Analysis Of Satellite Imagery Research Articles

Prolonged and gradual recovery of metazoan-algal reefs following the end-Permian mass extinction

The tempo of biotic recovery following extinction reflects the time scales of evolutionary processes and the long-term consequences of degraded ecosystems, but recovery patterns are poorly resolved. In this study, we investigated the tempo of biotic recovery by evaluating metazoan-algal reef assembly following the end-Permian mass extinction. We combined satellite imagery analysis, field mapping, biostratigraphy, and quantitative petrography to assess recovery in the oldest-known and most stratigraphically extensive Lower to Middle Triassic platform-margin reef. The reef occurs in upper Spathian (upper Lower Triassic) to upper Anisian (lower Middle Triassic) strata of the Great Bank of Guizhou (GBG) isolated carbonate platform in south China. Previous work suggests that metazoan-algal reefs were absent for 8−10 m.y. following extinction but were biologically diverse from their Pelsonian (middle Anisian) initiation. This pattern implies that reefs can reassemble rapidly (<< 1 m.y.) when environmental conditions are favorable. In contrast, our analyses indicate that calcareous sponges, calcareous algae, and early scleractinian corals occurred progressively in the GBG reef and that biotic recovery metrics increased gradually. Unlike nonreef ecosystems, biodiverse metazoan-algal reefs were delayed until the late Pelsonian or early Illyrian, postdating broader marine ecosystem recovery and isotopic evidence for carbon-cycle stabilization by 2−4 m.y. Our findings suggest that reef and nonreef ecosystems differ in their recovery pattern and tempo. Reef recovery from severe environmental perturbation can require several million years, even after hospitable conditions return, highlighting the importance of modern reef conservation.

Typology of planned housing in the city of Yogyakarta

This paper examined the planned housing in Yogyakarta City distributed in eight sub-districts, namely Umbulharjo, Tegalrejo, Wirobrajan, Mergangsan, Mantrijeron, Kotagede, Gondokusuman, and Jetis. Planned housing in Yogyakarta City can be classified into a gated community and a non-gated community. They were commonly identified based on the similarity and regularity of the buildings and the road network. The data was taken from their Building Permit (IMB; Izin Mendirikan Bangunan) from the year 2000 – 2019, Google Street View, Pleiades Satellite Imagery of Yogyakarta City in 2018, Google Map, and ArcMap base-map. Data analysis was undertaken by using satellite imagery, map interpretation, and quantitative analysis by using scoring technique to describe the score of typology. Most of the planned housing in Yogyakarta City are classified into Typology II, which had a medium-strength gated community characteristic. The typology was composed based on the physical-geographical and social-economic indicators. Most of them were more than 10 years old and were provided with walls/fences and portals to restrict outsiders’ access. The residents were classified into middle-class based on their social-economic status. Most of the planned housing in Yogyakarta have gated-community characteristics based on these features.

What is the extension of bench terrace construction for forest plantations? The case of North Central Portugal

AbstractOver the last decades, the establishment of new fast‐growing forest plantations has been prospering. Although the European continent has the lowest share worldwide of forest plantations out of its total forest area, the Portuguese reality contrasts this. Since the last century, eucalypt plantations have increased widely in Portugal, and nowadays, it represents 36% of the total country's forests. Consequently, the soils of these plantations are commonly targeted with intensive soil mobilization by heavy machinery before planting, which in the case of sloped areas, frequently results in bench terracing. This study aims to quantify the widespread bench terracing implementation over the last 20 years in the Caramulo Mountains in north central Portugal. To do so, an analysis of satellite imagery was performed with Google Earth Pro, which allowed determining the coverage of forest areas where new terraces have been implemented, and their respective temporal dynamics. These results were then compared with additional spatiotemporal databases on land cover, topography, and bedrock, in order to understand the drivers of terrace implementation. Till date, 15% of the forest area in the mountains of Caramulo is under terraces, and over the last 20 years, the construction rate of new terraced land decreased in time, from 4% between 2000 and 2004 to 2% between 2015 and 2019. Among the two bedrock types existent in the area, terracing was found nearly exclusive over schist bedrock type (97%), while few areas were implemented over granites (3%). Their distribution was found limited above 30° of slope angle while 39% were found implemented below 15° of slope angle, conflicting with literature recommendations. Terracing was also found to be a driver of land cover change in 12% of the newly constructed terraces, whereas 8% were constructed over previous pine plantations and 4% on shrublands. This study allowed identifying several knowledge gaps associated with terracing implementation. Therefore, the authors of this work suggest a multidisciplinary approach when planning new terraces for a better assessment of the benefits and impacts of such land management practices.

