Land Observing Satellite Research Articles

A Semi-Empirical Chlorophyll-a Retrieval Algorithm Considering the Effects of Sun Glint, Bottom Reflectance, and Non-Algal Particles in the Optically Shallow Water Zones of Sanya Bay Using SPOT6 Data

Chlorophyll-a (Chl-a) concentration retrieval is essential for water quality monitoring, aquaculture, and guiding coastline infrastructure construction. Compared with common ocean color satellites, land observation satellites have the advantage of a higher resolution and more data sources for retrieving the concentration of Chl-a from optically shallow waters. However, the sun glint (Rsg), bottom reflectance (Rb), and non-algal particle (NAP) derived from terrigenous matter affect the accuracy of Chl-a concentration retrieval using land observation satellite image data. In this paper, we propose a semi-empirical algorithm based on the remote sensing reflectance (Rrs) of SPOT6 to retrieve the Chl-a concentration in Sanya Bay (SYB), considering the effect of Rsg, Rb, and NAP. In this semi-empirical algorithm, the Cox–Munk anisotropic model and radiative transfer model (RTM) were used to reduce the effects of Rsg and Rb on Rrs, and the Chl-a concentration was retrieved by the Chl-a absorption coefficient at 490 nm (aphy(490)) to remove the effect of NAP. The semi-empirical algorithm was in the form of Chl-a = 43.3[aphy(490)]1.454, where aphy (490) was calculated by the total absorption coefficient and the absorption coefficients of each component by empirical algorithms. The results of the Chl-a concentration retrieval show the following: (1) SPOT6 data are available for Chl-a retrieval using this semi-empirical algorithm in oligotrophic or mesotrophic coastal waters, and the accuracy of the algorithm can be improved by removing the effects of Rsg, Rb, and NAP (R2 from 0.71 to 0.93 and root mean square error (RMSE) from 0.23 to 0.11 ug/L); (2) empirical algorithms based on the blue-green band are suitable for oligotrophic or mesotrophic coastal waters, and the algorithm based on the blue-green band difference Chl-a index (DCI) has stronger anti-interference in terms of the effects of sun glint and bottom reflectance than the algorithm based on the blue-green ratio (BGr); (3) in the case of ignoring Rsg unrelated to inherent optical properties (IOPs), NAP is the biggest interference factor when >9.5 mg/L and the effect of bottom reflectance should be considered when the water depth (H) <5 m in SYB; and (4) the inherent optical properties of the waters in SYB are dominated by NAP (Chl-a = 0.2–2.6 ug/L and NAP = 2.2–30.1 mg/L), and the nutrients are concentrated by enclosed terrain and southeast current. This semi-empirical algorithm for Chl-a concentration retrieval has the potential to monitor Chl-a in oligotrophic and mesotrophic coastal waters using other land observation satellites (e.g., Landsat8 OLI, ASTER, and GaoFen2).

ミクセル解析を目的としたLandsat/OLIデータとMODISデータの重ね合わせにおける要求精度

Currently, many land observation satellites can be used in order to monitor natural environment. JAXA has a plan to launch new satellite GCOM-C1. SGLI is mounted on GCOM-C1, which can observe 380-12000nm spectral range in 250m sampling distance and 1150km swath. A mixed pixel analysis is a very important issue for an accurate environmental monitoring. Therefore, required accuracy of geometric transformation for GCOM-C1/SGLI should be understood. In this study, Landsat/OLI was used as reference data for geometric transform. The accuracy of superposing OLI on MODIS was evaluated by using simulated MODIS data. MODIS has a same ground sampling distance with SGLI. As the results, 1/5 pixel accuracy is required for mixed pixel analysis. Finally, Mixed pixel analysis was carried out real Landsat OLI and MODIS. The positional error of MODIS showed around 40-60m. The root mean square error between OLI and MODIS showed 12.6 (W/m2/sr/μm). It was bigger than simulation results. The reason might be come from transit time difference of satellite.

