Dynamic monitoring of drought using HJ-1 and MODIS time series data in northern China

From early November 2008 to February 2009, lack of rainfall led to severe drought in northern China. More than 9.3 million ha of wheat in six major crop production provinces, including Henan, Anhui, Shandong, Shanxi, Gansu, and Shaanxi, were hit by drought. Supported by Chinese HJ-1 satellite images together with NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data, dynamic monitoring of the drought was conducted. HJ-1 CCD data with 30-m resolution were used to identify cropland information. Spatial–temporal variation of drought was detected using Vegetation Index and Water Index time series data derived from MODIS visible, infrared, and short-wave infrared bands. The influences of drought were classified into five levels based on MODIS-derived 8-day composite Anomaly Water Index (AWI) and field survey data. The results indicated that the drought deteriorated beginning in November 2008 and became most serious in late January 2009. HJ-1 data together with MODIS data proved to be valuable data sources for monitoring soil moisture and drought at a both regional and national scale.     

Aeolian processes and landscape change under human disturbances on the Sonid grassland of inner Mongolian Plateau,northern China

Based on remote sensing monitoring, observations and experiments in wind tunnel and field, aeolian processes and landscape change of the Sonid grassland of Inner Mongolia Plateau in northern China were explored in this paper. Aeolian process was very strong and seriously affected by human disturbances on the Sonid grassland of Inner Mongolia Plateau. Sand transport rate of grassland increased quickly with the increase of desertification severities, especially at the very severe desertification stage of sand sheet emergence. Human disturbances can seriously destroy balanced-state soil surface to induce new soil wind erosion over and over again, in particular at the higher wind speeds. Spatial variation of wind erosion was strongly related to land use/cover change, and finally led to landscape change, while emergence of erosional bare patches might be the key link, especially around herdsmen’s settlements and along roads or fences. Avoiding grazing before windy season is very important for decreasing soil wind erosion, not only to protect vegetation cover, but also to reduce trampling-inducing destruction of the soil surface structure. Prohibition of overgrazing must be strictly obeyed under any possible climate conditions, and reclamation should be more careful. Reducing human disturbances by selective emigration and eco-compensation mechanism would be considered as a priority for reducing local wind erosion.     

用卫星资料反演中国西北地区东部蒸散量的遥感模型

根据定西干旱气象与生态环境试验基地的麦田微气象观测和研究区的124个气象站常规资料,结合NOAA-16/AVHRR的资料,采用地表能量平衡算法的卫星遥感模型估算了中国西北地区东部4～8月的日蒸散量及其区域分布,并按气候和土地利用类型分别统计灌溉农田、干旱草地、冬春小麦农田、针阔混合林、常绿林和沼泽草甸等不同地表的蒸散量平均值和标准差,揭示了作物不同生育期自南到北由湿润的常绿林区至半干旱雨养农田直到干旱的荒漠地带的蒸散递减的分布特征.模型探索了卫星遥感无法得到近地层气温的难点,从而提高计算精度.经试验区54站蒸发皿推算的日蒸散量检验,相对误差为16.6%,与定西用LI500型CO₂/H₂O通量仪实测的日蒸散量误差仅16.2%.结果表明计算的蒸散量与实测值在整个试验区内有良好的一致性.     

基于HJ-1B卫星数据的疏勒河上游流域地表温度反演

地表温度是描述地表和大气之间物质交换和能量平衡的关键参数之一. 利用疏勒河上游流域2010年7月25日过境的HJ-1B卫星数据, 采用修正的Jimenez-Mufloz&Sobrino普适性单通道算法反演了疏勒河上游流域的地表温度. 与MODIS LST产品的对比验证表明, 该算法在研究区有较高的精度. 同时, 对不同土地利用类型的地表温度的分析表明, 土地利用类型不同, 其地表温度存在一定的差异, 其中, 稀疏草地的地表温度最高, 裸岩次之. 研究发现, 在河流和冰川区, 修正的单通道算法可能高估了表面温度. 同时, 对模型反演所需的关键地表参数的敏感性分析发现, 算法在一定范围(0~0.01)内对比辐射率不太敏感, 但超过该范围则变得非常敏感, 而对大气水汽含量比较敏感. 因此, 一定程度上, 地表比辐射率和大气水汽含量的精度对HJ-1B卫星数据反演地表温度的准确性起主要作用.     

