Environmental change detection in the central part of Iraq using remote sensing data and GIS

This study aims to assess the potential of several ancillary input data for the improvement of unsupervised land cover change detection in arid environments. The study area is located in Central Iraq where desertification has been observed. We develop a new scheme based on known robust indices. We employ Landsat (multispectral scanner, thematic mapper, and enhanced thematic mapper) satellite data acquired in 1976, 1990, and 2002. We use the Normalized Deferential Vegetation Index, Normalized Differential Water Index (NDWI), Salinity Index (SI), and Eolian Mapping Index. Two new equations were applied for the SI and the NDWI indices. Validation was performed using ground truth data collected in 16 days. We show that such an approach allows a robust and low-cost alternative for preliminary and large-scale assessments. This study shows that desertification has increased in the study area since 1990.     

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

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

Drought risk assessment using remote sensing and GIS techniques

Beginning with a discussion of drought definitions, this review paper attempts to provide a review of fundamental concepts of drought, classification of droughts, drought indices, and the role of remote sensing and geographic information systems for drought evaluation. Owing to the rise in water demand and looming climate change, recent years have witnessed much focus on global drought scenarios. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists. Temperatures; high winds; low relative humidity; and timing and characteristics of rains, including distribution of rainy days during crop growing seasons, intensity, and duration of rain, and onset and termination, play a significant role in the occurrence of droughts. In contrast to aridity, which is a permanent feature of climate and is restricted to low rainfall areas, a drought is a temporary aberration. Often, there is confusion between a heat wave and a drought, and the distinction is emphasized between heat wave and drought, noting that a typical time scale associated with a heat wave is on the order of a week, while a drought may persist for months or even years. The combination of a heat wave and a drought has dire socio-economic consequences. Drought risk is a product of a region’s exposure to the natural hazard and its vulnerability to extended periods of water shortage. If nations and regions are to make progress in reducing the serious consequences of drought, they must improve their understanding of the hazard and the factors that influence vulnerability. It is critical for drought-prone regions to better understand their drought climatology (i.e., the probability of drought at different levels of intensity and duration) and establish comprehensive and integrated drought information system that incorporates climate, soil, and water supply factors such as precipitation, temperature, soil moisture, snow pack, reservoir and lake levels, ground water levels, and stream flow. All drought-prone nations should develop national drought policies and preparedness plans that place emphasis on risk management rather than following the traditional approach of crisis management, where the emphasis is on reactive, emergency response measures. Crisis management decreases self-reliance and increases dependence on government and donors.     

Monitoring of the shoreline change using remote sensing and GIS: a case study of Al Hawasnah tidal inlet, Al Batinah coast, Sultanate of Oman

One of the most effective means of monitoring the cumulative effects of natural processes and human activities on the shoreline is to study the patterns of shoreline change over time. An attempt has been made to study the shoreline changes along Al Batinah, Sultanate of Oman, at the outlet of Wadi Al Hawasnah. The previous studies showed that Al Batinah coastline is generally stable except where coastal engineering structures like harbors, corniches, ports, and recharge dams are present. Remote sensing and GIS techniques are widely used in the coastal geomorphology because they provide the best sources to study the long-term shoreline changes. Rapid shoreline changes at the mouth of Wadi Al Hawasnah have been measured using proxy data derived mainly from satellite images from 2000 to 2005. The mouth of Wadi Al Hawasnah is now completely blocked after the construction of recharge dam at the upper stream of Wadi Al Hawasnah and Wadi Bani Umar in 1995. There has been no discharge to the sea after the construction of the dam. Furthermore, beach profiles of this area show erosion close to the south of the tidal inlet and accretion further south. The shorelines in the northwest of the tidal inlet remained stable.     

