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Architectural heritage health assessment is the basis of scientific repair and maintenance. However, existing methods do not adequately take into account the fuzziness, randomness and uncertainties unique to architectural heritage assessment. In this paper, a new evaluation model of VM-NCM is constructed by combining variable weight theory and normal cloud model theory. The model enables the combination of qualitative ratings and quantitative calculation, deals with the fuzziness in the assessment process, and resolves the randomness and reflects the uncertainty to a certain extent. Based on constructing the index system combining qualitative and quantitative indexes, the structural index values are acquired by the synergistic coupling of the fine laser point cloud model and finite element structural analysis model. The acquisition of surface index values is completed by the hyperspectral intelligent detection technology of surface materials and diseases. These reduce the generation of ambiguous information in the index detection process. An evaluation study is conducted using the Yingxian wooden pagoda in China as an example. The results show that this method takes into account the fuzziness and randomness in the evaluation process, and obtains more scientific and reliable evaluation results, which provides a research paradigm for assessing the architectural heritage health status. [ABSTRACT FROM AUTHOR]

Using deep learning in remote sensing interpretation could reduce a lot of human and material costs. Semantic segmentation is the main method for this task. It can automatically outline the objects and it has recently achieved great success in remote sensing images. However, in the appliance of remote sensing interpretation, the accuracy of contour largely determines the evaluation of remote sensing interpretation. Though the current loss functions reflect the segmentation performance, they could not guide the model to optimize itself toward a more precise contour. This paper proposed an exactly defined contour loss (CL) for remote sensing interpretation with Residual Attention U-Net (RA U-Net) as the main framework. The RA U-Net uses the residual attention module as the skip connection layer. It enhances the judgment of U-Net. In CL, image processing methods are used to extract the contours of the foreground. And elements-sum and elements-subtract operations are used to transfer the contour information to a matrix of the same size as label images. Then, these matrices would be the weights for CE. By assigning different weights for different elements in different regions, this function will guide the model to reach a balance between accurate segmentation results and precise contours. The experiment on open datasets shows a good performance. The proposed model was also trained on the Construction Disturbance Dataset collected from Jiang Xi Province, China. The dataset was labeled manually. The evaluation enhanced a lot on the Construction Disturbance Dataset and the IoU on two datasets increased 1 % to 2 % when using CL as the loss function. This paper also compared the proposed method with other state-of-the-art methods and the results showed extensive effectiveness. [ABSTRACT FROM AUTHOR]

On June 17, 2020, Aniangzhai landslide, an ancient landslide located in Danba County, southwest China, was reactivated by Meilonggou debris flow. The front edge of the slope collapsed, mobilizing a soil mass of about 2.35 × 106 m3. Evaluating the stability of the whole slope is of great importance to avoid further landslides and mitigate the damage for Aniangzhai villagers living on this slope. This paper focuses on the inaccessible upper slope of Aniangzhai landslide (no attention paid before) that exhibits a relative elevation difference of more than 1000 m. Multi-source remote sensing, including unmanned aerial vehicle (UAV) photogrammetry, light detection and ranging (LiDAR), and satellite-based interferometric synthetic aperture radar (InSAR) techniques, was used in this research to identify and evaluate this high mountain upper slope potential hazard in Aniangzhai landslide. Considering the huge height difference and the steep slope of Aniangzhai landslide, an iterative route planning method was proposed and adopted to obtain a 3D model with 0.02 m resolution and a DEM with 0.25 m resolution by using UAV and LiDAR close-in flight method, respectively. Meter-level huge cracks were clearly identified by the high-resolution UAV 3D model and LiDAR data, which confirm that the location of these cracks is related to the morphological structure of this ancient landslide. Time series InSAR analysis reveals the activity of this high-altitude area, with a maximum LOS displacement rate of 15 cm/a. The combination of the above remote sensing technologies confirms and reveals the high potential risk and the reactivated condition of the upper slope of Aniangzhai landslide. Through this finding, we show that the evolution of Aniangzhai landslide happened through four stages with a cascading effect. This paper proves the usefulness of an integrated method to successfully identify and evaluate the high-altitude upper slope potential hazard and compares the technical features of them, providing a reference for future works that aimed at mitigating the potential damage of the upper slope. [ABSTRACT FROM AUTHOR]

