The accuracy of change detection on the earth’s surface is important for understanding the relationships and interactions between human and natural phenomena. Remote Sensing and Geographic Information Systems (GIS) have the potential to provide accurate information regarding land use and land cover changes. In this paper, we investigate the major techniques that are utilized to detect land use and land cover changes. Eleven change detection techniques are reviewed. An analysis of the related literature shows that the most used techniques are post-classification comparison and principle component analysis. Post-classification comparison can minimize the impacts of atmospheric and sensor differences between two dates. Image differencing and image ratioing are easy to implement, but at times they do not provide accurate results. Hybrid change detection is a useful technique that makes full use of the benefits of many techniques, but it is complex and depends on the characteristics of the other techniques such as supervised and unsupervised classifications. Change vector analysis is complicated to implement, but it is useful for providing the direction and magnitude of change. Recently, artificial neural networks, chi-square, decision tree and image fusion have been frequently used in change detection. Research on integrating remote sensing data and GIS into change detection has also increased.

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Investigating the Use of Remote Sensing and GIS Techniques to Detect Land Use and Land Cover Change: A Review

Analysing the trend of land use/land cover change and its cause and consequence on human livelihoods as well as on the environment is a matter of concern for sustainable development and management of natural resource. Retrospective analysis of land use/land cover dynamics and its driving force has been undertaken using satellite images of Landsat5 TM 1984, Landsat5 TM 1999, and Landsat8 TM 2015 with 30 m spacial resolution for Beressa watershed of Ethiopia. ArcGIS10.2.2 and ERDAS Imagine14 have been used for image processing to produce 6 land uses/land cover classes in the study area. The result of classified image indicated that in the last 3 decades, farm land and settlement area increased @ 71.6 ha/year and 16.8 ha/year respectively. Between 1984 and 1999, forest cover and water body decreased @ 5 ha/year and 0.03 ha/year respectively but increased @15.6 ha/year and 7.1 ha/year between 1999 and 2015 respectively. This increase could be possible due to the involvement of local communities to plant trees around their homestead and farm lands. In this program, plantation of indigenous tree species other than eucalyptus (which affect the ecology) was encouraged. The % share of grazing land and barren land has been decreased to 10 and 10.1 % respectively during 1999 that further reduced to 6.1 and 5.2 % during 2015 as against the 12.4 and 13.1 % during 1984 respectively in the Beressa watershed. Rapid population growth demanded more land for cultivation, more trees for domestic fuelwood consumption and more area for settlement had been responsible for drastic change in the land use/land cover change in the last 3 decades in the Beressa watershed. In order to check the loss of area from gazing land and barren land, alternative source income opportunities to the community dwellers may be provided. Therefore, environmental conservation, management and rehabilitation require integrated approach of community development at various levels.

/pdf/analyses-of-land-use-and-land-cover-change-dynamics-using-3ugm3hb8lm.pdf

Analyses of land use and land cover change dynamics using GIS and remote sensing during 1984 and 2015 in the Beressa Watershed Northern Central Highland of Ethiopia

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city of Kathmandu in Nepal. We found that over a period of 20 years (from 1990 to 2010), the Kathmandu district has lost 9.28% of its forests, 9.80% of its agricultural land and 77% of its water bodies. Significant amounts of these losses have been absorbed by the expanding urbanized areas, which has gained 52.47% of land. Predictions of land use and land cover change trends for 2030 show worsening trends with forest, agriculture and water bodies to decrease by an additional 14.43%, 16.67% and 25.83%, respectively. The highest gain in 2030 is predicted for urbanized areas at 18.55%. Rapid urbanization—coupled with lack of proper planning and high rural-urban migration—is the key driver of these changes. These changes are associated with loss of ecosystem services which will negatively impact human wellbeing in the city. We recommend city planners to mainstream ecosystem-based adaptation and mitigation into urban plans supported by strong policy and funds.

https://www.mdpi.com/2071-1050/12/9/3925/pdf

Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS

Land use and land cover (LULC) have been and still changing, through human activities, creating variability in hydrological cycle. This paper investigates the hydrological impacts of LULC changes on water balance in the White Volta Basin located in the West of Africa using the Soil and Water Assessment Tool (SWAT). Two LULC data for 1990 and 2006 and two plausible scenarios of land use change were evaluated. Results show a link between land cover and the hydrologic response with a decrease in land cover corresponding to decrease in surface water and base flow and increase evapotranspiration (ET). The results indicated that different LULC contributed to various effects in annual water yield and ET. The results also indicate the capability of the SWAT model to be used in the West African subregion even though there are data limitations associated with the model in West Africa. Overall, the model results support the existing efforts of Volta Basin water resource managers to protect the area along the Volta river against farming and indicate that additional emphasis should be placed on improving land management practices.

Assessing the impact of land cover changes on water balance components of White Volta Basin in West Africa

Evaluation of land use/land cover changes and land degradation in Dera District, Ethiopia were undertaken using two remotely sensed datasets (Landsat 5 TM of 1985 and Landsat 7 ETM + imagery 2011). Land use/land cover change detection and Normalized Difference Vegetation Index analysis was carried out on the two images. Global positioning system and topographical maps of scale 1:50,000 for ground verification and ERDAS Imagine 9.1 and ArcGIS 9.2 software for satellite image processing and analysis were used for the study. Field observations and focus group discussions were also conducted to obtain addition information. The result of this study showed that cultivated and degraded lands were increased by 25.79% and 398% respectively at the expense of forest, shrub and grazing lands. Normalized Difference Vegetation Index analysis has also indicated the increased of land degradation between 1985 and 2011 images which mainly aggravated by land use/land cover changes.

Evaluations of Land Use/Land Cover Changes and Land Degradation in Dera District, Ethiopia: GIS and Remote Sensing Based Analysis

This paper assessed the Changes in land use/land cover in Kafur local government area of Katsina state, Nigeria over 13 year period. The study made use of Land use/land cover map of the study area for1995 and Google earth imagery of 2008. The image and the map were digitized into GIS environment using Arc view 3.2 GIS software for analysis. A paired t-test analysis was also used to see if there was significant change in the land use/land cover between 1995 and 2008.The results show that open space covered 13.56 square kilometers of the land area and constituted 34.00% in 1995 which constituted the most extensive type of land use/land cover in the study area. The increasing population and economic activities were noted to be putting pressure on the available land resources. This paper highlights the land use/land cover types, the change over the years and the causes of the change. The importance of remote sensing and GIS techniques in mapping and change detection was also highlighted.

K.M. Muazu

Papers

Mapping land use-land cover and change detection in Kafur local government, Katsina, Nigeria (1995-2008) using remote sensing and Gis.