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

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

Groundwater vulnerability and risk mapping in a geologically complex area by using stable isotopes, remote sensing and GIS techniques

Groundwater vulnerability and risk mapping is a relatively new scientific approach for facilitating planning and decision making processes in order to protect this valuable resource. Pan European methodology for aquifers vulnerability has recently been developed by assessing all the existing relevant techniques and emphasizing on karstic environments. In the particular study, state-of-the-art methods and tools have been implemented such as remote sensing, isotopic investigations and GIS to map the groundwater vulnerability and pollution risk in a geologically complex area of W. Greece. The updated land use map has been developed from a Landsat 7+TM image elaborated with image analysis software, while the detailed hydrogeologic properties of the area have been recorded with an intensive isotopic study. The local groundwater vulnerability map has been produced following the aforementioned Pan European method, in a GIS environment while the risk map, which was the final product of the study, has been developed after combining the vulnerability and the land use maps. The results indicated that the areas comprised of highly tectonized calcareous formations represented high vulnerability and risk zones while forested areas away from the karstic aquifer illustrated moderate to low vulnerability. Moreover, human activities increase the pollution risk in lowland areas consisting of sedimentary deposits that have been classified as moderate vulnerability. The particular methodology operated efficiently in this study and due to its accuracy and relatively easy implementation can be used as a decision support tool for local authorities.     

Slope failure susceptibility zonation using integrated remote sensing and GIS techniques: A case study over Jhingurdah open pit coal mine,Singrauli coalfield,India

The susceptibility of slopes in open pit coal mines to various modes of failure (i.e., plane, wedge, circular and toppling failure) could be envisaged by virtue of processing and analysis of pertinent satellite data. The aim of the present study was to integrate thematic maps generated using remote sensing image processing techniques, in order to finally produce slope failure hazard zonation maps in and around Singrauli coalfield, India. The various failure-inducing factors, variables and parameters can be extracted from different satellite data and imageries. The data acquired by different sensors such as TM, ETM+, etc., of LANDSAT series and CARTOSAT of ISRO Bhuvan was used in this study. All these data were subsequently used to create different thematic maps such as slope map, lithological map, land use/land cover map, principal component analysis map, digital elevation model (DEM), etc. An advanced analysis for extraction of lineament attributes was also undertaken.     

Regional soil erosion risk mapping using RUSLE,GIS, and remote sensing: a case study in Miyun Watershed,North China

This paper applied the Revised Universal Soil Loss Equation (RUSLE), remote-sensing technique, and geographic information system (GIS) to map the soil erosion risk in Miyun Watershed, North China. The soil erosion parameters were evaluated in different ways: the R factor map was developed from the rainfall data, the K factor map was obtained from the soil map, the C factor map was generated based on a back propagation (BP) neural network method of Landsat ETM+ data with a correlation coefficient (r) of 0.929 to the field collected data, and a digital elevation model (DEM) with a spatial resolution of 30 m was derived from topographical map at the scale of 1:50,000 to develop the LS factor map. P factor map was assumed as 1 for the watershed because only a very small area has conservation practices. By integrating the six factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the upper watershed of Miyun reservoir was obtained by the RUSLE model. The results showed that the annual average soil loss for the upper watershed of Miyun reservoir was 9.86 t ha⁻¹ ya⁻¹ in 2005, and the area of 47.5 km² (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.88% very low, 21.90% low, 6.19% moderate, 2.90% severe, and 1.84% very severe. Among all counties and cities in the study area, Huairou County is in the extremely severe level of soil erosion risk, about 39.6% of land suffer from soil erosion, while Guyuan County in the very low level of soil erosion risk suffered from 17.79% of soil erosion in 2005. Therefore, the areas which are in the extremely severe level of soil erosion risk need immediate attention from soil conservation point of view.     

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

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

Assessment of groundwater potential zone using remote sensing,GIS and multi criteria decision analysis techniques

The sustainable development and management of groundwater resource needs quantitative assessment, based on scientific principle and recent techniques. In the present study, groundwater potential zone is being determined using remote sensing, Geographical Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) techniques using various thematic layers viz. geomorphology, geology, drainage density, slope, rainfall, soil texture, groundwater depth, soil depth, lineament and land use/ land cover. The Analytic Hierarchy Approach (AHP) is used to determine the weights of various themes for identifying the groundwater potential zone based on weights assignment and normalization with respect to the relative contribution of the different themes to groundwater occurrence. Finally, obtained groundwater potential zones were classified into five categories, viz. low, medium, medium-high, high and very high potential zone. The result depicts the groundwater potential zone in the study area and found to be helpful in better development and management planning of groundwater resource.     

