Subsidence rate monitoring of Aghajari oil field based on Differential SAR Interferometry

Land subsidence, due to natural or anthropogenic processes, causes significant costs in both economic and structural aspects. That part of subsidence observed most is the result of human activities, which relates to underground exploitation. Since the gradual surface deformation is a consequence of hydrocarbon reservoirs extraction, the process of displacement monitoring is amongst the petroleum industry priorities. Nowadays, Differential SAR Interferometry, in which satellite images are utilized for elevation change detection and analysis – in a millimetre scale, has proved to be a more real-time and cost-effective technology in contrast to the traditional surveying method. In this study, surface displacements in Aghajari oil field, i.e. one of the most industrious Iranian hydrocarbon sites, are being examined using radar observations. As in a number of interferograms, the production wells inspection reveals that surface deformation signals develop likely due to extraction in a period of several months. In other words, different subsidence or uplift rates and deformation styles occur locally depending on the geological conditions and excavation rates in place.     

Temperature comparison between CHAMP radio occultation and TIMED/SABER measurements in the lower stratosphere

Global Positioning System (GPS) receiver on the CHAllenging Mini-satellite Payload (CHAMP) and the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument, one of four on board the TIMED satellite, provide middle atmosphere temperature profiles by Radio Occultation (RO) and limb viewing infrared emission measurements, respectively. These temperature profiles retrieved by two different techniques in the stratosphere are compared with each other using more than 1300 correlative profiles in March, September and December 2005. The over-all mean differences averaged over 15 and 35 km are approximately −2 K and standard deviation is less than 3 K. Below 20 km of altitude, relatively small mean temperature differences ∼1 K are observed in wide latitudinal range except for June (during the SABER nighttime observation). In the middle to low latitudes, between 30°S and 30°N, the temperature difference increases with height from ∼0–1 K at 15 km, to ∼−4 K at 35 km of altitude. Large temperature differences about −4 to −6 K are observed between 60°S and 30°N and 31–35 km of altitude for all months and between 0° and 30°N below 16 km during June (nighttime).     

Hypothesis-test-based landcover change detection using multi-temporal satellite images – A comparative study

Remote sensing images and technologies have been widely applied to environmental monitoring, in particular landuse/landcover classification and change detection. However, the uncertainties involved in such applications have not been fully addressed. In this paper two hypothesis-test-based change detection methods, namely the bivariate joint distribution method and the conditional distribution method, are proposed to tackle the uncertainties in change detection by making decisions based on the desired level of significance. Both methods require a data set of class-dependent no-change pixels to form the basis for class-dependent hypothesis test. Using an exemplar study area in central Taiwan, performance of the proposed methods are shown to be significantly superior to two other commonly applied methods (the post-classification comparison and the image differencing methods) in terms of the overall change detection accuracies. The conditional distribution method takes into consideration the correlation between digital numbers of the pre- and post-images and the effect of the known pre-image digital number on the range of the post-image digital number, and therefore yields the highest change detection accuracy. It is also demonstrated that the class-dependent change detection is crucial for accurate landuse/landcover change detection.     

线性尺寸未注公差标准演变及应用

从实际应用的角度出发，阐述了线性尺寸未注公差各标准的演变和主要特点，并提出了在机械加工应用中具有简明、省时、质优等特点。     

公差原则中相关要求的计算问题

关于公差原则中的相关要求的计算问题 ,本文提出了两种方法 :计算法和图解法。运用这两种方法可以简化此类问题的计算过程 ,准确求得计算结果。     

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.     

SPOT-5卫星系统性能概述

概要介绍SPOT - 5卫星的主要成像传感器 ,精确定位技术及数据格式。介绍分析卫星数据的应用前景     

2021 Turkey mega forest Fires: Biodiversity measurements of the IUCN Red List wildlife mammals in Sentinel-2 based burned areas

Mega wildfires are one of the environmental disasters worldwide. This study evaluates the pre-fire species diversity and the indirect effects, including habitat loss for one of the largest wildfires in Manavgat (Antalya-Turkey) in 2021, with a two-step methodology. Here, (1) burnt areas in the Manavgat district (2021) were detected with remote sensing data from Sentinel-2A by delta Normalized Burn Ratio calculation for a selected area in Google Earth Engine, and (2) mammals' habitat vector data of International Union for Conservation of Nature (IUCN) Red List were integrated into Habitat and Biodiversity modelling of Terrset to analyze the alpha, beta, gamma diversity and Range Restriction Index for the wildfire region. In the total 4210 km² study area, 696 km² of the area was damaged by different fire severity; also, there were 56 mammal species' habitats here. These species include bats (i.e. Nyctalus leisleri), felids (i.e. Felis chaus), rodents (i.e. Rattus norvegicus) and large mammals (i.e. Ursus arctos). 88 % of these species are in IUCN's Least Concern category. The remaining classes are Near Threatened (3.7 %) and Vulnerable (7.4 %). This study also indicated that the burnt area's species richness does not totally consist of endemic species. Therefore, pre-fire species richness analyses of this study can be a base for further studies about the species' post-fire activity and occupancy.Furthermore, the 2021 mega wildfires show us the necessity of wildfire monitoring and risk studies in the entire Mediterranean ecosystem to evaluate the risks to the Sustainable Development Goals. Therefore, post-fire spatial data, fire migration monitorization, and recording of the species' activities should be performed temporally. In this way, the ability of wildlife's recovering, and the direct and indirect effects of the fire will be examined for ecosystems in the long term.     

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.