Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin, India

Masroor, Md; Sajjad, Haroon; Rehman, Sufia; Singh, Roshani; Rahaman, Md Hibjur; Sahana, Mehebub; Ahmed, Rizwan Raheem; Avtar, Ram

doi:10.1016/j.gsf.2021.101312

Cited by 70 publications

(24 citation statements)

References 48 publications

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“…The health of vegetation conditions can be directly inferred from a spatially continuous NDVI parameter while the crop stress can be inferred inversely LST parameter. Therefore, a combined index resulting from VCI and TCI have been widely used to assess the health of vegetation characteristics, soil moisture status and drought characteristics in the region (Bento et al, 2020(Bento et al, , 2018aJiang et al, 2022;Masroor et al, 2022;Zeng et al, 2022). The reconstructed NDVI and LST images were used to develop VCI and TCI indices at province scales in the present study.…”

Section: Discussionmentioning

confidence: 99%

“…Vegetation health condition in the region was assessed with a Vegetation Health Index (VHI) which is function of both NDVI and LST variables (Bento et al, 2020(Bento et al, , 2018aMasroor et al, 2022). It is shown with the logic that the vegetation health is directly related to vegetation cover which can be calculated with a Vegetation Condition Index (VCI) and indirectly related to land surface temperature which can be calculated with a Temperature Condition Index (TCI).…”

Section: Vegetation Health Index Analysismentioning

confidence: 99%

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Reconstructing NDVI and land surface temperature from cloud cover pixels of Landsat-8 images and assessing vegetation health index in the Northeast region of Thailand

Mohanasundaram

Baghel

Thakur

et al. 2022

Preprint

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Critical applications of satellite data products include monitoring vegetation dynamics using vegetation indices such as Normalized Difference Vegetation Index (NDVI) and thermal characteristics such as Land Surface Temperature (LST) variations across different spatial and temporal scales. One of the major problems with passive remote sensing satellite data products is cloud and shadow cover that void the information from a specific image. The cloud cover problems further amplified during monsoon seasons as the formation of clouds are more frequent during these seasons. The present study proposes temporal aggregation of images and developing Harmonic Analysis of Time Series (HANTS) and Pixel-wise Multiple Linear Regression (PMLR) algorithms for retrieving cloud contaminated NDVI and LST information from Landsat-8 (L8) data products, respectively. The developed algorithms were applied in the northeastern part of Thailand to recover the missing NDVI and LST values from time series of L8 images acquired in 2018. The predicted NDVI and LST values at artificially clouded locations were compared with the corresponding clear pixel values. Additionally, the model predicted LST and NDVI values were also compared with MODIS LST and NDVI data sets. The calculated root mean square (RMSE) values were ranging from 0.004 to 0.05 and 1.05°C to 3.11°C for NDVI and LST variables, respectively. The validation statistics show that these models can be satisfactorily applied to retrieve NDVI and LST values from cloud-contaminated pixels of L8 images. Furthermore, a vegetation health index (VHI) calculated at province level show that most of the western provinces showed a healthy vegetation condition than other provinces in the northeast of Thailand.

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Section: Discussionmentioning

confidence: 99%

Section: Vegetation Health Index Analysismentioning

confidence: 99%

Reconstructing NDVI and land surface temperature from cloud cover pixels of Landsat-8 images and assessing vegetation health index in the Northeast region of Thailand

Mohanasundaram

Baghel

Thakur

et al. 2022

Preprint

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“…Drought leads to soil retrogression and degradation, water scarcity, desertification, vegetation destruction, sandstorm, wildfire, and other disaster phenomena [1], [2], [3]. Drought ranks first among different types of hazards due to climate change [4]. Changes in rainfall patterns and temperature are the critical determinant elements of drought, causing significant losses to agriculture and affecting crop production [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Spatiotemporal Characteristic of Droughts Using In Situ and Remote Sensing-Based Drought Indices

Jalayer

Sharifi

Abbasi‐Moghadam

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Drought has been identified as one of the significant complicated natural disasters exacerbated by land degradation and climate change. Hence, monitoring drought and evaluating its spatiotemporal dynamics are essential to manage regional drought conditions and protecting the natural environment. In this study, various single remote sensing-based drought indices including soil moisture condition index (SMCI), precipitation condition index (PCI), temperature condition index (TCI), and vegetation condition index (VCI) and combined RS-based drought Indices including optimized meteorological drought index (OMDI) and synthesized drought index (SDI) have been used to investigate the spatiotemporal variations of meteorological and agricultural droughts between 2000 and 2021 in Iran. The in situ drought indices, including the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) series of 1, 3, 6, 12, and 24 months were utilized to verify remote sensing-based drought indices and evaluate their applicability for analyzing drought conditions. The results indicated that the correlation coefficients of the in situ drought indices with the combined drought indices are higher than the RS-based single drought indexes. Generally, single-factor drought indexes, including VCI, TCI, PCI, and SMCI, have specific characteristics. The PCI and SMCI have an acceptable correlation with the short-term SPI and SPEI and are more applicable to monitoring short-term drought conditions. Further, the TCI has better performance in monitoring long-term drought conditions in Iran. This research concluded that the central, eastern, and southeastern parts of Iran mainly were experiencing exceptional and extreme drought conditions as the worst agricultural and meteorological drought conditions observed in the years 2008 and 2021 in the region during the last 20 years. The results also showed that, in 2019 and 2020, most areas of Iran had higher OMDI and

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“…Soil erosion and land degradation are serious concerns in arid and semi-arid regions worldwide. Owing to an increase in landslides, floods, and drought, the strength of soil erosion has increased [9].…”

Section: Introductionmentioning

confidence: 99%

Design of soil and water conservation techniques to minimize soil erosion on degraded land in Samarinda Tenggarong Axis Road

Sarminah,

Timo,

Aipassa

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Soil conservation activities are aimed at tackling land degradation, especially soil erosion, which occurs rapidly. If there is human intervention, land will become more sensitive to the influence of water (rainfall) and gravitational forces. This study aimed to identify the types of erosion that occur on degraded land and design appropriate soil and water conservation techniques based on vegetative and physically degraded land conditions on the Samarinda-Tenggarong Axis road. The results of the documentation collected from each research site identified the type of erosion, and designed soil and water conservation techniques. This research is focused on the design referring to Permenhut P.04/Menhut-11/2011 and UU RI/37/2014. The results of this study showed that location 1 of the recommended technique is the vegetative technique and the manufacture of Water Sewerage, location 2 is the bench terrace technique, location 3 is the retaining wall technique, location 4 is the individual terrace technique, location 5 is the stone terrace/wall technique, location 6 is the stone terrace/wall technique, and location 7 is the garden terrace technique. The design of the soil and water conservation techniques recommended in this study is expected to have a positive effect on minimizing soil erosion on degraded land.

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Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin, India

Cited by 70 publications

References 48 publications

Reconstructing NDVI and land surface temperature from cloud cover pixels of Landsat-8 images and assessing vegetation health index in the Northeast region of Thailand

Reconstructing NDVI and land surface temperature from cloud cover pixels of Landsat-8 images and assessing vegetation health index in the Northeast region of Thailand

Assessment of Spatiotemporal Characteristic of Droughts Using In Situ and Remote Sensing-Based Drought Indices

Design of soil and water conservation techniques to minimize soil erosion on degraded land in Samarinda Tenggarong Axis Road

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