Comprehensive analysis of glacier recession(2000-2020)in the Nun-Kun Group of Glaciers,Northwestern Himalaya

Himalayan glaciers are shrinking rapidly,especially after 2000.Glacier shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger scale.In this study,changes of 48 glaciers situated around the twin peaks of the Nun and Kun mountains in the northwestern Himalaya,hereafter referred to as Nun-Kun Group of Glaciers(NKGG),were investigated using Landsat satellite data during 2000-2020.Changes in glacier area,snout position,Equilibrium Line Altitude(ELA),surface thickness and glacier velocity were assessed using remote sensing data supplemented by field observations.The study revealed that the NKGG glaciers have experienced a recession of 4.5%±3.4%and their snouts have retreated at the rate of 6.4±1.6 m·a^(-1).Additionally,there was a 41%increase observed in the debris cover area during the observation period.Using the geodetic approach,an average glacier elevation change of-1.4±0.4 m·a^(-1)was observed between 2000 and 2012.The observed mass loss of the NKGG has resulted in the deceleration of glacier velocity from 27.0±3.7 m·a^(-1)in 2000 to 21.2±2.2 m·a^(-1)in 2020.The ELA has shifted upwards by 83.0±22 m during the period.Glacier morphological and topographic factors showed a strong influence on glacier recession.Furthermore,a higher recession of 12.9%±3.2%was observed in small glaciers,compared to 2.7%±3.1%in larger glaciers.The debris-covered glaciers showed lower shrinkage(2.8%±1.1%)compared to the clean glaciers(9.3%±5%).The glacier depletion recorded in the NKGG during the last two decades,if continued,would severely diminish glacial volume and capacity to store water,thus jeopardizing the sustainability of water resources in the basin.

Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

Modeling the effect of stand and site characteristics on the probability of mistletoe infestation in Scots pine stands using remote sensing data

Over the past decade,the presence of mistletoe(Viscum album ssp.austriacum)in Scots pine stands has increased in many European countries.Understanding the factors that influence the occurrence of mistletoe in stands is key to making appropriate forest management decisions to limit damage and prevent the spread of mistletoe in the future.Therefore,the main objective of this study was to determine the probability of mistletoe occurrence in Scots pine stands in relation to stand-related endogenous factors such as age,top height,and stand density,as well as topographic and edaphic factors.We used unmanned aerial vehicle(UAV)imagery from 2,247 stands to detect mistletoe in Scots pine stands,while majority stand and site characteristics were calculated from airborne laser scanning(ALS)data.Information on stand age and site type from the State Forest database were also used.We found that mistletoe infestation in Scots pine stands is influenced by stand and site characteristics.We documented that the densest,tallest,and oldest stands were more susceptible to mistletoe infestation.Site type and specific microsite conditions associated with topography were also important factors driving mistletoe occurrence.In addition,climatic water balance was a significant factor in increasing the probability of mistletoe occurrence,which is important in the context of predicted temperature increases associated with climate change.Our results are important for better understanding patterns of mistletoe infestation and ecosystem functioning under climate change.In an era of climate change and technological development,the use of remote sensing methods to determine the risk of mistletoe infestation can be a very useful tool for managing forest ecosystems to maintain forest sustainability and prevent forest disturbance.

An Analysis of Land Use and Land Cover Changes, and Implications for Conservation in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, 2002-2022

Understanding trends of land use land cover (LULC) changes is important for biodiversity monitoring and conservation planning, and identifying the areas affected by change and designing sustainable solutions to reduce the changes. The study aims to evaluate and quantify the historical changes in land use and land cover in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, from 2002 to 2022. The objective of the study was to analyse the LULC changes in Ward 2 (Mukumbura), Mt Darwin, Northern Zimbabwe, for a period of 20 years using geospatial techniques. Landsat satellite images were processed using Google Earth Engine (GEE) and the supervised classification with maximum likelihood algorithm was employed to generate LULC maps between 2002 and 2022 with a five (5) year interval, investigating the following variables, forest cover, barren land, water cover and the fields. Findings revealed a substantial reduction in forest cover by 38.8%, water bodies (wetlands, ponds, and rivers) declined by 55.6%, whilst fields (crop/agricultural fields) increased by 93.3% and the barren land cover increased by 26.3% from 2002 to 2022. These findings point to substantial changes in LULC over the observed years. LULC changes have resulted in habitat fragmentation, reduced biodiversity, and the disruption of ecosystem functions. The study concludes that if these deforestation trends, cultivation, and settlement land expansion continue, the ward will have limited indigenous fruit trees. Therefore, the causes for LULC changes must be controlled, sustainable forest resources use practiced, hence the need to domesticate the indigenous fruit trees in arborloo toilets.

