Assessment of Land Degradation Status and Its Impact in Arid and Semi-Arid Areas by Correlating Spectral and Principal Component Analysis Neo-Bands

Mfondoum, Alfred Homère Ngandam; Etouna, Joachim; Nongsi, Buji Kindess; Moto, Fabrice Armel Mvogo; Deussieu, Florine Gustave Noulaquape

doi:10.23953/cloud.ijarsg.77

Cited by 17 publications

(11 citation statements)

References 23 publications

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“…This work destroyed the natural environment and increased decertified areas, which caused the devastation of life and the ecosystem in the region and a rise in dust storms [4]. Multiple methods are applied in arid and semi-arid environments to estimate the percentage of land degradation and assess the severity of desertification, including mathematical models, barometric equations, and other methods using remote sensing, direct satellite observation, or making specific applications and measurements [5]. One of these models is the desertification and land uses model applied in the Middle East, called the Model of Desertification Potential Assessment MEDALUS.…”

Section: Introductionmentioning

confidence: 99%

Production of Environmental Sensitivity Maps for Desertification in Southern Marshes of Iraq

Al-Yasiry,

Al-Lami,

Al-Maliki

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The arid and semi-arid regions have faced critical desertification problems in the last decades. This phenomenon is caused either by human actions or natural circumstances. The study aims to identify the sensitive areas of desertification in the marshlands of southern Iraq using the Environmental Sensitivity Areas Index (ESAI) for desertification. The study area is located between longitudes (46.1° to 48.1° E) and latitude (29.55° to 32.55° N), which includes parts of the governorates of Al-Amarah, Al-Basara and Al-Nasiriyah in southern Iraq with an area of about 27,989 km2. Satellite image processing for the Landsat OLI sensor of 2021 was adopted to characterize the general appearance of the interest area. Arc Gis ver.10.7 programs were used to analyze different data and produce the Desertification Sensitivity Index (DSI) and maps for the parameters for evaluating southern marshes’ desertification. Nine parameters are grouped into three orderly indices concerning the behaviour of desertification, and weighting factors are assigned in each index. This study found that the study area highly sensitive to desertification represents (10781.14 km2 of the total area) about 38.52% of the study area. The area sensitive to desertification covers about 38.42%, about 10752.92 km2 of the total area. Areas of low sensitivity to desertification appear throughout the marshes, representing 23.06%, about 6454.67 km2 of the total area. The result shows that the area is suffering from reduced water supplies and the human destruction of natural grazing areas for urban expansion or cultivation of seasonal crops.

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Section: Introductionmentioning

confidence: 99%

Production of Environmental Sensitivity Maps for Desertification in Southern Marshes of Iraq

Al-Yasiry,

Al-Lami,

Al-Maliki

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…To pursue with this study, the main outlook is on one hand to build a complete model of the Revised Universal Soil Loss Equation (RUSLE) and integrate it to the model. On the other hand, integrating the status of the land degradation in the process, following the model proposed by [67] can bring more information to the site selection.…”

Section: Discussion and Outlookmentioning

confidence: 99%

Modelling Best Oil Palm Site Planting in Njimom, West-Cameroon: A GIS-Analysis Combining Weighted Linear Combination, Fuzzy Analytical Hierarchy Process and Utility Function

Mfondoum¹,

Mfondoum²,

Wokwenmendam³

et al. 2019

JGIS

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Oil Palm (Elaeis guineensis Jacq.) has recorded a boom production the last decades and its main productive zone is inside the tropics that meet the best biophysical conditions. Investors as well as geospatial practitioners are increasingly interested on the best growing and harvesting conditions. So said, the aim of this paper is to select the best oil palm planting site through the best methods combination. The study area is the district of Njimom located in the west-Cameroon, transitional between the equatorial and the climatic zones. In the same GIS environment, the Weighted Linear Combination (WLC) and Fuzzy Analytic Hierarchy Process (FAHP) respectively highlight the subtle differences between capability and suitability, while the Utility Function (UF) helps to assess the consideration of sustainability aspects. The first results consist in eight layers representing natural conditions, that is rainfall, temperatures, sunshine, slope, elevation, soil richness, soil moisture and forest cover, recoded in six classes ranked from 5 to 0 according to the FAO standardised scale. They are crossed using the straightforward method of WLC to give the "Capability layer". The second results consist in three layers related to the social-economical constraints for production, as built-up How to cite this paper: Mfondoum, A.H.N.,

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“…The soil is loamy, clay and alluvial, characterized by sediments deposits. Several types of soil degradation have been identified, modelled and mapped (Ngandam Mfondoum, A.H. et al, 2016;Ngandam Mfondoum, A.H. and Gbetkom, P.G., 2019;Gbetkom, P.G. et al, 2019).…”

Section: Research Locationmentioning

confidence: 99%

Improving the Land Surface General Drought Index Model

Mfondoum

Gbetkom

Cooper

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Drought affects all human activities and ecosystems. Nearly 40 percent of the world’s population inhabit Drylands, and they depend on agriculture for their food, security and livelihoods. Among the remote sensing indices developed, the Land Surface General Drought Index (LSGDI) was recently proposed. This paper proposes an improved model of LSGDI to face the issue of drought in semi-arid and arid regions. The experiment was conducted for the Maga’s floodplain, in North-Cameroon. The method uses satellite images of Landsat in 1987, 2003 and 2018, for January and March or April, corresponding to the middle and the end of the dry season. A Vegetation Moisture Index (VMI) and a Normalized Difference Soil Drought Index (NDSoDI) are both developed. On an orthogonal plan, their projections give a drought line that expresses the improved LSGDI (LSGDI2) as the root sum square of the NDSoDI and the VMI. The LSGDI2 results are ranged in [0.09 – 0.14] interval, which is used to define the threshold and ease the qualifiers for drought classes. The visual patterns easily match the sandy areas of the original Landsat images with the highest values, while the vegetation and water areas match the lowest values. Compared with the LSGDI and Second Modified Perpendicular drought Index (MPDI1), the new index reflectance values are higher. Finally, although LSGDI2 curve’s evolution follows the NDSoDI one at 94%, the new spectral index values depends on the both components, helping to map highest values of drought and moisture in Maga’s floodplain, for a sustainable rice culture expansion.

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Assessment of Land Degradation Status and Its Impact in Arid and Semi-Arid Areas by Correlating Spectral and Principal Component Analysis Neo-Bands

Cited by 17 publications

References 23 publications

Production of Environmental Sensitivity Maps for Desertification in Southern Marshes of Iraq

Production of Environmental Sensitivity Maps for Desertification in Southern Marshes of Iraq

Modelling Best Oil Palm Site Planting in Njimom, West-Cameroon: A GIS-Analysis Combining Weighted Linear Combination, Fuzzy Analytical Hierarchy Process and Utility Function

Improving the Land Surface General Drought Index Model

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