Monitoring of Land Degradation in Alluvial Plain in Iraq by Using Geomatics Techniques

Iraq faces a major environmental problem represented by severe deterioration, which threatens its food security. Many natural and human factors combine to make it, and it has dire environmental, economic, social and cultural consequences, most notably the loss of productive lands, the movement of sand dunes, severe sand and dust storms, and the resulting increase in air pollution. This study attempts to identify the development of the problem, analyze its causes and consequences, and propose a number of solutions to address it. In this article Remote Sensing techniques have been used to monitoring land degradation in ( Alluvial Plain ) of Iraq for the stage (1976 - 2021) using different sources of data such as satellite images (Landsat 1-5 MSS 1976, Landsat 5 1996 TM, Landsat8 2016 and sentinel 2 2021), also more than one software was used such as ENVI 5.3 and Erdas image 2015 to extract information from above images, Erdas imagine 2015 was use to sub set area of study, layer stack, merge resolution and classification stage, Arc GIS 10.7 use to make database and maps production), the article used supervise and unsupervised classification techniques to obtain the results, the article indicated that there is a big problem in the year 1976, this problem almost disappeared in the second station of work 1996, but it returned back after that through the results for the years 2016 and 2021. Finally, the article found a deterioration in the soil class during the stages from 2016 (988.547 Km2) to 2021(1342.398 Km2) and a decrease in the area of vegetation cover from (1931.596 Km2) in (2016) to (1632.695 Km2) in (2021).

Exploring environmental connection: ecological network opportunities in the Shahdagh National Park, Azerbaijan

The high growth rate of consumption of natural resources by people in the last century have seriously and negatively affected ecosystems and led to the loss of biodiversity. At present, it is important to take the necessary measures to ensure sustainable development and biodiversity conservation. Ecological networks play an important role in maintaining and controlling the stability and balance of communication between ecosystem complexes. For this purpose, the possibility of creating an ecological network that includes core areas, buffer zones, ecological corridors and restoration areas in the section of Shamakhi district of the Shahdagh National Park was explored. The designated buffer zone of the national park includes 14 villages and 1 settlement type administrative unit. Mountainous landscapes predominate in the area, and the absolute height ranges from 500-200 m. Riverbeds, intermountain depression, mountain passes, trails and forests which should be planted in the areas we offer, were considered as main factors during the construction of ecological corridors in the national park and the buffer zones. The materials obtained from the literature and our field studies, also, vector and raster data were used during the site identification. The data was processed in software such as ArcGIS 10, ERDAS Imagine, Global Mapper, Google Earth, etc. Existing ecosystems were identified, and areas were calculated in separate elements of the ecological network in the study area.

Remote sensing techniques in mapping spatial variability of salinity in Kano River Irrigation Project (KRIP), Nigeria

Salinity has become a major issue in most large scale irrigation schemes, assessing the extent of the spread has become daunting and laborious. Remote sensing techniques were used to map salinity and develop models for extracting and identifying salinity in soils. Sentinel-2B optical imaging satellite with 13 spectral bands and 10 m spatial resolution was used. SNAP Desktop, ERDAS Imagine, and ArcGIS 10.6 software were used as the main GIS packages for building models and running functions such as input, output, analysis, and processing. Stepwise Multiple Linear Regression (MLR) techniques were carried out for the assessment of the spatial distribution of ECe and to predict salinity level at different locations of the Kano River Irrigation Project (KRIP). Four models were developed, however, due to the lower Variance Inflation Factor (VIF), model 2 which is a combination of salinity Index and band 3 (Green band) was used in delineating the spatial extent of the salinity. Close monitoring of the salt development and application of reversal measures were recommended.