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies.

Precise Three-Dimensional Deformation Retrieval in Large and Complex Deformation Areas via Integration of Offset-Based Unwrapping and Improved Multiple-Aperture SAR Interferometry:Application to the 2016 Kumamoto Earthquake

Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.

Accuracy Assessment of Alos W3d30, Aster Gdem and Srtm30 Dem: A Case Study of Nigeria, West Africa

Digital Elevation Models (DEMs) depict the configuration of the earth surface and are being applied in many areas in earth and environmental sciences. In this study, the accuracy of the Advanced Land Observing Satellite World 3D Digital Surface Model version 2.1 (ALOS W3D30), the Shuttle Radar Topography Mission Digital Elevation Model version 3.0 (SRTM30) and the Advanced Space borne Thermal Emission and Reflection Radiometer Global DEM version 2.0 (ASTER GDEM2) was statistically assessed using high accuracy GPS survey data. Root-Mean-Square errors of ~5.40 m, ~7.47 m and ~20.03 m were obtained for ALOS W3D30, SRTM30 and ASTER GDEM2 respectively. In further analyses, we discovered that ALOS W3D30 and SRTM30 were much more accurate in regions where the height intervals were within 201 m - 400 m and >801 m. ALOS W3D30 proved to be the most accurate DEM that best represents the topography of the earth’s surface and could be used for some earth and environmental applications in Nigeria. We recommend that this study should serve as a guide in the use of any of these DEMs for earth and environmental applications in Nigeria.

Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study

It is practically impossible and unnecessary to obtain spatial-temporal information of any given continuous phenomenon at every point within a given geographic area. The most practical approach has always been to obtain information about the phenomenon as in many sample points as possible within the given geographic area and estimate the values of the unobserved points from the values of the observed points through spatial interpolation. However, it is important that users understand that different interpolation methods have their strength and weaknesses on different datasets. It is not correct to generalize that a given interpolation method (e.g. Kriging, Inverse Distance Weighting (IDW), Spline etc.) does better than the other without taking into cognizance, the type and nature of the dataset and phenomenon involved. In this paper, we theoretically, mathematically and experimentally evaluate the performance of Kriging, IDW and Spline interpolation methods respectively in estimating unobserved elevation values and modeling landform. This paper undertakes a comparative analysis based on the prediction mean error, prediction root mean square error and cross validation outputs of these interpolation methods. Experimental results for each of the method on both biased and normalized data show that Spline provided a better and more accurate interpolation within the sample space than the IDW and Kriging methods. The choice of an interpolation method should be phenomenon and data set structure dependent.

Retrieval of the Single Scattering Albedo of Asian Dust Mixed with Pollutants Using Lidar Observations

The vertical distribution of single scattering albedos （SSAs） of Asian dust mixed with pollutants was derived using the multi-wavelength Raman lidar observation system at Gwangju （35.10°N,126.53°E）.Vertical profiles of both backscatter and extinction coefficients for dust and non-dust aerosols were extracted from a mixed Asian dust plume using the depolarization ratio from lidar observations.Vertical profiles of backscatter and extinction coefficients of non-dust particles were input into an inversion algorithm to retrieve the SSAs of non-dust aerosols.Atmospheric aerosol layers at different heights had different light-absorbing characteristics.The SSAs of non-dust particles at each height varied with aerosol type,which was either urban/industrial pollutants from China transported over long distances at high altitude,or regional/local pollutants from the Korean peninsula.Taking advantage of independent profiles of SSAs of non-dust particles,vertical profiles of SSAs of Asian dust mixed with pollutants were estimated for the first time,with a new approach suggested in this study using an empirical determination of the SSA of pure dust.The SSAs of the Asian dust-pollutants mixture within the planetary boundary layer （PBL） were in the range 0.88-0.91,while the values above the PBL were in the range 0.76-0.87,with a very low mean value of 0.76 ± 0.05.The total mixed dust plume SSAs in each aerosol layer were integrated over height for comparison with results from the Aerosol Robotics Network （AERONET） measurements.Values of SSA retrieved from lidar observations of 0.92 ± 0.01 were in good agreement with the results from AERONET measurements.

