Satellite Remote-sensing Techniques Research Articles

Assessment of smoke plume height products derived from multisource satellite observations using lidar-derived height metrics for wildfires in the western US

Abstract. As wildfires intensify and fire seasons lengthen across the western US, the development of models that can predict smoke plume concentrations and track wildfire-induced air pollution exposures has become critical. Wildfire smoke plume height is a key indicator of the vertical placement of plume mass emitted from wildfire-related aerosol sources in climate and air quality models. With advancements in Earth observation (EO) satellites, spaceborne products for aerosol layer height or plume injection height have recently emerged with increased global-scale spatiotemporal resolution. However, to evaluate column radiative effects and refine satellite algorithms, vertical profiles of regionally representative aerosol properties from wildfires need to be measured directly. In this study, we conducted the first comprehensive evaluation of four passive satellite remote-sensing techniques specifically designed for retrieving plume height. We compared these satellite products with the airborne Wyoming Cloud Lidar (WCL) measurements during the 2018 Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign in the western US. Two definitions, namely, “plume top” and “extinction-weighted mean plume height”, were used to derive the representative heights of wildfire smoke plumes, based on the WCL-derived vertical aerosol extinction coefficient profiles. Using these two definitions, we performed a comparative analysis of multisource satellite-derived plume height products for wildfire smoke. We provide a discussion related to which satellite product is most appropriate for determining plume height characteristics near a fire event or estimating downwind plume rise equivalent height, under multiple aerosol loadings. Our findings highlight the importance of understanding the sensitivity of different passive remote-sensing techniques on space-based wildfire smoke plume height observations, in order to resolve ambiguity surrounding the concept of “effective smoke plume height”. As additional aerosol-observing satellites are planned in the coming years, our results will inform future remote-sensing missions and EO satellite algorithm development. This bridges the gap between satellite observations and plume rise modeling to further investigate the vertical distribution of wildfire smoke aerosols.

Impact of land use and land cover dynamics on urban heat island in the Sunyani Municipality using satellite remote sensing

The rapid urbanization coupled with tremendous growth in population and built-up areas in the cities has led to issues associated with global climate change impacts such as urban heat islands. This study is concerned with the spatial impact of the dynamics of urbanisation on urban heat island (UHI) in the Sunyani Municipality using Satellite Remote Sensing techniques. Sunyani municipal is a growing area in Ghana with increasing population and urbanisation. Many people in Ghana are moving to settle in Sunyani for different purposes. In this process, vegetated areas have been converted to urban areas and this has led to a reduction in the vegetation cover and increased the urban temperature in the municipality. Therefore, there is a need for a study on how the dynamics in the land use and land cover (LULC) in the municipal are contributing to urban heat. The main aim of this research is to identify the impact of LULC dynamics on UHI using multi-temporal Landsat images from 2001 to 2021 with a 5-year epoch in the Sunyani Municipal. Landsat images acquired over Sunyani and its environs for the period from 2001 to 2021 with a 5-year epoch, were download freely from the USGS Earth Explorer website. These images were pre-processed in QGIS 3.16 using the Semi-automatic classification plugin (SCP). The pre-processed images were classified using the Random Forest (RF) algorithm. The supervised classification was done using the semi-automatic classification plugin in QGIS 3.16. This study considered two (2) classes (urban and vegetation). The thermal infrared bands of the Landsat images were used to compute the land surface temperature (LST) for each year, starting from 2001 up to 2021, at a 5-year interval. The standard deviation and mean LST were extracted and used to extract all the UHIs in the municipality. Regression analyses were used to determine the impact of LULC dynamics on LST and UHIs in the Sunyani Municipality. The analysis yielded a strong impact with an R-squared value of 75% and 77% for UHI and LST respectively. The vegetated covers yielded a strong negative correlation with UHIs while Urbanisation yielded a strong positive correlation with the intensity of UHIs. On the other hand, Vegetation reduced the intensity of UHIs in the municipality. This gives a clear understanding of how dynamics in urbanisation and vegetation are affecting UHIs in the Sunyani Municipality. A Linear model was developed for LULC dynamics, LST and UHIs in the Sunyani municipality. It was concluded that LULC dynamics have a strong impact on UHI. It is recommended that the environmental Agencies in the Municipality should ensure the protection of the vegetated areas as well as improve the green areas in the Municipality to minimize urban heat.