Assessment of Land Use/Cover Change Using Remote Sensing and GIS Techniques: A Case of Osogbo and Its Peripheral Areas in Nigeria

The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing city areas. Landsat satellite imageries of three different time periods, i.e., Landsat Thematic Mapper (TM) of 1982, 2000 and 2018 were acquired by Global Land Cover Facility Site (GLCF) and earth explorer site, quantify the changes in the Osogbo and its peripheral areas from 1982 to 2018 over a period of 36 years. These data sets were imported in ArcGIS 10.3, ERDAS Imagine and IDRIS Selva, satellite image processing softwares to create a false colour composite (FCC), supervised classification methodology was employed using maximum likelihood technique. The images of the study area were categorized into four different classes namely Core-urban, Peri-urban, Vegetation, water body. The results indicate that during the last thirty-six (36) years, Core-Urban land and water body have been increased by 2.74% (38.20 km2) and 0.98% (13.69 km2) while Peri-Urban land, and vegetation cover have decreased by 0.35% (5.00 km2), and 3.36 % (46.87 km2), respectively. The results quantify the land cover change patterns in the city and its peripheral area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyse changes in land cover over time that can be used as inputs to land management and policy decisions.

Возможности применения космических снимков высокого разрешения при мониторинге городских территорий

В статье рассмотрены особенности выявления изменений, происходящих на территории городского пространства в связи со строительством новых объектов, с помощью архивных спутниковых снимков высокого разрешения Sentinel-2. Применен алгоритм автоматизированного выявления изменений, основанный на использовании индексных изображений в программе ERDAS IMAGINE 2010. Выявлены дальнейшие перспективы мониторинга городских территорий по космическим снимкам.

Возможность использования данных дистанционного зондирования при мониторинге водных объектов

В статье рассмотрены первостепенные задачи мониторинга водных объектов, цели, возможности использования данных дистанционного зондирования с применением программного комплекса Erdas Imagine 2015. Показано как с помощью данных дистанционного зондирования можно получить достоверную информацию о состоянии водных объектов, выявить и спрогнозировать неблагоприятные экологические явления, а также извлечь полезную информацию.

Habitat Suitability Index Modelling for Bluebull (Boselaphus tragocamelus) in Pench Tiger Reserve, M.P. India

The habitats for the wild animals are shrinking due to the clearance of forests for agriculture and industrialization. The idea of wildlife conservation begins with the identification of their acceptable habitat. Since this crucial information helps in the development and maintenance of the protected areas. The requirement of habitat varies with different landscapes.The bluebull (Boselaphus tragocamelus) is Asia’s largest antelope,widespread throughout the northern Indian subcontinent. Peter Simon Pallasin (1766) described it as the only member of the genus Boselaphus.The Wildlife (Protection) Act of 1972 lists it as a Schedule III animal, while the IUCN lists it as Least Concern (LC). Our goal was to design a habitat appropriateness model for blue bull so that it could reduce the conflict with farming community due to crop damage. Model will be develop using RS & GIS technique to protect the species inside the Pench Tiger Reserve (77° 55’ W to 79° 35’ E and 21° 08’ S to 22° 00’ N) the central highlands of India. The satellite data from LANDSAT-8 of 4th April 2015, Path- 144,Row- 45, with a ground resolution of 30 meters, were collected from the USGS website. This satellite image was then transferred in image format to ERDAS IMAGINE 2013 for further analysis. The data from satellites were gathered and analysed. The purpose of the field survey was to gather information about the presence of various ungulates. A ground truthing exercise was also carried out. For data processing and GIS analysis,ERDAS IMAGINE 13 and Arc GIS 10 were used. Analytical Hierarchy Process (AHP) was used Factors were identified who were influencing the spatial distribution of the species for conservation planning. The linear additive model was used for HSI. The results show that 242 km2 (29.48 percent) of Pench Tiger Reserve forest was recognized to be highly suitable for bluebull, while 196 km2 (23.87 percent) was moderately suitable,231 km2 (28.14 percent) was suitable, 109 km2 (13.28 percent) was least suitable, and about 43 km2 (5.249 percent) of PTR was completely avoided by bluebull.