Land cover mapping and data availability in critical terrestrial ecoregions: A global perspective with Landsat thematic mapper and enhanced thematic mapper plus data

Land cover provides objective and multi scale information on the extent and conditions of habitats both currently and retrospectively. Over four decades since the launch of the first land-observation satellite – Landsat-1 in 1972, a tremendous number of earth observation images have been acquired and archived. Here we examined land cover mapping in 142 critical terrestrial ecoregions (identified by WWF Global 200) from three aspects: Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) data availability, literature and existing global land cover map. We found that: (1) the availability of Landsat TM/ETM+ for historical land-cover change analysis in those ecoregions is poor. Only 17 ecoregions and 38 ecoregions have sufficient number of seasonal images in the Landsat archive for change analysis at 10-year and 5-year intervals, respectively. (2) Only 26 of 142 ecoregions belong to research hotspots of land cover mapping based on a spatialized literature database. (3) From a 30m global land cover map (which is FROM-GLC, Finer Resolution Observation and Monitoring – Global Land Cover), only 28 ecoregions have greater than 80% map accuracy while 36 ecoregions have poorer than 50% map accuracy. Our finding suggests a significant gap of observation and understanding of these critical ecoregions from space, and an urgent need to meet the requirement of the conservation science community, in order for land cover data to fulfil its potential to timely monitor the loss of biodiversity from space, improve our knowledge of the state of conservation, and inform better decision making.

The application of China's land observation satellites within the framework of Digital Earth and its key technologies

Digital Earth is an interdisciplinary field involving space technology, information technology, and geoscience. This article introduces the land observation satellite system of China and discusses the requirements for satellite payloads in terms of spatial, temporal, and spectral resolution to establish a Digital Earth. The applications of land satellites under the framework of Digital Earth are introduced from the perspectives of data support, special subject services, and integrated information services. It is concluded that China's land observation satellites and ground processing systems will be fundamental components of the Digital Earth system, in which satellite data and their derived information will serve as the principal information source and greatly promote applications of Digital Earth.

我国陆地观测卫星现状及发展战略思考

In this paper, the current situation and achievements of China's land observation satellites such as payload development, construction of ground data processing systems and remote sensing data applications are summarized, and current challenges and tasks are analyzed. We then discuss strategic considerations and prospects for future development and suggest concentrating on five areas: (1) strengthening the national top- level plan for China's land observation system development; (2) planning the construction of the united ground system; (3) developing satellite series for business operations; (4) participating in international cooperation for global change detection; and (5) promoting the industrial development of remote sensing technology.

F-6-3-4 Modeling of a flywheel suspension mechanism for internal disturbance estimation

As the requirement for pointing accuracy of applications spacecraft such as land observation satellite becomes higher, the attitude control is subject to more and more demanding accuracy requirement. This results in the necessity of managing internal disturbance attributed to mechanical moving parts such as rotating mirror, solar array driving mechanism, and so on. Flywheels used for attitude control actuator can be a major cause of the internal disturbance. In this paper, the disturbance torques and forces induced by a flywheel is investigated precisely based on the rotor dynamics and the contact dynamics of the supporting bearings. The wheel rotor model includes static and dynamic mass unbalance as in the common practice. The bearing model with six (6) balls reflects the actual hardware currently manufactured, which uses an angular contact bearing with relatively small preload pressure to reduce the friction torque. The most challenging part of the modeling is the contact dynamics of the bearing unit consisting of inner lace-balls-retainer-outer lace configuration. At the contact point, the normal force is a nonworking constraint force while tangential and axial forces are normally working forces given as a function of velocity components at the contact. Taking this situation into account, a flywheel model is established as a multibody system with seven (7) degrees of freedom. Based upon this modeling, spinning rigid body dynamics is evaluated as well as the precise estimation of the disturbance torques and forces, and compared with the experimental results obtained from the low friction test-bed.

Introduction to remote sensing

Preface. Part I: Foundations. History and Scope of Remote Sensing. Electromagentic Radiation. Part II: Image Acquisition. Photographic Sensors. Digital Data. Image Interpretation. Land Observation Satellites. Active Microwave and Lidar. Thermal Radiation. Image Resolution. Part III: Analysis. Preprocessing. Image Classification. Field Data. Accuracy Assessment. Hyperspectral Remote Sensing. Part IV: Applications. Geographic Information Systems. Plant Sciences. Earth Sciences. Hydrospheric Sciences. Land Use and Land Cover. Global Remote Sensing.

Marine observation satellite

MOS-1 (Marine Observation Satellite-1) is the first of Japan's earth observation satellite programs consisting of a series of land and marine observation satellites. Since it is the first of the series, it was decided to install sensors in order to observe both marine and land phenomena. Therefore, it would be more appropriate to call it an experimental earth observation satellite rather than MOS-1. Although certain aspects of the MOS-1 program have been introduced in international remote sensing communities'-, an overall view has not so far been introduced. In this report, therefore, an attempt is made to cover all aspects of the MOS-1 program. There were various background activities before the realization of the program and the selection of sensors, which will be described at the