Search Results

• Performance evaluation of vine canopy detection methods using multispectral images.
• Deep learning methods achieved the best performance in vineyard canopy detection.
• U-Net and Mask R-CNN provide more accurate monitoring to assess ...

In viticulture, the rapid and accurate acquisition of canopy spectral information through ultra-high spatial resolution imagery is increasingly demanded for decision support. The prevalent practice involves creating vigor maps using spectral data ...

Due to rising rural labor costs, farmland abandonment is common in China's hilly areas. Timely, accurate extraction of its spatiotemporal changes is crucial for sustainable farmland use. This study presents a novel approach for extracting abandoned ...

• A new method to isolate only grapevine NDVI from a Sentinel-2 mixed signal is proposed.
• UAV imagery was used to retrieve vines fraction cover within Sentinel-2 pixel.
• Two-endmembers spectral linear mixture model was assumed.
• ...

Satellite-based multispectral remote sensing in the wine sector is expanding, aiming at improving vineyard management for both environmental sustainability and vine quality/yield. However, vineyards present a discontinuous vegetative surface, ...

Precision agriculture has emerged as a dominant force in the United States, with widespread adoption of advanced technologies and decision support systems (DSS) since the 1980s. Key tools such as variable rate application (VRA), autopilot systems,...

• A crop yield predicting model for promoting sustainable production and facilitating local stakeholder decision-making.
• LSTM with Attention model can perform well better than panel regression but falls short when trained with small ...

The accurate prediction of soybean yield is vital for global food market stabilization and food security. Recent advancements in remote sensing technology have significantly amplified interest in leveraging satellite-based methods for predicting ...

• Predict the normalized difference vegetation index (NDVI) using RGB drone imagery data.
• The curvelet coefficients were analysed using Empirical Curvelet Transform method from RGB.
• The deep DenseNet model predict the NDVI using the ...

Predicting accurately the Normalized Difference Vegetation Index (NDVI) trends from RGB images are essential to monitor crops and identify issues related to plant diseases, and water shortages. The current NDVI prediction models are primarily ...

In order to extract valuable ground information from images, supervised classification is an extensively adopted technique. However, it has a substantial downside in that choosing and labeling training samples requires a lot of time and resources. ...

• Robot driven combined site-specific seeding and N fertilization (CSSF = SSS + SNF).
• Both Kings (KA) and Robin Hood (RHA) prescriptions are contrasted in SNF.
• SNF-KA reduces N and seed inputs but SNF-RHA increases little N use.
• ...

Autonomous agricultural management combats the labor crisis in farming industry and ensures efficient farm operations, whereas variable rate technology has proven to increase resource use efficiency and reduce environmental impacts. This study ...

Net Primary Productivity (NPP) is a fundamental ecological metric that underpins the functioning of ecosystems. NPP estimation using the Carnegie–Ames–Stanford Approach (CASA) biosphere model is carried out for the Roorkee and Hyderabad study ...

• The AGB estimation performance of ASD and UHD185 was compared.
• HD was employed to improve spectral sensitivity to AGB.
• The AGB spatial distribution map was created.

Accurately estimating potato above-ground biomass (AGB), which is closely associated with the growth and yield of crops, carries significant importance for guiding field management practices. Hyperspectral techniques have emerged as a powerful ...

Generative Adversarial Networks (GANs) are one of the most significant research directions in the field of Deep Learning (DL). GANs has received wide attention due to their outstanding ability to produce realistic-looking images and can ...

• Presents GAN for multi-step NDVI forecasting, capturing ST relationships in MTS.
• Provides generic module for combining heterogeneous data sources for more accurate inference.
• Outperforms existing state-of-the-art methods on real-...

Tropical coastal lagoons are valuable ecosystems that provide vital ecological services. Understanding vegetation health dynamics is essential to conserve and manage these environments effectively. Also, some landscape-related aspects suffer ...

Temporal variation in forest cover, the largest terrestrial ecosystem on Earth, influences the climate at both local, regional, and global scales through physical, chemical, and biological processes. At the same time, forests sequester and store more ...

• Combination of vegetation indices, morphological characteristics and ecological factors improves the accuracy of leaf area index estimation.
• Texture information and ecological factors exhibit a close relationship with vegetation ...

Leaf area index (LAI) is an important phenotypic trait closely related to photosynthesis, respiration, and water utilization. In recent years, unmanned aerial vehicles (UAVs) multispectral capabilities enable the acquisition of spectral ...

Accurate yield prediction is essential for precision agriculture as it enables farmers to optimize their inputs and manage their resources more efficiently, ultimately leading to higher profitability and sustainable farming practices. The aim of ...

Land use and land cover modeling is an essential tool because it enables scientists and policymakers to foresee prospective changes in landscape heritage and examine trends to minimize potential dangers. To attain this purpose, a continuous stream ...

Peru is a country that distributes its economic activity in the export of oil, natural gas, precious metals and mining, the latter being often extracted illegally, which causes havoc and damage to a certain geographical area. The Peruvian jungle and ...

The present study used time-series Landsat-8 and 9 satellite datasets of June to February 2016–2017 and 2021–2022 to classify and detect the changes in vegetation covers. The studied Akole region of Ahmednagar district of Maharashtra, India, is ...

• Mapping of LULC change in the mangrove forest of Gulf of Khambhat, Gujarat.
• Identification of mangrove area affected by land-use and climate change activities.
• Deforestation of mangroves as a result of land conversion to non-...

The most important biological ecosystems on the earth are mangroves, palms, shrubs, and trees that have adjusted to the challenging environments of high salinity, warm air and temperatures, severe tides, murky, sediment-hampered waterways, and ...

• A comparison of crop masks to spatially aggregate NDVI for yield forecasting in EU.
• Forecasts improve when using annual crop group-specific than generic crop masks.
• Improvements concern both accuracy and timeliness of yield ...

Operational crop yield forecasting services typically provides crop yield forecasts based on regression models between official yields and agro-environmental variables, among which meteorological data, crop simulation model or satellite-derived ...