Journal of the Indian Society of Remote Sensing最新文献

{"title":"Moon-Based Monitoring of the Earth’s Energy Imbalance and Climate, Near-Earth Asteroids and Comets, Potentially Habitable Exoplanets, Supernovae and Novae","authors":"Habibullo Abdussamatov","doi":"10.1007/s12524-024-01971-6","DOIUrl":"https://doi.org/10.1007/s12524-024-01971-6","url":null,"abstract":"<p>High-precision data on the Earth’s energy imbalance (EEI) require the creation of long-term fixed space platforms at a sufficient distance from the Earth. The Lunar Observatory (LO) is a single system of two identical special optical robotic telescopes installed along the equator at the opposite edges of the Moon, functioning sequentially as a single telescope. LO provides monitoring of the energy flux of the share of the total solar irradiance (TSI) reflected by the planet within the range of 0.2-4 micron and the outgoing intrinsic thermal radiation of the Earth within the ranges of 4–50 and 8–13 micron continuously during more than 94% of the lunar day. All these data will make it possible to calibrate and determine the dependence of the absolute value of the annual average EEI on cyclical TSI variations, which serves as a reliable indicator for reconstruction EEI variations for the total period of high-precision space TSI measurements since 1978. This will make it possible to reliably reveal the physical mechanisms of formation, reasons, and regularities of climate change on our planet. In the time free of the observations of the Earth LO will also produce a continuous all-sky survey: coordinate-photometric monitoring and study of near-Earth asteroids and comets, particularly moving from the side of the Sun, and also of exoplanets, supernovae and novae within the range of 0.2-2 micron and in its three individual broad bands.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation Between Space Borne Night-Time Light Data and Seismic Activity in Mountainous Region of Shughnon, Tajikistan","authors":"Mathur Mudit, Sanjay Bhatia, Praveen K Thakur, Prakash Chauhan","doi":"10.1007/s12524-024-02000-2","DOIUrl":"https://doi.org/10.1007/s12524-024-02000-2","url":null,"abstract":"<p>The seismically active Shughnon district of the central-western part of the Gorno-Badakhshan Autonomous Region of Tajikistan nestled within the Pamir Mountain range, has experienced a significant number of seismic events of moderate to strong magnitude (&gt; 4.0 to 6.8<i>M</i>_w) in the last decade. A deeper understanding and investigation of aftershock patterns and any potential seismic precursors is necessary for forecasting seismic hazards and its impact on human life, settlement and property. In this regard, utilization and correlation of night light disturbances data and night-time light emission anomalies against any pre- or post-seismic event offers a novel and unique approach to quantify the seismic impact on the mega cities especially situated in seismically active hilly and mountainous terrain. The study explores and examine the possible application of the Space borne night light imaging of Visible Infrared Imaging Radiometer Suite (VIIRS) as a potential tool for post-seismic impacts assessment and identification of any potential precursors or patterns of seismic activity and its impact on the mega city of Shughnon, Tajikistan. A retrospective analysis of VIIRS data cross-referencing with available historical seismic records of an eleven-year period (from 2012 to 2023) was evaluated and quantified by observing the variations in night light patterns and emission anomalies. About 15% reduction in night light brightness observed prior to three earthquakes, potentially linked to preemptive power grid shutdowns, infrastructure damage and population displacement. Post-earthquake imagery indicated a 60% decrease in lit areas and Recovery progress was quantified by a gradual 5% monthly increase in night light brightness, signaling restoration efforts.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Sensing and GIS-Based Landslide Susceptibility Mapping in a Hilly District of Bangladesh: A Comparison of Different Geospatial Models","authors":"Saiful Islam Apu, Noshin Sharmili, Md. Yousuf Gazi, Md. Bodruddoza Mia, Shamima Ferdousi Sifa","doi":"10.1007/s12524-024-01988-x","DOIUrl":"https://doi.org/10.1007/s12524-024-01988-x","url":null,"abstract":"<p>Landslide is a common hazardous phenomenon in Bangladesh’s hilly areas, and Khagrachari is one of the regions that face frequent causalities due to landslide events. The present study has utilized the analytical hierarchy process (AHP) based multi-criteria evaluation techniques, frequency ratio (FR), modified frequency ratio (MFR), and information value method (IVM) approaches in the GIS environment to identify the landslide susceptible zones. The study uniquely employed 12 distinct parameters in this region to prepare the landslide susceptibility index (LSI) map of Khagrachari. The six unique LSI maps have been produced by three classification