Thunderstorms are usually accompanied by heavy precipitation and other disasters. Therefore, it is very important to study the thermodynamic and dynamic mechanisms that control the occurrence and development of storms. However, the relatively coarse resolution of the reanalysis may limit the evaluation and application of its derived convective parameters at regional and local scales, especially in high mountains. Given that the effect of grid averaging on ERA5 can be well-reflected in the monthly mean, the paper proposes a methodological framework to achieve the statistical downscaling of convective parameters (SDCP). After the convection-related variables are decomposed, we introduce a multi-scale geographically weighted regression (MGWR) model and take the Normalized Difference Vegetation Index (NDVI) and the Digital Elevation Model (DEM) as explanatory variables to improve the spatial resolution of monthly-scale convective parameters. The convective parameters chosen for the downscaling experiments are closely related to thunderstorm occurrence, involving instability, moisture, and wind shear. ERA5 and SDCP datasets' quality is evaluated based on measurements available from 11 radiosonde stations over 10 years. We also explore the climatology of thunderstorm environments and the corresponding trends. The results show that the accuracy of the SDCP data obtains additional added value in complex-terrain areas. Compared with ERA5, the downscaled results have a finer spatial structure. A strong but spatially and scale-varying relationship exists between the monthly mean convective parameter and the resampled NDVI and DEM. Considering the very high predictive ability of the MGWR model, the performance of the SDCP algorithm mainly depends on the accuracy of the ERA5 data. Our study demonstrates the possibility of high spatial resolution land surface features observed by remote sensing satellites in improving the spatial resolution of thermodynamic parameters. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in crop yield estimation, irrigation management, etc. Remote sensing technology has potential for large-scale and high spatial soil moisture mapping. However, offline remote sensing data processing is time-consuming and resource-intensive, and significantly hampers the efficiency and timeliness of soil moisture mapping. Due to the high-speed computing capabilities of remote sensing cloud platforms, a High Spatial Resolution Soil Moisture Estimation Framework (HSRSMEF) based on the Google Earth Engine (GEE) platform was developed in this study. The functions of the HSRSMEF include research area and input datasets customization, radar speckle noise filtering, optical-radar image spatio-temporal matching, soil moisture retrieving, soil moisture visualization and exporting. This paper tested the performance of HSRSMEF by combining Sentinel-1, Sentinel-2 images and in-situ soil moisture data in the central farmland area of Jilin Province, China. Reconstructed Normalized Difference Vegetation Index (NDVI) based on the Savitzky-Golay algorithm conforms to the crop growth cycle, and its correlation with the original NDVI is about 0.99 (P < 0.001). The soil moisture accuracy of the random forest model (R2 = 0.942, RMSE = 0.013 m3/m3) is better than that of the water cloud model (R2 = 0.334, RMSE = 0.091 m3/m3). HSRSMEF transfers time -consuming offline operations to cloud computing platforms, achieving rapid and simplified high spatial resolution soil moisture mapping. [ABSTRACT FROM AUTHOR]

Based on the digital elevation data, snow depth and snow cover remote sensing data, this paper divides six snow evolution areas and geographical partitions, extracts the geographical partitions of each evolution area and obtains the geographical characteristics of the evolution area for analysis. The results show that: (1) From 2003 to 2017, the average snow area decreased at a rate of − 0.004, and the average snow depth increased at a rate of 0.03. (2) The snow in the middle altitude hill with shady gentle slope area is the most obvious in the seasonal evolution, and the percentage of this region in the seasonal snow evolution area is 5.46%, the snow depth in the middle altitude hill with sunny and gentle slopes area increased and decreased significantly in the past 15 years, and the percentage of this region in the SD significant changes evolution area was 6.32%. The snow in the low relief middle altitude mountain with shady and moderate slope area not only shows obvious seasonal evolution, but also increases and decreases significantly in snow depth. And the percentage of this region in the seasonal snow significant evolution area is 5.82%. (3) The geographical partitions with the largest area in all evolution areas is the middle altitude hill with sunny and gentle slopes area (4.75%). (4) The geographical partition with the largest variation of snow depth in Tianshan region is the low relief middle altitude mountain with shady and moderate slope area (12.02 cm). (5) The snow accumulation and melting are obvious in the range of 1000–3500 m above altitude, different geomorphology types lead to obvious differences in snow characteristics. The snow melting is most obvious in the gentle slope area of the low topographic relief geomorphology types, and the snow accumulation is most obvious in the steep slope area of the middle relief geomorphology types. [ABSTRACT FROM AUTHOR]