The correlation between geochemical data and SPOT satellite imagery of lateritic terrain in southern Mali

Detailed geochemical mapping of superficial lateritic formations is compared with recent high-resolution SPOT satellite images in the Dagadamou prospect in southern Mali.The two main landscape features standing out in SPOT images are expressed by thematic indices derived from multispectral data. They reflect the distribution of vegetation cover and the distinction between silty clay soils in the valleys and ferruginous duricrust exposed on the plateaus. Geochemical differentiation factors are closely related to the nature of sampled materials and reflect the relative amounts of major constituent minerals estimated by normative calculation.Duricrust samples with high Fe and Al content are also enriched in trace elements, P, V, Cr, As, Mo, Nb and Cu, immobilized in the weathering profile with secondary oxihydroxide minerals.Soils of flats are composed mainly of quartz and kaolinite; they also concentrate heavy minerals characterized by high contents of Zr, Ti, Ce and Y.Accumulation of detrital material at the periphery of duricrust plateaus is marked by a geochemical halo of higher contents in Zr and quartz at their periphery. This feature is clearly visible on SPOT imagery as a zone of high reflectance, devoid of vegetation.The density of vegetation on duricrust is related to its kaolinite content. Its distribution is characterized by a striped pattern, which is probably controlled by bedrock lithological structures preserved in the lateritic cover.This study shows the relationships, both direct and indirect, existing between spectral reflectance and geochemical composition of superficial lateritic formations. Many other landscape features identified with high resolution on SPOT images provide complementary information, which could be very helpful at various stages of geological and mineral exploration in lateritic terrain.     

夏季黑河流域蒸散发量卫星遥感估算研究

依据空气动力学方法和蒸散发量时间尺度扩展方案,利用MODIS资料和气象资料,计算中国西北内陆河黑河流域复杂地形下,2004年夏季7月蒸散发量空间分布及总量。利用Landsat-5TM资料对比分析发现,估算地表水热传输过程时,采用高分辨率遥感资料的估算结果受下垫面非均匀性影响程度,明显小于采用中分辨率资料。通过"金塔实验"湍流观测资料验证表明,利用高分辨率资料估算日蒸散发量的相对误差在10%以内。对月蒸散发量计算分析表明,黑河流域海拔2000m以上祁连山区,7月平均蒸散发量是海拔2000m以下山前地区的2.2倍,而山前平原区绿洲(NDVI>0.10区域)平均蒸散发量又是荒漠戈壁地区的12.3倍。因此,流域中下游绿洲地区特别是农业灌溉区是夏季主要水资源消耗区。     

Medium-range forecast of cyclogenesis over North Indian Ocean with multilayer perceptron model using satellite data

An attempt is made in this study to develop a model to forecast the cyclonic depressions leading to cyclonic storms over North Indian Ocean (NIO) with 3 days lead time. A multilayer perceptron (MLP) model is developed for the purpose and the forecast quality of the model is compared with other neural network and multiple linear regression models to assess the forecast skill and performances of the MLP model. The input matrix of the model is prepared with the data of cloud coverage, cloud top temperature, cloud top pressure, cloud optical depth, cloud water path collected from remotely sensed moderate resolution imaging spectro-radiometer (MODIS), and sea surface temperature. The input data are collected 3 days before the cyclogenesis over NIO. The target output is the central pressure, pressure drop, wind speed, and sea surface temperature associated with cyclogenesis over NIO. The models are trained with the data and records from 1998 to 2008. The result of the study reveals that the forecast error with MLP model varies between 0 and 7.2 % for target outputs. The errors with MLP are less than radial basis function network, generalized regression neural network, linear neural network where the errors vary between 0 and 8.4 %, 0.3 and 24.8 %, and 0.3 and 32.4 %, respectively. The forecast with conventional statistical multiple linear regression model, on the other hand, generates error values between 15.9 and 32.4 %. The performances of the models are validated for the cyclonic storms of 2009, 2010, and 2011. The forecast errors with MLP model during validation are also observed to be minimum.     

