SPOT Satellite Images Research Articles

Transit-oriented development (TOD) or development-oriented transit (DOT): how does it matter for sustainable urban growth?

ABSTRACT Urban growth patterns occur in various ways with tangible practical consequences. A key dilemma with regard to development and transportation revolves around whether the former follows the latter or vice versa. This study assessed this nexus with transit-oriented development (TOD) and development-oriented development (DOT) cases by using the land use/land cover (LU/LC) classification technique in a developing country example of a city in Turkey. Spatial data included high-resolution Sentinel 2A, Rapid Eye, and two SPOT satellite images and CORONA air photos acquired in 2021, 2013, 2000, 1989, and 1979, respectively, within three buffer zones (500, 750, and 1000 m) for both development forms. While the study acknowledges unorthodox TOD selection criteria and generalizability concerns, the results demonstrate that the TOD drastically reduced green areas (as opposed to ideal TOD requirements), while the DOT excessively grew commercial land uses and street networks. Both developments commonly impaired agricultural, vacant, and water land use. Such transformations direct local governments, transit agencies, and city planners to resolve ideal sustainable urban growth patterns by using remote sensing data and quantitative analysis.

Evaluating pasture cover density mapping: a comparative analysis of Sentinel-2 and Spot-5 multispectral sensor images

Vegetation density extraction is influenced by the characteristics of satellite images, vegetation type, classification algorithm, and region, but there is little information about multispectral imaging (MSI). Studying the compatibility of the information content of sensors to replace sensors in areas where there is no easy access to their data is necessary for remote sensing (RS) studies. This study aims to assess the suitability of MSI from Sentinel-2 and Spot-5 satellites for generating pasture density maps. The Middle Kashkan watershed in the Lorestan Province of Iran was the study area. Geometric correction of the images was performed using ground control points (GCP) and the area's digital elevation model, achieving an accuracy of 0.21 pixels or better. Supervised classification techniques including parallelogram, minimal distance, maximum likelihood, and artificial neural network (ANN) algorithms were applied to the primary MSI of each satellite, as well as the integrated image of Spot-5 and the resulting pasture density map. Three density categories were considered: 5–25%, 25–50%, and over 50%. To validate the accuracy of the classification, a ground truth map of the region was created by interpreting a referenced official digital orthophotomosaic image at a scale of 1:40,000. Comparative analysis of the classified images revealed that the Sentinel-2 image with PCA-2-8 band composition and ANN classification algorithm yielded superior results, with an overall accuracy of 65.72% and a kappa coefficient of 0.08, compared to the Spot-5 image with PCA-3-1 band composition and the ANN classification algorithm. Spot-5 satellite images demonstrated greater effectiveness in generating pasture cover maps across the three density categories. These findings suggest that satellite images with suitable spatial and spectral resolution can be effectively utilized for generating accurate pasture density maps and monitoring long-term pasture preservation, particularly in regions characterized by high aerial photography altitudes in pasture areas. This approach holds the potential for effective pasture management and conservation efforts on a global scale.

Assessing sandbar morphology in the Nakdong River Estuary using SPOT series satellite imagery

This study assessed sandbar-topography changes in Nakdong River Estuary. The island shorelines in the study area, including Jinwoo Island, Shinja Island, and Doyo Sandbar, were analyzed using SPOT satellite images from 2006 to 2022. Shoreline analysis via ArcGIS revealed that Jinwoo Island is expanding at 6.46 m/year towards Nulcha Island. Shinja Island’s western side is expanding at 4.76 m/year, while the eastern side is retreating at 24.41 m/year. Doyo Sandbar’s southern shoreline is retreating at 14.69 m/year, with a gradual decrease in speed. Significant topographical changes indicate that the interlinked barrier islands are undergoing deposition and erosion, altering the shoreline.

Analysis of the Occurrent Models of Potential Debris-Flow Sources in the Watershed of Ching-Shuei River

The areas around the Ching-Shuei River saw numerous landslides (2004–2017) after the Jiji earthquake, profoundly harming the watershed’s geological environment. The 33 catchment areas in the Ching-Shuei River watershed and five typhoon and rainstorm events, with a total of 165 occurrences and non-occurrences, were analyzed, and the training and validation were categorized into 70% training and 30% validation. A landslide disaster is deemed, for the purposes of this research, to have taken place if SPOT satellite images taken before and after an incident show a Normalized Difference Vegetation Index difference larger than 0.25, a slope of less than 30 degrees, and a number of connected grids greater than 10. The analysis was carried out using the instability index method analysis with Rogers regression analysis and artificial neural network. The accuracy rates of neural network, logit regression, and instability index analyses were, respectively, 93.3%, 80.6%, and 70.9%. The neural network’s area under the curve was 0.933, indicating excellent discrimination ability; that of the logit regression analysis was 0.794, which is considered good; and that of the instability index analysis was 0.635, or fair. This suggests that any of the three models are suitable for the danger assessment of large post-earthquake debris flows. The results of this study also provide a reference and evidence for specific sites’ potential susceptibility to debris flows.