Landslides which occur at unexpected locations and times, and which have unrecognizable risk areas, often cause mass casualties. Despite there being few preceding landslides in the same season, the catastrophic Qijiaba landslide occurred in the new government-selected settlement of Wufu village, Sichuan Province, China, on September 5, 2021, killing three people and destroying 13 houses. In this paper, the landslide features and causes are discussed based on field investigations, remote sensing interpretations, and laboratory-based soil experiments. The results showed that it was a typical soil landslide within a geomorphic hollow of the slope with a volume of 20,230 m3, recurrence interval of at least 69 years, and runout distance of 137.5 m. This type of landslide is difficult to predict. The soil strength in the sliding surface decreased suddenly as the water content increased, and the soil's rich clay mineral and high clay particle contents determined its high mobility (Heim's ratio of 0.44). The occurrence time of the Qijiaba landslide lagged 1.3 days behind the peak rainfall, and the 2-day cumulative rainfall was a crucial factor in the landslide occurrence. Finally, the large water confluence area behind the main scarp was determined to be 3.9 times the area of the landslide itself, thereby providing abundant water conditions to induce failure. The factors underlying the casualties included inappropriate site selection, insufficient awareness of potential landslides, and failure to evacuate in time. The results of this study provide a basis for future prevention, mitigation, and early warning of similar landslides. [ABSTRACT FROM AUTHOR]

Algal blooms in lakes have become a common global environmental problem. Nowadays, remote sensing is widely used to monitor algal blooms in lakes due to the macroscopic, fast, real-time characteristics. However, it is often difficult to distinguish between algal blooms and aquatic vegetation due to their similar spectral characteristics. In this paper, we used modified vegetation presence frequency index (VPF) based on Moderate-resolution Imaging Spectroradiometer (MODIS) imagery to distinguish algal blooms from aquatic vegetation, and analyzed the spatial and temporal variations of algal blooms and aquatic vegetation from a phenological perspective for five large natural lakes with frequent algal bloom outbreaks in China from 2019 to 2020. We simplified the VPF method to make it with a higher spatial transferability so that it could be applied to other lakes in different climatic zones. Through accuracy validation, we found that the modified VPF method can effectively distinguish between algal blooms and aquatic vegetation, and the results vary from lake to lake. The highest accuracy of 97% was achieved in Hulun Lake, where the frequency of algal outbreaks is low and the extent of aquatic vegetation is stable, while the lowest accuracy of 76% was achieved in Dianchi Lake, which is rainy in summer and the lake is small. Analyses suggests that the time period when algal blooms occur most frequently might not coincide with that when they have the largest area. However, in most cases these two are close in terms of time period. The modified VPF method has a broad scope of application, is easy to implement, and has a high practical value. Furthermore, the method could be established using only a small amount of measured data, which is useful for water quality monitoring on large spatial scales. [ABSTRACT FROM AUTHOR]

To better implement the Strategy of Rural Revitalization, it is essential to characterize the rural settlements and understand their roles in the socio-environmental interactive system. This paper is hence aimed at achieving such a study using different spatial analysis such as kernel density and spatial autocorrelation (SA) and modeling approaches, e.g., simple and multiple linear regression analyses taking Jiangxi, a province in China as an example. Remote sensing, topographic and socioeconomic data were employed for this purpose. Through these analyses, it is found that the rural settlements in the study area appear to have a spatial distribution pattern of "dense north and sparse south" as an "F" type, and are quantitatively characterized as low elevations, flat terrain, high river and road densities, rich cultivated land resources and susceptible to the impact of urban radiation with a R2 of 0.520–0.748. Based on this understanding, a new inequality evaluation indicator of rural development, i.e., socio-environmental evaluation index (SEI), was developed. Areas with SEI lower than 0.40 should be given a priority to implement the revitalization strategy in the province. This index can also be extended to study of the imbalance of rural development in other regions and countries. [ABSTRACT FROM AUTHOR]