河岸带潜流层动态过程与生态修复

河岸带潜流层是河岸带内地表水与地下水相互作用的生态交错带,在水文地理学、生态学、环境学上含义不尽相同。河岸带潜流层具有复杂的垂向、横向、纵向结构特征,其边缘效应显著,表现为泥沙、水流、生物、环境化学因子之间的复杂动态过程,主要包括水动力动态过程、生态学过程、溶质循环与化学过程等。水动力动态过程是驱动条件,氧气浓度是生态过程、溶质循环和化学过程的决定性因素。在各动态过程的驱动下,河岸带潜流层具有调蓄洪水、削减污染、净化缓冲环境和提供适宜栖息地等功能。针对河岸带潜流层功能退化的问题,需开展健康诊断,明确致病机理,实施适宜的生态修复。未来中国在开展河岸带潜流层研究时,应根据中国河岸带特点,采用示踪试验、数值模拟等方法,集成GIS等现代技术手段,研究多尺度下,水文条件、地形变化、土壤渗透系数、河岸带建设方式、植被分布等对河岸带潜流层水文、热传导、生化、生态等的影响机制,准确界定河岸带潜流层区域范围,制定适宜的生态修复策略。     

Direct tangible damage assessment for regional snowmelt flood disasters with HJ-1 and HR satellite images: a case study of the Altay region,northern Xinjiang,China

Regional snowmelt flood disasters (RSFDs) can cause significant direct tangible damage which generally refers to the physical destruction due to direct contact with the flood water, such as damage to buildings, croplands, livestock, and infrastructure. Information about people, habitations, and infrastructure affected by the flood is essential for disaster responders and the humanitarian community to plan and coordinate emergency response activities. However, this direct tangible damage information obtained in the ground is limited, incomplete, contradictory, and sometimes impossible to obtain in a short time. Earth observation satellites help overcome operational uncertainties after the RSFDs. Here, we present an improved rapid direct tangible damage assessment model using HJ-1 and GF-1/2 satellite images. We selected the Altay region in northern Xinjiang, China, as the study area, and investigated a RSFD occurring in spring 2017. A series of HJ-1 and GF-1 images were used to track the flood extent over the duration of the disaster, and the maximum affected flood area was assigned as the area in which direct tangible damage occurred. Pre-disaster GF-2 images were then used to estimate direct tangible damage to habitations (2375 households and 6388 rooms), infrastructure (102 km of roads), and affected population (7125) in the flood area, which covered an area of 185,240 m². Our method is an effective approach for the design of rescue plans and disaster subsidy programs.     

Impact of industrial effluents on groundwater around Pali city, Rajasthan using field and satellite data

Groundwater pollution due to industrial effluents from textile units around Pali city area is the major concern to the local villagers and the district administration. Indiscriminate discharge of these effluents in the past two decades caused severe damage to the agricultural land and groundwater resources within 3 km buffer zone of the Bandi river. Remote Sensing and GIS techniques are found to be better tools in assessing the damage in agricultural crops during 1997 and 2006 with the help of high resolution satellite images. Groundwater fluctuation trend with annual rainfall pattern during 1985 and 2005 indicate good recharge in the study area. Detailed analysis of groundwater quality parameters (TDS, Cl and SO₄) and heavy metals (Cu, Pb, Zn, Fe, Cd and Cr) for 1997–98 indicates maximum concentration around Chatelao village and Dholera Jagir in the downstream direction of Bandi river. However, temporal analysis of groundwater samples collected in January, 2009 shows marginal decrease in concentration of TDS, Cl, SO₄, Pb and Cu in both groundwater as well as river effluents. Slight improvement in water quality especially heavy metals in the last 12 years (1998–2009) may be attributed to the appropriate measures (treatment of wastewater and solid waste disposal) taken by the establishment of three Common Effluent Treatment Plants (CETP) in Pali city area. However, a few stringent actions may be taken to avoid direct discharge of the effluents into Bandi river.     

