Delineation of groundwater potential zones using remote sensing and Geographic Information Systems(GIS)in Kadaladi region,Southern India

The primary objective of this research is to delineate potential groundwater recharge zones in the Kadaladi taluk of Ramanathapuram,Tamil Nadu,India,using a combination of remote sensing and Geographic Information Systems(GIS)with the Analytical Hierarchical Process(AHP).Various factors such as geology,geomorphology,soil,drainage,density,lineament density,slope,rainfall were analyzed at a specific scale.Thematic layers were evaluated for quality and relevance using Saaty's scale,and then inte-grated using the weighted linear combination technique.The weights assigned to each layer and features were standardized using AHP and the Eigen vector technique,resulting in the final groundwater potential zone map.The AHP method was used to normalize the scores following the assignment of weights to each criterion or factor based on Saaty's 9-point scale.Pair-wise matrix analysis was utilized to calculate the geometric mean and normalized weight for various parameters.The groundwater recharge potential zone map was created by mathematically overlaying the normalized weighted layers.Thematic layers indicating major elements influencing groundwater occurrence and recharge were derived from satellite images.2 Results indicate that approximately 21.8 km of the total area exhibits high potential for groundwater recharge.Groundwater recharge is viable in areas with moderate slopes,particularly in the central and southeastern regions.

An operational satellite remote sensing system for ocean fishery

Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from -3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.

Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China

The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean (i.e.,arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error (RMSE ) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.

Cultivated Land Changes and Their Driving Forces——A Satellite Remote Sensing Analysis in the Yellow River Delta,China

Taking Kenli County in the Yellow River Delta, China, as the study area and using digital satellite remote sensing techniques, cultivated land use changes and their corresponding driving forces were explored in this study. An interactive interpretation and a manual modification procedure were carried out to acquire cultivated land information. An overlay method based on classification results and a visual change detection method which was supported by land use maps were employed to detect the cultivated land changes. Based on the changes that were revealed and a spatial analysis between cultivated land use and related natural and socio-economic factors, the driving forces for cultivated land use changes in the study area were determined.The results showed a decrease in cultivated land in Kenli County of 5321.8 ha from 1987 to 1998, i.e.,an average annual decrement of 483.8 ha, which occurred mainly in the central paddy field region and the northeast dry land region. Adverse human activities, soil salinization and water deficiencies were the driving forces that caused these cultivated land use changes.

Satellite remote-sensing technologies used in forest fire management

Satellite remote sensing has become a primary data source for fire danger rating prediction, fuel and fire mapping, fire monitoring, and fire ecology research. This paper summarizes the research achievements in these research fields, and discusses the future trend in the use of satellite remote-sensing techniques in wildfire management. Fuel-type maps from remote-sensing data can now be produced at spatial and temporal scales quite adequate for operational fire management applications. US National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are being used for fire detection worldwide due to their high temporal resolution and ability to detect fires in remote regions. Results can be quickly presented on many Websites providing a valuable service readily available to fire agency. As cost-effective tools, satellite remote-sensing techniques play an important role in fire mapping. Improved remote-sensing techniques have the potential to date older fire scars and provide estimates of burn severity. Satellite remote sensing is well suited to assessing the extent of biomass burning, a prerequisite for estimating emissions at regional and global scales, which are needed for better understanding the effects of fire on climate change. The types of satellites used in fire research are also discussed in the paper. Suggestions on what remote-sensing efforts should be completed in China to modernize fire management technology in this country are given.

A Comparison of Cloud Layers from Ground and Satellite Active Remote Sensing at the Southern Great Plains ARM Site

Using the data collected over the Southern Great Plains ARM site from 2006 to 2010, the surface Active Remote Sensing of Cloud （ARSCL） and CloudSat-CALIPSO satellite （CC） retrievals of total cloud and six specified cloud types [low, midlow （ML）, high-mid-low （HML）, mid, high-mid （HM） and high] were compared in terms of cloud fraction （CF）, cloud-base height （CBH）, cloud-top height （CTH） and cloud thickness （CT）, on different temporal scales, to identify their respective advantages and limitations. Good agreement between the two methods was exhibited in the total CF. However, large discrepancies were found between the cloud distributions of the two methods at a high （240-m） vertical grid spacing. Compared to the satellites, ARSCL retrievals detected more boundary layer clouds, while they underestimated high clouds. In terms of the six specific cloud types, more low- and mid-level clouds but less HML- and high-level clouds were detected by ARSCL than by CC. In contrast, the ARSCL retrievals of ML- and HM-level clouds agreed more closely with the estimations from the CC product. Lower CBHs tended to be reported by the surface data for low-, ML- and HML-level clouds; however, higher CTHs were often recorded by the satellite product for HML-, HM- and high-level clouds. The mean CTs for low- and ML-level cloud were similar between the two products; however, the mean CTs for HML-, mid-, HM- and high-level clouds from ARSCL were smaller than those from CC.

