Regular monitoring and assessment on radiometric performance of satellite sensors is necessary for the quantitative remote sensing application and development. HJ satellite was launched by China on 2008, which was put forward to achieve dynamic monitoring of environment and disasters, also need to monitor radiometric performance and provide stable and reliable calibration coefficients timely. In this study, Terra/MODIS data were used to calibrate HJ-1A CCD camera by cross-calibration technique in Dunhuang radiometric calibration site. Total thirteen HJ -1A CCD images were utilized, the 6s model was used to estimate the spectral matching factors. Finally, this study obtains long-term HJ-1A CCD calibration coefficients from 2009 to 2012. Results show that each band of HJ-1A CCD is varying degrees of degradation after HJ satellites launched 5 years later. This study is helpful to obtain high accuracy and reliable calibration coefficients and monitor radiometric performance of HJ-1A CCD.
Global change research requires high spatial, multi-scale, and consistent remote sensing data.
Advanced land observing Satellite (ALOS) implemented a systematic data observation program,
providing free polarimetric Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaics to
support global change research. The study took Mangrove Nature Reserve of Dongzhai Harbor in
Hainan Province as an example, investigating the performance of PALSAR mosaics to map
mangrove distribution in this area. In addition, backscattering characteristics of different objects
were also compared, which proved the monitoring capability of PALSAR mosaics. The study
indicates that PALSAR mosaics is a reliable data source for monitoring mangrove and is helpful to
regional-scale research while high spatial resolution is guaranteed.
Dynamic monitoring forest is critical for forest management and protection, while existing satellites
hardly meet the requirements of the temporal and spatial resolution for forest mapping. HJ-1 A/B,
recently launched by China, can form the 700m-wide multi-spectrum image with 30-m resolution of
any location every 2 days, also leading to large data to process. In this study, seven-feature approach,
utilizing Principal Components, NDVIs, and DEM, is developed to map forest effectively, promising
potential applications of HJ-1 A/B in land resources.
Remote Sensing surveillance constitutes an important component of oil spill disaster management system, but subject to
monitoring accuracy and ability, which suffered from resolution, environmental conditions, and look-alikes. So this
article aims to provide information of identification and distinguishing of look-alikes for optical sensors, and then
improve the monitoring precision. Although limited by monitoring conditions of the atmosphere and night, optical
satellite remote sensing can provide the intrinsic spectral information of the film and the background sea, then affords the
potentiality for detailed identification of the film thickness, oil type classification (crude/light oil), trends, and sea surface
roughness by multi-type data products. This paper focused on optical sensors and indicated that these false targets of sun
glint, bottom feature, cloud shadow, suspend bed sediment and surface bioorganic are the main factors for false alarm in
optical images. Based on the detailed description of the theory of oil spill detection in optical images, depending on the
preliminary summary of the feature of look-alikes in visible-infrared bands, a discriminate criteria and work-flow for
slicks identification are proposed. The results are helpful to improve the remote sensing monitoring ability and the
In recent years, large-sized seaweed, such as ulva lactuca, blooms frequently in coastal water in China, which threatens
marine eco-environment. In order to take effective measures, it is important to make operational surveillance. A case of
large-sized seaweed blooming (i.e. enteromorpha), occurred in June, 2008, in the sea near Qingdao city, is studied.
Seaweed blooming is dynamically monitored using Moderate Resolution Imaging Spectroradiometer (MODIS). After
analyzing imaging spectral characteristics of enteromorpha, MODIS band 1 and 2 are used to create a band ratio
algorithm for detecting and mapping large-sized seaweed blooming. In addition, chlorophyll-α concentration is inversed
based on an empirical model developed using MODIS.
Chlorophyll-α concentration maps are derived using
multitemporal MODIS data, and chlorophyll-α concentration change is analyzed. Results show that the presented
methods are useful to get the dynamic distribution and the growth of large-sized seaweed, and can support contingency
Remote sensing is an effective tool to monitor oil spills. The theory of oil spill remote sensing is based on the differences
between oil slick and other environmental objects. For optical sensor, the ability of different bands to find oil film at sea
is different. Oil spill object could be intensified by composing appropriate bands. In addition, image enhancements could
also strengthen oil spill features. For SAR, image characteristics of oil spill are crucial to oil detection. Applications
show that sensors loaded on satellite can find oil slick at sea. Optical sensor and SAR have their own advantages, and
play different roles in oil spill remote sensing. It is necessary to integrate them to establish an all-weather,
omnidirectional 3-D monitoring network for monitoring oil spills and illicit vessel discharges.
Oil spills are seriously affecting marine ecosystem and cause political and scientific concern. In order to implement an emergency in case of oil spills, it is necessary to monitor oil spill using remote sensing. Techniques for monitoring oil spills includes optical, microwave, and radar approaches using aircraft or satellites. However, Satellites have wider coverage and lower price. Recent years, with more sensors launching, correctness and real time of oil spills monitoring using satellites are improved. Based on many successful experiences in oil spills monitoring, sensitivities of different bands to different oil types are analyzed using AVHRR and TM data, and methodologies to extract oil spills information, especial oil thickness, are presented. In addition, with regard to requirements of customers, position, area, drifting trajectory and velocity can be calculated, which supports marine oil spill fast emergency response effectively. It is believed that it is possible to establish an oil spill monitoring network using satellite covering main sea area in China.
Oil spills are seriously affecting the marine ecosystem. In order to implement an emergency in case of oil spills, it is
necessary to monitor oil spill using remote sensing. Spectral measurements are undertaken for several oil types in 1998
and 1999. Based on the oil spectral characteristics, this study demonstrates how MODIS (Moderate Resolution Imaging
Spectroradiometer) can monitor oil spills in an oil spill event occurred near Dalian in North China Sea. The study shows
that MODIS has possessed some hyperspectral characteristics, which improve the capability of oil spill monitoring.
Wetland is a very important land resource and a natural resource, which has many functions like forest, cropland, and ocean, and has close relationship with human being. Northeast China has largest wetland distribution and richest wetland types in China. However, under economic interests driving, wetland in this area is exploited blindly, which causes wetland's functions and benefits decreasing. With the involvement of RS (Remote Sensing) and computer technology, we can monitor wetlands dynamically, which decreases labor intensity of field investigation. Although MODIS, loaded on Terra of new generation EOS, has a coarser spatial resolution than TM, it has higher spatial, temporal, and spectral resolution than AVHRR, which make it capabile to monitor wetland timely and dynamically. The article takes Songnen Plain as study area, uses multi-temporal MODIS-NDVI data to study wetland distribution, and makes validation of result. The research indicates that using multi-temporal MODIS-NDVI data is capable to get wetland distribution, and monitor wetland change effectively.
In order to remove MODIS bowtie effect, an analytical algorithm is proposed, which is based on solid geometry projection and requires no ephemeris information. The geometry projection model is established from the parameters of MODIS platform and the amount of overlapping pixels is quantified as a function of the instantaneous scanning angle. Lookup table is utilized to guide the deletion of overlapping pixels and improve efficiency, and cubic spline interpolation is applied to subpixelly restore data following their profile. Resampling is followed to generate integral pixel coordinates. The border incontinuity problem that occurs due to the gap between different swaths is solved by introducing of a special blocking method. The validity of out algorithm is verified by comparing with three other Non-ephemeris algorithms, and the result shows that not only the bowtie effect within a single swath is effectively removed, the incontinuity caused by conventional pixel grouping method is mostly well eliminated.