Study of land surface temperature and spectral emissivity using multi-sensor satellite data

In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km², is a part of Singhbhum-Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show difference of LST up to 2°C. The results of the present study indicate that continuous monitoring of LST and emissivity can be undertaken with the aid of multi-sensor satellite data over a thermally homogeneous region.     

Evaluation and correction of the TRMM 3B43V7 and GPM 3IMERGM satellite precipitation products by use of ground-based data over Xinjiang,China

Satellite retrieval of precipitation is a great challenge in arid regions where light precipitation prevails. To improve the accuracy of satellite precipitation products in Xinjiang, which is the driest region in China, this study first evaluated the performance of two widely used monthly satellite products from April 2014 to August 2017. The first was the Tropical Rainfall Measuring Mission (TRMM) 3B43 version 7 (hereafter 3B43V7), and the second was the Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) (hereafter 3IMERGM). The 3IMERGM product was then corrected by a stepwise regression model using topographic variables derived from digital elevation model (DEM). A comparison between satellite estimates and in situ measurements indicates that both 3B43V7 and 3IMERGM overestimate precipitation overall, but that 3IMERGM performs better than 3B43V7. The relative biases (RB) of 3B43V7 and 3IMERGM were found to be 10.24 and 7.76%, respectively. The correlation coefficient (CC) between 3IMERGM and the gauges is 0.68, which is higher than the CC observed (i.e., 0.62) between 3B43V7 and the gauges. To comprehensively evaluate the performance of the corrected model, a tenfold cross-validation method was used. The results showed that the corrected 3IMERGM (C-3IMERGM) performed much better than 3IMERGM. Specifically, CC was increased from 0.68 to 0.73, and RB is decreased from 7.76 to ? 1.65%. Furthermore, C-3IMERGM achieves a better precipitation distribution than the uncorrected satellite product and even than scarce gauge measurements. The actual spatial pattern of precipitation represented that the precipitation bands in the Kunlun Mountains located in southern Xinjiang were captured by C-3IMERGM, but missed by the other products.     

Mapping and monitoring geological hazards using optical,LiDAR, and synthetic aperture RADAR image data

Geological hazards and their effects are often geographically widespread. Consequently, their effective mapping and monitoring is best conducted using satellite and airborne imaging platforms to obtain broad scale, synoptic coverage. With a multitude of hazards and effects, potential data types, and processing techniques, it can be challenging to determine the best approach for mapping and monitoring. It is therefore critical to understand the spatial and temporal effects of any particular hazard on the environment before selecting the most appropriate data type/s and processing techniques to apply. This review is designed to assist the decision-making and selection process when embarking on a hazard mapping or monitoring exercise. It focuses on the application of optical, LiDAR, and synthetic aperture RADAR technologies for the assessment of pre-event risk and post-event damage. Geological hazards of global interest summarized here are landslides and erosion; seismic and tectonic hazards; ground subsidence; and flooding and tsunami.     

Monitoring of urban heat island in Shanghai,China, from 1981 to 2010 with satellite data

This paper investigates the urban heat island (UHI) characteristics of Shanghai, China, during 1981–2010 using Landsat thematic mapper/multispectral scanner and moderate-resolution imaging spectroradiometer satellite data from the perspectives of time and space, with further analysis of the landscape pattern, the urban heat island effect ratio, and formative factors. The results show the following: (1) From the interannual variation, the secondary-medium temperature area and the medium temperature area are the main bodies of Shanghai UHI, accounting for 67.16–83.69 % of the total area, and have a rising trend over time. (2) From the landscape pattern, the secondary-medium temperature area and the medium temperature area have a dominant position over the whole UHI landscape pattern of Shanghai; the relatively high-temperature area gradually decreases, and its dominance over the whole UHI landscape pattern declines. (3) From the spatial distribution, the pattern in which the urban area initially had complete domination has gradually transformed to become primarily urban area centered and other construction land supplemented with rapid urbanization. Rapid increase of the green land in the urban area has to some extent reduced the UHI characteristics of the Shanghai area in recent years.     