Footprints of Sedimentation on Loss of Reservoir Life using Satellite Remote Sensing Technique

Reservoir is the most important water storage systems especially in areas where groundwater potential is low which can be used for domestic, irrigation as well as industrial water supply. The sedimentation which is a natural phenomenon of settling sediment particles in a reservoir is observed to be enhanced with construction of dams due to change in flow dynamics. Sedimentation in a reservoir takes place in dead storage zone as well as in live storage zone causing reduction in useful capacity of reservoir over a period of time, thereby affecting the designed water supply planning. Sedimentation in live storage zone can be estimated using Remote Sensing Technique which will gives us synoptic view of a reservoir. Present study aimed at estimating a reduction in live storage capacity with the help of satellite imageries. For this, the Totladoh Reservoir which is situated on the boundary of Maharashtra and Madhya Pradesh, India has been selected for the study. Totladoh reservoir is situated in calc gneisses type of metamorphic rocks. Green and near-infrared bands were used to calculate the Normalized Difference Water Index (NDWI). The rate of siltation for Totladoh reservoir has been estimated for the period of 1982-2020 using LANDSAT 8 satellite imageries having 30 m spatial resolution. Percentage loss of live storage for year 2020 is found to be 17.63. Rate of Siltation in the reservoir is 1173 m3/km2/year which is more under prevailing conditions when compared to CWC values.

A novel method of identifying and analysing oil smoke plumes based on MODIS and CALIPSO satellite data

Abstract. Black carbon aerosols are the second largest contributor to global warming while also being linked to respiratory and cardiovascular disease. These particles are generally found in smoke plumes originating from biomass burning and fossil fuel combustion. They are also heavily concentrated in smoke plumes originating from oil fires, exhibiting the largest ratio of black carbon to organic carbon. In this study, we identified and analysed oil smoke plumes derived from 30 major industrial events within a 12-year timeframe. To our knowledge, this is the first study of its kind that utilized a synergetic approach based on satellite remote sensing techniques. Satellite data offer access to these events, which, as seen in this study, are mainly located in war-prone or hazardous areas. This study focuses on the use of MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) products regarding these types of aerosol while also highlighting their intrinsic limitations. By using data from both MODIS instruments on board Terra and Aqua satellites, we addressed the temporal evolution of the smoke plume while assessing lidar-specific properties and plume elevation using CALIPSO data. The analysis method in this study was developed to better differentiate between oil smoke aerosols and the local atmospheric scene. We present several aerosol properties in the form of plume-specific averaged values. We believe that MODIS values are a conservative estimation of plume aerosol optical depth (AOD) since MODIS algorithms rely on general aerosol models and various atmospheric conditions within the look-up tables, which do not reflect the highly absorbing nature of these smoke plumes. Based on this study we conclude that the MODIS land algorithms are not yet suited for retrieving aerosol properties for these types of smoke plumes due to the strong absorbing properties of these aerosols. CALIPSO retrievals rely heavily on the type of lidar solutions showing discrepancy between constrained and unconstrained retrievals. Smoke plumes identified within a larger aerosol layer were treated as unconstrained retrievals and resulted in conservative AOD estimates. Conversely, smoke plumes surrounded by clear air were identified as opaque aerosol layers and resulted in higher lidar ratios and AOD values. Measured lidar ratios and particulate depolarization ratios showed values similar to the upper ranges of biomass burning smoke. Results agree with studies that utilized ground-based retrievals, in particular for Ångström exponent (AE) and effective radius (Reff) values. MODIS and CALIPSO retrieval algorithms disagree on AOD ranges, for the most part, due to the extreme light-absorbing nature of these types of aerosols. We believe that these types of studies are a strong indicator for the need of improved aerosol models and retrieval algorithms.