Urban land policy and urban land use efficiency: An analysis based on remote sensing and institutional credibility thesis

Ethiopia has an urban land lease policy in place to facilitate the transfer of land for residential, commercial and industrial purposes. Because of the lease policy, many cities have experienced significant expansion through massive conversion of agricultural land. Although the lease policy has been in place for nearly three decades, little is known about its effectiveness in promoting sustainable urban land use. This paper examines the effects of the lease policies on urban land use efficiency (ULUE). Building on the institutional credibility thesis, this paper investigated the performance of land institutions using the urban land use efficiency approach. Remote sensing data was used to investigate urban land use efficiency through spatiotemporal analysis of land use change. Analysis of satellite imagery was performed using ArcGIS. Moreover, quantitative and qualitative data from secondary sources were studied. The study findings show that in almost all study areas, urban land use efficiency is low, which is mainly reflected in the forms of land hoarding, land banking, illegal land grabbing, informal settlement, land use fragmentation and urban sprawl. A significant portion of the land transferred for various urban uses has remained vacant or underutilised for years, in direct violation of the provisions of the lease policy. This means that the lease policy has hardly been enforced to ensure efficient urban land utilization. This demonstrates the ineffectiveness (dysfunctionality) of the existing land institutions. It is concluded that some elements of the lease policy have evolved into an empty institution, i.e., a symbolic institutional arrangement that is largely ignored by socioeconomic and political actors.

Field path optimization to reduce headland and turning maneuvers at regional scales: automated detection of cultivation direction in the state of Brandenburg, Germany

Path planning for optimized field-work pattern is an important task within precision farming. The decision on a particular direction and path to cultivate and manage the field is complex and can significantly affect working time, energy consumption, soil compaction and yield. This study proposed a new method for automated detection of the current cultivation direction of several thousands of agricultural fields and compared the current cultivation direction with an optimized cultivation direction generated from a path planning algorithm. Airborne imagery from 2019 was analyzed using a modified Gabor filter. The identification takes place on a sub-plot level and can therefore detect small-scale differences in cultivation direction within fields. The method for identification of current cultivation direction had a high success rate of 87.5%. Fields with a high potential to save turning maneuvers and to reduce the area of headland were identified. From 3410 fields, a total of 58162 turning maneuvers and 507 ha headland were saved. This corresponds to 14.1% of all turning maneuvers and 7.6% of the total headland area for all analyzed fields in Brandenburg. A high optimization potential was demonstrated for field paths when efficient processing directions are taken into account. The method can be extended to the analysis of satellite imagery and thus offers the possibility of identifying current cultivation directions with a high spatial and temporal resolution. In future, this knowledge can be embedded within decision support systems for real-time optimization of field machinery path planning to support sustainable cropping practices.

Hydrological Dynamics of the Pantanal, a Large Tropical Floodplain in Brazil, Revealed by Analysis of Sentinel-2 Satellite Imagery

Extensive tropical floodplain wetlands, such as the Brazilian Pantanal, are complex ecosystems composed of mosaics of permanently and seasonally flooded habitats and are increasingly threatened by land use and climate change. Spatial and interannual variability in the seasonal flood pulse is a fundamental ecological driver in these ecosystems. This study analyzes optical imagery from the Sentinel-2 satellite to determine the extent and seasonal patterns of inundation over five years in the northern Pantanal, a Ramsar site renowned for its wildlife. The study site is bordered by the Cuiabá and São Lourenço rivers, each with distinct flow regimes. Inundation patterns were revealed with a combination of water indices, supervised classification of land cover, and a digital elevation model. Total extent of flooding was underestimated by the optical imagery, but open water bodies were readily delineated with the land cover classification.