An Integration of Logistic Regression and Geographic Information System for Development of a Landslide Hazard Index to Land Use: A Case Study in Pingtung County in Southern Taiwan

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Land use/land cover and plant community dynamics in the Benin's forest reserves: The effectiveness of participatory forest management

Assessing Participatory Forest Management (PFM) is crucial to design sustainable conservation biodiversity policies. Such assessments often prioritize PFM's impact on livelihoods and deforestation, overlooking the spatial and biodiversity dimensions. Thus underscores the need for tools like Land Use/Land Cover Change (LULCC) overviews and forest diversity assessments. Here, we integrated LULCC of fours forests reserves (Wari-maro Mont-Kouffé, Agoua, Goungoun and Lama), taxonomic (alpha index) and temporal beta diversity index to provide insight into PFM effectiveness over thirty-five years (1986–2021). Landsat MSS (1986), SPOT (2005) and Sentinel 2b (2021) satellite images were used to assess the LULCC, via supervised classification and visual interpretation. Temporal dynamics of trees diversity was evaluated using forest inventory data from two years (2007 and 2023). A linear regression was performed to identify the anthropogenic factors (fire, grazing, distance from villages to forests) driving temporal changes in floristic composition. We found a decline in forests area which was more critical after the implementation of PFM (2005 and 2021), with a slight decline in species diversity (1.80 ± 0.68 in 2007 and 1.65 ± 0.56 in 2023). PFM efficiency was higher in larger forests, which have experienced less deforestation than smaller ones. Significant variations in forest land cover were observed among forests from 1986 to 2021, particularly in Agoua (26.76% and 52.13% between 1986 and 2005 and 2005–2021 respectively) and Wari-maro Mont-Kouffé (1.96% and 0.16% between 1986 and 2005 and 2005–2021 respectively). There was a significant decline in trees density from 2007 (252 trees/ha) to 2023 (155 trees/ha), while tree diameter (15 to 22 cm) and height (8 to 12 m) have increased between 2007 and 2023. The foristic composition of forests has changed, with an overall downward trend in diversity, affected by forest fires. The study provides valuable insights into the effectiveness of PFM as a conservation policy.

Classifying forest cover and mapping forest fire susceptibility in Dak Nong province, Vietnam utilizing remote sensing and machine learning

Forest fires can cause significant harm to the biodiversity, air quality, economy, and industries that depend on forests, which is particularly critical given the current climate change scenario. Therefore, it is crucial to predict potential fire risks, especially in Dak Nong, a province located in the highland region of Vietnam, where forest farming is prevalent. In this study, the utilization of remote sensing data from unmanned aerial vehicles (UAV) revealed a decline in forest areas while agricultural rubber and industrial crops witnessed an increase. Furthermore, the integration of SPOT satellite images with UAV and the eXtreme gradient boosting (XGBoost) classification algorithm proved highly efficient in mapping forest types in this province (OA = 81.446%, and Kappa = 0.803). To assess forest fire susceptibility in this study, a hybrid model known as Artificial bee colony-Adaptive neuro fuzzy inference system (ABC-ANFIS) was employed, which indicated that the majority of forests in the area face high to very high of fires, particularly in bamboo and dipterocarp forest areas. The present model is proposed to suggest better prevention and suppression strategies. These facts can help managers stop fires or deal with this disturbance more effectively that may occur in the future. Policymakers and researchers in different areas, such as the limestone forest in the north or the Dipterocarp forests in Vietnam, may consider replicating this study to evaluate specific wildfire risks and develop appropriate fire prevention strategies tailored to their local circumstances.