On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully. [ABSTRACT FROM AUTHOR]

A rainfall-induced catastrophic landslide occurred at UTC + 8 03:50 local time on August 21, 2020, in Zhonghaicun village (N 29°20′30″, E 102°41′40″), Hanyuan County, Sichuan Province, China, resulting in damage to 6 buildings and 9 casualties (7 fatalities and 2 missing). In this paper, multitemporal remote sensing images, comprehensive field investigations, drilling holes, deformation monitoring, and numerical simulations are used to identify the main characteristics and the formation mechanism of the event. The results showed that long-term intensive rainfall in 2020 played an essential role in the failure of the Zhonghaicun landslide and that strong earthquakes in Wenchuan County (Ms 8.0, on 12 May 2008) and Lushan County (Ms 7.0, on 20 April 2013) also exerted a negative influence on the evolution process of this catastrophic landslide. Several traction zones appeared after the occurrence of the landslide. Fortunately, no evident deformation was observed and these slopes were in a stable state. In addition, a large-scale potential sliding slope, four small-scale landslides, and a debris flow were found in the study area. [ABSTRACT FROM AUTHOR]

China's first Mars exploration mission (HuoXing-1) has been named as 'Tianwen-1' meaning Heaven Inquiry. Tianwen-1 was launched on July 23, 2020. In this paper, the scientific objectives of earlier and current Mars exploration missions worldwide are reviewed, and the scientific objectives, payloads and preliminary scientific investigation plan of China's first Mars exploration mission are introduced, and expected scientific achievements are analyzed. [ABSTRACT FROM AUTHOR]

PM2.5 (Fine particulate matter in the atmosphere) pollution has become a major problem affecting human health and social development, especially in developing countries like China. The interaction between PM2.5 and the underlying factors across different regions or spatial scales are very complex, so it is helpful to study the spatial distribution and evolution of PM2.5, which is the foundation for carrying out regional collaborative governances. However, there is a paucity of this kind of research in China. This paper tries to put forward a new multi-scalar framework based on the spatiotemporal synthesis. After the spatial distribution and evolution of PM2.5 data is integrated with the methods of remote sensing, geographic information system and social ecological system analysis, we can more properly describe the evolving trajectory and characteristics of PM2.5 at different time–space scales. The paper defines and divides the space influenced by PM2.5 into four categories, which indicate the paths of spatial diffusion and finally puts forward the methodology of regional collaboration and environmental governance. [ABSTRACT FROM AUTHOR]

Time series land cover maps are important materials for the work related to land use and land cover change. Satellite remote sensing images prove advantageous in fast mapping with low cost. In most time series land cover products yielded by the satellite remote sensing images, a number of illogical transitions exist between different time phases. The time series land cover products cannot exactly reflect the real land cover types and land cover changes for each pixel. The accuracy evaluation based on the limited ground truth cannot well guide the users because the reliability of different pixels of the land cover products is unknown. A generic model for the reliability evaluation of time series land cover products should be developed based on a strong theoretical frame. In order to better guide the use of the land cover products, this paper proposed an approach to evaluate the reliability of time series land cover products by exploiting the joint probability of hidden Markov model (HMM), in which the classification performance and the spatio-temporal relationships were taken into account. We applied the proposed evaluation method on the time series land cover maps of Poyang Lake Eco-economic Region in China. The reliability of the land cover products was presented by the grading of the joint probability of HMM. The results effectively reflected the classification performance, the spatio-temporal relationships and even the quality of the data source. [ABSTRACT FROM AUTHOR]

Landslide disasters are associated with severe losses on the Loess Plateau of China. Although early warning systems and susceptibility mapping have mitigated this issue to some extent, most methods are qualitative or semi-quantitative in the site-specific range. In this paper, a quantitative spatial distribution model is presented for site-specific loess landslide hazard assessment. Coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides that have occurred since 2004 on the Heifangtai terrace were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter back analysis, and the accuracy of the simulation results is quantitatively evaluated by the centroid distance and overlapping area. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume, and different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. The results of this study reveal that landslide volumes mainly range between 1 × 103 and 5 × 105 m3, and the historical occurrence probability reaches 0.551. The optimal parameters are estimated by the maximum likelihood method to obtain a uniform distribution parameter value probability model, and the results show that the error of the estimated length within a range of 0.05 from the optimal parameter does not exceed 15%. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. This work provides a useful reference for local disaster reduction and a theoretical methodology for hazard assessments. [ABSTRACT FROM AUTHOR]