Study on Thermal Deformation Measurement of Optical RemoteSensing Satellite Platform Based on Machine Vision

To solve the special requirements of the high orbit optical remote sensing satellite for the thermal deformation of the platform the thermal deformation test and measurement scheme of the satellite platform is designed. Through the comparative analysis of test results the rationality of the thermal deformation design of the platform structure is verified. The results of thermal deformation measurement show that the maximum deformation of A camera mounting surface is 57.5〃 and the maximum deformation of B camera mounting surface points to 79.3〃 which can be used as the basis for thermal deformation prediction of satellite during the orbit operation.

Simulate New Near Equatorial Satellite System by a Novel Multi-Fields and Purposes Remote Sensing Goniometer

Researchers in the remote sensing field use different types of images from satellite systems and simulator devices, such as goniometers. However, no device can simulate the new generation of optical satellite system called near-equatorial satellite system to perform different kinds of remote sensing applications in equatorial regions. This study proposed a newly invented laboratory and fieldwork goniometer designed to simulate and capture intensity variation and measure the bidirectional spectral reflectance of earth surface. The proposed goniometer is a multi-purpose and multi-field device. It is able to simulate different satellite systems and measure the intensity variation and spectral reflectance of earth’s surface features with freely azimuth and zenith angles of sensors and illumination source in fieldwork and/or laboratory. However, the system of invention is focusing on specific satellite orbital to work with the parameters and properties of NEqO satellite system in order to obtain NEqO system imagery for performing different applications such as geometric correction, relative radiometric normalization and change detection for future work. The significant of this invention is that most of the invented goniometers of remote sensing are able to work just in field or just in laboratory and use, carry just optical sensor or hyperspectral sensor. Specifically, our invention can do all these functions that are not available in existing goniometers. The proposed device offers several advantages, namely, high measurement speed, flexibility, low cost, efficiency, and possible measurement depending on the free zenith/azimuth angles of sensors and illumination sources. The proposed goniometer includes ten parts, and two different sensors (optical and hyperspectral).

A Review of Satellite Remote Sensing Monitoring Methods for Sea Surface Oil Spill

Using satellite remote sensing to monitor oil spill on the sea is an advanced means of oil spill monitoring, and it has the characteristics of wide coverage, speediness and real time, synchronization, continuity, and low cost. Hence, accelerating the research on this technology and establishing a satellite remote sensing monitoring mechanism suitable for oil spill emergency situations is of great significance to improve China's oil spill monitoring capability and prevent or reduce the pollution damage caused by oil spill in the marine environment.This paper analyzes and studies the current situation using satellite remote sensing to monitor oil spills at home and abroad. Based on the basic principle of satellite remote sensing, this paper systematically studies the satellite remote sensing monitoring oil spill principles, satellite data processing methods and oil spill information identification, and summarizes an oil spill identification system that can realize oil spill information reproduction. This system provides an important means of support for the handling of oil spill accidents.

China Launches Remote Sensing Satellite For Venezuela

China launched a Venezuelan remote sensing satellite,VRSS-2,into a preset orbit from the Jiuquan Satellite Launch Center at 12：13 Beijing time on October 9.The satellite was launched by a LM-2D carrier rocket which was developed by the Shanghai Academy of Spaceflight Technology.

WITHDRAWN: High-Resolution Radiometer for Remote Sensing of Solar Flare Activity from Low Earth Orbit Satellites

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause.

Information Service System for Receiving and Processing Multi Source Remote Sensing Images

Based on international requirements for the application of commercial remote sensing data,an information service system for receiving and processing multi source remote sensing data was developed and introduced.The system consists of an Oversea Fixed Ground Service Station(OFGS),a Transportable Vessel-Borne Service Station(TVBS) and a Data Operation and Management Center(DOMC).Fixed and transportable service stations were developed in Venezuela,Latin America and for the China's Xuelong polar research vessel respectively,and serve the function of remote sensing data receiving,processing and application.The DOMC connects the OFGS and TVBS,so that they constitute a network to provide receiving,distribution,retrieval,browsing,ordering,and downloading functions for multi remote sensing satellite data and products.It validates the competence in providing 40 kinds of typical application products.The development of this system provides a reliable and comprehensive service for commercial remote sensing data applications for users both in domestic and oversea markets.