The Impact and Prediction of Shoreline Dynamics in Pekalongan, Indonesia

Shoreline in Pekalongan has changed and impacted land use significantly. This research investigates historical changes in shoreline dynamics and their impact on land use from 2003–2021. This research also examines the trend of shoreline prediction for 2031–2041. Multitemporal SPOT5 and SPOT6 satellite images were used as primer data to detect shoreline and land use changes. The DSAS (Digital Shoreline Analysis System) analyzes the shoreline change and generates shoreline prediction. This research shows that the coastal areas of Pekalongan have been impacted by erosion, with 528.08 hectares of area and 56.33 hectares of accretion. The North Pekalongan sub-district is the worst area hit by erosion. The shoreline has retreated 2405.8 meters with a 353.3 m/year erosion rate. Several areas of land use were heavily affected by erosion trends, such as ponds, rice fields, and open land. Shoreline predictions generated by DSAS were heavily reliant on historical rates of shoreline change dynamics. The predicted area of the shoreline is estimated to retreat 49.9–466.2 meters from the existing position in the next 10 and 20 years. This research is expected to provide information to local governments for evaluating the maintenance and development planning of the coastal area

Influence of DEM resolution on topographic correction models using spot satellite image

Topographic correction models (TCMs) are valid on satellite image data preprocessing steps. Theillumination angle may be sensitive to different terrain slope and aspect conditions base on sun-terrain-sensorgeometry. Although the topographic correction is influenced by the sun azimuth and zenith angle, the correction resultcan be equally in the same image status. By contrast, the terrain factors change with different digital elevation model(DEM) resolution in the topographic correction equations and cause a significant effect. Slope is sensitive in ruggedterrain, and aspect is impressionable at flat surface at a coarse DEM resolution data. As the DEM resolution lead adistinct result on TCMs, this research is aimed to examine the impact of DEM resolution on the accuracy of terrainrepresentation and of the gradient determined. In this study, five TCMs, including cosine correction, C correction, SCS correction, SCS+C correction and Minnaert correction models are compared by different resolutions using SPOTimage data. The 5 meter DEM obtained from Ministry of the interior will be resampled to 10 to 500 meters to testthose topographic models sustainability on Lienhuachih Research Center. The accuracy of five topographic correctionmodels base on different DEM resolution will be evaluated by root-mean-square error (RMSE).

Dynamics and Drivers of Land Use and Land Cover Change in the Upper Awash Basin, Central Rift Valley of Ethiopia.

This study analyzed the patterns and drivers of LULC dynamics in relation to the expansion of large-scale irrigated agriculture in the Central Rift Valley of Ethiopia from 1972 to 2016. Aerial photographs (1972), Landsat images (1980, 2000) and SPOT5 satellite images (2016) were analyzed using GIS tools to reveal LULC changes, and documentation, key informant interviews and focus group discussions were used to ascertain the biophysical and socioeconomic implications and drivers of these dynamics. The study revealed that cultivated and rural settlement land, and urban built-up areas had expanded at the expense of forestland, woodland, shrubland and grassland. While an increase in the production of cash crops had brought some benefits to smallholder farmers, such as access to irrigation and modern agricultural inputs and technologies, the unregulated conversion of natural vegetation to cultivated land resulted in a loss of biodiversity, deforestation, and reduction of pasture and firewood. We identified that significant LULC changes in the study area were caused by intersecting biophysical, economic, institutional, technological and demographic factors, which reinforced each other with varying magnitudes at different moments in time. These changes were underpinned by one key driver, that is, government agricultural policies that promoted investment in commercial agriculture for national and export markets. The study shows that understanding the complex interaction between the contributing factors and drivers of LULC change is crucial to inform decision-making and policies, in particular, by directing responses towards the underlying drivers of change rather than only the proximate causes.

Mechanisms of vegetation restoration at landslides caused by a catastrophic earthquake in Central Taiwan

The vegetation restoration of a large-scale landslide, triggered by the catastrophic earthquake on 21 September 1999, in Jiujiu Peaks, Central Taiwan with an impacted area of 821 ha recovered 80% by 2020 was studied using self-organizing map (SOM) coupled with multi-temporal SPOT satellite images and a terrain-based distribution index for a 20-year period. Although disturbed by several typhoons during two decades of natural vegetation succession, the landslide restoration rate has reached 87.5% with the invasion or regrowth of vegetation gradually. A predicted logarithmic model with statistically significant difference was derived to estimate the restoration trend of the landslide in the studied area. Most of the poorly vegetated areas are located along the ridgelines, as verified by field surveys. Landslide restoration was carried out in three stages, (1) vulnerable landslides and fast-growing invasive vegetation (1999/9 - 2005/9); (2) stabilized landslides and slow-growing vegetation toward the vegetated strips (2005/9 - 2009/11); and (3) more stabilized landslides and vegetation toward secondary forest (2009/11–2020/2). Topographic location, water supply, typhoon disturbance, invasive or residual vegetation patterns and succession time are the main factors of landslide restoration. The evaluated results indicate that nature itself is a complex ecological balance system with a strong capacity for vegetation recovery at landslides, and can be used by government agencies to add in the recovery of landslide areas.

