Estimation of earthquake casualties using high-resolution remote sensing: a case study of Dujiangyan city in the May 2008 Wenchuan earthquake

Natural Hazards - From a disaster relief perspective, an immediate and efficient rescue operation after an earthquake can greatly increase the number of survivors. An effective rescue operation...     

遥感技术在断裂研究中的应用——以张家口—蓬莱断裂带为例

张家口一蓬莱断裂带是一条北西西向活动断裂带。本文选取ETM+光学影像和SRTM高程影像作为主要数据源,结合研究区已有地质资料研究发现该带断裂构造的北西西向线性特征明显。从水系分布和错断地形等地貌标志判断,该断裂具有左阶组合样式和左行走滑活动特征。据遥感影像综合特征,可将该带分为张家口段、延庆-怀来段和北京一天津段,影像特征分段性显著,并与断裂带的分段性一致。研究结果表明,张家口-蓬莱断裂具有左行走滑的运动学特征,限制或错断北北东或北东向断裂,并且控制该区域的左阶雁列式第四纪盆地群和第四纪冲洪积物的分布。该断裂带各段对不同规模的水系分布和形态影响比较大,且北京-天津地区的华北平原段断裂对第四纪冲洪积扇和沿海地区的贝壳堤的形态和分布有一定的控制作用。地球物理深部数据和野外地质考察资料也证实了遥感解泽的结果,证明遥感技术在探查断裂构造空间展布和活动性鉴定中有着广泛的应用前景。     

Fire danger assessment with remote sensing: a case study in Northern China

Every year several million hectares of forest and grassland in China are affected by wildfires. The majority of wildfires occur in the northern part of China, where grasslands and forests are ubiquitous. A critical step toward the protection of life, property, and natural resources from wildfires is the development of a fire danger rating system. This paper presents a new method to assess fire danger that capitalizes on the abundance of environmental data available via remote sensing and applies this new method to the northern part of China. Using an analytical hierarchy process, a fire danger index was developed based on five environmental factors that are known to affect fire frequency and severity, including land surface temperature, vegetation curing, equivalent water thickness, vegetation continuity degree, and fuel weight. Data for these five factors were derived from satellite imagery, instead of point data, allowing for predictions to be made over a large geographic area. Fire danger ratings were then mapped for the region based on the fire danger index. In addition, the accuracy of the fire danger index was evaluated by statistical analyses. The fire danger index was significantly correlated with air temperature and precipitation, suggesting that changes in these two environmental variables will affect the predictions of the index.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

Mapping land limitations for agricultural land use planning using fuzzy logic approach: a case study for Marinduque Island,Philippines

This study demonstrated the use of fuzzy logic approach in mapping land limitations for agricultural land use planning using publicly available data for the province of Marinduque, Philippines. The paper focused only on the two major crops in the province, coconut, and banana. Based on the results, slope is the major factor limiting the production of these two crops. Slope is identified as a limitation in approximately 80% and 18% of the agricultural land of the province for coconut and banana production, respectively. Other land limitations for coconut production in the province include rainfall, soil, and combination of these factors with slope. In the case of banana, soil and combination of this factor with slope were identified as land limitations.

     

Estimation of spatial patterns of soil erosion using remote sensing and GIS: a case study of Indravati catchment

Soil erosion is a serious environmental problem in Indravati catchment. It carries the highest amount of sediments compared with other catchments in India. This catchment spreading an area of 41,285 km² is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the present study, USLE is used to estimate potential soil erosion from river Indravati catchment. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined. The derived soil loss map from USLE model is classified into six categories ranging from slight to very severe risk depending on the calculated soil erosion amount. The soil erosion map is linked to elevation and slope maps to identify the area for conservation practice in order to reduce the soil loss. From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield at the out let of the catchment is 22.30 Million tons per annum. The predicted sediment yield verified with the observed data.     

