scholarly journals Spatial analysis of Prosopis Juliflora trees, its environmental and developmental effects on Wadi Yiba in the southwest of Saudi Arabia: التحليل المكاني لأشجار البرسوبس وآثاره البيئية والتنموية على وادي يــبة جنوب غرب المملكة العربية السعودية

2021 ◽  
Vol 5 (4) ◽  
pp. 97-63
Author(s):  
Norah Ali Alshehri Norah Ali Alshehri
Keyword(s):  
Saudi Arabia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spatial Information ◽  
Prosopis Juliflora ◽  
South American ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Invasive Shrub ◽  
Future Situation

Prosopis Juliflora is an invasive shrub or tree native to South American countries. It is one of the most important exotic and invasive organisms that are spread in the Kingdom of Saudi Arabia. This study concentrates on investigating the widespread of Prosopis Juliflora  in Wadi Yiba، located in the southwest of the Kingdom، and given the possibilities offered by geographic information system (GIS) and remote sensing to help determine the areas of spread of the plant and its size، and to take the best capabilities، especially with regard to processing and analyzing large and diverse spatial information، the present research aims to use this in evaluating the current and future situation of the spread of plants in Wadi Yiba، and the extent of its impact on the environment، while suggesting appropriate ways to manage it. The research relied on the use of Landsat images، working with the subtraction method، and subjecting the images to the object-oriented classification، by taking 30 specimens for each cover and merging these specimens، and the layers of vegetation cover were derived using the normalized difference vegetation index (NDVI) for each year. The research concluded that there is a concentration in the spread of Prosopis Juliflora in the center and north of Wadi Yiba، especially in the city of Therban and villages of Al-Balqa’a، Al-Tala’i، Sabt Al-Jara، and Khamis Harb، with a spread along the valley to the estuary. At the end، the research recommended the establishment of a research center for the study of Prosopis Juliflora in Assir region، and an attempt to develop economic plans to benefit from Prosopis Juliflora in Wadi Yiba.

scholarly journals Monitoring Land Cover Change Using Remote Sensing and GIS Techniques: a Case Study of Al-Dalmaj Marsh, Iraq

2018 ◽  
Vol 24 (9) ◽  
pp. 96 ◽  
Author(s):  
Marwah Moojid Kadhim
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Accurate Information ◽  
Past Century ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Vegetation Water ◽  
Set Up

Al-Dalmaj marsh and the near surrounding area is a very promising area for energy resources, tourism, agricultural and industrial activities. Over the past century, the Al-Dalmaje marsh and near surroundings area endrous from a number of changes. The current study highlights the spatial and temporal changes detection in land cover for Al-Dalmaj marsh and near surroundings area using different analyses methods the supervised maximum likelihood classification method, the Normalized  Difference Vegetation Index (NDVI), Geographic Information Systems(GIS),  and Remote Sensing (RS). Techniques spectral indices were used in this study to determine the change of wetlands and drylands area and of other land classes, through analyses Landsat images for different three years (1990, 2003, 2016). The results indicated that there was an annual increase in vegetation was from 1990 with 980.68 km2, and 1420.35km2 in 2003 to 2072.98km2 in 2016. Whereas, the annual water coverage was about 185.95km2 in 1990 then dropped to 68.27km2 in 2003, and rose to 180.23 km2 in 2016. The water coverage increasing was on the account of barren lands areas, which were significantly decreased. These collected data can be used to deliver accurate information of the values of vegetation,water, wetlands and drylands sustainability of resources which can be used to make plans to increase tourism and protected areas by using barren lands which cannot be reclaimed for agriculture, and cultivate a new renewable energy can be set up  as solar power stations.  

scholarly journals APPLICATION OF REMOTE SENSING AND GIS FOR ASSESSING LAND COVER RESOURCES VARIABILITY IN THE SELOUS GAME RESERVE, TANZANIA

2017 ◽  
Vol 1 (2) ◽  
pp. 74
Author(s):  
Phillip W. Mambo ◽  
John E. Makunga
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing And Gis ◽  
Vegetation Density ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Game Reserve ◽  
Year 2000

Purpose: The study was conducted in Selous Game Reserve, with intention of developing GIS and Remote Sensing based wildlife management system in the protected area.Methodology: All habitats were digitised using ArcGIS9.3 in which five scenes of Landsat TM and ETM+ digital images were acquired during dry seasons of the year 2000 and 2010. Band 3 and 4 of the Landsat images were used for calculation of normalized difference vegetation index (NDVI) for determination of vegetation spatial distributionResults: The NDVI maps of year 2000 to 2010 revealed the vegetation density depletion from 0.72 (obtained in 0.46─0.72 value interval and covering 46.5% pixel area) in 2000 as compared to 0.56 ( found in 0.38─0.56 value interval and covering 8.04% pixel area) in 2010 NDVI maps.Unique contribution to theory, practice and policy: It was recommended that there was a necessity to integrate applications of remote sensing and GIS techniques for the assessment and monitoring of the natural land cover variability to detect fragmentation and loss of wildlife species.