The radiation shielding proficiency and hyperspectral-based spatial distribution of lateritic terrain mapping in Irikkur block, Kannur, Kerala

The practice of identifying the potential zones for mineral exploration in a speedy and low-cost method includes the use of satellite imagery analysis as a part of remote sensing techniques. It is challenging to explore the iron mineralization of a region through conventional methods which are a time-consuming process. The current study utilizes the Hyperion satellite imagery for mapping the iron mineralization and associated geological features in the Irikkur region, Kannur, Kerala. Along with the remote sensing results, the field study and laboratory-based analysis were conducted to retrieve the ground truth point and geochemical proportion to verify the iron ore mineralization. The MC simulation showed for shielding properties indicate an increase in the linear attenuation coefficient with raising the Fe2O3+SiO2 concentrations in the investigated rocks where it is varied at 0.662 MeV in the range 0.190 cm−1- 0.222 cm−1 with rising the Fe2O3+SiO2 content from 57.86 wt% to 71.15 wt%. The analysis also revealed that when the γ-ray energy increased from 0.221 MeV to 2.506 MeV, sample 1 had the largest linear attenuation coefficient, ranging from 9.33 cm−1 to 0.12 cm−1. Charnockite rocks were found to have exceptional shielding qualities, making them an excellent natural choice for radiation shielding applications.

Time-series analysis of satellite imagery for detecting vegetation cover changes in Indonesia

Indonesia has one of the world’s largest tropical forests; thus, its deforestation and environmental degradation are a global concern. This study is the first to perform comprehensive big data analyses with coherent vegetation criteria to measure the vegetation change at a high temporal resolution (every 16-day period) for 20 years and the high administrative resolution (regency or city) all over Indonesia. The normalized difference vegetation index (NDVI) of the Moderate Resolution Imaging Spectroradiometer is analyzed through state space modeling. The findings reveal that the NDVI increases in almost all regencies, except in urban areas. A high correlation between the NDVI change and the time is observed in Sumatra, Papua, and Kalimantan. The gain of the NDVI values is obvious in the Central and Eastern Java Island. Human activities, such as the expansion of agriculture and forestry and forest conservation policies, are the key factors for the observed pattern.

SPATIAL ANALYSIS OF MANGROVE DENSITY AND ITS EFFECT ON MACROZOOBENTHOS IN TEKKOLABBUA, SOUTH SULAWESI.

This study aims to detect changes in mangrove cover using 30-meter resolution Landsat imagery in 2019 and 2021 and analysis of changes in density to macrozoobenthos abundance. The research method used is the analysis of satellite imagery with NDVI transformation integrated with field surveys, the relationship between mangrove density and abundance of macrozoobenthos was tested by regression analysis. The results showed that in 1 decade (2009-2021) there was an improvement in the quality of the mangrove ecosystem with an increase in the cover of the mangrove ecosystem by 5.49 Ha, which was accompanied by an increase in mangrove density. Improvement of ecosystem conditions also affects the increase in the abundance of macrozoobenthos in substrates, roots, and stems in mangrove ecosystems even though with a small coefficient of determination.

AiTLAS: Artificial Intelligence Toolbox for Earth Observation

We propose AiTLAS—an open-source, state-of-the-art toolbox for exploratory and predictive analysis of satellite imagery. It implements a range of deep-learning architectures and models tailored for the EO tasks illustrated in this case. The versatility and applicability of the toolbox are showcased in a variety of EO tasks, including image scene classification, semantic image segmentation, object detection, and crop type prediction. These use cases demonstrate the potential of the toolbox to support the complete data analysis pipeline starting from data preparation and understanding, through learning novel models or fine-tuning existing ones, using models for making predictions on unseen images, and up to analysis and understanding of the predictions and the predictive performance yielded by the models. AiTLAS brings the AI and EO communities together by facilitating the use of EO data in the AI community and accelerating the uptake of (advanced) machine-learning methods and approaches by EO experts. It achieves this by providing: (1) user-friendly, accessible, and interoperable resources for data analysis through easily configurable and readily usable pipelines; (2) standardized, verifiable, and reusable data handling, wrangling, and pre-processing approaches for constructing AI-ready data; (3) modular and configurable modeling approaches and (pre-trained) models; and (4) standardized and reproducible benchmark protocols including data and models.