基于深度学习和高分遥感影像的青藏高原东部融冻泥流阶地提取研究

融冻泥流阶地是一种典型的斜坡冷生型冰缘地貌,在青藏高原东部发现大量古融冻泥流阶地,其空间分布对于重建该区古多年冻土分布和古气候环境具有重要意义。融冻泥流阶地纹理复杂、几何形态不一、表面覆盖多样化,导致融冻泥流阶地遥感解译和自动提取困难,然而,深度学习方法能获取上下文多尺度语义信息,提高特征表达的能力,为融冻泥流阶地的大范围提取提供了重要手段。因此,本文提出了一种基于DeepLab V3+深度学习模型和高分辨率光学遥感影像的融冻泥流阶地自动提取方法,并在四川甘孜州新都桥周边地区开展了实验研究。结果表明：与人工解译结果对比,本方法提取结果的综合精度达到0.68以上,并经野外调查验证了其有效性;在该区共识别了9 203条融冻泥流阶地,主要分布在新都桥镇附近的山谷两侧;泥流阶地主要朝西北方向,坡度集中分布在20°~25°,海拔高程大部分位于3 650~3 750 m间,主要地表覆盖类型是草地。     

Monitoring land use/land cover change using multi-temporal Landsat satellite images in an arid environment: a case study of El-Arish,Egypt

Environment in arid conditions is dynamic and needs more investigation to understand the complexity of change. This spatiotemporal study will help to assess and monitor the land use and land cover change in the arid region of El-Arish area, where the climate and human activities are the major threats to rural development. In the past 11 years, dramatic changes of environment have been recorded in case studies. The post-classification comparison method was used to observe the changes using multi-temporal satellite images which were captured in the years 1999, 2001, 2005, and 2010. The overall accuracy of the produced thematic images was assessed regarding to the quantity and allocation disagreements. Five classes were defined in this investigation: bare soil, vegetation, urban, sand dunes, and fertile soil. From the year 1999 to 2010, fertile soil was increased by 13 %. Bare soil class occupied more than 50 % of land in the case study during for over a decade. From year 1999 to 2010, vegetation cover witnessed a dramatic increase. Soil and water management are the keys of land development and positive land use and land cover dynamics. Changing agricultural policies of using the available water resources are needed in the case study to prevent severe food shortage in the future.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.     

Modelling of stream run-off and sediment output for erosion hazard assessment in Lesser Himalaya: need for sustainable land use plan using remote sensing and GIS: a case study

Assessment and inventory on soil erosion hazard are essential for the formulation of successful hazard mitigation plans and sustainable development. The objective of this study was to assess and map soil erosion hazard in Lesser Himalaya with a case study. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India, in district Nainital has been selected for the case illustration. The average rate of erosion hazard is 0.68 mm/year or 224 tons/km²/year. Anthropogenic and geo-environmental factors have together significantly accelerated the rate of erosion. This reconnaissance study estimates the erosion rate over the period of 3 years (2006–2008) as 1.21 mm/year (398 tons/km²/year) in the barren land having geological background of diamictite, siltstone and shale rocks, 0.92 mm/year (302 tons/km²/year) in the agricultural land with lithology of diamictite, slates, siltstone, limestone rocks, while in the forest land, it varies between 0.20 mm/year (66 tons/km²/year) under dense forest land having the geology of quartzwacke and quartrenite rocks and 0.40 mm/year (132 tons/km²/year) under open forest/shrubs land having geological setup of shale, dolomite and gypsum rocks. Compared to the intensity of erosion in the least disturbed dense forest, the erosion rate is about 5–6 times higher in the most disturbed agricultural land and barren land, respectively. The erosion hazard zones delineated following scalogram modelling approach. Integrated scalogram modelling approach resulted in severe classes of soil erosion hazard in the study area with numerical values of Erosion Hazard Index (EHI) ranging between 01 (very low hazard) and 5 (very high hazard).     