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

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

Morphometric analysis of Morar River Basin, Madhya Pradesh, India, using remote sensing and GIS techniques

Hydrogeological mapping and drainage analysis can form an important tool for groundwater development. Assessment of drainage and their relative parameters have been quantitatively carried out for the Morar River Basin, which has made positive scientific contribution for the local people of area for the sustainable water resource development and management. Geographical Information System has been used for the calculation and delineation of the morphometric characteristics of the basin. The dendritic type drainage network of the basin exhibits the homogeneity in texture and lack of structural control. The stream order ranges from first to sixth order. The drainage density in the area has been found to be low which indicates that the area possesses highly permeable soils and low relief. The bifurcation ratio varies from 2.00 to 5.50 and the elongation ratio (0.327) reveals that the basin belongs to the elongated shaped basin category. The results of this analysis would be useful in determining the effect of catchment characteristics such as size, shape, slope of the catchment and distribution of stream net work within the catchment.     

Study on the oasis landscape fragmentation in northwestern China by using remote sensing data and GIS: a case study of Jinta oasis

The purpose of this study is to investigate the oasis landscape fragmentation in northwestern China’s arid regions. Landscape maps of Jinta oasis were compiled by using GIS based on Landsat TM data of 1990 and 2000. Landscape indexes for evaluating fragmentation are patch area, patch density, corridor density and split index. Results indicated many difference. First, between the years 1990 and 2000, the landscape fragmentation in Jinta oasis decreased slightly. Second, the area of the matrix decreased at the class level. The landscape fragmentation of the matrix (bare soil) increased as a result of increased influence of human activities on matrix and was opposite to the irrigated farmland whose area is larger and more aggregated in 2000 than in 1990. Third, dense corridor system is one of the most prominent characteristics of the arid regions. It is one of the key factors resulting in the landscape fragmentation; especially the fragmentation within the same patch types. The corridor density of irrigated farmland, residential area and forestland were quite large in Jinta oasis both in 1990 and 2000. The pattern of Jinta oasis is characterized by agricultural oasis embedded in Gobi and in the desert, where the ecosystem was disturbed strongly by the intense human activities.     

Assessment of land degradation east of the Nile Delta, Egypt using remote sensing and GIS techniques

Land degradation is one of the most common issues in the eastern part of the Nile Delta area that threatens the ongoing agricultural activities and prohibits further reclamation expansions. The different degradation types and the associated risk assessment of some soils types of western Suez Canal region during the period from 1997 to 2010 is discussed. The assessment of the different degradation degrees in the investigated area has been carried out through integrating remote sensing, GIS and GLASOD approaches. Results revealed that the salinization, alkalization, soil compaction and water logging are the main types of land degradation in the area. The main causative factors of human induced land degradation types are; over irrigation, human intervention in natural drainage, improper time use of heavy machinery and the absence of conservation measurements. Low and moderately clay flats, gypsifferous flats, have high to very high risk in both salinization sodication and physical degradation. Values such as EC, ESP, and ground water level reach 104.0 dS/m, 176? % and 60 cm, respectively. These results will be of great help and be basic sources for the planners and decision makers in sustainable planning. The spatial land degradation model was developed based on integration between remote sensing data, geographic information system, soil characteristics and DEM.     

Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques

This paper summarizes the findings of groundwater potential zonation mapping at the Bharangi River basin, Thane district, Maharastra, India, using Satty’s Analytical Hierarchal Process model with the aid of GIS tools and remote sensing data. To meet the objectives, remotely sensed data were used in extracting lineaments, faults and drainage pattern which influence the groundwater sources to the aquifer. The digitally processed satellite images were subsequently combined in a GIS with ancillary data such as topographical (slope, drainage), geological (litho types and lineaments), hydrogeomorphology and constructed into a spatial database using GIS and image processing tools. In this study, six thematic layers were used for groundwater potential analysis. Each thematic layer’s weight was determined, and groundwater potential indices were calculated using groundwater conditions. The present study has demonstrated the capabilities of remote sensing and GIS techniques in the demarcation of different groundwater potential zones for hard rock basaltic basin.     

Delineation of groundwater potential zones in Kakund watershed,Eastern Rajasthan,using remote sensing and GIS techniques

The remotely sensed data provides synoptic viewing and repetitive coverage for thematic mapping of natural resources. In the present study hydrogeomorphological mapping has been carried out in Kakund watershed, Eastern Rajasthan for delineating groundwater potential zones. IRS-1D LISS III Geocoded FCC data in conjunction with Survey of India toposheet (1:50000 scale) and field inputs were used for thematic mapping. Geomorphic units identified through visual interpretation of FCC include: alluvial plain, plateau, valley fills, intermontane valleys, burried pediment, residual hills, and linear ridges. In addition, lineaments were mapped since they act as conduit for groundwater recharge. Majority of the lineaments trends NE-SW and a few along NW-SE directions and are confined to the southern and southeastern parts of the watershed. Based on hydrogeomorphological, geological and lineament mapping the Kakund watershed has qualitatively been categorized into four groundwater potential zones, viz. good to very good, moderate to good, poor to moderate and very poor to poor. The study reveals that only 10.97% of the area has good to very good, 35.41% area with moderate to good, 49.04 % of the area has poor to moderatel, while remaining 4.57% has poor to very poor groundwater potential.     

Monitoring desertification by remote sensing using the Tasselled Cap transform for long-term change detection

Sensitive areas like oases are threatened by climatic variations and human activities that can catalyze desertification processes. Remote sensing the Earth surface from satellites is a good tool to monitor such types of change through several techniques. In this paper a remote sensing method that has been widely used for vegetated areas is adapted to study dry regions. The method consists of a combination of the Change Vector Analysis and the Tasselled Cap (TC) transform. To adapt it to dryland conditions a new set of parameters for the TC transform is hereby calculated for the Landsat 8 OLI system. The new TC parameters are tested in the analysis of the surface change in Azraq Oasis, Jordan, over a time span of 30 years (1984–2013) for Landsat satellites images. Azraq is considered a good testing site since in the early 1990s it has been subject to a complete drying up of the superficial springs, mainly due to over-exploitation of the groundwater basin. Results show that the chosen technique is able to detect the expected change on the surface, consistent with photo-interpretation and historical information available.     

Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques

Fire in forested areas can be regarded as an environmental disaster which is triggered by either natural forces or anthropogenic activities. Fires are one of the major hazards in forested and grassland areas in the north of Iran. Control of fire is difficult, but it is feasible to map fire risk by geospatial technologies and thereby minimize the frequency of fire occurrences and damages caused by fire. The fire risk models provide a suitable concept to understand characterization of fire risk. Some models are map based, and they combine effectively different forest fire–causing variables with remote sensing data in a GIS environment for identifying and mapping forest fire risk. In this study, Structural Fire Index, Fire Risk Index, and a new index called Hybrid Fire Index were used to delineate fire risk in northeastern Iran that is subjected to frequent forest fire. Vegetation moisture, slope, aspect, elevation, distance from roads, and vicinity to settlements were used as the factors influencing accidental fire starts. These indices were set up by assigning subjective weight values to the classes of the layers based on their sensitivity ratio to fire. Hot spots data derived from MODIS satellite sensor were used to validate the indices. Assessment of the indices with receiver operating characteristic (ROC) curves shows that 76.7 % accuracy of the HFI outperformed the other two indices. According to the Hybrid Fire Index, 57.5 % of the study area is located under high-risk zone, 33 % in medium-risk zone, and the remaining 9.5 % area is located in low-risk zone.