Pemetaan Habitat Burung Air Berdasarkan Analisis Citra Satelit di Hutan Mangrove Cagar Alam Pulau Dua, Banten

Waterbirds are birds that live around the coast that use migration sites to carry out life activities. This research was conducted in 2022, aiming to determine the condition of waterbird habitat, mapping waterbird habitat, and the relationship between the results of satellite imagery analysis and the presence of waterbirds in the mangrove forest of Pulau Dua Nature Reserve. The research method used is the point count or index point of abundance (IPA) method to determine the habitat conditions of waterbirds and remote sensing methods using Google Earth Engine (GEE) satellite imagery. The results of the study showed that waterbirds are mostly active in wetland areas. The mapping results from the MNDWI (Modified Normalized Difference Water Index) analysis obtained negative results because the detected land is not a body of water and the surrounding area is overgrown with vegetation, it can be said that the results are negative due to air mixing with other objects. Mapping results from MSAVI (Modified Soil Adjusted Vegetation Index) analysis were obtained with a range of 0.3-0.4 which indicates moderate vegetation conditions. The correlation result of the water presence (MNDWI) with the presence of waterbirds have a value of r = 0.944 belong to the category of very strong relationship and the correlation result of the land presence (MSAVI) to the presence of waterbirds have a value of r = 0.537 belong to the category of strong relationship too. The results of this study can be implemented in education in the form of material analysis using KD. 3.10 and KD. 4.10 class X high school. Keywords: Google Earth Engine, Pulau Dua Nature Reserve, and Waterbird Habitat

Monitoring of forest management. Prediction of area change

The current problems of monitoring of the state and changes in areas of green plantings are considered. The assessment of dynamics of the distribution of forest park plantations would allow making decisions on taking appropriate measures for forest restoration or sanitary logging to maintain the areas of the “lungs of the city” at the appropriate level. The analysis of global trends in the use of GIS and remote sensing to study the situation with green plantings shows that this allows obtaining up-to-date and reliable information promptly. Namely, it enables quick monitoring of ecological aspects on large areas and significantly speeds up taking necessary measures, if necessary. The available approaches to observe the tasks of monitoring of green areas are analysed. The existing problems of assessing the state of the forest park economy in complex environments such as cities are proposed to be solved by using software products such as ERDAS IMAGINE and ArcGIS for processing and further analysis of satellite imagery of the area. To solve the task of predicting the change in the forest park economy area over time, modelling linear regression is proposed using the built-in programming language in the ArcGIS. The developed application with an intuitive interface will provide an opportunity to conveniently work with databases and attribute information, graphics and images. The development includes five options for performing calculations, which allows analysing the results in each of the anticipated scenarios. All calculations were performed on the example of the Kharkiv Forest Park “Sokolniki-Pomirki”. An algorithm for processing and analysing satellite images was developed. The proposed algorithm can be applied to increase the speed of monitoring of the state of forests and predicting changes not only in Kharkiv, but also in other cities in Ukraine and worldwide. The paper demonstrates the capabilities of GIS for monitoring of green areas, which allow performing similar work with minimal time costs. Thus, the GIS product is promising at the current stage of observing changes in the areas of green plantings.

Surface Formations Salinity Survey in an Estuarine Area of Northern Morocco, by Crossing Satellite Imagery, Discriminant Analysis, and Machine Learning

The salinity of estuarine areas in arid or semi-arid environments can reach high values, conditioning the distribution of vegetation and soil surface characteristics. While many studies focused on the prediction of soil salinity as a function of numerous parameters, few attempted to explain the role of salinity and its distribution within the soil profile in the pattern of landscape units. In a wadi estuary in northern Morocco, landscape units derived from satellite imagery and naturalistic environmental analysis are compared with a systematic survey of salinity by means of apparent electrical conductivity (Eca) measurements. The comparison is based on the allocation of measurement points to an area of the estuary from Eca measurements alone, using linear discriminant analysis and four machine learning methods. The results show that between 57 and 66% of the points are well-classified, highlighting that salinity is a major factor in the discrimination of estuary zones. The distribution of salinity is mainly the result of the interaction between capillary rise and flooding by the tides and the wadi. The location of the misclassified points is analysed and discussed, as well as the possible causes of the confusions.