approaches, i.e., Quantile, Equal Interval, and Natural Break for decision matrix, and three different statistical modeling to compare the result. We found that the most susceptible zones of the Khagrachari district are Matiranga, Khagrachari Sadar, and Dighinala Upazila. The higher susceptibility has been primarily contributed by moderate-higher slope angle (14°–68°), high relative relief (176–601 m), geological structures, spares to moderate vegetation indices, and a high percentage of soil moisture (35–65%). Considering the classification approaches, around 9% of the area (~ 676 km²) is classified as a very high-hazard zone. In addition, we suggest that the MFR geospatial model has better prospects than IVM, AHP, and FR, as ~ 40% of the susceptible areas include more than 80% of the total landslide areas for the modified frequency ratio model. This study emphasizes the importance of implementing specific initiatives and activities to minimize landslide risks in Khagrachari. In addition, the present study installs the groundwork for future research to enhance geospatial modeling techniques and allows for comparisons with neighboring areas, thus expanding our knowledge of landslide susceptibility in the Chittagong Hill Tracts and adjacent regions of the Bengal Basin.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Earthquake-Induced Vulnerability of Critical Infrastructure in Kahramanmaraş Using Geographic Information Systems and Remote Sensing Technologies","authors":"Mehmet Cetin, Ceren Ozcan Tatar, Yalcin Ozturk, Balca Agacsapan, Zahra Khoda Karimi, Mehtap Ozenen Kavlak, Muzeyyen Anil Senyel Kurkcuoglu, Ahmet Dabanli, Alper Cabuk, Tuncay Kucukpehlivan, Saye Nihan Cabuk","doi":"10.1007/s12524-024-01975-2","DOIUrl":"https://doi.org/10.1007/s12524-024-01975-2","url":null,"abstract":"<p>This study employs advanced technologies, specifically remote sensing (RS) and geographic information systems (GIS), to investigate the impact of earthquakes on critical infrastructure in Kahramanmaraş. Critical infrastructure encompasses physical and digital systems crucial for national security, economic stability, and public well-being. Disruption or failure of these interdependent systems, including energy, transportation, communication, water supply, healthcare, and emergency services, can have profound impacts on regional security and societal necessities. Protecting and prioritizing critical infrastructure during disaster response is vital for minimizing damage and expediting recovery. The study employs an innovative approach by integrating building damage assessment results with Point of Interest (POI) data to swiftly assess earthquake effects on critical infrastructure in Kahramanmaraş. Real-time earthquake vulnerability of 57 critical infrastructure elements in 15 POI categories is analyzed. Results indicate financial institutions and commercial areas as the most damaged POIs, while muster points exhibit the least damage. Historical facilities, health facilities, governmental institutions, road facilities, and sports facilities also show varying degrees of damage. Overall, 34% of critical infrastructure structures experienced damage. The proposed method offers a pragmatic approach for rapidly identifying damaged critical infrastructure POIs during disaster-based assessments, addressing a research gap.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"29 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Image Compression Technique and Secured Transmission of Compressed Satellite Images Via Optical Fiber Using 6D Hyper Chaos","authors":"Banhi Das, Arijit Saha, Somali Sikder","doi":"10.1007/s12524-024-01984-1","DOIUrl":"https://doi.org/10.1007/s12524-024-01984-1","url":null,"abstract":"<p>The present work proposes an efficient optical transceiver system for secured transmission of compressed satellite images. However, most of the reported techniques fail to achieve a good balance between the compression ratio and Peak Signal to Noise (PSNR) value of the restored image maintaining system robustness against illegal eavesdropping at the same time. To improve these weaknesses, we have introduced an encryption technique combining 6D hyperchaotic sequence with random number controlled by the designed logic circuit for enciphering images before transmission. To optimize the transmission bandwidth through the optical channel, the Modified Run Length Encoding and decoding compression-decompression algorithm is used which is proven to provide a better compression ratio in comparison to existing methods. Furthermore, efficient restoration of the transmitted image with a sufficiently high PSNR and an appropriate correlation coefficient are the two crucial aspects of any authentication-based image compression technique addressed in this communication. The results are examined in terms of correlation parameter, PSNR, information entropy, histogram analysis, key sensitivity analysis, key space analysis, differential analysis and compression ratio. Robustness of the cryptosystem is verified by Known Plaintext Attack (KPA), Chosen Plaintext Attack (CPA), Chosen Ciphertext Attack (CCA), cropping attack and noise attack. Randomness of the bit stream generated by the cryptosystem is tested by the NIST SP 800-22 Randomness Test Suite. Simulation results show that the proposed technique is efficient enough for proper recovery of images with very high PSNR and correlation coefficient of value 1. The compression ratio achieved by our proposed technique is 2.008, which is proven to be much better as compared to contemporary lossless compression techniques.