Remote sensing application system for water environments developed for Environment Satellite 1
TL;DR: The Remote Sensing Application System for Water Environments (RSASWE) as discussed by the authors is an integrated platform for remote sensing data processing, parameter information extraction and thematic mapping using both remote sensing and GIS technologies.
Abstract: Remote sensing data collected by the Environment Satellite I are characterized by high temporal resolution, high spectral resolution and mid-high spatial resolution. We designed the Remote Sensing Application System for Water Environments (RSASWE) to create an integrated platform for remote sensing data processing, parameter information extraction and thematic mapping using both remote sensing and GIS technologies. This system provides support for regional water environmental monitoring, and prediction and warning of water pollution. Developed to process and apply data collected by Environment Satellite I, this system has automated procedures including clipping, observation geometry computation, radiometric calibration, 6S atmospheric correction and water quality parameter inversion. RSASWE consists of six subsystems: remote sensing image processing, basic parameter inversion, water environment remote sensing thematic outputs, application outputs, automated water environment outputs and a non-point source pollution monitoring subsystem. At present RSASWE plays an important role in operations at the Satellite Environment Center.
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TL;DR: In this article, the current status of satellite environmental monitoring in China and the existing problems of inadequate load design and low data utilization efficiency, and discusses the demand for environmental monitoring satellites.
Abstract: With the increase in global environmental problems, the necessity and urgency of remote sensing technology being applied to environmental monitoring has been widely recognized around the world. China has launched the environment and disaster monitoring and forecasting small satellite constellation HJ-1A/B and the FY3 atmosphere and environmental satellite, but they still cannot fully satisfy requirements for environmental monitoring. This paper summarizes the current status of satellite environmental monitoring in China and the existing problems of inadequate load design and low data utilization efficiency, and discusses the demand for environmental monitoring satellites. Based on the development of foreign satellite systems for environmental monitoring, the future development and key tasks of the environmental monitoring satellite system in China is discussed, as are some related initiatives.
44 citations
TL;DR: This special issue includes seven articles focusing on nonpoint source pollution, environmental quality, and ecosystem health in China, and the major issues, and results, are discussed in this introduction.
Abstract: The rapid economic and industrial growth of China, exemplified by a 10-fold increase in its gross domestic product in the past 15 years, has lifted millions of its citizens out of poverty but has simultaneously led to severe environmental problems. The World Health Organization estimates that approximately 2.4 million deaths in China per year could be attributed to degraded environmental quality. Much of China's soil, air, and water are polluted by xenobiotic contaminants, such as heavy metals and organic compounds. In addition, soil quality is degraded by erosion, desertification, and nutrient runoff. Air quality is further compromised by particulates, especially in heavily populated areas. Research shows that 80% of urban rivers in China are significantly polluted, and poor water quality is a key contributor to poverty in rural China. Economic and industrial growth has also greatly expanded the demand for water sources of appropriate quality; however, pollution has markedly diminished usable water resource quantity. Desertification and diminishing water resources threaten future food security. In recent years, China's government has increased efforts to reverse these trends and to improve ecosystem health. The Web of Science database showed that the percentage of articles on China devoting to environmental sciences increased dramatically in recent years. In addition, the top 25 institutes publishing the papers in environmental sciences were all in China. This special issue includes seven articles focusing on nonpoint source pollution, environmental quality, and ecosystem health in China. The major issues, and results of these studies, are discussed in this introduction.
15 citations
Cites background from "Remote sensing application system f..."
...Tools such as remote sensing, modeling, and geographic information systems (GIS), which are crucial for understanding the spatially diff use sources contributing to NPS pollution, will continue to be developed (e.g., Wu et al., 2010; Zhang and Huang, 2011)....
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TL;DR: Comparisons of results from all three L8/OLI image atmospheric corrections with the in situ remote sensing reflectance data show that M6SV produces reliable atmospheric corrections in the green and red spectral bands and is an effective alternative for Landsat 8 OLI atmospheric correction in inland waters.
Abstract: During the atmospheric correction of remote sensing data in inland waters, the original Second Simulation of the Satellite Signal in the Solar Spectrum-Vector version (6SV) model does not eliminate the specular reflection of downward skylight radiance at the air-water interface. Thus, we propose a modified version of the 6SV model (M6SV) that does remove reflected skylight at the air-water interface. We apply the new model to the atmospheric correction of a Landsat 8 Operational Land Imager (OLI) image over Taihu Lake, China, where the aerosol optical depth is known. In situ reflectance measurements acquired concurrently with the L8/OLI image are used to validate the performance of the new M6SV algorithm. To further analyze the merits and demerits of M6SV, the model is compared with two short-wave infrared (SWIR)-based atmospheric correction models: the Sea-Viewing Wide Field-of-View Sensor Data Analysis System short-wave infrared (SD-SWIR) model and the Vanhellemont & Ruddick short-wave infrared with a per scene fixed aerosol type (VR-SWIR-F) model. Comparisons of results from all three L8/OLI image atmospheric corrections with the in situ remote sensing reflectance data show that M6SV produces reliable atmospheric corrections in the green and red spectral bands and is an effective alternative for Landsat 8 OLI atmospheric correction in inland waters.
