Remote Sensing (RS) and Geographical Information System (GIS)

Remote Sensing (RS) and Geographical Information System (GIS)

The invent of GIS, and RS techniques play a crucial role in transforming land use/cover mapping by providing a detailed way of improving the selection area designed for various agriculture or urban areas. RS offers a continuous and constant source of information concerning the earth while GIS is a methodology for handling geographical data. Large scale analysis of the land surface has been possible by the advancement of GIS and RS. They have proven to be useful in providing detailed knowledge of natural resources, addressing the threat of global change, and designing networks of protected areas. Most developing countries are currently undergoing rapid urbanization (Ganasri & Ramesh, 2016).  The growth is mainly characterized by a rapidly increasing population, unorganized expansion, and increased immigration. Land use and land cover change have emerged to be one of the critical components in the current strategies of monitoring environmental changes and managing natural resources. As a result, GIS and RS are of great importance in the present century (Hegazy & Kaloop, 2015) by facilitating accessibility of geographical information and enabling monitoring and evaluation of land cover and use over some time.

The rapidly changing land use and the cover have a profound impact on the local, regional and global environment. The global carbon cycle is induced by human activities thereby contributing to the increase in atmospheric carbon dioxide level. Therefore, it is critical to examine changes in land use and cover to make it possible for the discernment of its effects on the terrestrial ecosystem. GIS and RS methods are used in assessing change detection on land thereby facilitating the formulation of sustainable land use. Urban growth monitoring entails studying the differences in the state of an object through remote observation at different times (Ganasri & Ramesh, 2016). Growth monitoring mainly involves the application of RS data and GIS. Growth monitoring determines and describes changes in land-cover and land-use properties through the use of remote sensing data. The purpose of remote sensing data is crucial in identifying the change that occurs between two or more periods that is characteristics of normal variation. The problem of accurately monitoring changes in land use and cover in a wide variety of environments have been addressed by numerous research studies (Rawat & Kumar, 2015).

Hegazy and Kaloop (2015) assert that urban growth has contributed to severe losses in water bodies and agricultural land in Egypt. Environmental problems such as decreased quality of water and air, a rise in local temperature, increased runoff and subsequent flooding can be attributed to urban growth. Egypt has several rapidly growing cities. Geospatial technology and RS technique provide vital tools that are helpful in the analysis of land use change detection. The study by Hegazy and Kaloop (2015) conducted a change detection analysis using GIS between 1958 to 2010, in Mansoura and Talkha and established that built environment has increased by over 30%, and agricultural land has decreased by 33% (Hegazy & Kaloop, 2015).

Digital change detection assists in understanding landscape dynamics through the use of multi-temporal satellite imagery. A variety of social causes drives changes in land cover and use. Shifting land use patterns eventually affects biodiversity. Land use/cover change detection is considered crucial in gaining a better understanding of landscape dynamic. The application of GIS and RS facilitates the understanding of landscape patterns, changes, and interactions that occur between the natural environment and human activities. The geospatial techniques assist in proper management and decision improvement. The application of remotely sensed data makes it possible to study changes in land cover efficiently and produces better accuracy (Rawat & Kumar, 2015).

 

References

Hegazy, I. R., & Kaloop, M. R. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), 117-124.

Ganasri, B. P., & Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), 953-961.

Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77-84.

 

 

Annotated Bibliography

Hegazy, I. R., & Kaloop, M. R. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), 117-124.

Although urban growth is experienced all over the world, the countries with the highest rate of urbanization are the ones classifies as developing countries such as Egypt. The high rate of urbanization is due to rapid population growth, immigration, and unorganized expansion, especially in the big towns. Therefore, it is essential for such countries to monitor environmental changes and natural resources as strategies of managing how land is used or how the land cover changes. For instance in Egypt, there has been a lot of adverse effects on the environment due to urbanization such as loss of water bodies and agricultural land which is dangerous. In such instances, geospatial technologies and remote sensing method s are used as tools of land analysis and to evaluate the change in different factors of the environment. Therefore, this paper is relevant to the project as it tries to assess how the use of GIS uses land. The results from analysis using GIS are essential to the government as they help urban planners to make decisions that will result in sustainable development.

Ganasri, B. P., & Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), 953-961.

Research has shown that soil erosion has increased over the last three decades due to factors such as land degradation, agricultural intensification, and reduction of land cover. Soil erosion negatively affects watersheds, and in an attempt to conserve these watersheds, soil erosion must be assessed. The best method of evaluating soil erosion is by using a model as it provides a consistent approach to evaluate sediment yield and soil erosion in numerous conditions. This source is vital to the project because it analyzes a model which utilizes the Revised Universal Soil Loss Equation and GIS to determine the extent of soil erosion in Nethravathi Basin in India. When using this model, the parameters of RUSLE are measured using erosion probability and remote sensing data which use GIS. From this activity, one can determine soil erosion factors such as soil erdability, topographic, rainfall erosivity and crop management factors. These results are then used to aid the implementation of soil conservation initiatives that are aimed at reducing soil erosion and sedimentation.

Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77-84.

This source by Rawat and Kumar is essential to this project because it discusses how digital change detection techniques such as GIS are used to help in understanding the dynamic nature landscapes. The sources illustrate how GIS was used to understand the spatiotemporal dynamics of the land in Hawalbagh Block in India. In the exercise, there were two different periods used during the Landsat Satellite imaging. From the activity, the images were classified into five major categories; vegetation, water body, agriculture, built-up and barren. Therefore, by using GIS are remote sensing, researchers were able to know the changes that have happened to each of the five categories over the last twenty years which is the timeframe between the two periods.

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