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"15 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Oil Spill Pollution over the North Eastern Arabian Sea Using EOS-04 C-Band SAR Data","authors":"M. Swapna, S. Rajesh, R. K. Nayak, P. V. Nagamani, Rajashree V. Bothale, G. Srinivasa Rao, Prakash Chauhan","doi":"10.1007/s12524-024-01991-2","DOIUrl":"https://doi.org/10.1007/s12524-024-01991-2","url":null,"abstract":"<p>The North Eastern Arabian Sea (NEAS) is one of the regions highly vulnerable to oil spill pollution due to massive shipping activity, international oil tanker routes, and oil rig operations. Recent studies have indicated that Bombay High Field, located in the NEAS, significantly contributes to oil spill pollution into the sea. This study pioneers the utilization of ISRO’s EOS-04 SAR data in assessing the oil pollution in the NEAS. We also tested the performance of various speckle filters for reducing speckle noise in the EOS-04 data with an oil spill event. We found that the Medain speckle filter performed better and additionally, demonstrated an example of EOS-04 oil-spill look-alike case over the Bombay High region. An inter-sensor comparison of EOS-04 against Sentinel-1 A is also carried out to evaluate the performance of EOS-04 in mapping the ocean features of oil spills and ships. Subsequently, a time series data of EOS-04 from March 2022 to November 2023 is used to quantitatively estimate the oil pollution due to oil leaks in each month in terms of spill area and volume. The distribution of oil pollution in terms of spreading area is high in October 2023 with 556 sq km (25.25%) and very low in August 2023 with 6.79 sq km (0.31%). During the study period, we estimated the total surface contamination of oil pollution to be 2193 sq km and oil released is around 435.35 tons. This study emphasizes the need to regularly monitoring and safeguard the marine environment from the unaccounted and unreported oil entering the Arabian Sea from the Bombay High Region.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"3 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determining Variable Rate Fertilizer Dosage in Forage Maize Farm Using Multispectral UAV Imagery","authors":"Nikrooz Bagheri, Maryam Rahimi Jahangirlou, Mehryar Jaberi Aghdam","doi":"10.1007/s12524-024-01976-1","DOIUrl":"https://doi.org/10.1007/s12524-024-01976-1","url":null,"abstract":"<p>This research aimed to evaluate the capability of the combination of aerial UAV multispectral imagery and an equation-oriented approach for monitoring nitrogen status and variable-rate nitrogen fertilizer management in forage maize farms. To achieve this goal, four levels of nitrogen fertilizer were applied in a randomized complete block design (0, 50, 100, and 150%) in eight-leaf and tasseling growth stages. A method based on the biomass of aerial organs and leaf nitrogen content was used to estimate variable rate nitrogen application. Among vegetative indices extracted from aerial images, the correlation between the Normalized Difference Vegetation Index (r = 0.77, <i>P</i> ≤ 0.01), Nitrogen Reflectance Index (r = 0.70, <i>P</i> ≤ 0.01) and Modified Triangular Vegetation Index2 (r = 0.67, <i>P</i> ≤ 0.01) with leaf nitrogen content were positive and significant at the eight-leaf growth stage. Similarly, the Normalized Difference Vegetation Index (r = 0.77, <i>P</i> ≤ 0.01), Nitrogen Reflectance Index (r = 0.87, <i>P</i> ≤ 0.01) and Modified Triangular Vegetation Index2 (r = 0.66, <i>P</i> ≤ 0.01) had a high correlation with the leaf nitrogen content at the tasseling growth stage. Based on the obtained results, a total of 223, 192, 173, and 100 kg/ha urea fertilizer were estimated to be applied in 0, 50, 100, and 150% nitrogen fertilizer plots, respectively. Findings suggested that the nitrogen changes and nitrogen rate needed to apply were detected by aerial multispectral imagery with good accuracy.