Assessment of Reservoir Sedimentation using Satellite Remote Sensing Technique (SRS)

Assessment of Reservoir Sedimentation using Satellite Remote Sensing Technique (SRS)

Deserted Medieval Village Reconstruction Using Applied Geosciences

This study presents a new way to reconstruct the extent of medieval archaeological sites by using approaches from the field of geoinformatics. Hence, we propose a combined use of non-invasive methodologies which are used for the first time to study a medieval village in Romania. The focus here will be on ground-based and satellite remote-sensing techniques. The method relies on computing vegetation indices (proxies), which have been utilized for archaeological site detection in order to detect the layout of a deserted medieval town located in southwestern Romania. The data were produced by a group of small satellites (3U CubeSats) dispatched by Planet Labs which delivered high-resolution images of the Earth’s surface. The globe is encompassed by more than 150 satellites (dimensions: 10 × 10 × 30 cm) which catch different images for the same area at moderately short intervals at a spatial resolution of 3–4 m. The four-band Planet Scope satellite images were employed to calculate a number of vegetation indices such as NDVI (Normalized Difference Vegetation Index), DVI (Difference Vegetation Index), SR (Simple Vegetation Ratio) and others. For better precision, structure from motion (SfM) techniques were applied to generate a high-resolution orthomosaic and a digital surface model in which the boundaries of the medieval village of “Șanțul Turcilor” in Mașloc, Romania, can be plainly observed. Additionally, this study contrasts the outcomes with a geophysical survey that was attempted inside the central part of the medieval settlement. The technical results of this study also provide strong evidence from an historical point of view: the first documented case of village systematization during the medieval period within Eastern Europe (particularly Romania) found through geoscientific methods.

Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring

The lack of reference ground-based PM2.5 observation leads to large gaps in air quality information, particularly in many areas of the developing world. This study investigated a new solution for urban air-quality monitoring in regions with limited reference ground-based monitoring. We developed an observation-based method by combining satellite remote-sensing techniques and a newly established low-cost sensor network to estimate long-term PM2.5 concentrations over Krasnoyarsk, a highly industrialized Siberian city. First, a physical model was developed to estimate PM2.5 concentrations using satellite remote-sensing with the aid of ground-based meteorological and radiosonde observations. Observations from the ground-based sensor network were then used to calibrate the deviations in the satellite-derived PM2.5 concentrations. The results show that the satellite-based PM2.5 concentrations obtained by our physical model were in good agreement with the sensor observations (R = 0.78 on the monthly scale). The deviation in satellite-derived annual PM2.5 concentrations resulted from data restrictions that occurred at noon and data loss in winter were identified as 20% and 30%, respectively. The regional transport of smoke from forest wildfires increased PM2.5 concentration to 150 μg/m3 in the summer 2018. The average PM2.5 concentrations in the urban districts could reach 35 μg/m3, which far exceeded the World Health Organization air quality guideline. These results underscore the good ability of our new method to determine PM2.5 concentrations in regions with limited reference ground-based monitoring. Use of sensor and meteorological observations greatly improved satellite detection of PM2.5 concentration. In addition, our method has the potential for global application to improve determination of PM2.5 concentrations, especially in sparsely monitored regions.

Assessment of Sedimentation and Useful Life of Tehri Reservoir using Integrated Approaches of Hydrodynamic Modelling, Satellite Remote Sensing and Empirical Curves

The higher rate of sedimentation in reservoirs is one of the main concerns in sustainable reservoir management, which impairs the functional capacity of reservoirs that may lead to various environmental risks. Estimation of sedimentation rate and useful life of a reservoir using appropriate methods is imperative for sustainable management. This paper deals with the computation of sedimentation rate and useful life of Tehri reservoir of Bhagirathi river, in India, using hydrographic survey analysis, Hydrologic Engineering Center’s River Analysis System (HEC-RAS) modelling, satellite remote sensing (SRS) technique, and trap efficiency based empirical curve methods. The rate of sedimentation was found as 5.33 million cubic metres (MCM)/year based on hydrographic survey analysis from the data obtained for the years 2005, 2008 and 2013. Likewise, the mean annual rate of sedimentation was estimated to be 5.07 MCM/year and 5.75 MCM/year based on the HEC-RAS model and SRS techniques respectively. Brune’s method and Churchill’s method of trap efficiency were found to be inconsistent with the hydrographic survey results. The reservoir can be classified as Type III reservoir with respect to the sediment vertical distribution analysis. Changes in bathymetry obtained in the simulation studies showed that the Bhagirathi river’s 28–30 km reach would be most vulnerable to sedimentation problems. The estimated useful life of Tehri reservoir was found to be in the range of 160–180 years. The SRS technique and hydrodynamic model provided a better fit with the observed data.