Desertification is one of the major challenges facing humanity. However, there is no effective way to effectively control desertification. China is experiencing serious desertification, and to alleviate this trend, China has implemented a series of major ecological projects since 1978 and has achieved good results. Remote sensing can record changes in surface processes over a long period of time and can play an active role in desertification monitoring and governance. However, there is no systematic remote sensing monitoring method for desertification. In response to this problem, this paper takes a demonstration and reconstruction project of the United Nations desertification in the Kubuqi Desert in China as an example. By using the 30-year time series Landsat data, we propose a new remote sensing monitoring method for the impact of ecological restoration engineering of desert to monitor the spatial and temporal evolution pattern of the Kubuqi Desert in the past 30 years and the impact of the human ecological reconstruction project on the location of land use types in the Kubuqi Desert. In addition, the method analyzes the impact of the Kubuqi Desert Reconstruction Project on the local ecological environment changes from time and space perspectives. The results show the following: (1) During 1991–2017, the Kubuqi Desert Reconstruction Project improved the cultivated land, afforestation, and the Yellow River Drainage to control the sand and in conjunction with other renovation projects improved the ecological environment. The area of the sandy land decreased from 45.76% to 28.66%, while the areas of the waters wetland and artificial forest (shrub), urban construction land, and agricultural land increased; (2) There are obvious time and space differences in the transformation, and the vegetation cover increases as a whole. The obvious change areas are mainly distributed in the riverbank irrigation area of the Yellow River section of the Kubuqi Desert and the torrents such as the Maobula Kong, Buer Taigou and Heilaigou and other mountain gully areas. The relevant experience of the Kubuqi Desert Reconstruction Project in China has important reference significance for world desertification transformation. [ABSTRACT FROM AUTHOR]

Satellite remote sensing technology has been widely used in environmental protection in China. Based on China's environmental protection characteristics, this paper reviews the application advancements of optical, infrared, microwave and hyperspectral satellite remote sensing techniques in atmospheric environment, water environment and ecological environment, respectively, including the atmospheric environment monitoring of aerosols, particulate matter, pollution gases, and greenhouse gases; the water environment monitoring of water blooms water quality, oil spills, water pollution and drinking water safety; the ecological environment monitor of national nature reserves, environmental damages from mines development, soil contamination, urban/rural ecological environment and biodiversity richness. Furthmore, it summarizes the limitations and future directions of satellite remote sensing studies in China environmental protection. The paper specifically notes that the development of high-resolution satellite remote sensing technology, as well as the launch and use of China series satellites could significantly improve the level of government's environmental management. [ABSTRACT FROM AUTHOR]

Extreme heat events have serious effects on human daily life. Accurately capturing the dynamic variance of extreme high-temperature distributions in a timely manner is the basis for analyzing the potential impacts of extreme heat, thereby informing risk prevention strategies. This paper demonstrates the potential application of multiple source remote sensing data in mapping and monitoring the extreme heat events that occurred on Aug. 8, 2013 in Jiangsu Province, China. In combination with MODIS products, the thermal sharpening (TsHARP) method and a binary linear model are compared to downscale the original daytime FengYun 2F (FY-2F) land surface temperature (LST) imagery, with a temporal resolution of 60 min, from 5 km to 1 km. Using the meteorological measurement data from Nanjing station as the reference, the research then estimates the instantaneous air temperature by using an iterative computation based on the Surface Energy Balance Algorithm for Land (SEBAL), which is used to analyze the spatio-temporal air temperature variance. The results show that the root mean square error (RMSE) of the LST downscaled from the binary linear model is 1.30°C compared to the synchronous MODIS LST, and on this basis the estimated air temperature has the RMSE of 1.78°C. The spatial and temporal distribution of air temperature variance at each geographical location from 06:30 to 18:30 can be accurately determined, and indicates that the high temperature gradually increases and expands from the city center. For the spatial distribution, the air temperature and the defined scorching temperature proportion index increase from northern to middle, to southern part of Jiangsu, and are slightly lower in the eastern area near the Yellow Sea. In terms of temporal characteristics, the percentage of area with air temperature above 37°C in each city increase with time after 10:30 and reach the peak value at 14:30 or 15:30. Then, they decrease gradually, and the rising and falling trends become smaller from the southern cities to the northern regions. Moreover, there is a distinct positive relationship between the percentage of area above 37°C and the population density. The above results show that the spatio-temporal distributions of heat waves and their influencing factors can be determined by combining multiple sources of remotely sensed image data. [ABSTRACT FROM AUTHOR]