Prediction of Petroleum Prospect in the South Yellow Sea Basin Using Satellite Remote Sensing

Using satellite remote sensing to measure the sea surface temperature of the East China Sea Shelf Basin can serve the purpose of predicting the petroleum prospect in the South Yellow Sea Basin. The satellite thermal infrared temperature anomaly area always repeats in the same position as the proved oil prospect area in the East China Sea Shelf Basin, and coincides well with both the CH4 content curve at the water-atmosphere interface and the seafloor geochemical anomaly. The sea surface temperature anomaly areas of the South Yellow Sea Basin in the satellite remote sensing image go banded along 123030, in the S-N direction, and naturally follow the aeromagnetically interpreted eastern nose-type uplift that shows a S-N strike. The north and south ends of the eastern nose are considered as good oil prospect areas because temperature anomaly often occurs there.

Improved strategy for estimating stem volume and forest biomass using moderate resolution remote sensing data and GIS

This study presents the utility of remote sensing （RS）, GIS and field observation data to estimate above ground biomass （AGB） and stem volume over tropical forest environment. Application of those data for the modeling of forest properties is site specific and highly uncertain, thus further study is encouraged. In this study we used 1460 sampling plots collected in 16 transects measuring tree diameter （DBH） and other forest properties which were useful for the biomass assessment. The study was carded out in tropical forest region in East Kalimantan, Indo- nesia. The AGB density was estimated applying an existing DBH - biomass equation. The estimate was superimposed over the modified GIS map of the study area, and the biomass density of each land cover was calculated. The RS approach was performed using a subset of sample data to develop the AGB and stem volume linear equation models. Pearson correlation statistics test was conducted using ETM bands reflectance, vegetation indices, image transform layers, Principal Component Analysis （PCA） bands, Tasseled Cap （TC）, Grey Level Co-Occurrence Matrix （GLCM） texture features and DEM data as the predictors. Two linear models were generated from the significant RS data. To analyze total biomass and stem volume of each land cover, Landsat ETM images from 2000 and 2003 were preprocessed, classified using maximum likelihood method, and filtered with the majority analysis. We found 158±16 m^3.ha^-1 of stem volume and 168±15 t.ha^-1 of AGB estimated from RS approach, whereas the field measurement and GIS estimated 157±92 m^3.ha^-1 and 167±94 t.ha^-1 of stem volume and AGB, respectively. The dynamics of biomass abundance from 2000 to 2003 were assessed from multi temporal ETM data and we found a slightly declining trend of total biomass over these periods. Remote sensing approach estimated lower biomass abundance than did the GIS and field measurement data. The earlier approach predicted 10.5 Gt and 10.3 Gt of total biomasses in 2000 and 2003, while the later estimated 11.9 Gt and 11.6 Gt of total biomasses, respectively. We found that GLCM mean texture features showed markedly strong correlations with stem volume and biomass.

Analysis of Remote Sensing Images of Ground Ruptures Resulting from the Kunlun Mountain Pass Earthquake in 2001

On November 14, 2001, an earthquake measuring a magnitude of 8.1 occurred to the west of the Kunlun Mountain Pass which is near the border between Xinjiang and Qinghai of China. Since its epicenter is located in an area at an elevation of 4900 m where the environment is extremely adverse, field investigation to this event seems very difficult. We have performed interpretation and analysis of the satellite images of ETM, SPOT, Ikonos, and ERS-1/2SAR to reveal the spatial distribution and deformation features of surface ruptures caused by this large earthquake. Our results show that the rupture zone on the ground is 426 km long, and strikes N90-110°E with evident left-lateral thrusting. In spatial extension, it has two distinct sections. One extends from the Bukadaban peak to the Kunlun Mountain Pass, with a total length of 350 km, and trending N95-110°E. Its fracture plane is almost vertical, with clear linear rupture traces and a single structure, and the maximum left-lateral offset is 7.8 m. This section is the main rupture zone caused by the earthquake, which is a re-fracturing along an old fault. The other is the section from Kushuihuan to the Taiyang Lake. It is 26 km long, trending N90-105°E, with the maximum strike-slip displacement being 3 m, and is a newly-generated seismic rupture. In a 50 km-long section between the Taiyang Lake and the Bukadaban peak, no rupture is found on the ground. The eastern and western rupture zones may have resulted from two earthquakes. The macroscopic epicenter is situated at 65 km east of the Hoh Sai Lake. The largest coseismic horizontal offset in the macroscopic epicenter ranges from 7 m to 8 m. Based on the dislocation partition of the whole rupture zone, it is suggested that this rupture zone has experienced a process of many times of intensification and fluctuation, exhibiting a remarkable feature of segmentation.