The Impact of Building Thermal Anisotropy on Surface Urban Heat Island Intensity Estimation: An Observational Case Study in Beijing

The surface urban heat island intensity (SUHII) defined as the average temperature difference between urban and rural surfaces is mainly measured by satellite remote-sensing techniques. However, the satellite can only provide 2-D land surface temperature (LST) and not complete surface temperature (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> ) which integrates the horizontal and vertical urban surface temperatures. The thermal anisotropy is very much prominent in the urban system; therefore, T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> may be more important than the 2-D LST for SUHII study. Furthermore, the 3-D LST measurement of a real urban is limited. In this letter, we measured a building's 3-D surface temperatures in Beijing, China, and the roof temperature (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> ) was assumed as “satellite measurement.” The SUHII using T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> (SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> ) and T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> (SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> ), as well as air urban heat island intensity (AUHII) were compared. Results showed that: 1) the building's thermal anisotropy was evident with 18 K between roof and north wall at noon; 2) SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> during the day was actually a cold island, while SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> was a heat island, caused by the different diurnal variation of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> and T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> ; and 3) The SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roof</sub> has diurnal maximum value in daytime and minimum value in nighttime, which is opposite to AUHII. However, the diurnal pattern of SUHII_T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> is similar to AUHII which is like the shape of a spoon. This letter preliminarily explores the building's thermal anisotropy on SUHII and could be an important reference for urban SUHII study at microscale.

Satellite Measurement of GHG Emissions: Prospects for Enhancing Transparency and Answerability under International Law

AbstractRecent technological advancements are facilitating the use of satellite remote-sensing techniques for the measurement of atmospheric concentrations of greenhouse gas emissions. This article evaluates the potential for these satellite-enabled measurements to contribute to transparency and answerability for state emissions, with a focus on international space law and policy, and the Paris Agreement to the United Nations Framework Convention on Climate Change. We show that in the context of the international space governance framework, the dissemination of integrated emissions data sets has the potential to enhance public answerability for the mitigation performance of states. Under the Paris Agreement, there is scope for space-based measurement techniques to provide an independent data source to support verification activities for national emissions inventories, and for aggregated data to be utilized as part of the global stocktake under Article 14. There are, however, a number of impediments to translating these transparency gains into enhanced answerability for states’ emissions reduction pledges.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel.

On the potential of hand-held GPS tracking of fjord ice features for remote-sensing validation

ABSTRACTResearch on young thin sea ice is essential to understand the changes in the Arctic. But it is also the most challenging to investigate, both in situ and from satellites. If satellite remote-sensing techniques are developing rapidly, fieldwork remains crucial for the mandatory validation of such data. In April 2016, an Arctic fieldwork campaign was conducted at Kongsfjorden, Svalbard. This campaign provided an opportunity to combine various techniques to record the fjord ice properties ranging from local field sampling to broader ground-based and satellite radar remote sensing of the fjord. Tracking the boat used to access the field sites with hand-held GPS devices offered a good opportunity to map fjord ice and assess the limits of radar identification of small icebergs and thin ice. During 1 week, 17 icebergs and the thin ice edges in two different locations were mapped. The GPS tracks present a good agreement with the Radarsat-2 data analysis for one of the two ice edges. The second ice edge track only partly corresponds to the radar scene. Ice movement, recorded by a ground-based radar, is likely to explain this result. Grounded icebergs could be identified in both Radarsat-2 and ground-based radar.