scholarly journals An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data

2020 ◽  
Vol 12 (24) ◽  
pp. 4181
Author(s):  
Kunlun Xiang ◽  
Wenping Yuan ◽  
Liwen Wang ◽  
Yujiao Deng
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Statistical Data ◽  
Spatial Information ◽  
Hydrological Cycle ◽  
Mainland China ◽  
Mean Annual Precipitation ◽  
Irrigated Area ◽  
Moderate Resolution

Accurate spatial information about irrigation is crucial to a variety of applications, such as water resources management, water exchange between the land surface and atmosphere, climate change, hydrological cycle, food security, and agricultural planning. Our study proposes a new method for extracting cropland irrigation information using statistical data, mean annual precipitation and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data and surface reflectance data. The approach is based on comparing the land surface water index (LSWI) of cropland pixels to that of adjacent forest pixels with similar normalized difference vegetation index (NDVI). In our study, we validated the approach over mainland China with 612 reference samples (231 irrigated and 381 non-irrigated) and found the accuracy of 62.09%. Validation with statistical data also showed that our method explained 86.67 and 58.87% of the spatial variation in irrigated area at the provincial and prefecture levels, respectively. We further compared our new map to existing datasets of FAO/UF, IWMI, Zhu and statistical data, and found a good agreement with the irrigated area distribution from Zhu’s dataset. Results show that our method is an effective method apply to mapping irrigated regions and monitoring their yearly changes. Because the method does not depend on training samples, it can be easily repeated to other regions.

scholarly journals Consideration of NDVI thematic changes in density analysis and floristic composition of Wadi Yalamlam, Saudi Arabia

2018 ◽  
Vol 7 (4) ◽  
pp. 297-306 ◽  
Author(s):  
Amal Y. Aldhebiani ◽  
Mohamed Elhag ◽  
Ahmad K. Hegazy ◽  
Hanaa K. Galal ◽  
Norah S. Mufareh
Keyword(s):  
Saudi Arabia ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Floristic Composition ◽  
Water Source ◽  
Shannon Index ◽  
Landsat 8 ◽  
Main Stream

Abstract. Wadi Yalamlam is known as one of the significant wadis in the west of Saudi Arabia. It is a very important water source for the western region of the country. Thus, it supplies the holy places in Mecca and the surrounding areas with drinking water. The floristic composition of Wadi Yalamlam has not been comprehensively studied. For that reason, this work aimed to assess the wadi vegetation cover, life-form presence, chorotype, diversity, and community structure using temporal remote sensing data. Temporal datasets spanning 4 years were acquired from the Landsat 8 sensor in 2013 as an early acquisition and in 2017 as a late acquisition to estimate normalized difference vegetation index (NDVI) changes. The wadi was divided into seven stands. Stands 7, 1, and 3 were the richest with the highest Shannon index values of 2.98, 2.69, and 2.64, respectively. On the other hand, stand 6 has the least plant biodiversity with a Shannon index of 1.8. The study also revealed the presence of 48 different plant species belonging to 24 families. Fabaceae (17 %) and Poaceae (13 %) were the main families that form most of the vegetation in the study area, while many families were represented by only 2 % of the vegetation of the wadi. NDVI analysis showed that the wadi suffers from various types of degradation of the vegetation cover along with the wadi main stream.

scholarly journals A Study of Desertification Using Remote Sensing Techniques in Basra Governorate, South Iraq

2021 ◽  
pp. 912-926
Author(s):  
Fadel Abbas Zwain ◽  
Thair Thamer Al-Samarrai ◽  
Younus I. Al-Saady
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arid Zone ◽  
Sand Dunes ◽  
Risk Index ◽  
Anthropogenic Factors ◽  
Landsat Images

Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and Land Degradation Risk Index (LDI) which was used for the assessment of degradation severity .Three Landsat images, acquired in 1973, 1993, and 2013, were used to evaluate the potential of using remote sensing analysis in desertification monitoring. The approach applied in this study for evaluating this phenomenon was proven to be an effective tool for the recognition of areas at risk of desertification. The results indicated that the arid zone of Basra governorate encounters substantial changes in the environment, such as decreasing surface water, degradation of agricultural lands (as palm orchards and crops), and deterioration of marshlands. Additional changes include increased salinization with the creeping of sand dunes to agricultural areas, as well as the impacts of oil fields and other facilities.

