Post‐tsunami land degradation on a South Asian island: Implications for conservation priorities

Velmurugan, A.; Adamala, Sirisha; Palanivel, Swarnam

doi:10.1002/ldr.3884

Cited by 4 publications

(3 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The soils of the study region are greatly influenced by climate and vegetation. The soils are medium to deep with low to medium available water holding capacity (Velmurugan et al 2016;Velmurugan et al 2021). The soils are slightly strongly acidic, medium to high in organic carbon content (0.7 to 1.8%) and moderate to low (40-70%) in base saturation (Ganeshamurthy et al 2002).…”

Section: Study Area Descriptionmentioning

confidence: 99%

Soil Moisture Mapping in Indian Tropical Island Ecosystem using C-band SAR Data and Neural Network Models

Adamala,

Ayyam,

Palanivel

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Soil moisture is one of the critical variables in identifying the stress or health of plants and its accurate information in agricultural land use is of greater importance under the threat of climate change. This study focuses on mapping the spatio-temporal dynamics of soil moisture in the Indian tropical Island ecosystem (Andaman and Nicobar Islands) using the fusion of radar (Sentinel-1A C-band synthetic aperture radar (SAR)) and optical/thermal (Sentinel-2A and Landsat 8) data. Field-based soil moisture measurements using the gravimetric method are monitored for different land uses of the study area. The study was carried out in the South Andaman district (E 92°’ to E 94°’ and latitude N 6°’ to N 14°’). A total of 60 surface soil samples (0–10 cm) were collected from four predominant land uses of the study area for 2020-22 years to represent real-time soil moisture status. Soil moisture index (SMI) is assessed based on thermal remote sensing data as Land Surface Temperature (LST) besides, normalized difference vegetation index (NDVI) from red and infrared bands data, and dielectric constants from soil textural analysis. Artificial Neural Network (ANN) based models were developed along with multiple linear regression (MLR) to retrieve the soil moisture accurately using satellite and field-derived input parameters such as backscatter coefficients (σ°: VV & VH), NDVI, SMI, and dielectric constants. The performance of modelled soil moisture is evaluated using different statistical index-based criteria concerning field-based soil moisture measurements (SMCv). It is found that positive correlation among (σ°: VV+VH) and (SMCv: %) for all land uses and high agreements (R2 values) between them for barren and vegetable fields. The vegetation interferes the backscatter signal and misinterprets the soil moisture estimation solely with only SAR data. However, consideration of NDVI and SMI improves the soil moisture estimation in case of vegetation abundance land uses. The comparative results showed that ANN models surpass the MLR models in soil moisture estimation with high R2 (0.67-0.99) and η (62.6-99.9) and low RMSE (0.05-2.19%) and MAE (0.03-1.74%) values without over or under estimations (Rratio ≈ 1) in South Andaman area of Andaman and Nicobar tropical ecosystem. This kind of study helps as baseline information for hydrological modelling and policy makers to plan irrigation systems, accurate management of crop quantity and quality in farms, and schedule critical irrigations accurately.

show abstract

Section: Study Area Descriptionmentioning

confidence: 99%

Soil Moisture Mapping in Indian Tropical Island Ecosystem using C-band SAR Data and Neural Network Models

Adamala,

Ayyam,

Palanivel

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is further noted that conservation measures such as level or inward slope bench terraces on steep areas are highly effective for arresting soil erosion in plantation-based intercropping systems [87]. The vegetable cultivation fields of the Islands, where more cultural working or tillage practices are required, yield a soil erosion of 120-130 t/ha/year, with shallow mass movements due to highly intensive storms [63].…”

Section: Conservation Measuresmentioning

confidence: 99%

Application of RMMF-Based GIS Model for Soil Erosion Assessment in Andaman Ecosystem

Adamala

Velmurugan

Kumari

et al. 2023

Land

Self Cite

View full text Add to dashboard Cite

Water erosion is one of the major land degradation problems all over the globe, and its accurate quantification in different land use contexts is required in order to propose suitable conservation measures and curtail related hazards. In the Andaman and Nicobar (A&N) Islands, the land use changes due to faster urbanization and deforestation practices have led to accelerated erosion at many points around the inhabited Islands. Moreover, agricultural land uses in the A&N Islands are vulnerable to severe soil erosion, mainly due to cultivation practices along the steep slopes and mono-cropping culture. A study was conducted by establishing runoff plots in areas with different land uses to measure soil and nutrient losses and to estimate soil erosion using a semi-process-based soil erosion model, i.e., Revised Morgan Morgan and Finney (RMMF). The RMMF model was calibrated using primary data from runoff plots for the years 2019–21, validated for the year 2022, and applied in a Geographical Information System (GIS) to estimate soil erosion spatially over the Andaman ecosystem. The RMMF model simulated soil erosion during validation with a coefficient determination (R2) greater than 0.87 as compared to measured soil erosion from the runoff plots. The study revealed that annual N, P, and K losses of 41–81%, 42–95%, and 7–23%, respectively, due to runoff from various land uses. The land use land classification analysis of the Andaman Islands revealed that about 88% of the total geographical area is under the forest and mangrove land uses, which exhibited very slight soil erosion of <5 t/ha. This 88% of forest and mangrove areas requires suitable conservation measures such as afforestation and rehabilitation/restoration of mangroves. Moreover, 6% of cultivated areas need terracing, bunding, intercropping, etc., at the highest priority in order to conserve a sustainable Andaman ecosystem. On average, the annual soil loss from the Andaman Islands is 3.13 t/ha. About 6% of the study area exceeds the soil tolerance limit of 2.5–12.5 t/ha/year, which needs suitable soil and water conservation measures at the lowest priority due to economic implications.

show abstract

“…These indicators are applied in a semiarid grassland coal mine area, where they successfully capture landscape dynamics across various types. In the Andaman Islands, India, Velmurugan et al (2021) reveal the fragility of island ecosystems. The worsening of forest‐cover loss due to land degradation in these islands endangers biodiversity and heightens the vulnerability of these regions to further ecological disturbances.…”

Section: Land Use/cover Changes Degradation and Environmental Implica...mentioning

confidence: 99%

Land use changes, degradation, and impact on ecosystem services in Asia and Southeast Asia

Vadrevu,

Gutman,

Tsuneo

et al. 2023

Land Degrad Dev

View full text Add to dashboard Cite

Post‐tsunami land degradation on a South Asian island: Implications for conservation priorities

Cited by 4 publications

References 43 publications

Soil Moisture Mapping in Indian Tropical Island Ecosystem using C-band SAR Data and Neural Network Models

Soil Moisture Mapping in Indian Tropical Island Ecosystem using C-band SAR Data and Neural Network Models

Application of RMMF-Based GIS Model for Soil Erosion Assessment in Andaman Ecosystem

Land use changes, degradation, and impact on ecosystem services in Asia and Southeast Asia

Contact Info

Product

Resources

About