Pertanggungjawaban Negara China Akibat Pencemaran Di Laut China Selatan Dalam Prespektif Hukum Lingkungan Internasional

Introduction: One of the satellite imagery analysis companies, Head Of Simularty, based in the United States, found that there has been pollution to the marine environment in the South China Sea area, precisely in the Spratly Islands, namely the coral island of Whitsun Reef which is still part of the Exclusive Economic Zone of the Philippines.Purposes of the Research: Aims to find out and analyze the regulation of international law on pollution in the South China Sea and to find out and analyze the form of accountability of the Chinese State due to marine pollution carried out under international environmental law. Methods of the Research: This legal research uses normative juridical research, case approach, statutory approach, and conceptual approach, primary and secondary legal materials, legal material procedures using primary legal materials which are then associated with secondary legal materials and processing and analysis of legal materials using qualitative descriptive analysis.Results of the Research: The results showed that China had violated international environmental law obligations as stipulated in the Stockholm Declaration 1972, Rio Declaration 1992, UNCLOS 1982 and MARPOL 73/78. Furthermore, marine pollution carried out by the State of China in the territory of the Exclusive Economic Zone of the Philippine State has opposed the provisions of international environmental law as stipulated in the 1972 Stokcholm Declaration and UNCLOS 1982 which states that it prohibits any country from taking acts of pollution against the environment against both its own territory and in the jurisdiction of other countries. Therefore, it is necessary to have accountability efforts that must be carried out due to the pollution actions carried out.

Damage Model and the Influence Factors of Mitigation Engineering against Glacial Debris Flow in the Parlung River Basin, SE Tibetan Plateau

Understanding the damage mechanism of glacial debris flow mitigation systems is crucial for the risk prevention and assessment of the 200 km traffic corridor in the Southeast of the Tibetan Plateau, where the Sichuan-Tibet railway and expressway have been planned. Based on the phenomena, position and residual efficiency of damaged engineering, our analysis of satellite imagery and field investigation in multitype spatial reveals the damage types and influencing factors of glacial debris flow mitigation engineering. An evaluation model which can be used to estimate the engineering damage grade is established by using the relationship between mono engineering works and mitigation systems. In the new model, the engineering damage is divided into five grades: undamaged, slightly damaged, relatively damaged, seriously damaged, and totally damaged. For glacial debris flow in the Parlung river basin, the five grades of damage of mitigation works account for 8.70%, 34.78%, 21.74%, 13.04% and 21.74%, respectively. Furthermore, the soil source type and channel profile gradient are the key factors in engineering damage. Design defect of profile gradient is the controlling factor of damage in drainage channel engineering. Based on those results, an engineering damage model is established, which can provide an important reference for risk reduction and prevention of hazards due to the increasing development of traffic engineering.

Assessment of The Antropogenic Impact on Mangrove Ecosystem and Endemic Fauna in Muaragembong, Bekasi, West Java

The Muaragembong coast is degraded by anthropogenic factors such as pollution and ponds. The area that used to be a mangrove ecosystem is now experiencing abrasion. Trash trapped in the mangrove ecosystem also affects the ecosystem and its biodiversity. This research is descriptive in nature with the aim of knowing changes in mangrove areas through analysis of Landsat satellite imagery and identifying the causes of changes and impacts on endemic species. This research was conducted with the stages of literature study, analysis of satellite imagery in 2000, 2009, 2010, 2014, 2019 and 2020. Based on the analysis of satellite imagery, it was found that changes in mangrove area were confirmed with secondary data so that the factors that caused these changes were known. The results of the analysis show that the degradation of the mangrove ecosystem in 2017 was approximately 2800 ha and affected the existence of the Lutung Jawa (Trachypithecus auratus) as an endemic fauna in Muaragembong which inhabits the mangrove ecosystem on the north coast of Bekasi. It is currently estimated that there are no more than 50 present in the area, therefore the Lutung Jawa is considered a vulnerable species as cited in CITES Annex II 2008.

Three‐Dimensional Data Preparation and Immersive Mission‐Spanning Visualization and Analysis of Mars 2020 Mastcam‐Z Stereo Image Sequences