With rapid urban development in China in the last two decades, the three-dimensional (3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area (two-dimensional (2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System (GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes. [ABSTRACT FROM AUTHOR]

Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions (GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority (UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the characteristics of the landslides developed in the epicentral area of AD 1556 M~8.5 Huaxian Earthquake, and discuss their relations to the active normal faults in the SE Weihe Graben, Central China. The results from analyzing high-resolution remote-sensing imagery and digital elevation models (DEMs), in combination with field survey, demonstrate that: (i) the landslides observed in the study area range from small-scale debris/rock falls to large-scale rock avalanches; (ii) the landslides are mostly developed upon steep slopes of ≥30°; and (iii) the step-like normalfault scarps along the range-fronts of the Huashan Mountains as well as the thick loess sediments in the Weinan area may facilitate the occurrence of large landslides. The results presented in this study would be helpful to assess the potential landslide hazards in densely-populated areas affected by active normal faulting. [ABSTRACT FROM AUTHOR]

Wetland databases can provide the basic data that necessary for the protection and management of wetlands. A large number of wetland databases have been established in the world as well as in China. In this paper, we review China's wetland databases based on remote sensing (RS) technology after introducing the background theory to the application of RS technology in wetland surveys. A key conclusion is that China's wetland databases are far from sufficient in fulfilling protection and management needs. Our recommendations focus on the use of the hyper-spectral imagery, microwave data, multi-temporal images, and automatic classifications in order to improve the accuracy and efficiency of wetland inventory. Further, attention should also be paid to detect major biophysical features of wetlands and build wetland databases in years after the 1980s in China. Considering that great gap exists between RS experts and wetland experts, further cooperation between wetland scientists and RS scientists are needed to promote the application of RS in the foundation of wetland databases. [ABSTRACT FROM AUTHOR]

Drought is a serious problem in southwestern China, where drought risk exceeds the national average. Climate change is likely to exacerbate the problem, thereby endangering China's food security. In this paper, we used the analytic hierarchy process and meteorological, geographic, soil, and remote-sensing data to develop a drought risk assessment model based on the drought hazard, environmental vulnerability, sensitivity and exposure of the values at risk, and capacity to prevent or mitigate the problem. Using the model, we assessed the drought risk (defined using a comprehensive drought risk index, R) and its spatial distribution in southwestern China and revealed complex zonality. The eastern part of the study area had an extremely high risk, and risk was generally greater in the north than in the south, and increased from southwest to northeast. The comprehensive risk ( R) was lowest in Yunnan province. It was highest in Sichuan Province and Chongqing Municipality. The contribution of the risk factors to R was highest for the capacity for prevention and mitigation, followed by the drought hazard, sensitivity and exposure, and environmental vulnerability. [ABSTRACT FROM AUTHOR]

The arid region of northwest China is a large area with complex topography. Hydrological research is limited by scarcity and uneven distribution of rain gauges. Satellite precipitation products provide wide coverage and high spatial-temporal resolutions, but the accuracy needs to be evaluated before application. In this paper, the reliability of four satellite precipitation products (CMORPH [Climate Prediction Center's morphing technique], PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks], TRMM [Tropical Rainfall Measuring Mission] 3B42, and TRMM 3B43) were evaluated through comparison with ground data or reported values on daily, monthly, and annual scales from 2003 to 2010. Indices including frequency bias index, probability of detection, and false alarm ratio were used to evaluate recorded precipitation occurrences; relative mean bias, the correlation coefficient, and the Nash coefficient were used to assess precipitation amount. Satellite precipitation products were more accurate in the warm than in the cold season, and performed better in northern Xinjiang than in other regions during the cold season. CMORPH and PERSIANN tended to overestimate precipitation. TRMM 3B42 and TRMM 3B43 performed best because the former most accurately detected precipitation occurrences on a daily scale, and both produced accurate space-time distribution of precipitation and the best consistency with rain gauge observations. Only a few monthly precipitation values for TRMM 3B42 and TRMM 3B43, and annual precipitation values for TRMM 3B42 were with satisfactory precision. TRMM3B42 and TRMM 3B43 are therefore recommended, but correction will be needed before application. Factors including elevation, relative relief, longitude, and latitude had significant effects on the performance of satellite precipitation products, and these factors may be helpful in correcting satellite precipitation. [ABSTRACT FROM AUTHOR]