Fusion and Classification of Beijing-1 Small Satellite Remote Sensing Image for Land Cover Monitoring in Mining Area

In order to promote the application of Beijing-1 small satellite(BJ-1) remote sensing data,the multispectral and panchromatic images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining.An improved Intensity-Hue-Saturation(IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images,in which intensity component and panchromatic image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation degree.This improved IHS fusion algorithm outper-forms traditional IHS fusion method to a certain extent,evidenced by its ability in preserving spectral information and enhancing spatial details.Dempster-Shafer(D-S) evidence theory was adopted to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that by any individual classifier.Based on this study,we conclude that Beijing-1 small satellite remote sensing images are useful to monitor and analyze land cover change and ecological environment degradation in mining areas,and the proposed fusion algorithms at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers,improve the overall accuracy and produce a more reliable land cover map.

An Efficient Approach for Historical Storage and Retrieval of Segmented Road Data in Geographic Information System for Transportation

One of the most powerful functions of Geographic Information System for Transportation (GIS-T) is Dynamic Segmentation (DS), which is used to increase the efficiency and precision of road management by generating segments based on attributes. The road segments describing transportation data are both spatially and temporally referenced. For a variety of transportation applications, historical road segments must be preserved. This study presents an appropriate approach to preserve and retrieve the historical road segments efficiently. In the proposed method, only the portions of segments of a time stamp that have been changed into new segments rather than storing the entire segments for every old time stamp are recorded .The storage of these portions is based on the type of changes. A recursive algorithm is developed to retrieve all segments for every old time stamp. Experimental results using real data of Tehran City, Iran justify the strength of the proposed approach in many aspects. An important achievement of the results is that database volume for 2006, 2007 and 2008 within the Historical Line Event Table (HLET) is reduced by 70%, 80% and 78%, respectively. The proposed method has the potential to prevent from vast data redundancy and the unnecessary storage of entire segments for each time stamp. Since the present technique is performed on ordinary plain tables that are readable by all GIS software, special software platforms to manage the storage and retrieval of historical segments are not needed. In addition, this method simplifies spatio-temporal queries.

Paleo-glacial reconstruction of the Thajwas glacier in the Kashmir Himalaya using 10Be cosmogenic radionuclide dating

Quantitative glacial chronologies of past glaciations are sparse in the Himalaya, and mostly absent in the Kashmir Himalaya. We used cosmogenicBe exposure dating, and geomorphological mapping to reconstruct glacial advances of the Thajwas Glacier(TG) in the Great Himalayan Range of the Kashmir Himalaya. FromBe exposure dating of ten moraine boulders, four glacial stages with ages ~20.77 ±2.28 ka, ~11.46 ± 1.69 ka, ~9.12 ± 1.39 ka and ~4.19 ± 0.78 ka, were identified. The reconstructed cosmogenic radionuclide ages confirmed the global Last Glacial Maximum(g LGM), Younger Dryas, Early Holocene, and Neoglaciation episodes. As per area and volume change analyses, the TG has lost 51.1 km~2 of its area and a volume of 2.64 km~3 during the last 20.77 ± 2.28 ka. Overall, the results suggested that the TG has lost 64% of area and 73% of volume from the Last glacial maximum to Neoglaciation and about 85.74% and 87.67% of area and volume, respectively, from Neoglaciation to the present day. The equilibrium line altitude of the TG fluctuated from 4238 m a.s.l present to3365 m a.s.l during the g LGM(20.77 ± 2.28 ka). The significant cooling induced by a drop in mean ambient temperature resulted in a positive mass balance of the TG during the g LGM. Subsequently the melting accelerated due to the continuing rise of the global ambient temperature. Paleo-glacial history reconstruction of the Kashmir Himalaya, with its specific geomorphic and climatic setting, would help close the information gap about the chronology of past regional glacial episodes.