Retrieval and analysis of precipitable water vapour based on GNSS, AIRS, and reanalysis models over Nigeria

ABSTRACTPrecipitable water vapour (PWV) retrieved from ground-based Global Navigation Satellite System (GNSS) stations over Nigeria from 2013 to 2014 is compared with PWV from a satellite remote-sensing technique (Atmospheric Infrared Sounder [AIRS]) and a global reanalysis model (ERA-Interim) over Nigeria. The PWV for AIRS and ERA-Interim was obtained from the respective data providers. PWV estimates from the different techniques were grouped into daily estimates and were matched and re-grouped into monthly and seasonal averages. The performance of the PWV techniques was evaluated using recommended indices by the World Meteorological Organization. All datasets gave a reasonable estimate of PWV when compared against GNSS at daily, monthly, and seasonal scales, the agreement between the various techniques was better at monthly and seasonal scales. In terms of bias, precision, accuracy, fitness, and reliability of measurement, ERA-Interim outperformed the other technique and could possibly be a complementary data source to GNSS PWV, although as a reanalysis, it cannot be used for meteorology. The AIRS night-time (or descending) retrieval was ranked next to the ERA-Interim; AIRS daytime (or ascending) retrieval agreed less with GNSS PWV when compared with ERA Interim and night-time AIRS. These results indicate that GNSS PWV as observed over the study area represents a remarkable dataset for further evaluation studies and serves as a useful source of humidity information to improve the water cycle in numerical weather models for varying applications in the region.

Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery

Satellite remote-sensing techniques face challenges in extracting vegetation-cover information in desert environments. The limitations in detection are attributed to three major factors: (1) soil background effect, (2) distribution and structure of perennial desert vegetation, and (3) tradeoff between spatial and spectral resolutions of the satellite sensor. In this study, a modified vegetation shadow model (VSM-2) is proposed, which utilizes vegetation shadow as a contextual classifier to counter the limiting factors. Pleiades high spatial resolution, multispectral (2 m), and panchromatic (0.5 m) images were utilized to map small and scattered perennial arid shrubs and trees. We investigated the VSM-2 method in addition to conventional techniques, such as vegetation indices and prebuilt object-based image analysis. The success of each approach was evaluated using a root sum square error metric, which incorporated field data as control and three error metrics related to commission, omission, and percent cover. Results of the VSM-2 revealed significant improvements in perennial vegetation cover and distribution accuracy compared with the other techniques and its predecessor VSM-1. Findings demonstrated that the VSM-2 approach, using high-spatial resolution imagery, can be employed to provide a more accurate representation of perennial arid vegetation and, consequently, should be considered in assessments of desertification.

Quantifying lava flow hazards in response to effusive eruption

The integration of satellite data and modeling represents a step toward the next generation of quantitative hazard assessment in response to effusive volcano eruption onset. Satellite-based thermal remote sensing of hotspots related to effusive activity can effectively provide a variety of products suited to timing, locating, and tracking the radiant character of lava flows. Hotspots show the location and occurrence of eruptive events (vents). Discharge rate estimates may indicate the current intensity (effusion rate) and potential magnitude (volume). High-spatial-resolution multispectral satellite data can complement field observations for monitoring the front position (length) and extension of flows (area). Physics-based models driven, or validated, by satellite-derived parameters are now capable of fast and accurate forecast of lava flow inundation scenarios (hazard). Here, we demonstrate the potential of the integrated application of satellite remote-sensing techniques and lava flow models by using a retrospective analysis of the 2004–2005 effusive eruption at Mount Etna in Italy. The lava flow hazard was assessed by using the HOTSAT volcano hotspot detection system, which works with satellite thermal infrared data, and the MAGFLOW lava flow emplacement model, which is able to relate the flow evolution to eruption conditions at the vent. We used HOTSAT to analyze Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data to output hotspot location, lava thermal flux, and effusion rate estimation. This output was used to drive the MAGFLOW simulations of lava flow paths and to continuously update flow simulations. We also show how Landsat-7 Enhanced Thematic Mapper+ (ETM+) and Earth Observing 1 ( EO-1 ) Advanced Land Imager (ALI) images complement the field observations to track the flow front position in time and add valuable data on lava flow advancement with which to validate the numerical simulations. Such integration at last makes timely forecasts of lava flow hazards during effusive crises possible at the great majority of volcanoes for which no monitoring exists.