喀斯特生态系统生物地球化学过程与物质循环研究:重要性、现状与趋势

喀斯特地质与生态系统是地球表层系统中的重要组成部分,其变化将对其他地区以及整个地球系统产生影响.生物地球化学循环是全球和区域变化研究的核心内容,而生态系统的演化与系统内水分和养分的生物地球化学循环密切相关。因此,我们有必要将喀斯特生态系统纳入到更大区域或全球生态系统中进行分析研究,在充分研究认识整个喀斯特生态系统物质生物地球化学循环规律的基础上,进一步研究喀斯特生态系统的全球变化响应或影响机制,为喀斯特生态系统优化调控对策和措施提供科学基础。研究生态系统演化过程中物质的生物地球化学循环规律,是研究植物适生性、物种优化配置和适应性生态系统调控机理的关键基础。在介绍前人工作基础的同时,本文全面而概括地总结了我们近年利用元素、同位素(如δ13C、δ15N、δ34S、87Sr/86Sr)示踪和化学计量学理论和方法对喀斯特生态系统中不同界面和流域中物质的生物地球化学循环及其生态环境效应的研究成果。认识到:喀斯特流域生物地球化学循环活跃,相互耦合,并与流域生态环境变化相互制约;人类活动正干预流域物质的自然生物地球化学循环过程,并导致相应的生态和环境效应;全球变化科学深化有赖于区域生态环境变化及物质生物地球化学循环的研究。这些认识是我们将来系统深入开展喀斯特以及其他流域生态系统物质生物地球化学循环研究的重要方向。     

Estimation of snow cover distribution in Beas basin,Indian Himalaya using satellite data and ground measurements

In the present paper, a methodology has been developed for the mapping of snow cover in Beas basin, Indian Himalaya using AWiFS (IRS-P6) satellite data. The complexities in the mapping of snow cover in the study area are snow under vegetation, contaminated snow and patchy snow. To overcome these problems, field measurements using spectroradiometer were carried out and reflectance/snow indices trend were studied. By evaluation and validation of different topographic correction models, it was observed that, the normalized difference snow index (NDSI) values remain constant with the variations in slope and aspect and thus NDSI can take care of topography effects. Different snow cover mapping methods using snow indices are compared to find the suitable mapping technique. The proposed methodology for snow cover mapping uses the NDSI (estimated using planetary reflectance), NIR band reflectance and forest/vegetation cover information. The satellite estimated snow or non-snow pixel information using proposed methodology was validated with the snow cover information collected at three observatory locations and it was found that the algorithm classify all the sample points correctly, once that pixel is cloud free. The snow cover distribution was estimated using one year (2004–05) cloud free satellite data and good correlation was observed between increase/decrease areal extent of seasonal snow cover and ground observed fresh snowfall and standing snow data.     

Four major unknown active faults identified,using satellite data,in India and Pakistan portions of NW Himalaya

Natural Hazards - New mapping through geomorphic analysis of tectonic landforms using a variety of freely available satellite data, including shuttle radar topography and Google Maps, has revealed...     

Monitoring of Dead Sea water surface variation using multi-temporal satellite data and GIS

Remote sensing (RS) and geographic information systems (GIS) are very useful for environmental-related studies, particularly in the field of surface water studies such as monitoring of lakes. The Dead Sea is exposed to very high evaporating process with considerable scarcity of water sources, thus leading to a remarkable shrinkage in its water surface area. The lake suffers from dry out due to the negative balance of water cycle during the previous four decades. This paper discusses the application of RS, GIS, and Global Positioning System to estimate the lowering and the shrinkage of Dead Sea water surface over the period 1810–2005. A set of multi-temporal remote sensing images were collected and processed to show the lakes aerial extend shrinkage from 1973 up to 2004. Remote sensing data were used to extract spatial information and to compute the surface areas for Dead Sea for various years. The current study aims at estimating the fluctuation of Dead Sea level over the study period with special emphasis on the environmental impact assessment that includes the degradation level of the Dead Sea. The results indicated that there is a decrease of 20 m in the level of the Dead Sea that has occurred during the study period. Further, the results showed that the water surface area of the Dead Sea has shrunk from 934.26 km² in 1973 to 640.62 km² in 2004.