Implications of changes in land use on soil and biomass carbon sequestration: a case study from the Owabi reservoir catchment in Ghana

Land use changes affect soil and biomass carbon sequestration potential of the agroecosystems of most Sub-Sahara Africa facing rising temperatures due to global climate change. One such ecosystem is the Owabi reservoir catchment in Ghana, which has undergone extensive changes in land use through urbanization. Our study aimed to determine the impact of the spatial and temporal variability of the different land uses on soil and biomass carbon storage in the Owabi catchment. Land use/cover maps were elaborated using SPOT satellite images of 30 × 30-m resolution and Erdas Imagine and ArcGIS Pro softwares. Soil and vegetation were sampled along three transects in the Y plane in early 2014. Nested plot design and temporary sample plots of 50 × 50 m were demarcated within a 1 ha plot in each of the land uses. Trees, herbs and litter were sampled to assess aboveground carbon, and soil samples were taken at 0–15 cm and 15–30 cm depth. Belowground (root) biomass was calculated using the root:shoot ratio. Seven (7) land use types – dense forest, sparse forest, grassland, cropland, wetland, settlement, and excavated land – were identified and differences in carbon stocks were assessed. Soil carbon stock (0–30 cm) ranged from 51.80 Mg/ha in dense forest to 7.00 Mg/ha in excavated land. Our study showed that the conversion of forest lands to other land uses through excavation resulted in about 30-folds loss in carbon and also a major loss of carbon in the catchment from c. 1.4 × 106 Mg C in 1990 to 0.55 × 106 Mg C in 2014. Enhancing forests or growing trees to sequester carbon seems to be the optimum choice among the seven land uses if the introduction of payment for environmental services options is considered.

Using of intensity analysis approach in Benin coastal zone (West Africa) to assess land use/land cover change for further decision making

Coastal areas are fruitful environments with a complex diversity of ecosystems. These areas are very sensitive and therefore, changes in the region of interest (ROI) require special attention due to the consequences. The changes observed in the coastal zone of Benin, such as: coastal erosion, the decrease of mangrove ecosystems and its consequences, and the pressure on agricultural land, have motivated this study, which aims to assess land use land cover in the coastal zone of Benin in order to better anticipate the phenomena of loss and fragmentation of ecosystems and to provide guidelines for policy-making. To achieve this objective, remote sensing and field surveys were used. Spot and Landsat satellite images of the years 1991–2006 and 2021 have been uploaded to regards. cnes.fr and USGS. Direct field observations and group discussions to determine the driving forces behind the changes were conducted. Supervised classification using the Maximum Likelihood approach of ENVI software was used and QGIS 3.16 to process the data. Significant changes have been observed in the coastal zone our study area over the past thirty years. During the period 1991–2006, palm fields constituted the largest land use with 84786 ha or 28.9% of the total area. This occupation will decrease over time to reach 66773.2 ha in 2006 (22.7% of the total area) and 27406.5 ha or 7.2% of the total area in 2021. Classes such as Mosaic of crop and out of crop, dense forest have experienced the same evolution while the opposite trend is observed in built-up areas. From 11543 ha or 3.9% of the total area in 1991, this class has increased to 25138 ha or 8.7% of the total area in 2006 and 44418.5 ha or 15.1% in 2021. Urbanization and the need for agricultural land have been identified as driving forces behind these changes and Markov chain analysis reveals future regression of coastal ecosystems such as mangroves, dense forest, swamp, and crop ender palm. These outcomes have far-reaching policy direction of environmental sustainability target in Benin coast.

