Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya

This research was conducted to explore the changes in the land use and land cover to advance our understanding of their potential effects on soil quality indicators under native land cover and farming systems in the region of Al-Jabal Al-Akhdar in the north-east of Libya through a case study in the...

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Main Author: Belkasem, Jamal S. A.
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/104492/1/JAMAL%20S%20A%20BELKASEM%20-IR.pdf
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id my-upm-ir.104492
record_format uketd_dc
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
advisor Balasundram, Siva K.
topic Soils - Analysis
Soils - Quality
Soils - Analysis
spellingShingle Soils - Analysis
Soils - Quality
Soils - Analysis
Belkasem, Jamal S. A.
Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
description This research was conducted to explore the changes in the land use and land cover to advance our understanding of their potential effects on soil quality indicators under native land cover and farming systems in the region of Al-Jabal Al-Akhdar in the north-east of Libya through a case study in the area of Al-Bayda-Lussaitah, in the middle northern part of the region. This would be very essential for the management and preservation of soil resource and future land use planning. A Post-classification comparison approach has been employed for change detection analysis using four multi-temporal Landsat images from 1985, 2000, 2010, and 2017. A total number of 180 soil samples were collected in the summer of 2016 from three different land use and cover types (rainfed agriculture, irrigated crops, and forest) and analyzed to evaluate change effects on soil parameters and assess soil quality using an indexing approach. The investigation outcomes highlight the importance of satellite digital image processing with the aid of GIS technology in mapping land use and land cover changes at the regional level. The changes observed in this study indicated a decline in the area of natural forest land, which lost 9,018 ha over 32 years (1985-2017), approximately 39% of its initial total area. Most natural forest losses were due to the conversion into rainfed and irrigated agricultural lands, which expanded over 4,095 and 2,266 ha, about 55% and 85% of initial areas, respectively. This was a consequence of increased food demand which requires opening new land for agriculture production mainly through deforestation. The highest deforestation rate was registered in the third period (2010-2017) at an estimated 513 ha year-1, about the double of the rate in the second period (2000-2010) and three times that recorded in the first period (1985-2000). Indeed, if this present deforestation trend continues, the study area will lose more than 50% of its natural forest cover over the next 15 years. The present study indicated that converting forest into agricultural land uses and adapting unsuitable farming practices has a significant negative influence on most soil parameters leading to considerable land degradation and increased soil erosion as observed in the study area due to the absence of protective vegetation cover, which makes soil surface directly exposed to erodibility factors. The negative influence of agricultural practices on soil properties suggests the need for intervention through sustainable land management procedures to sustain the soil quality in the native and cultivated land. This study used three different indexing methods to evaluate the soil quality of native and agricultural lands (i.e., simple additive index, weighted functional index, and minimum dataset-based index) and suggested that using these methods can provide a similar pattern of results with the highest soil quality rating under the natural forest and the lowest in irrigated land. The results obtained from the three indexing methods revealed a significant decline in the soil quality of the cultivated lands relative to the reference soil under forest cover, estimated between 19-30 %. In general, the soil quality of agricultural land ranged from moderate to very low, whereas soil under forest cover was classified as high to very high quality. At least 75% of cultivated sites were subjected to great soil quality decline, which required improving the agricultural practices to improve soil quality and land productivity. The study compared the performance of the three indexing methods and found perfect agreements and correlations among pairs of soil quality indices. The study concluded that principal component analysis could be used successfully for minimizing the number of soil quality indicators required to be measured in the subsequent investigations. Thus, the soil quality index based on the minimum data set of four soil quality indicators (i.e., organic matter, available phosphorus, electrical conductivity, and microporosity) was suggested as a superior index to predict overall soil quality in the region considering its perfect agreement and correlation with the other indices and capability to provide an effective assessment in terms of cost and time required for soil analysis and the ability to replicate over time due to the lower number of soil indicators that need to be measured. The adoption of this index would help farmers and producers to assess and monitor soil quality under the current land management, which can provide early alarm of land degradation so the required remediation or improvement measures can be implemented in due course. This strategy would sustainably improve food production by improving the quality of the current agricultural lands instead of opening new lands for agriculture through deforestation, thus preserving both agricultural and forest lands from degradation.
format Thesis
qualification_level Doctorate
author Belkasem, Jamal S. A.
author_facet Belkasem, Jamal S. A.
author_sort Belkasem, Jamal S. A.
title Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
title_short Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
title_full Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
title_fullStr Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
title_full_unstemmed Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya
title_sort land use, land cover change and soil quality indices in agricultural practices in al-bayda-lussaitah, al-jabal al-akhdar, libya
granting_institution Universiti Putra Malaysia
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/104492/1/JAMAL%20S%20A%20BELKASEM%20-IR.pdf
_version_ 1783725790716755968
spelling my-upm-ir.1044922023-09-07T07:47:56Z Land use, land cover change and soil quality indices in agricultural practices in Al-Bayda-Lussaitah, Al-Jabal Al-Akhdar, Libya 2021-10 Belkasem, Jamal S. A. This research was conducted to explore the changes in the land use and land cover to advance our understanding of their potential effects on soil quality indicators under native land cover and farming systems in the region of Al-Jabal Al-Akhdar in the north-east of Libya through a case study in the area of Al-Bayda-Lussaitah, in the middle northern part of the region. This would be very essential for the management and preservation of soil resource and future land use planning. A Post-classification comparison approach has been employed for change detection analysis using four multi-temporal Landsat images from 1985, 2000, 2010, and 2017. A total number of 180 soil samples were collected in the summer of 2016 from three different land use and cover types (rainfed agriculture, irrigated crops, and forest) and analyzed to evaluate change effects on soil parameters and assess soil quality using an indexing approach. The investigation outcomes highlight the importance of satellite digital image processing with the aid of GIS technology in mapping land use and land cover changes at the regional level. The changes observed in this study indicated a decline in the area of natural forest land, which lost 9,018 ha over 32 years (1985-2017), approximately 39% of its initial total area. Most natural forest losses were due to the conversion into rainfed and irrigated agricultural lands, which expanded over 4,095 and 2,266 ha, about 55% and 85% of initial areas, respectively. This was a consequence of increased food demand which requires opening new land for agriculture production mainly through deforestation. The highest deforestation rate was registered in the third period (2010-2017) at an estimated 513 ha year-1, about the double of the rate in the second period (2000-2010) and three times that recorded in the first period (1985-2000). Indeed, if this present deforestation trend continues, the study area will lose more than 50% of its natural forest cover over the next 15 years. The present study indicated that converting forest into agricultural land uses and adapting unsuitable farming practices has a significant negative influence on most soil parameters leading to considerable land degradation and increased soil erosion as observed in the study area due to the absence of protective vegetation cover, which makes soil surface directly exposed to erodibility factors. The negative influence of agricultural practices on soil properties suggests the need for intervention through sustainable land management procedures to sustain the soil quality in the native and cultivated land. This study used three different indexing methods to evaluate the soil quality of native and agricultural lands (i.e., simple additive index, weighted functional index, and minimum dataset-based index) and suggested that using these methods can provide a similar pattern of results with the highest soil quality rating under the natural forest and the lowest in irrigated land. The results obtained from the three indexing methods revealed a significant decline in the soil quality of the cultivated lands relative to the reference soil under forest cover, estimated between 19-30 %. In general, the soil quality of agricultural land ranged from moderate to very low, whereas soil under forest cover was classified as high to very high quality. At least 75% of cultivated sites were subjected to great soil quality decline, which required improving the agricultural practices to improve soil quality and land productivity. The study compared the performance of the three indexing methods and found perfect agreements and correlations among pairs of soil quality indices. The study concluded that principal component analysis could be used successfully for minimizing the number of soil quality indicators required to be measured in the subsequent investigations. Thus, the soil quality index based on the minimum data set of four soil quality indicators (i.e., organic matter, available phosphorus, electrical conductivity, and microporosity) was suggested as a superior index to predict overall soil quality in the region considering its perfect agreement and correlation with the other indices and capability to provide an effective assessment in terms of cost and time required for soil analysis and the ability to replicate over time due to the lower number of soil indicators that need to be measured. The adoption of this index would help farmers and producers to assess and monitor soil quality under the current land management, which can provide early alarm of land degradation so the required remediation or improvement measures can be implemented in due course. This strategy would sustainably improve food production by improving the quality of the current agricultural lands instead of opening new lands for agriculture through deforestation, thus preserving both agricultural and forest lands from degradation. Soils - Analysis Soils - Quality Land use, Rural - Libya 2021-10 Thesis http://psasir.upm.edu.my/id/eprint/104492/ http://psasir.upm.edu.my/id/eprint/104492/1/JAMAL%20S%20A%20BELKASEM%20-IR.pdf text en public doctoral Universiti Putra Malaysia Soils - Analysis Soils - Quality Land use, Rural - Libya Balasundram, Siva K.