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised Multispectral Gaussian Mixture Model-Based Framework for Road Extraction","authors":"Elaveni Palanivel, Shirley Selvan","doi":"10.1007/s12524-024-01972-5","DOIUrl":"https://doi.org/10.1007/s12524-024-01972-5","url":null,"abstract":"<p>The inherent composition of roads and buildings project spectral and hierarchically similar characteristics in remote-sensing images. Gray values of both background pixels and roads overlap when a large area of a remote-sensing image is considered. As a consequence, segmenting road networks and buildings in an urban environment presents critical challenges. So far, the literature suggests that supervised algorithms outperform their unsupervised counterparts when it comes to segmenting roads and buildings. However, supervised algorithms require a massive database in the training stage. This can cause a bottleneck as the percentage of pixels in urban remote sensing images depicting roads is very low when compared to the background. Index integrated spatially constrained Gaussian Mixture model (IISC-GMM), a novel unsupervised algorithm that overcomes the aforementioned constraints by integrating a Morphological Building Index (MBI) mask with a novel Gaussian mixture model (GMM) is proposed. To better distinguish foreground from background pixels, this novel algorithm blends localized spatial smoothness of neighboring pixels with spectral information. The gaps in the road network are eliminated by applying path morphology. The algorithm generates a Dice coefficient of 80.00%, a Completeness of 77.41%, a Correctness of 82.75%, a Quality of 73.80%, and a Misclassification rate (MCR) of 11.36% when validated on the Massachusetts Road dataset. In addition to being faster and less computationally intensive, the results obtained by IISC-GMM are comparable to those obtained by the computationally intensive Deep Learning methods.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"33 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lithological Discrimination of Parts of the Bhukia Area, Banswara District, Rajasthan Using Hyperspectral Data","authors":"Ashutosh Rohta, Richa Upadhyay Sharma, Shovan L. Chattoraj","doi":"10.1007/s12524-024-01955-6","DOIUrl":"https://doi.org/10.1007/s12524-024-01955-6","url":null,"abstract":"<p>In developing countries, exploration and exploitation of mineral resources help create the infrastructure that can sustain the population and economic growth. Remote sensing makes a brilliant tool to boost this growth. Hyperspectral Remote Sensing has been a key technology in mineral exploration and mapping for some time now. In this study, Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRIS-NG) data with the high spatial and spectral resolution was deployed to map the metasedimentary rocks in parts of the Bhukia region of Banswara district, Rajasthan. Similarly, PRecursore IperSpettrale della Missione Applicativa (PRISMA) data is also utilized to achieve a similar goal. The rock spectra obtained from both the surface reflectance hyperspectral datasets after applying the processing techniques were compared against the USGS spectral library and the field/ laboratory spectra to identify the diagnostic spectral features. The spectral Angle Mapper algorithm was applied to both datasets and detected limestone, dolomite, phyllite, and quartzite rocks. Furthermore, absorption band parameters were estimated and interpreted to corroborate the chemistry of the rock which helped in the identification of limestones based on Al³⁺/ Mg²⁺ content.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"6 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Stage Polsar Scattering Model-Based Classification Scheme for Improved Glacier Facies Mapping","authors":"Ruby Panwar, Amit Kumar, Praveen Kumar","doi":"10.1007/s12524-024-01966-3","DOIUrl":"https://doi.org/10.1007/s12524-024-01966-3","url":null,"abstract":"<p>Variations in glacier facies may signify the glacier’s response to the surrounding climate, and continuous monitoring of glacier facies can reveal a lot about the glacier’s behavior and stability. The swift development of remote sensing and the handiness of polarimetric SAR data has gained popularity for monitoring glaciers and their dynamics. We used ALOS-1/PALSAR-1 L-band data over the Siachen glacier in the Karakoram Himalayan region for this study. For glacier facies/zones classification, we employed a two-stage scattering model-based SVM classification scheme for improved glacier facies mapping. Results showed that two-stage classification using 6SD-SVM is effective, with a kappa coefficient of 0.82 and an overall accuracy of 87.58%. Integration of scattering-based polarimetric information extends a new dimension in glaciated terrain classification, and generates enhanced accuracy in classified images. Even though the employed technique produces satisfactory results, but classes for mid- &amp; low-percolation and debris cover are misclassified. To further clear up any ambiguity between the aforementioned classes, the probability difference between surface and volume backscattering has been added as a second step in the second stage of the classification process. In comparison, 6SD-SVM outperforms the backscatter [T]-SVM classification and the overall accuracy is enhanced by 7%.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"283 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}