Structural features and petroleum geology of the fold-thrust belt in the southern Tarim basin, China

The west Kunlun fold-thrust belt (WKFTB) and the Altun fold-thrust belt (AFTB) are respectively located in the southern margin of the Tarim basin, NW China. The analyses of typical structures and regional dynamics of the fold-thrust belts reveal their different structural and petroleum features and mechanisms. WKFTB differs from AFTB by abundant fault-related folds and triangles zones, and was formed by northward extrusion of the west Kunlun orogen. AFTB was affected synchronously by northward extrusion of the Altun orogen and the sinistral strike-slipping of the Altun Fault, so it is characterized by the minor scale and the monotonous structural styles. The Aqike anticline and the Aqike fault, of which the strikes are orthogonal to the strike of the fold-thrust belts, are regarded as the adjustive structures between both of the fold-thrust belts. The oil-gas pools of WKFTB develop mainly in the faulted-related anticline traps, but the oil-gas pools of AFTB develop mainly in the low fault-block and anticlines traps related with the paleo-uplifts. There are different exploration countermeasures for both of the fold-thrust belts.     

Spatio-temporal suspended sediment fingerprinting under different land management practices

Understanding spatio-temporal suspended sediment dynamics is more important in large watersheds due to the decisive role of local source apportionment in sediment transport and yield. The Talar River with a large mountainous watershed in northern Iran, which plays a vital role in water supply for agriculture and drinking, recently has faced quality degradation. The current study explores the relative contribution of suspended sediment sources using geochemical tracers and fingerprinting techniqu...     

基于DOM的宁波市城市用地调查

介绍以DOM，进行城市用地调查方式，极大的提高了调查的效率。     

基于3S技术的土地开发整理探讨

土地开发整理对于节约土地资源、维持可持续发展具有重要作用,是一项涉及多方面的复杂系统工程。3S技术为土地利用信息获取和土地开发整理提供了必要的技术支撑,本文在总结分析3S技术特点的基础上,设计了基于3S技术的土地开发整理体系,该体系可以为土地开发整理工作提供借鉴。     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.     

基于最佳用途的土地用途有偿管制机制探索

当前基于现状用途的管制存在管制方式偏行政化、管制手段无偿化导致农村集体土地收益偏向国有、非农产业和城市分配,重塑用途管制制度已显示出迫切性。本文探索基于最佳用途,通过"用途差"和"用途差"交易实现土地用途有偿管制的机制,认为通过用途有偿管制机制不仅可以保护农用地,特别是耕地资源,保障土地资源的可持续利用。而且,可激活土地资源价值,特别是有助于农用地资源资产、资本化,缩小农村、农业和农民家庭资产与收入与城镇的差距。     

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.     

Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellites

Stresses building up during an earthquake preparation phase also manifest themselves in the form of a so called increased land surface temperature (LST) leading to a thermal precursor prior to the earthquake event. This phenomenon has now been validated by our observations of short-term thermal anomalies detected by infrared satellite sensors for several recent past earthquakes around the world. The rise in infrared radiance temperature was seen to vary between 5 and 12 °C for different earthquakes. We discuss in this paper different explanations for the generation of such anomalies that have been offered. Emission of gases due to the opening and closure of micropores upon induced stresses and also the participation of ground water have been propounded as a possible cause for generation of thermal anomalies. Seismo-ionosphere coupling, by which gases like radon move to the earth–atmosphere interface and cause air ionization thus bringing about a change in air temperature, relative humidity, etc., has been put forth by some workers. A mechanism of low frequency electromagnetic emission was tested and experimented by scientists with rock masses in stressed conditions as those that exist at tectonic locations. The workers proposed the positive hole pair theory, which received support from several scientific groups. Positive holes (sites of electron deficiency) are activated in stressed rocks from pre-existing yet dormant positive hole pairs (PHPs) and their recombination at rock–air interface leads to a LST rise. A combination of remote sensing detection of rock mechanics behavior with a perception of chemistry and geophysics has been applied to propose the remote sensing rock mechanics theory. Remote sensing detections of such anomalies confirm so far proposed lab theories for such a hotly debated field as earthquake precursor study by providing unbiased observations with consistency in time and space distribution.     

乡镇土地利用规划管理信息系统设计与实现

针对当前乡镇土地利用规划中存在的问题,运用GIS的数据管理和空间分析等功能,结合规划区域的实际状况,开发了一个面向乡镇的土地利用规划管理信息系统,提高了土地管理的工作效率和信息化水平,能够实现乡镇土地的合理利用。