Assessing land use and land cover change in the Wassa West District of Ghana using remote sensing

Vast tracts of forests are lost globally every year especially in the developing countries of the tropics due to various human activities such as lumbering, farming, bush fires, surface mining and urbanization. The rainforest in Ghana has experienced rapid depletion since the 1980s. The impact of deforestation is widespread, affecting the livelihoods of local people and disrupting the tropical ecosystem. There is a serious concern in the study area about climatic change, soil erosion, siltation of rivers and loss in biodiversity which have an adverse impact on traditional medicinal plants of the local people. The study examined the extent of land cover change through image differencing of Landsat TM 1986 and 2002. The image classification indicated that, vegetative cover from 1986 to 2002 has been reducing whiles land use activities have been increasing. Closed canopy, open canopy and plantation have significantly diminished and land use activities especially built ups, farms, mining and openfields are more than doubled. The driving forces for the change in land cover are population growth, lumbering, socio-economic and cultural practices of the people. Lumbering and mining have been some of the major causes of the changing landscape in primary forest. Also the reliance on wood for domestic energy and the need to increase food productivity to feed growing population have also contributed greatly to the rapid depletion of the vegetative cover.     

新疆苇湖梁煤矿塌陷区遥感监测研究

苇湖梁煤矿已有50多年的开采历史, 长期的地下开采造成了严重的地面塌陷。本文将新疆苇湖梁煤矿塌陷区作为研究区, 以2013年的IKONOS高分遥感影像为主要数据源, 以ArcGIS为支撑平台, 采用人机交互的解译方法对塌陷区的相关信息进行提取, 结合实地调查验证的方法, 分析研究区内地质灾害的特征。通过遥感调查发现: 研究区内发育规模较大、位于塌陷区周围的拉伸区的地裂缝约有64条;塌陷坑(群)约有94个, 主要分布于南北塌陷槽及两侧;塌陷回填区总面积达0.92 km², 并在回填区发现了3个新塌陷坑。本文充分发挥了遥感技术宏观性强、速度快的特点, 调查结果反映了塌陷区灾害的实际情况。     

Land transformation assessment using the integration of remote sensing and GIS techniques: a case study of Al-Anbar Province,Iraq

Human activities and climate changes significantly affect our environment, altering hydrologic cycles. Several environmental, social, political, and economical factors contribute to land transformation as well as environmental changes. This study first identified the most critical factors that affect the environment in Al-Anbar city including population growth, urbanization expansion, bare land expansion, and reduction in vegetation cover. The combination of remote sensing data and fuzzy analytic hierarch process (Fuzzy AHP) enabled exploration of land transformations and environmental changes in the study area during 2001 to 2013 in terms of long and short-term changes. Results of land transformation showed that the major changes in water bodies increased radically (94 %) from the long-term change in 2001 to 2013 because of water policies. In addition, the urban class expanded in two short-term periods (2001–2007 and 2007–2013), representing net changes of 46 and 60 %, respectively. Finally, barren land showed 25 % reduction in the first period because of the huge expansion of water in the lake; a small percentage of growth gain was observed in the second period. Based on the land transformation results, the environmental degradation assessment showed that the study area generally had high level of environmental degradation. The degradation was mostly in the center and the north part of the study area. This study suggested for further studies to include other factors that also responsible for environmental degradation such as water quality and desertification threatening.     

Earthquake damage identification: a case study using soft classification approach

The October 8, 2005, Kashmir earthquake (M _w 7.6) affected the rough mountainous regions of India and Pakistan with poor accessibility, and thus, no proper comprehensive ground survey was possible. However, due to the ability of remote sensing technology to acquire spectral measurements of damaged areas at various spatial and temporal scales, extraction of damaged areas can be carried out quickly and with great reliability. The fuzzy-based classifiers [Possibilistic c-Means (PCM), noise cluster (NC), and NC with entropy (NCE)] were applied to identify 2005 Kashmir earthquake, induced landslides, as well as built-up damage (BD) areas, as soft computing approaches using supervised classification. Results indicate that for the identification of landslides and BD areas, NCE classifier generated the best outputs, while for the identification of built-up undamaged areas, NC classifier generated the best output. Further, it was found that the proposed Class Based Sensor Independent (CBSI) technique can improve spectral information of specific class for better identification.     