Influence of environmental predispositions on temperate mountain forest damage at different spatial scales during alternating drought and flood periods:case study in Hruby Jeseník Mts.(Czech Republic)

Mountain forests are more prone to environmental predispositions(EPs)than submountain ones.While remote sensing of mountain forests enables instantaneous damage mapping,the investigation of the causes requires field data.However,a local field or regionally modeled environmental characteristics influence remote data evaluation differently.This study focused on the evaluation of EPs effects damaging mountain forests between various spatial resolutions during environmental change.The evaluation was divided into managed and natural forests in the Hruby Jeseník Mts.(Czech Republic;240-1491 m a.s.l.;50.082°N,17.231°E).Damage was assessed through the discrimination analysis of the normalised difference vegetation index(NDVI)by MODIS VI during alternating drought and flood periods 2003-2014.The local environmental influence was assessed using the discrimination function(DF)separability of forest damage in the training sets.The regional influence was assessed through map algebra estimated via the DF and a forest decline spatial model based on EPs from differences between risk growth conditions and biomass fuzzy sets.Management,EPs and soil influenced forest NDVI at different levels.The management afflicted the NDVI more than the EPs.The EPs afflicted the NDVI more than the soil groups.Strong winters and droughts had a greater influence on the NDVI than the flood events,with the winter of 2005/2006 inverting the DF direction,and the 2003 drought increasing differences in managed forest biomass and decreasing differences in natural forest biomasses.More than 50% of declining managed forests in the training sets occurred on Leptosols,Podzols and Histosols.On a regional scale,the soil influence was eliminated by multiple predispositions.The EPs influenced 96% of natural forest and 65% of managed forest,though managed forest damage was more evident.The mountain forest NDVI decline was dependent on both management and risk predispositions.

Comparison of SRTM-V4.1 and ASTER-V2.1 for Accurate Topographic Attributes and Hydrologic Indices Extraction in Flooded Areas

This research compares the potential of SRTM-V4.1 and ASTER-V2.1 with 30-m pixel size to derive topographic attributes （elevation, slopes, aspects, and flow accumulation） and hydrologic indices such as STI （sediment transport index）, CTI （compound topographic index） and SPI （stream power index） to detect areas associated with flash floods cansed by rainfall storms and sediment accumulation. The study area is Guelmim city in Morocco, which has been flooded several times over the past 50 years, and which was declared a ＂disaster area＂ in December 2014 after violent rainfall storms killed 46 people and caused significant damage to the infrastructure. The obtained results indicate that the SRTM DEM performs better than ASTER in terms of micro-topography, hydrologic-network and structural information characterization. In addition, with reference to a topographic contours map （1：50000）, the derived global height surfaces accuracies are ＋3.15 m and 4-9.17 m for SRTM and ASTER, respectively. These accuracies are significantly influenced by topography; errors are larger （SRTM = 11.34 m, ASTER = 19.20 m） for high altitude terrain with strong slopes, while they are smaller （SRTM = 1.92 m, ASTER = 3.76 m） in the low to medium-relief areas with indulgent slopes. Moreover, all the considered hydrological indices are significantly characterized with SRTM compared to ASTER. They demonstrated that the rainfall and the topographic morphology are the major contributing factors in flash flooding and catastrophic inundation in this area. The runoff waterpower delivers vulnerable topsoil and contributes strongly to the erosion and transport of soil material and sediment to the plain areas through waterpower and gravity. Likewise, the role of the lithology associated with the terrain morphology is decisive in the erosion risk and land degradation in this region.

Geospatial Technology Potentials in Reawakening the Consciousness of Soil Distribution in Nigeria’s North-Central Region and Mediating the Herdsmen-Farmers Conflicts

The pervasive herdsmen-farmers conflicts in the north-central region of Nigeria have changed the narrative of Nigeria’s enduring ethnic crises to ideologies, which are in-controvertibly sinister. The consequences of this tension, which has defied possible military responses, political, religious and cultural strategies are potentially devastating, not just for Nigeria, but the whole of West African region. Since the particular nature of these conflicts increasingly highlights the significance and inevitability of land resources for crops farming and cattle rearing, it is imperative to create awareness of the elemental nature of soils, especially their diversities in these conflict-prone areas. This study’s objective was to produce a Geographic Information System (GIS) based digital soil map (DSM) of the north-central region of Nigeria, and to delineate soil distribution and unique properties. Based on this study, the DSM offers a quick access to quantitative soil data covering the study area. It indicates that soil mapping units 15d, 18d and 24b are dominant, and constitute about 40% of the local arable lands. The broad pattern of distribution of these soils reflects both the climatic conditions and the geological structure of the region. The soils are highly weathered with limited capacities to supply essential nutrients needed by crop plants. These issues raise a number of questions, most of which focuses on the best possible way to maximize these soils to accommodate both crop farming and cattle rearing. It is our hope that taking the advantage of GIS to stimulate the knowledge and consciousness of soil distribution in the region will place the weight where it is appropriate in terms of food security through crops production and cattle rearing, and hence forge a more realistic pathway to reconciliation and conflict resolution.