China is a major coal-producing country that consumes large amounts of coal every year. Due to the existence of many small coal kilns using backward mining methods, numerous worked-out areas have been formed. The coal mines were abandoned with no mitigation, so air penetrates into the roadways and contacts the coal seams; as a result, the residual coal seams spontaneously ignite to form coal fires. These coal fires have burned millions of tons of valuable coal resources and caused serious environmental problems. To implement fire suppression more effectively, coal fire detection is a key technology. In this paper, thermal infrared remote sensing from unmanned aerial vehicle combined with a surface survey is used to identify the range of coal fires in the Huojitu coal mine in Shenmu city. The scopes and locations of the fire zones are preliminarily delineated, which provides an accurate basis for the development of fire suppression projects. [ABSTRACT FROM AUTHOR]

Rapid social and economic development results in increased demand for water resources. This can lead to the unsustainable development and exploitation of water resources which in turn causes significant environmental problems. Conventional water resource management approaches, such as supply and demand management strategies, frequently fail to restore regional water balance. This paper introduces the concept of water consumption balance, the balance between actual evapotranspiration (ET) and target ET, and establishes a framework to realize regional water balance. The framework consists of three stages: (1) determination of target ET and actual ET; (2) quantification of the water-saving requirements for the region; and (3) reduction of actual ET by implementing various water saving management strategies. Using this framework, a case study was conducted for Guantao County, China. The SWAT model was utilized to aid in the selection of the best water saving management strategy by comparing the ET of different irrigation methods and crop pattern adjustments. Simulation results revealed that determination of SWAT model parameters using remote sensing ET is feasible and that the model is a valuable tool for ET management. Irrigation was found to have a greater influence on the ET of winter wheat as compared to that of maize, indicating that reduction in winter wheat cultivation is the most effective way to reduce regional ET. However, the effect of water-saving irrigation methods on the reduction of ET was not obvious. This indicates that it would be difficult to achieve regional ET reduction using water-saving irrigation methods only. Furthermore, selecting the best water saving management strategy by relying solely on the amount of reduced ET was insufficient, because it ignored the impact of water conservation measures on the livelihood of the agricultural community. Incorporating these considerations with our findings, we recommend changing the current irrigation method to sprinkler irrigation and replacing 20% of the winter wheat-maize cultivated area with cotton, as the best strategy to achieve water balance in the study area. [ABSTRACT FROM AUTHOR]

To advance global change rssearch, it is essential to reconstruct changes in historical cropland coverage on a regional scale in China. This paper presents data collected from 244 local gazetteers, government statistical records and remote-sensing land cover data from the Shandong Province. The study reconstructed the spatial distribution of the rate of reclaimed land at the county level and compared this map with a map of the current spatial distribution of suitable cropland. The following conclusions were drawn: (i) The rate of cultivated land grew exponentially. The extent of reconstruction in cropland areas during the 17th century, 18th~19th centuries, the beginning of the 20th century, the 1980 s, and the beginning of the 20th century are 4.51 mha, 6.51 mha, 7.52 mha, 8.53 mha and 11.80-12.00 mha, respectively. (ii) Several agricultural centers formed during the late 17th century. Until the beginning of the 20th century, the reclamation rate increased rapidly near the four southern lakes, which are located in the Zaozhuang and Linyi regions. (iii) Most reclamation activities before the 19th century occurred in suitable agricultural areas, and the cultivated land was already reclaimed by the beginning of the 20th century. [ABSTRACT FROM AUTHOR]