Eco-environmental change detection by using remote sensing and GIS techniques: a case study Basrah province, south part of Iraq

This study examines the temporal and spatial dynamics of eco-environment degradation processes and change detection as evident from land use survey datasets (1990–2003) for the Basrah province, Iraq was taken as a case. Using a combination of techniques of RS, GIS, and GPS, the study identifies five prominent eco-environment degradation processes, namely: desertification, secondary salinization, urbanization, vegetation degradation, and loss of wetlands. Rates of conversion were calculated and distribution patterns were mapped with the aid of GIS. The results suggest that wind erosion was the dominant cause of eco-environment degradation in more than half of the study area. Coupled with this were increases in salinization processes, affecting 17.6% of the land area in 2003. Overall, severe eco-environment degradation was noticed to be the dominant eco-environment degradation grade (61.9% of total area), followed by moderate eco-environment degradation (18.9% of total area) in 2003. Incorporation of both natural and anthropogenic factors in the analysis provided realistic assessment of the risk of land degradation. The study area, in general, is exposed to a high-risk of eco-environment degradation.     

Land use/land cover change impact on groundwater quantity and quality: a case study of Ajman Emirate,the United Arab Emirates,using remote sensing and GIS

Ajman is a rapidly urbanizing emirate with land development succeeding at a fast pace. This study aims to monitor land use/land cover changes and assesses the impact of these changes on groundwater quality and quantity of the shallow aquifer using multitemporal remote sensing data and geographic information system (GIS). To monitor the land use/land cover changes, the Spectral Angle Mapper (SAM) and the Normalized Difference Vegetation Index (NDVI) algorithms were utilized. The obtained maps were correlated against a set of total dissolved solid (TDS); Mg, Cl, and NO₃ groundwater quality index; and depth to the groundwater table maps constructed from groundwater data. The spatial analysis revealed a sharp depletion in groundwater quality and quantity related to the increase in the land use/land cover classes. The mean total TDS is from 21,971 to 26,450 mg/L and depth to groundwater level from ?12.33 to ?17.2 m over a period of 15 years. Maps of normalized difference and groundwater quality sustainability showed that the eastern side of the study area has a high value of groundwater quality sustainability and normalized difference, while the western side of the study area has a minimal value of groundwater quality sustainability and normalized difference. This study is of great assistance for decision makers and land developers to relate to municipal land allotment in rapidly developing regions such as Ajman.     

基于高分辨率遥感影像的石漠化演变趋势分析———以蒙自东山生态治理区为例

为了快速准确获取小区域高精度、大比例尺岩溶石漠化的演变趋势,为小区域岩溶石漠化的定量评价和精准治理提供科学依据和基础数据,本文选择岩溶石漠化典型地区——蒙自东山生态治理研究区为例,基于2006年11月SPOT5和2015年1月Pleiades两期高分辨率遥感影像,通过研究区归一化植被指数（NDVI）与植被覆盖度（FVC）进行岩溶石漠化遥感信息提取,得到生态治理区2006年与2015年岩溶石漠化空间分布特征,并对两期FVC数据进行叠加,分析生态治理区石漠化的演变趋势。遥感调查表明,研究区内石漠化十分严重,重度石漠化面积占比73.55%,中度石漠化5.36%,轻度石漠化0.53%,无石漠化14.86%,阴影及水域面积5.71%。不同等级石漠化面积的变化情况显示,2006-2015年,重度石漠化和无石漠化面积比例增加,重度石漠化由72.37%增加到73.55%,无石漠化从6.06%增加到14.86%,而中度、轻度石漠化面积比例减少,中度石漠化面积从11.58%减小到5.36%,轻度石漠化面积从4.35%减小到0.53%。轻度、中度和无石漠化区变幅明显。研究区石漠化发生率从88.27%降低到79.43%,总体呈降低趋势。      

Compression of remote sensing data using second-generation wavelets: a review

Wavelet-based methods have been widely used for compression of remotely sensed images and data. Recently, second generation of wavelets which is based on a method called lifting has proven to be more effective than traditional wavelets as it provides lossless compression, lowers the memory usage, and is computationally faster. This study explores the literature related to applying second-generation wavelets for the compression of remote sensing data. Nevertheless, in order to compare the results of two wavelet types, some applications of traditional wavelets are also presented.