Refinement and Quantification of Terrain-Induced Effects on Global Gravity Data

The geodetic and geophysical applications of Earth Gravity Field parameters computed from Global Geopotential Models (GGMs) are quite on the increase despite the inherent commission and omission errors of these models. In view of this, this study focuses on refining and quantifying terrain-induced effects on Bouguer gravity anomalies computed directly from a total of seven recent GGMs. In the study, the Residual Terrain Model (RTM) technique was used to estimate the residual terrain effects that were added to the GGM-computed Bouguer gravity anomalies at the sixty test points in Enugu State, Nigeria. The computed residual terrain effects range from -24.6 to 37.5 mgal while the percentage of the omission errors of the GGMs based on their Root-Mean-Square (RMS) differences ranges from 7.8% to 44.7%. It can be concluded that GGM-refined Bouguer gravity anomalies are better in accuracy than the unrefined GGM-computed Bouguer gravity anomalies and hence there is need for accurate height information in the development of GGMs. We, therefore, recommend that refined Bouguer gravity anomalies obtained from HUST-Grace2016s, EIGEN-6C4 and GECO that gave best improvement amongst the seven GGMs under consideration should be used to supplement the available terrestrial Bouguer anomalies for geodetic and geophysical applications within the study area.

Modern Development for the Improvement of Accuracy of Nigerian Coordinate Transformation Process Using the Adapted NTv2 Model: The Critical Issues of the Mathematical Algorithm

Changing coordinates using appropriate mathematical models from one reference system to another may be influenced if the operation requires the change of datum. A set of transformation parameters has been adopted for Nigeria. However, the critical concern usually associated with the problem of transformation of coordinates is the issue of recoverability of the original values of transformed coordinates. The recursive effect of variables associated with spatial problems can be aptly modelled with an appropriate algorithm that set out a process to achieve a definite output. Consequently, the main thrust of this paper is to highlight the critical elements of the mathematical algorithm associated with the National Transformation Version 2 (NTv2) model adapted for the Nigerian Datum Transformation process. The adapted NTv2 model adopts the bi-linear interpolation approach and the covariance function obtained were used to generate transformation elements in latitude (Δφp) and longitude (Δλp) and corresponding accuracies at the lattice nodes. The mathematical algorithm of this adapted NTv2 model underscores the likely attainment of better and significant values and statistical indicator of the improved accuracy as the average shift values for latitude and longitude for any transformed points in Nigeria. This capability makes the mathematical algorithm to be adaptable and fit for the purpose of the transformation process. The improvement in the positional accuracy is directly attributable to the application of the NTv2 model which provides a flexible and robust system of modelling any inherent systematic error in the national network.

Integrating Remote Sensing and Field Survey to Map Shallow Water Benthic Habitat for the Kingdom of Bahrain

Identification and classification, as well as mapping of marine habitats, are of primary importance to plan management activities, especially in disturbed ecosystems like the ones in the marine areas of Bahrain. Remotely sensed Landsat-8 imagery coupled with field survey was used to identify, classify and map the benthic habitats in Bahrain marine area. The used geospatial techniques include advanced image processing procedures, which comprise of radiometric and atmospheric corrections, sun glint removal, water depth correction and image classification. Extensive ground-truthing analyses through in-situ field surveys by a team of scuba divers were conducted in October 2014 and June 2015 to inform and refine the classifications. The variables collected from this survey included physical and chemical characteristics of the water, habitat type, substrata, fauna and flora. A total of 176 field points were collected and utilized to perform an accurate assessment of the image classification. Initial habitat classification resulted in 20 habitat categories. However, due to the inability of the Landsat-8 sensors to accurately discriminate that level of classification, categories were merged into seven classes. The derived map shows that the benthic marine habitats of Bahrain consist of deep water （2,523 km2）, rock （1,738 km2）, sand （1,191 km2）, deep water/sand （1,006 km2）, algae （922 km2）, seagrass （591 km2） and corals （275.50 km2）. Although limited by the spatial and spectral resolutions of Landsat 8, the used methods produced a suitable map of the benthic habitats within the marine area of Bahrain with an overall accuracy of 84.1%. The use of very high spatial resolution satellite imagery will most likely increase such accuracy significantly.

