Time series analysis from 1984 to 2023 of Earth Observation Satellites data for evaluating changes in vegetation cover and health at flaring sites in the Niger Delta, Nigeria. DOI
Barnabas Morakınyo

Academic Platform Journal of Natural Hazards and Disaster Management, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 17, 2024

Normalized Difference Vegetation Index (NDVI) is the most popular vegetation index used to clarify difficulties of multi-spectral imagery, for example evaluation vegetation.The data (11 Landsat 5 TM, 49 7 ETM+, 27 8 OLI-TIRS, and 15Landsat 9 OLI-TIRS)dated from 10/10/1984 17/12/2023 with < 3 % cloud cover wereused study 11 flaring sites in Rivers State, Nigeria. Data processing analysis were carried out using MATLAB codes. NDVI For 7, was determined atmospherically corrected multispectral bands (1-4) are (2-5) N, E, S W directions at distances 60 m, 90 120 m 240 respectively flare. Generally, results show that lowest. increases as distance 240m flare all sites. decreases each year passes away however, Onne Flow Station gives an unsteady pattern years 1984 2007 before flow station built. The lowest mean (0.290) obtained recorded Umudioga East stack, followed by Obigbo (0.300) SD site small a range value (5.0786 ×10-5- 2.0689 × 10-4). Therefore, it can be concluded sensors evaluate changes its health Niger Delta.

Language: Английский

Evaluation of the monitoring capability of various vegetation indices and mainstream satellite band settings for grassland drought DOI Creative Commons
Xiufang Zhu, Qingfen Li,

Chunhua Guo

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102717 - 102717

Published: July 6, 2024

In the context of global climate change and increasing human activities, grassland drought has become increasingly severe complex. The monitoring is crucial for reducing drought-related losses ensuring national ecological security. This study used coupled PROSPECT SAIL radiative transfer models (PROSAIL) to simulate canopy reflectance, considering factors such as growth stages varying conditions. Our objective was reveal spectral response characteristics grasslands conditions identify sensitive bands suitable during different stages. We aligned commonly available satellite from moderate resolution imaging spectroradiometer (MODIS), Sentinel 2, Landsat 8, WorldView Gaofen 2 (GF 2) with these assess capabilities existing data monitoring. Furthermore, this research evaluated suitability 16 remote sensing vegetation indices monitoring, including Normalized Difference Vegetation Index (NDVI), Enhanced (EVI), Ratio (RVI), (DVI), Modified Soil Adjusted (MSAVI), Atmospherically Resistant (ARVI), Water (MNDWI), Global Moisture (GVMI), Land Surface (LSWI), Visible Shortwave Infrared Drought (VSDI), index(WI), Stress Index(MSI), Index(NDWI), (NDII), Photochemical Reflectance (PRI), Optimized Soil-Adjusted (OSAVI). simulation analysis results revealed: 1) Grassland in exhibit similar sensitivities certain bands, namely those within ranges 540 nm–720 nm, 1250 nm–1690 1805 nm–2190 2264 nm–2500 which are more various Suitable both growing stable include NDII, MSI, PRI, LSWI, GVMI, silhouette coefficients exceeding 0.6 stage 0.7 stage. least index DVI, an average coefficient 0.15 over entire 3) From band perspective, among five assessed satellites, MODIS Band 7 exhibits highest sensitivity water content across all bands. MODIS's configuration most stages, while 2's suitable.

Language: Английский

Citations

13
Remote Sensing and Soil Moisture Sensors for Irrigation Management in Avocado Orchards: A Practical Approach for Water Stress Assessment in Remote Agricultural Areas DOI Creative Commons
Emmanuel A. Torres-Quezada, Fernando Fuentes-Peñailillo,

Karen Gutter

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(4), P. 708 - 708

Published: Feb. 19, 2025

Water scarcity significantly challenges agricultural systems worldwide, especially in tropical areas such as the Dominican Republic. This study explores integrating satellite-based remote sensing technologies and field-based soil moisture sensors to assess water stress optimize irrigation management avocado orchards Puerto Escondido, Using multispectral imagery from Landsat 8 9 satellites, key vegetation indices (NDVI SAVI) NDWI, a water-related index that specifically indicates changes crop contents, rather than vigor, were derived monitor health, growth stages, contents. Crop coefficient (Kc) values calculated these combined with reference evapotranspiration (ETo) estimates three meteorological models (Hargreaves–Samani, Priestley–Taylor, Blaney–Criddle) requirements. The results revealed data at 30 cm depth strongly correlated satellite-derived estimates, reflecting trees’ critical root zone dynamics. Additionally, seasonal patterns showed NDVI SAVI effectively tracked vegetative while NDWI indicated canopy content, particularly during periods of stress. Integrating field measurements allowed comprehensive assessment requirements stress, providing valuable insights for improving practices. Finally, this demonstrates potential large-scale assessment, offering scalable cost-effective solution optimizing practices water-limited regions. These findings advance precision agriculture, environments, provide foundation future research aimed enhancing accuracy

Language: Английский

Citations

1
Estimation of Leaf Area Index of Mustard and Potato from Sentinel-2 data using Parametric, Non-parametric and Physical Retrieval models DOI
Sanjoy Dey, Koushik Saha,

Rucha Dave

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: 37, P. 101493 - 101493

Published: Jan. 1, 2025

Language: Английский

Citations

0
Advancing lettuce physiological state recognition in IoT aeroponic systems: A meta-learning-driven data fusion approach DOI
Osama Elsherbiny, Jianmin Gao, Ming Ma

et al.

European Journal of Agronomy, Journal Year: 2024, Volume and Issue: 161, P. 127387 - 127387

Published: Oct. 14, 2024

Language: Английский

Citations

3
Time series analysis from 1984 to 2023 of Earth Observation Satellites data for evaluating changes in vegetation cover and health at flaring sites in the Niger Delta, Nigeria. DOI
Barnabas Morakınyo

Academic Platform Journal of Natural Hazards and Disaster Management, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 17, 2024

Normalized Difference Vegetation Index (NDVI) is the most popular vegetation index used to clarify difficulties of multi-spectral imagery, for example evaluation vegetation.The data (11 Landsat 5 TM, 49 7 ETM+, 27 8 OLI-TIRS, and 15Landsat 9 OLI-TIRS)dated from 10/10/1984 17/12/2023 with < 3 % cloud cover wereused study 11 flaring sites in Rivers State, Nigeria. Data processing analysis were carried out using MATLAB codes. NDVI For 7, was determined atmospherically corrected multispectral bands (1-4) are (2-5) N, E, S W directions at distances 60 m, 90 120 m 240 respectively flare. Generally, results show that lowest. increases as distance 240m flare all sites. decreases each year passes away however, Onne Flow Station gives an unsteady pattern years 1984 2007 before flow station built. The lowest mean (0.290) obtained recorded Umudioga East stack, followed by Obigbo (0.300) SD site small a range value (5.0786 ×10-5- 2.0689 × 10-4). Therefore, it can be concluded sensors evaluate changes its health Niger Delta.

Language: Английский

Citations

0