Effects of Aerosol Vertical Inhomogeneity on the Upwelling Radiance and Satellite Remote Sensing of Surface Reflectance

There are two widely used radiative models without consideration of aerosol inhomogeneity for satellite remote sensing application, the Homogeneous Model and the Two-layer Model with aerosol in the lower layer. In this paper, effects of the aerosol vertical inhomogeneity on upwelling radiance and satellite remote sensing of surface reflectance are analyzed through numerical simulations by using two models. As shown in the simulations by using 24 representative aerosol models, there is often a considerably large error in upwel-ling radiance calculated by two models (Homogeneous and Two-layer) for the short wavelength channel with strong molecular scattering, owing to the difference between molecular and aerosol scattering proper-ties. For the long wavelength channel, the error is small if aerosol optical parameters are less variable with height, but it could also be significant if there are aerosol layers with different scattering phase functions and single scattering albedo. The radiance errors by the Homogeneous Model and the Two-layer Model can be up to 31.4% and 31.5% for the clean atmosphere, and in case of turbid atmosphere 67.8% and 59.2%, respectively. The radiance error could result in a large uncertainty of surface reflectance retrievals, especially for the short wavelength channel and the strongly absorbing aerosol. For the turbid atmosphere with strong-ly absorbing aerosol, the Homogeneous Model and the Two-layer Model are not suitable for atmospheric correction application. Key words Satellite remote sensing - Aerosol inhomogeneity - Surface reflectance - Radiance

Quantizing and analyzing the feature information of coastal zone based on high-resolution remote sensing image

On the basis of realization of beach information and its differentiating of high-resolution remote sensing image on coastal zone, extracting objects are carried through RS multi-scale diagnostic analysis, and fast information extraction methods and key technologies are put forward. Meanwhile image segmentation methods are set forth for objects of coastal zone. And through the application of Otsu2D to the segmentation of water area and dock and the applying of Gabor filter to the separation and extraction of construction, some typical applications of high-resolution RS image are presented in the field of coastal zone surface objects＇ recognition. Quantizing high-resolution RS information on the coastal zone proved to be of great scientific and practical significance for coastal development and management.

The first quantitative remote sensing of ocean internal waves by Chinese GF-3 SAR satellite

Quantitative analysis and retrieval is given by the State Key Laboratory of Satellite Ocean Environment Dynamics（SOED）,Second Institute of Oceanography（SIO）,State Oceanic Administration（SOA）,China,from the first batch of GF-3 synthetic aperture radar（SAR）data with ocean internal wave features in the Yellow Sea.

Classification of snow cover days in western China and comparison with satellite remote sensing data

The daily snow cover data from 232 meteorological stations to the west of 105°E in China for the period 1951-2004 were used to classify the snow cover and analyze decadal variations of snow cover types in western China, and comparison was made between the observational data and those retrieved from passive microwave remote sensing data （SMMR and SSM/I） in 1980-2004. The results show that stable snow-covered areas included northern Xinjiang, the Tianshan Mountains, and the eastern Tibetan Plateau with more than 60 snow cover days; no snow cover was found in the center of the southern Xinjiang Basin, the Sichuan Basin, and southern Yunnan. In addition to the above-mentioned, there were unstable snow-covered areas in western China. Furthermore, the snow cover types in northern Xinjiang, the Tianshan Mountains, the Hexi Corridor, and the vast areas from Chengdu to Kunming were unchanged. In the 1980s, the south-north dividing line between the major snow-covered area and snow-free area advanced to its most southern position. The snow cover days calculated from satellite remote sensing were generally longer than those from observational data in western China, mainly in the higher-altitude mountains, the Hexi Corridor, and the western Sichuan Plateau.

A study of the validation of atmospheric CO_2 from satellite hyper spectral remote sensing

Three total column dry-air mole fractions of CO_2(XCO_2) products from satellite retrievals, namely SCIAMACHY, NIES-GOSAT, and ACOS-GOSAT, in the Northern Hemisphere were validated by ground data from the Total Carbon Column Observing Network(TCCON). The results showed that the satellite data have the same seasonal fluctuations as in the TCCON data, with maximum in April or May and minimum in August or September. The three products all underestimate the XCO2. The ACOS-GOSAT and the NIES-GOSAT products are roughly equivalent, and their mean standard deviations are 2.26 × 10^(-6)and 2.27 × 10^(-6)respectively. The accuracy of the SCIMACHY product is slightly lower, with a mean standard deviation of 2.91 × 10^(-6).