Application of Satellite Remote Sensing Techniques to Quantify Terminus and Ice Mélange Behavior at Helheim Glacier, East Greenland

AbstractIceberg calving is an efficient mechanism for ice mass loss, and rapidly calving glaciers are often considered to be inherently unstable. However, the physical controls on calving are not well understood. Recent studies hypothesize that the presence of a rigid ice mélange (composed of icebergs, bergy bits, and sea ice) can reduce iceberg calving by providing “backstress” to the terminus. To test this hypothesis we use remote sensing techniques to construct a time series model of calving rate and size and composition of the adjacent ice mélange. We describe a semi-automated routine for expediting the digitization process and illustrate the methods for Helheim Glacier, East Greenland, using 2008 data. Ice velocities of the glacier terminus and ice mélange are derived with feature-tracking software applied to radar imagery, which is successfully tracked year-round. Object-based image analysis (OBIA) is used to inventory icebergs and sea ice within the ice mélange. We find that the model successfully identifies the calving rate and ice mélange response trends associated with seasonal increases in terminus retreat and advance and shows seasonal trends of ice mélange potentially providing seasonal backstress on the glacier terminus.

Internal solitary waves in the China seas observed using satellite remote-sensing techniques: a review and perspectives

Internal solitary waves (ISWs) occur ubiquitously in China’s waters: the South China Sea (SCS), the East China Sea (ECS), the Yellow Sea (YS), and the Bohai Sea (BS). ISWs have long attracted much research interest because of their important role in ocean acoustics, offshore engineering, ocean mixing, primary productivity, and submarine navigation. ISWs have sea surface signatures that can be detected by satellite synthetic aperture radar (SAR) and optical sensors. Satellite remote-sensing images provide excellent two-dimensional views of the ISW field. Our understanding of ISWs in the China Seas has been greatly improved using satellite remote-sensing techniques. The primary objectives of this paper are to review the development of remote-sensing techniques in the study of ISWs and to summarize ISW characteristics in the China seas, mainly demonstrated by remote-sensing techniques. In addition, several issues with remote-sensing techniques and interesting research topics are discussed.

LAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIES

Land use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. T he Nilgiris district of Tamilnadu state in India is th e first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by fr equent landslides. Therefore in this present study land use land cover dynamics of Nilgiri district has bee n studied from 1990 to 2010 using Satellite Remote Sensing Technique. The temporal changes of land use and land cover changes of Nilgiris district over t he period of 1990 to 2010 were monitored using LISS I and LISS III of IRS 1A and IRS-P6 satellites. Land use dynamics were identified using Maximum likelihood classification under supervised classification technique. From the remote sensing study, it is fou nd that during the study period of 1990 to 2010, ar ea of dense forest increased by 27.17%, forest plantat ion area decreased by 54.64%. Conversion of forest plantation, Range land and open forest by agricultu re and settlement leading to soil erosion and landslides. Tea plantation increased by 33.95% and agricultural area for plantation of vegetables increased rapidly to 217.56% in the mountain steep area. The accuracy of classification has been asses sed by forming confusion matrix and evaluating kappa coefficient. The overall accuracy has been obtained a s 83.7 and 89.48% for the years 1990 and 2010 respect ively. The kappa coefficients were reported as 0.80 and 0.88 respectively for the years 1990 and 2010.

Temporal change assessment of agricultural land by Satellite Remote Sensing (SRS) technique

Agriculture is the vital economic activity of rural society in nearly all of Pakistan. The Winder-Sonmiani area located at the Makran coast near the city of Hub in Pakistan is economically very promising. Cropping, horticulture, fruit farming and animal husbandry are the common land use activities in the area while fishing along the coast is an important economic activity. Owing to the use of the Satellite Remote Sensing technique (SRST), the triangular basin shape structure of the Winder area has been found to be spatially very promising for agricultural activities. Positive change in the use of agriculture land was detected from the Satellite images of different periods. Use of modern technology and incentives provided by the government have advanced improvement in agriculture.

Investigation of Ocean Current in Closed Bay using Satellite Remote Sensing Technique and its Availability

Investigation of Ocean Current in Closed Bay using Satellite Remote Sensing Technique and its Availability