Estimation of Evapotranspiration Using SEBAL Algorithm and Landsat-8 Data--A Case Study： Tatra Mountains Region

ET （Evapotranspiration） is one of the climate elements, which plays an important role in water balance, and effects on the ecosystem of any region. Therefore, many mathematical equations and algorithms have been found and designed to calculate and estimate values of evapotranspiration. Calculation methods are either based on data from meteorological stations or using other sources of data where the area is lacking from meteorological stations. Remote sensing data are one of the important sources and techniques to estimate many climate elements including evapotranspiration. The selected study area is located in Tatra Mountains on the borders between Poland and Slovakia. Tatra Mountains are the most valuable areas in Poland and Slovakia. The main objective of current study is to estimate the spatial variation of ET using SEBAL algorithm and Landsat-8 imagery. The analysis is carried out using Landsat-8 （OLI/TIRS） data, ASTER GDEM and reference weather parameters. Sixteen ERDAS models are prepared to calculate the various parameters related to solar radiation. The models are prepared to calculate the values of surface radiance surface reflectance, surface albedo, NDVI, LAI, surface emissivity, surface temperature, net radiation, soil heat flux, sensible heat flux, latent heat flux, which are consequently used to calculate the hourly and daily evapotranspiration in study area. Results ofpixel wise calculations show the values of surface temperature which are varied from 6.2℃ at mountain shadow areas to 34.6 ℃ at bare rocks and bare land area, while the spatial variation of ET at different land covers shows the hourly ET ranged from 0 to 0.72 mm/hr, while the daily ET varied from 0.0 to 17.0 mm/day. Results show clear relation between land use/land cover and solar radiation parameters and impact of vegetation cover on the ET values in pixel wise domain.

Assessment of Land Erosion and Sediment Accumulation Caused by Runoff after a Flash-Flooding Storm Using Topographic Profiles and Spectral Indices

This research deals with the characterization of areas associated with flash floods and erosion caused by severe rainfall storm and sediment transport and accumulation using topographic attributes and profiles, spectral indices (SI), and principal component analysis (PCA). To achieve our objectives, topographic attributes and profiles were retrieved from ASTER-V2 DEM. PCA and nine SI were derived from two Landsat-OLI images acquired before and after the flood-storm. The images data were atmospherically corrected, sensor radiometric drift calibrated, and geometric and topographic distortions rectified. For validation purposes, the acquired photos during the flood-storm, lithological and geological maps were used. The analysis of approximately 100 colour composite combinations in the RGB system permitted the selection of two combinations due to their potential for characterizing soil erosion classes and sediment accumulation. The first considers the “Intensity, NDWI and NMDI”, while the second associates form index (FI), brightness index (BI) and NDWI. These two combinations provide very good separating power between different levels of soil erosion and degradation. Moreover, the derived erosion risk and sediment accumulation map based on the selected spectral indices segmentation and topographic attributes and profiles illustrated the tendency of water accumulation in the landscape, and highlighted areas prone to both fast moving and pooling water. In addition, it demonstrated that the rainfall, the topographic morphology and the lithology are the major contributing factors for flash flooding, catastrophic inundation, and erosion risk in the study area. The runoff-water power delivers vulnerable topsoil and contributes strongly to the erosion process, and then transports soil material and sediment to the plain areas through waterpower and gravity. The originality of this research resides in its simplicity and rapidity to provide a solid basis strategy for regional policies to address the real causes of problems and risks in developing countries. Certainly, it can help in the improvement of the management of water regulation structures to develop a methodology to maximize the water storage capacity and to reduce the risks caused by floods in the Moroccan Atlas Mountain (Guelmim region).