zone (BRSZ) of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR) data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.

The potential of synthetic aperture radar (SAR) for quantifying the biomass of Australia's woodlands.

2000 ◽  
Vol 22 (1) ◽  
pp. 124 ◽  
Author(s):  
RM Lucas ◽  
AK Milne ◽  
N Cronin ◽  
C Witte ◽  
R Denham
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Strong Relationship ◽  
Carbon Stocks ◽  
Synthetic Aperture ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Branch Biomass ◽  
Aperture Radar

The potential of Synthetic Aperture Radar (SAR) for estimating the above ground and component biomass of woodlands in Australia is demonstrated using two case studies. Case Study 1 (In,june; central Queensland) shows that JERS-1 SAR L HH data can be related more to the trunk than the leaf and branch biomass of woodlands. A strong relationship between L HH and above ground biomass is obtained when low biomass pasture sites are included. Case Study I1 (Talwood, southern Queensland) determines that L and P band data can be related both to trunk and branch biomass, due to the similarity in the orientation and size of these scattering elements, and also to total above ground biomass. Saturation of the C. L and P band data occurred at approximately 20-30 Mglha; 60-80 Mglha and 80-100 Mglha. These preliminary results indicate that data from SAR are useful for quantifying changes in carbon stocks resulting from land use change in Australia's woodlands and for applications in rangeland assessment and management. Key words: remote sensing, biomass, woodlands

scholarly journals Fault-Based Geological Lineaments Extraction Using Remote Sensing and GIS—A Review

Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 183
Author(s):  
Hemayatullah Ahmadi ◽  
Emrah Pekkan
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Thermal Emission ◽  
Active Faults ◽  
Remote Sensing Data ◽  
Shuttle Radar Topography Mission ◽  
Synthetic Aperture ◽  
Optical Remote Sensing ◽  
Remotely Sensed Data ◽  
Aperture Radar

Geological lineaments are the earth’s linear features indicating significant tectonic units in the crust associated with the formation of minerals, active faults, groundwater controls, earthquakes, and geomorphology. This study aims to provide a systematic review of the state-of-the-art remote sensing techniques and data sets employed for geological lineament analysis. The critical challenges of this approach and the diverse data verification and validation techniques will be presented. Thus, this review spanned academic articles published since 1975, including expert reports and theses. Landsat series, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Sentinel 2 are the prevalent optical remote sensing data widely used for lineament detection. Moreover, Shuttle Radar Topography Mission (SRTM) derived Digital Elevation Model (DEM), Synthetic-aperture radar (SAR), Interferometric synthetic aperture radar (InSAR), and Sentinel 1 are the typical radar remotely sensed data which are widely used for the detection of geological lineaments. The geological lineaments acquired via GIS techniques are not consistent even though a variety of manual, semi-automated, and automated techniques are applied. Therefore, a single method may not provide an accurate lineament distribution and may include artifacts requiring integration of multiple algorithms, e.g., manual and automated algorithms.

scholarly journals Combinational Fusion and Global Attention of the Single-Shot Method for Synthetic Aperture Radar Ship Detection

2021 ◽  
Vol 13 (23) ◽  
pp. 4781
Author(s):  
Libo Xu ◽  
Chaoyi Pang ◽  
Yan Guo ◽  
Zhenyu Shu
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Loss Function ◽  
Global Perspective ◽  
Synthetic Aperture ◽  
Single Shot ◽  
Sar Images ◽  
Ship Detection ◽  
Function Block ◽  
Aperture Radar

Synthetic Aperture Radar (SAR), an active remote sensing imaging radar technology, has certain surface penetration ability and can work all day and in all weather conditions. It is widely applied in ship detection to quickly collect ship information on the ocean surface from SAR images. However, the ship SAR images are often blurred, have large noise interference, and contain more small targets, which pose challenges to popular one-stage detectors, such as the single-shot multi-box detector (SSD). We designed a novel network structure, a combinational fusion SSD (CF-SSD), based on the framework of the original SSD, to solve these problems. It mainly includes three blocks, namely a combinational fusion (CF) block, a global attention module (GAM), and a mixed loss function block, to significantly improve the detection accuracy of SAR images and remote sensing images and maintain a fast inference speed. The CF block equips every feature map with the ability to detect objects of all sizes at different levels and forms a consistent and powerful detection structure to learn more useful information for SAR features. The GAM block produces attention weights and considers the channel attention information of various scale feature information or cross-layer maps so that it can obtain better feature representations from the global perspective. The mixed loss function block can better learn the positions of the truth anchor boxes by considering corner and center coordinates simultaneously. CF-SSD can effectively extract and fuse the features, avoid the loss of small or blurred object information, and precisely locate the object position from SAR images. We conducted experiments on the SAR ship dataset SSDD, and achieved a 90.3% mAP and fast inference speed close to that of the original SSD. We also tested our model on the remote sensing dataset NWPU VHR-10 and the common dataset VOC2007. The experimental results indicate that our proposed model simultaneously achieves excellent detection performance and high efficiency.