AbstractThe Mars 2020 Mastcam‐Z stereo camera investigation enables the generation of three dimension (3D) data products needed to visualize and analyze rocks, outcrops, and other geological and aeolian features. The Planetary Robotics Vision Processing framework “PRoViP” as well as the Instrument Data System on a tactical—sol‐by‐sol—timeframe generate 3D vision products, such as panoramas, distance maps, and textured meshes. Structure‐from‐motion used by the Advanced Science Targeting Toolkit for Robotic Operations (ASTTRO) “Landform” tool and long baseline stereo pipelines add to the 3D vision products' suite on various scales. Data fusion with textured meshes from satellite imagery and 3D data analysis and interpretation of the resulting large 3D data sets is realized by visualization assets like the Planetary Robotics Vision 3D Viewer PRo3D, the 3D Geographical Information System GIS CAMP (Campaign Analysis Mapping and Planning tool), the ASTTRO 3D data presentation and targeting tool, and the Mastcam‐Z planning tool Viewpoint. The pipelines' workflows and the user‐oriented features of the visualization assets, shared across the Mars 2020 mission, are reported. The individual role and interplay, complements and synergies of the individual frameworks are explained. Emphasis is laid on publicly available 3D vision data products and tools. A representative set of scientific use cases from planetary geology, aeolian activity, soil analysis and impact science illustrates the scientific workflow, and public data deployment modes are briefly outlined, demonstrating that 3D vision processing and visualization is an essential mission‐wide asset to solve important planetary science questions such as prevailing wind direction, soil composition, or geologic origin.

Diversified land conversion deepens understanding of impacts of rapid rubber plantation expansion on plant diversity in the tropics

Understanding the status and changes of plant diversity in rubber (Hevea brasiliensis) plantations is essential for sustainable plantation management in the context of rapid rubber expansion in the tropics, but remains very limited at the continental scale. In this study, we investigated plant diversity from 10-meter quadrats in 240 different rubber plantations in the six countries of the Great Mekong Subregion (GMS)—where nearly half of the world's rubber plantations are located—and analyzed the influence of original land cover types and stand age on plant diversity using Landsat and Sentinel-2 satellite imagery since the late 1980s. The results indicate that the average plant species richness of rubber plantations is 28.69 ± 7.35 (1061 species in total, of which 11.22 % are invasive), approximating half the species richness of tropical forests but roughly double that of the intensively managed croplands. Time-series satellite imagery analysis revealed that rubber plantations were primarily established in place of cropland (RPC, 37.72 %), old rubber plantations (RPORP, 27.63 %), and tropical forests (RPTF, 24.12 %). Plant species richness in RPTF (34.02 ± 7.62) was significantly (p < 0.001) higher than that in RPORP (26.41 ± 7.02) and RPC (26.34 ± 5.37). More importantly, species richness can be maintained for the duration of the 30-year economic cycle, and the number of invasive species decreases as the stand ages. Given diverse land conversions and changes in stand age, the total loss of species richness due to rapid rubber expansion in the GMS was 7.29 %, which is far below the traditional estimates that only consider tropical forest conversion. In general, maintaining higher species richness at the earliest stages of cultivation has significant implications for biodiversity conservation in rubber plantations.

Estimasi Simpanan Karbon Hutan Mangrove Menggunakan Citra (SAR) Synthetic Aperture Radar Sentinel -1 di Taman Hutan Raya Ngurah Rai,Bali

&#x0D; &#x0D; &#x0D; &#x0D; Taman Hutan Raya (Tahura) Ngurah Rai, Bali, is recorded to have a mangrove forest covering an area of 1,373.5 ha, which plays a role in absorbing carbon from the atmosphere. Carbon is stored in the form of biomass. The bigger the biomass, the bigger the carbon stock in it. Direct measurement of biomass in the field requires an expensive method, a relatively long time, and narrow area coverage. Nowadays, the weakness of measuring carbon stocks directly in the field can be overcome by remote sensing approaches, especially estimations from satellite imagery combined with geographic information systems (SIG). One of the images that can be used to estimate carbon stock is the Sentinel-1 Synthetic Aperture Radar (SAR) image. The aim of this research is to estimate biomass and carbon stocks based on SAR backscatter distribution. The method used is the analysis of satellite imagery combined with field data. Field data collection and above-ground biomass (AGB) calculations were carried out by taking 30 plots with a plot size of 10 x 10 m. The results showed that there was a correlation between the backscatter value of SAR images and AGB from field measurements (r = 0.59 and the AGB estimation model y = 57.42x + 1223.8, where y is biomass and x is backscatter), and the coefficient of determination R2 = 0.36. The estimation model developed next is used to calculate the overall AGB, which is then used to estimate the overall aboveground carbon storage.&#x0D; &#x0D; &#x0D; &#x0D;

Identifying Rip Channels Along RK Beach, Visakhapatnam Using Video and Satellite Imagery Analysis

Identifying Rip Channels Along RK Beach, Visakhapatnam Using Video and Satellite Imagery Analysis