6 citations
Patent•
04 Jul 2017
TL;DR: In this paper, the spectral slope of each pixel in the water area image is used to determine the water quality of a set geographic area, and water quality is determined by analyzing the spectral slopes of the water-area remote sensing image.
Abstract: The invention brings forward a method and a device for detecting water quality The method for detecting water quality comprises the following steps: obtaining a remote sensing image of a set geographic area; carrying out radiometric calibration treatment and atmospheric correction treatment on the remote sensing image to obtain a pretreated remote sensing image; extracting a water area image from the pretreated remote sensing image; and determining water quality of the water area according to spectral slope of each pixel in the water area image According to the above technical scheme, by analyzing the spectral slope of the water-area remote sensing image in the set geographic area, water quality of the water area is determined The analysis data come from the satellite remote sensing images without the need of manual on-site acquisition of water samples Thus, manpower cost can be saved, and efficiency is higher
6 citations
29 Nov 2022
TL;DR: In this paper , an improved method of fusing data and inversing surface reflectivity is presented to obtain the HJ-1 inversion network-based application resolution (NBAR) data using linear matching of the Ross Thick-Li Sparse Reciprocal (RTLSR) model, and then predicted reflectivity using the seasonal autoregressive integrated moving average (SARIMA) model.
Abstract: HJ-1 charge-coupled device (CCD) data with high temporal and medium spatial resolution are widely used in environmental and disaster monitoring in China. However, due to bad weather, it is difficult to obtain sufficient time-continuous HJ-1 CCD data for environmental monitoring. In this study, the mountain valley with farmland and forestland in North China is selected as the experimental area, and HJ-1 CCD and moderate resolution imaging spectroradiometer (MODIS) data are used in the case study. An improved method of fusing data and inversing surface reflectivity is presented to obtain the HJ-1 inversion network-based application resolution (NBAR) data using linear matching of the Ross Thick-Li Sparse Reciprocal (RTLSR) model, and then predicted reflectivity using the seasonal autoregressive integrated moving average (SARIMA) model. The fusion data have advantages of high spatial and temporal resolution, as well as meeting the requirements of high quality and quantity of small-scale regional data. This case study provides a feasibility method for the HJ-1 satellites to produce the secondary products for small-scale remote sensing ground surface research. It also provides a reference for dynamic information acquisition and application of small satellite data, contributing to the improvement in RS estimation of surface environment variables.
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01 Jan 2001
TL;DR: In this article, the basic principles of imaging spectrometry are discussed and a review of the potential applications of image spectrometers are presented, including agricultural applications, geological applications, and urban applications.
Abstract: Acknowledgements About the Editors Contributors Introduction Part I: Basic principles of imaging spectrometry 1. Basic physics of spectrometry 2. Imaging spectrometry: Basic analytical techniques Part II: Prospective applications of imaging spectrometry 3. Imaging spectrometry for surveying and modelling land degradation 4. Field and imaging spectrometry for identification and mapping of expansive soils 5. Imaging spectrometry and vegetation science 6. Imaging spectrometry for agricultural applications 7. Imaging spectrometry and geological applications 8. Imaging spectrometry and petroleum geology 9. Imaging spectrometry for urban applications 10. Imaging spectrometry in the Thermal Infrared 11. Imaging spectrometry of water Acronyms Index References
332 citations
TL;DR: In this paper, the authors evaluated the extent to which near-infrared (NIR) to red reflectance ratios could be applied to the Sea Wide Field-of-View Sensor (SeaWiFS) and the Moderate Imaging Spectrometer (MODIS) to estimate Chl in productive turbid waters.
283 citations
TL;DR: In this paper, the spatial and spectral resolutions of Hyperion and the capability of physics-based approaches were considered highly suitable for testing the integration of remote sensing related technologies into the water quality monitoring programs of Lake Garda (the largest Italian lake), and water quality was assessed by defining a bio-optical model, converting the Hyperion at-sensor radiances into subsurface irradiance reflectances, and adopting a Bio-Optical model inversion technique.
273 citations
TL;DR: In this paper, an analytical optical model based on knowledge of the in situ inherent optical properties is used to estimate suspended matter concentration in lakes for the data from the SPOT and Landsat TM sensors.
Abstract: Suspended matter in inland waters is related to total primary production and fluxes of heavy metals and micropollutants such as PCBs. Synoptic information on suspended matter cannot be obtained from an in situ monitoring network since suspended matter is a spatially inhomogeneous parameter. This problem can be solved by the integrated use of remote sensing data, in situ data and water quality models. To enable retrospective model and remote sensing data comparison of suspended matter concentration and distribution, a methodology is required for processing satellite images that is independent of in situ measurements. Analytical optical modelling, based on knowledge of the in situ inherent optical properties, leads to reliable multi-temporal algorithms for estimating suspended matter concentration in lakes for the data from the SPOT and Landsat TM sensors. This methodology allows multi-temporal, multi-site and multi-instrument comparison of TSM maps derived from satellite imagery. This means that satellite ...
265 citations
01 Jan 2002
110 citations