scholarly journals Determination of Internal Waves Off the Coast of Morocco According to Earth Remote Sensing Data

2020 ◽  
pp. short24-1-short24-7
Author(s):  
Tatyana Tatarnikova ◽  
Irma Martyn ◽  
Sergey Stepanov ◽  
Yaroslav Petrov ◽  
Artem Sidorenko
Keyword(s):  
Remote Sensing ◽  
Wave Packet ◽  
Synthetic Aperture Radar ◽  
Internal Waves ◽  
Remote Sensing Data ◽  
Synthetic Aperture ◽  
Northern Coast ◽  
Sensing Data ◽  
Periodic Linear ◽  
Aperture Radar

This paper presents the results of a study of the internal wave isolation of the Northern coast of Morocco using synthetic aperture radar (SAR) images. A filter is applied to the remote sensing data to reduce the image grain, after which the direction of propagation of the wave is determined and its length is calculated. In most cases, internal waves appear on satellite images as quasi-periodic linear structures whose brightness is lower or higher than the background, which is well registered in the visible range and by synthetic aperture radar. When analyzing images off the coast of Morocco, internal waves were detected, the wave packet propagates in the direction from West to East. When comparing the obtained images with the bottom relief map, it can be assumed that the generation of internal waves is caused by the roughness of the bottom near the Northern coast of Morocco. The maximum wave length in the wave packet is almost 0.7 km, consists of at least 5 solitons, the prints of these solitons in the sea roughness area are visible in the images mainly in the Central part of a wave packet, the distance between a wave packet solitons is different. The wavelength decreases when moving to the back of a wave packet, which can be traced by changing the contrast on the site. As a result, internal waves were detected off the Northern coast of Morocco in rads images with a synthesized aperture, and the main characteristics of these waves were determined.

scholarly journals Ship Detection Based on Information Theory and Segmentation from Synthetic Aperture Radar (SAR) Images

2020 ◽  
Vol 8 (6) ◽  
pp. 2513-2517
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Satellite Images ◽  
Synthetic Aperture ◽  
Morphological Operations ◽  
Sar Images ◽  
Ship Detection ◽  
Radar Images ◽  
Vessel Detection ◽  
Aperture Radar

Ship detection is a procedure which asserts in fields such as ocean and sea management, vessel detection, marine superintendence, and rein, and also can be applied to exclude extralegal actions. Remote sensing can be utilized as a potential tool for zonular and universal monitoring to attain the forenamed goals. Among the radar images, the precious datum from Synthetic Aperture Radar (SAR) is playing a serious duty in remote sensing. Howsoever, vessel detecting in heterogeneous and strong clutter is still a question in this regard. The letter points to a ship detection scheme for SAR images exploiting a segmentation-based morphological operation using entropy. In the presented scheme, the morphological operations are adopted to intercept the background and foreground in the satellite images. The method was implemented and tested on the homogenous, heterogeneous and strong clutter SAR images and the results are promising and showing that the proposed method can improve the vessel detection from homogenous and heterogeneous and strong clutter satellite images

scholarly journals FUSING OF OPTICAL AND SYNTHETIC APERTURE RADAR (SAR) REMOTE SENSING DATA: A SYSTEMATIC LITERATURE REVIEW (SLR)

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 127-138
Author(s):  
S. Mahyoub ◽  
A. Fadil ◽  
E. M. Mansour ◽  
H. Rhinane ◽  
F. Al-Nahmi
Keyword(s):  
Remote Sensing ◽  
Literature Review ◽  
Synthetic Aperture Radar ◽  
Image Fusion ◽  
Systematic Literature Review ◽  
Remote Sensing Data ◽  
Synthetic Aperture ◽  
Sensing Data ◽  
Aperture Radar ◽  
Sar Remote Sensing

<p><strong>Abstract.</strong> Remote sensing and image fusion have recognized many important improvements throughout the recent years, especially fusion of optical and synthetic aperture radar (SAR), there are so many published papers that worked on fusing optical and SAR data which used in many application fields in remote sensing such as Land use Mapping and monitoring. The goal of this survey paper is to summarize and synthesize the published articles from 2013 to 2018 which focused on the fusion of Optical and synthetic aperture radar (SAR) remote sensing data in a systematic literature review (SLR), based on the pre-published articles on indexed database related to this subject and outlining the latest techniques as well as the most used methods. In addition this paper highlights the most popular image fusion methods in this blending type. After conducting many researches in the indexed databases by using different key words related to the topic “fusion Optical and SAR in remote sensing”, among 705 articles, chosen 83 articles, which match our inclusion criteria and research questions as results ,all the systematic study ‘ questions have been answered and discussed.</p>

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