SPOT vs Landsat satellite images for the evolution of the north Peloponnese coastline, Greece

The littoral zone of Achaia prefecture, located in northwestern Peloponnese of Greece, is an area which has experienced significant modification the last two decades. It is a linear and sandy coast with limited curves and infrastructures, suitable for the comparison of the shoreline derived from SPOT and Landsat satellite images. Nowadays, the application of the remote sensing has overshadowed the traditional methods of shoreline mapping, such as ground survey along with transects and airborne stereophotogrammetry, as low-cost repeatable observations can be made, providing reliable results.The normalized difference water index (NDWI), which is computed from multispectral satellite data, have been successfully applied to shoreline discrimination. Consequently, the current manuscript applies to the specific index on Landsat and SPOT data for the 1987–2008 period in order to detect the shoreline position. Moreover, shorelines were generated from the Landsat and SPOT satellite images of medium spatial resolution, 30 m and 20 m respectively, for the years of 1987, 1996, and 2008, and their accuracy was compared to respective data derived from air photos with high spatial resolution (0.50 m to 1 m).The analysis revealed that the Landsat TM 5 data provide more accurate vectorized shorelines than the SPOT 1 to 4 series with 20 m spatial resolution via the NDWI. Both are not suitable for high-scale​ accurate diachronic shoreline monitoring, even if image fusion techniques were used, as they emerged bad overlapping ratio following significant distortions on the two axes in relation to the respective high-resolution reference data. Moreover, they provided quite different results regarding the shoreline evolution in relation to the respective high-resolution data.

Assessment of landslide susceptibility, exposure, vulnerability, and risk in shahpur valley, eastern hindu kush

This study assessed landslide susceptibility in Shahpur valley, situated in the eastern Hindu Kush. Here, landslides are recurrent phenomena that disrupt the natural environment, and almost every year, they cause huge property damages and human losses. These damages are expected to escalate in the study area due to the high rate of deforestation in the region, population growth, agricultural expansion, and infrastructural development on the slopes. Landslide susceptibility was assessed by applying “weight of evidence” (WoE) and “information value” (IV) models. For this, the past landslide areas were identified and mapped on the SPOT5 satellite image and were verified from frequent field visits to remove the ambiguities from the initial inventory. Seven landslide contributing factors including surface geology, fault lines, slope aspect and gradient, land use, and proximity to roads and streams were identified based on indigenous knowledge and studied scientific literature. The relationship of landslide occurrence with contributing factors was calculated using WoE and IV models. The susceptibility maps were generated based on both the WoE and IV models. The results showed that the very high susceptible zone covered an area of 14.49% and 12.84% according to the WoE and IV models, respectively. Finally, the resultant maps were validated using the success and prediction rate curves, seed cell area index (SCAI), and R-index approaches. The success rate curve validated the results at 80.34% for WoE and 80.13% for the IV model. The calculated prediction rate for both WoE and IV was 83.34 and 85.13%, respectively. The SCAI results showed similar performance of both models in landslide susceptibility mapping. The result shows that the R-index value for the very high LS zone was 29.64% in the WoE model, and it was 31.21% for the IV model. Based on the elements at risk, a landslide vulnerability map was prepared that showed high vulnerability to landslide hazards in the lower parts of the valley. Similarly, the hazard and vulnerability maps were combined, and the risk map of the study area was generated. According to the landslide risk map, 5.5% of the study area was under high risk, while 2% of the area was in a very high-risk zone. It was found from the analysis that for assessing landslide susceptibility, both the models are suitable and applicable in the Hindu Kush region.

Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques

The Near-equatorial orbit (NEqO) satellite represents a new generation of optical satellite images characterized by nonlinear distortion when captured. Conventional modeling techniques are insufficient to overcome the geometric distortion in these satellite images. This study proposes a new methodology for overcoming the geometric distortion of the NEqO images. The data used are obtained from RazakSAT and SPOT-5 satellite images in Malaysia. The method starts with applying the RI-SIFT algorithm to extract control points (CPs) automatically. These CPs are used to solve for the transformation parameters of the geometric correction model by applying spline transformations. The result is verified through statistical comparison: 1) geometric correction on the RazakSAT image is performed with Spot satellite image with using first-order polynomial trans-formation. 2) Then calculate the root mean square error (RMSE). 3) Compare the calculated RMSE with that obtained from the first step with that of the proposed method. The RMSE value of the geometric corrections using the proposed method was 7.08 × 10−9 m. The proposed method provides promising results.

Deteksi Perubahan Garis Pantai Menggunakan Teknik Geospasial, Studi Kasus Kecamatan Tejakula


 
 
 
 The coastal area in Tejakula Subdistrict has many potential benefits for local people and the development of the region. Regarding its economic perspective, marine biodiversity can be utilized for tourism development. In terms of culture and history, this area has many archaeological findings ranging from prehistory until the colonial period. However, the recent study from Balai Arkeologi Bali stated the objects were sunk into underwater at a depth of 1-2 meters due to the abrasion process. Therefore, this research discussed the changes of shoreline in the Tejakula Subdistrict area as a preliminary study to protect and preserve its potential values. This research, both in terms of economy, culture, and history. The calculation of shoreline changes is using the Digital Shoreline Analysis System (DSAS) application with Net Shoreline Movement (NSM) and End Point Rate (EPR) methods. The results showed that the coastal segment in Tejakula District experienced an abrasion change with an abrasion rate of 0.89 m/year based on the SPOT satellite image analysis and 0.17 m/year from Landsat satellite imagery.
 