scholarly journals Monitoring of Inland Surface Water Quality Using Remote Sensing on the Example of Wigry Lake

2018 ◽  
Vol 63 ◽  
pp. 00017
Author(s):  
Michał Lupa ◽  
Katarzyna Adamek ◽  
Renata Stypień ◽  
Wojciech Sarlej
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Water Quality ◽  
Lake Area ◽  
Landsat Images ◽  
Secchi Disc ◽  
Water Index ◽  
Normalized Difference Water Index

The study examines how LANDSAT images can be used to monitor inland surface water quality effectively by using correlations between various indicators. Wigry lake (area 21.7 km2) was selected for the study as an example. The study uses images acquired in the years 1990–2016. Analysis was performed on data from 35 months and seven water condition indicators were analyzed: turbidity, Secchi disc depth, Dissolved Organic Material (DOM), chlorophyll-a, Modified Normalized Difference Water Index (MNDWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The analysis of results also took into consideration the main relationships described by the water circulation cycle. Based on the analysis of all indicators, clear trends describing a systematic improvement of water quality in Lake Wigry were observed.

Factors influencing the pattern of fire severities in a large wildfire under extreme meteorological conditions in the Mediterranean basin

2009 ◽  
Vol 18 (7) ◽  
pp. 755 ◽  
Author(s):  
Imma Oliveras ◽  
Marc Gracia ◽  
Gerard Moré ◽  
Javier Retana
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Severity ◽  
Fire Behavior ◽  
Negative Relationship ◽  
Canopy Cover ◽  
Mediterranean Ecosystems ◽  
Meteorological Conditions ◽  
Landsat Images ◽  
The Difference

In Mediterranean ecosystems, large fires frequently burn under extreme meteorological conditions, but they are usually characterized by a spatial heterogeneity of burn severities. The way in which such mixed-severity fires are a result of fuels, topography and weather remains poorly understood. We computed fire severity of a large wildfire that occurred in Catalonia, Spain, as the difference between the post- and pre-fire Normalized Difference Vegetation Index (NDVI) values obtained through Landsat images. Fuel and topographic variables were derived from remote sensing, and fire behavior variables were obtained from an exhaustive reconstruction of the fire. Results showed that fire severity had a negative relationship with percentage of canopy cover, i.e. green surviving plots were mainly those with more forested conditions. Of the topographic variables, only aspect had a significant effect on fire severity, with higher values in southern than in northern slopes. Fire severity was higher in head than in flank and back fires. The interaction of these two variables was significant, with differences between southern and northern aspects being small for head fires, but increasing in flank and back fires. The role of these variables in determining the pattern of fire severities is of primary importance for interpreting the current landscapes and for establishing effective fire prevention and extinction policies.

scholarly journals A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture

2021 ◽  
Vol 13 (23) ◽  
pp. 13438
Author(s):  
Mostafa A. Abdellatif ◽  
Ahmed A. El Baroudy ◽  
Muhammad Arshad ◽  
Esawy K. Mahmoud ◽  
Ahmed M. Saleh ◽  
...  
Keyword(s):  
Soil Quality ◽  
Environmental Sustainability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kriging Interpolation ◽  
Quality Model ◽  
Soil Quality Index ◽  
Gis And Remote Sensing ◽  
Geostatistical Approach ◽  
Total Study Area

Assessing soil quality is considered one the most important indicators to ensure planned and sustainable use of agricultural lands according to their potential. The current study was carried out to develop a spatial model for the assessment of soil quality, based on four main quality indices, Fertility Index (FI), Physical Index (PI), Chemical Index (CI), and Geomorphologic Index (GI), as well as the Geographic Information System (GIS) and remote sensing data (RS). In addition to the GI, the Normalized Difference Vegetation Index (NDVI) parameter were added to assess soil quality in the study area (western part of Matrouh Governorate, Egypt) as accurately as possible. The study area suffers from a lack of awareness of agriculture practices, and it depends on seasonal rain for cultivation. Thus, it is very important to assess soil quality to deliver valuable data to decision makers and regional governments to find the best ways to improve soil quality and overcome the food security problem. We integrated a Digital Elevation Model (DEM) with Sentinel-2 satellite images to extract landform units of the study area. Forty-eight soil profiles were created to represent identified geomorphic units of the investigated area. We used the model builder function and a geostatistical approach based on ordinary kriging interpolation to map the soil quality index of the study area and categorize it into different classes. The soil quality (SQ) of the study area, classified into four classes (i.e., high quality (SQ2), moderate quality (SQ3), low quality (SQ4), and very low quality (SQ5)), occupied 0.90%, 21.87%, 22.22%, and 49.23% of the total study area, respectively. In addition, 5.74% of the study area was classified as uncultivated area as a reference. The developed soil quality model (DSQM) shows substantial agreement (0.67) with the weighted additive model, according to kappa coefficient statics, and significantly correlated with land capability R2 (0.71). Hence, the model provides a full overview of SQ in the study area and can easily be implemented in similar environments to identify soil quality challenges and fight the negative factors that influence SQ, in addition to achieving environmental sustainability.