Cognition of Graphical Notation for Processing Data in ERDAS IMAGINE

This article presents an evaluation of the ERDAS IMAGINE Spatial Model Editor from the perspective of effective cognition. Workflow models designed in Spatial Model Editor are used for the automatic processing of remote sensing data. The process steps are designed as a chain of operations in the workflow model. The functionalities of the Spatial Model Editor and the visual vocabulary are both important for users. The cognitive quality of the visual vocabulary increases the comprehension of workflows during creation and utilization. The visual vocabulary influences the user’s exploitation of workflow models. The complex Physics of Notations theory was applied to the visual vocabulary on ERDAS IMAGINE Spatial Model Editor. The results were supplemented and verified using the eye-tracking method. The evaluation of user gaze and the movement of the eyes above workflow models brought real insight into the user’s cognition of the model. The main findings are that ERDAS Spatial Model Editor mostly fulfils the requirements for effective cognition of visual vocabulary. Namely, the semantic transparency and dual coding of symbols are very high, according to the Physics of Notations theory. The semantic transparency and perceptual discriminability of the symbols are verified through eye-tracking. The eye-tracking results show that the curved connector lines adversely affect the velocity of reading and produce errors. The application of the Physics of Notations theory and the eye-tracking method provides a useful evaluation of graphical notation as well as recommendations for the user design of workflow models in their practice.

Remote Sensing Application for Exploring Land Use and Land Cover Dynamics in and Around Chatra Wetland, English Bazar, West Bengal

Wetlands are often called as biological “supermarket” and “kidneys of the landscape” due to their multiple functions, including water purification, water storage, processing of carbon and other nutrients, stabilization of shorelines and support of aquatic lives. Unfortunately, although being dynamic and productive ecosystem, these wetlands have been affected by human induced land use changes. India is losing wetlands at the rate of 2 to 3 per cent each year due to over-population, direct deforestation, urban encroachment, over fishing, irrigation and agriculture etc (Prasher, 2018). The present study tries to investigate the nature and degree of land use/land cover transformation, their causes and resultant effects on Chatra Wetland. To fulfil the purpose of the study, GIS and remote sensing techniques have been employed. Satellite imageries have been used from United States Geological Survey (USGS) Landsat 7 Enhanced Thematic Mapper plus and Landsat 8 Operational Land Imager for the year 2003 and 2018. Cloud free imageries of 2003 and 2018 have been downloaded from USGS (https://glovis.usgs.gov/) for the month of March and April respectively. Image processing, supervised classificationhas been done in ArcGis 10.5 and ERDAS IMAGINE 14. The study reveals that the settlement hasincreased by about 90.43 per cent in the last 15 years around the Chatra wetland within the bufferzone of 2 Sq km. Similarly agriculture, vegetation, water body, swamp and wasteland witnessed asignificant decrease by 5.94 per cent, 57.69 per cent, 26.64 per cent 4.52 per cent and 55.27 per centrespectively from 2003 to 2018.

Automatic extraction of digital elevation from IKONOS in-track stereo images

This Thesis addresses the topic of the extraction of Digital Elevation Models (DEMs) from the in-track stereo images acquired by IKONOS satellite. Research on this topic is mainly motivated by the need of DEMs in trasportation and the potential use of very high resolution satellite stereo images to replace the traditional aerial photography to generate the DEMs that may be used for preliminary planning and location issues, limiting expensive and time consuming photogrammetry work to the final alignment corridor. In this thesis, two methods for DEM extraction from IKONOS stereo images using a modified Rational Function Model (RFM) and the 3D physical model developed at the Canada Centre for Remote Sensing (CCRS) are used and the accuracy of the DEMs generated using these two models are evaluated. The nominal accuracy of ground points determined with the vendor-supplied RPCs is evaluated and systematic biases are found. A significant improvement in the DEM accuracy is made by removing the biases in both the image and ground domain with the information of ground control. DEMs are automatically generated bya chain of processes using the PCI Geomatica OrthoEngine software package with the refined RFM and 3D physical model, respectively. The DEMs from these two methods are then compared in a desktop ERDAS Imagine environment and the accuracy of the DEMs is evaluated by comparing the extracted DEMs with the DEM from airphotos. The DEMs generated using different mathematical models have a very good consistence and more than 97% of the difference between the generated DEMs and the DEM from airphotos is between -2 m to 2m.