 
 

Evaluation of the sufficiency of urban green spaces: Nigde city example

Objective: In this study, the numerical values that will guide the planner and the manager depending on the accessibility, adequacy and effective service areas of the Niğde urban green areas (GA) have been obtained. 
 Material and Methods: The usage of GA of Niğde City is examined as children's playground, park and sports areas. The data was obtained from ASTER, Landsat 7-ETM and SPOT satellite images, the Niğde Development Plan (2017) with a scale of 1/1000 and ArcGIS software was used in spatial competence and accessibility analyzes of green spaces.
 Results: Active GA of Niğde city center is distance between neighborhood centers and percentages are calculated for each neighborhood. There are sport areas only in 4 parks in 61 neighborhood. 91% of the neighborhood and district parks are below 1 ha, while 9% are between 0.001-0.004 ha. Sports areas, 6% is between 4-6 ha, while 1% is 0.1 ha. 
 Conclusion: Nigde urban green space assets quite low when compared with cities of the European Union, within the framework of the Reconstruction Act in Turkey have also been found to be inadequate.

Assessment of flash flood hazard based on morphometric aspects and rainfall-runoff modeling in Wadi Nisah, central Saudi Arabia

The lack of monitoring and observational data is hampering the assessment of flash flood hazard in arid environments. This study forecasts and investigates flash floods hazards in Wadi Nisah basin in the central region of Saudi Arabia. An integrated approach of Geographic Information System (GIS), Remote Sensing (RS), and Watershed Modeling System (WMS) is presented to determine the flash flood hazards based on morphometric analysis along with rainfall runoff modeling. RS datasets including Shuttle Radar Topography Mission (SRTM) data for digital elevation model (DEM), and SPOT-5 satellite images for land cover mapping, in addition to meteorological data (represented in historical rainfall logs) are used. The study area is divided into 14 sub-basins according to the 5th stream order. The morphometric parameter's analysis clearly show that 42.3%–62% of the total region of Wadi Nisah is highly prone to flooding. Furthermore, medium- and low-hazard areas make up 2.1%–36.4% and 16.5%–55.6% of the total area, respectively. Rainfall-runoff modeling shows that the peak discharge values of sub-basin 14, covers 39.6% of the Wadi Nisah total area, making it greater than that of other sub-basins for each return period, ranging from 12.3 m3/s for a 5-year return period to 294.5 m3/s for a 100-year return period. Accordingly, sub-basin 14 poses more flood risk than other Wadi Nisah sub-basins, as confirmed by the morphometric ranking method analysis.

Effect of Erosion and Accretion on Beach Profile in Kuala Terengganu Coastal Areas

Coastal erosion and accretion are long-term process that may cause changes in shoreline and beach profiles. Due to erosion and accretion effects, most of the coastal areas in Malaysia are suffering from destruction of property especially at the coastal areas in east coast of Peninsular Malaysia. This study was conducted to determine the effects of erosion and accretion on beach profiles at four (4) coastal areas in Kuala Terengganu using remote sensing and GPS observation methods. The objectives include to derive the coastal erosion and accretion rate, to measure coastal elevation for beach slope angle calculation, and to determine the relationship between beach slope angle with coastal erosion and accretion. The erosion and accretion rate was derived from SPOT-5 satellite image and unmanned aerial vehicles (UAV). In order to obtain the beach profile, the elevation with 50m offset for every chainage, and 5m offset for each cross-section point were carried out using real-time kinetic (RTK) observation methods. It was found that the highest and lowest erosion and accretion rates were 170.29 m²/year and 57.53 m²/year, respectively. The beach profile became steeper with the beach slope values of 11.004° and 7.652° at high and low erosion areas, respectively. The relationships between beach slope angle and coastal erosion/accretion were found as 0.12 and 0.86 respectively. The findings showed that steeper beach profiles influenced the high rate values of erosion and accretion. For more accurate findings, further studies on the factors affecting the erosion and accretion such as monsoon seasonal changes and morphological impact are necessary to support the reliable decision-making process for sustainable coastal management.