scholarly journals Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods

2019 ◽  
Vol 10 (1) ◽  
pp. 48-56 ◽  
Author(s):  
Muhammad Khubaib Abuzar ◽  
Muhammad Shafiq ◽  
Syed Amer Mahmood ◽  
Muhammad Irfan ◽  
Tayyaba Khalil ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Social Life ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Standardized Precipitation Index ◽  
Temporal Analysis ◽  
Agricultural Drought ◽  
Natural Phenomenon ◽  
Drought Risk ◽  
Gis And Remote Sensing

Drought is a harmful and slow natural phenomenon that has significant effects on the economy, social life,agriculture and environment of the country. Due to its slow process it is difficult to study this phenomenon. RemoteSensing and GIS tools play a key role in studying different hazards like droughts. The main objective of the study wasto investigate drought risk by using GIS and Remote Sensing techniques in district Khushab, Pakistan. Landsat ETMimages for the year 2003, 2009 and 2015 were utilized for spatial and temporal analysis of agricultural andmeteorological drought. Normalized difference vegetation index (NDVI) Standardized Precipitation Index (SPI) andrainfall anomaly indices were calculated to identify the drought prone areas in the study area. To monitormeteorological drought SPI values were used and NDVI was calculated for agricultural drought. These indices wereintegrated to compute the spatial and temporal drought maps. Three zones; no drought, slight drought and moderatedrought were identified. Final drought map shows that 30.21% of the area faces moderate drought, 28.36% faces slightdrought while nearly 41.3% faces no drought situation. Drought prevalence and severity is present more in the southernpart of Khushab district than the northern part. Most of the northern part is not under any type of drought. Thus, anoverall outcome of this study shows that risk areas can be assessed appropriately by integration of various data sourcesand thereby management plans can be prepared to deal with the hazard.

scholarly journals Satellite-based evaluation of temporal change in cultivated land in Southern Punjab (Multan region) through dynamics of vegetation and land surface temperature

2021 ◽  
Vol 13 (1) ◽  
pp. 1561-1577
Author(s):  
Sajjad Hussain ◽  
Muhammad Mubeen ◽  
Ashfaq Ahmad ◽  
Nasir Masood ◽  
Hafiz Mohkum Hammad ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Environmental Changes ◽  
Anthropogenic Activities ◽  
Cropping Pattern ◽  
Landsat Images ◽  
Urban Climatology

Abstract The rapid increase in urbanization has an important effect on cropping pattern and land use/land cover (LULC) through replacing areas of vegetation with commercial and residential coverage, thereby increasing the land surface temperature (LST). The LST information is significant to understand the environmental changes, urban climatology, anthropogenic activities, and ecological interactions, etc. Using remote sensing (RS) data, the present research provides a comprehensive study of LULC and LST changes in water scarce and climate prone Southern Punjab (Multan region), Pakistan, for 30 years (from 1990 to 2020). For this research, Landsat images were processed through supervised classification with maps of the Multan region. The LULC changes showed that sugarcane and rice (decreased by 2.9 and 1.6%, respectively) had less volatility of variation in comparison with both wheat and cotton (decreased by 5.3 and 6.6%, respectively). The analysis of normalized difference vegetation index (NDVI) showed that the vegetation decreased in the region both in minimum value (−0.05 [1990] to −0.15 [2020]) and maximum value (0.6 [1990] to 0.54 [2020]). The results showed that the built-up area was increased 3.5% during 1990–2020, and these were some of the major changes which increased the LST (from 27.6 to 28.5°C) in the study area. The significant regression in our study clearly shows that NDVI and LST are negatively correlated with each other. The results suggested that increasing temperature in growing period had a greatest effect on all types of vegetation. Crop-based classification aids water policy managers and analysts to make a better policy with enhanced information based on the extent of the natural resources. So, the study of dynamics in major crops and surface temperature through satellite RS can play an important role in the rural development and planning for food security in the study area.

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