Accurate and timely crop type mapping and rotation monitoring play a critical role in crop yield estimation, soil management, and food supplies. To date, to our knowledge, accurate mapping of crop types remains challenging due to the intra-class vari...
In the context of climate change, the remote sensing identification of crops is extremely important for the rapid development of agricultural economy and the detailed assessment of the agro-meteorological disasters. The Jilin Province is the main gra...
Knowledge about crop type distribution is valuable information for effective management of agricultural productivity, food security estimation, and natural resources protection. Algorithms for automatic crop type detection have great potential to pos...
Crop type inventory and within season estimates at moderate (<30 m) resolution have been elusive in many regions due to the lack of temporal frequency, clouds, and restrictive data policies. New opportunities exist from the operational fusion of L...
To improve crop yields and incomes, farmers consistently adapt their practices to climate and market fluctuations, resulting in highly variable crop field distribution and coverage in space and time. As these dynamics illustrate farmers’ challe...
Remote sensing offers a way to map crop types across large spatio-temporal scales at low costs. However, mapping crop types is challenging in heterogeneous, smallholder farming systems, such as those in India, where field sizes are often smaller than...
In situ ground truth data are an important requirement for producing accurate cropland type map, and this is precisely what is lacking at vast scales. Although volunteered geographic information (VGI) has been proven as a possible solution for in sit...
This study investigates the impact of crop type and soil characteristics on greenhouse gas (GHG) emissions in Latvian agriculture, offering insights directly relevant to policymakers and practitioners focused on sustainable land management. From 2020...
Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food sec...
Long-term temporal and spatial information of crop type supports a wide range of applications including hydrological and climatological studies. In the U.S., yearly crop data layers (CDLs) are available starting in the early 2000s and have been devel...
Timely and accurate crop type mapping is a critical prerequisite for the estimation of water availability and environmental carrying capacity. This research proposed a method to integrate time series Sentinel-1 (S1) and Sentinel-2 (S2) data for crop...
The creation of crop type maps from satellite data has proven challenging and is often impeded by a lack of accurate in situ data. Street-level imagery represents a new potential source of in situ data that may aid crop type mapping, but it requires...
Crop type identification is the initial stage and an important part of the agricultural monitoring system. It is well known that synthetic aperture radar (SAR) Sentinel-1A imagery provides a reliable data source for crop type identification. However,...
Crop type mapping at high resolution is crucial for various purposes related to agriculture and food security, including the monitoring of crop yields, evaluating the potential effects of natural disasters on agricultural production, analyzing the po...
We present a study on the effectiveness of using varying data sizes to transfer crop type classification models from one year to the next, emphasizing the balance between data sufficiency and model accuracy. The significance of crop detection through...
Large-scale crop type mapping often requires prediction beyond the environmental settings of the training sites. Shifts in crop phenology, field characteristics, or ecological site conditions in the previously unseen area, may reduce the classificati...
In-season crop-type maps are required for a variety of agricultural monitoring and decision-making applications. The earlier the crop type maps of the current growing season are obtained, the more beneficial it is for agricultural decision-making and...
High-resolution crop type mapping is of importance for site-specific agricultural management and food security in smallholder farming regions, but is challenging due to limited data availability and the need for image-based algorithms. In this paper,...
Accurate crop type maps play an important role in food security due to their widespread applicability. Optical time series data (TSD) have proven to be significant for crop type mapping. However, filling in missing information due to clouds in optica...
Cropland monitoring is important for ensuring food security in the context of global climate change and population growth. Freely available satellite data allow for the monitoring of large areas, while cloud-processing platforms enable a wide user co...
Remote sensing (RS) spectral time series provide a substantial source of information for the regular and cost-efficient monitoring of the Earth’s surface. Important monitoring tasks include land use and land cover classification, change detecti...
Crop area extent estimates and crop type maps provide crucial information for agricultural monitoring and management. Remote sensing imagery in general and, more specifically, high temporal and high spatial resolution data as the ones which will be a...
The differences in soil fungal communities in four agricultural areas growing wheat (Triticum aestivum), rapeseed (Brassica napus), and barley (Hordeum vulgare) in the Qinghai Province, namely the Dulan (DL), Gonghe (GH), Huzhu (HZ), and Datong (DT)...
The Hetao irrigation area is one of the largest irrigation areas in the Yellow River Basin and a typical salinized agricultural area. Crop type shifts in this area can alter soil phosphorus (P) morphology and microbial functional diversity, thereby i...
High temporal and spatial resolution optical image time series have been proven efficient for crop type mapping at the end of the agricultural season. However, due to cloud cover and image availability, crop identification earlier in the season is di...
Large-scale crop mapping is of fundamental importance to tackle food security problems. SAR remote sensing has lately received great attention for crop type mapping due to its stability in the revisit cycle and is not hindered by cloud cover. However...
With the ever-increasing number of satellites and the availability of data free of charge, the integration of multi-sensor images in coherent time series offers new opportunities for land cover and crop type classification. This article investigates...
This paper provides recommendations on how large-scale household surveys should be conducted to generate the data needed to train models for satellite-based crop type mapping in smallholder farming systems. The analysis focuses on maize cultivation i...
This investigation evaluates the potential of combining Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) satellite data in producing a detailed Land Use and Land Cover (LULC) map with 19 crop type classes and 2 broader categories containing Woodland/Sh...
One of the most challenging aspects of obtaining detailed and accurate land-use and land-cover (LULC) maps is the availability of representative field data for training and validation. In this manuscript, we evaluate the use of the Eurostat Land Use...
A timely and accurate distribution of crop types and cropping patterns provides a crucial reference for the management of agriculture and food security. However, accurately mapping crop types and cropping patterns in subtropical hilly and mountainous...
High resolution satellite imagery and modern machine learning methods hold the potential to fill existing data gaps in where crops are grown around the world at a sub-field level. However, high resolution crop type maps have remained challenging to c...
Sustainable agricultural practices necessitate accurate baseline data of crop types and their detailed spatial distribution. Compared with field surveys, remote sensing has demonstrated superior performance, offering spatially explicit crop distribut...
Appropriate crop type mapping to monitor and control land management is very important in developing countries. It can be very useful where digital cadaster maps are not available or usage of Remote Sensing (RS) data is not utilized in the process of...
Soil microorganisms are crucial for nutrient cycling, with abundant and rare taxa playing distinct roles. However, the mechanisms by which soil microbes influence nutrient cycling under different crop types remain unclear. In this study, we investiga...
Soil microorganisms play a crucial role in maintaining soil functionality and ecological balance by participating in key processes such as organic matter decomposition, nutrient cycling, soil structure formation, and plant health support. High-throug...
Farmers’ ability to accurately anticipate crop type is critical to global food production and sustainable smart cities since timely decisions on imports and exports, based on precise forecasts, are crucial to the country’s food security....
Accurate extraction of crop cultivated area and spatial distribution is essential for food security. Crop classification methods based on machine learning and deep learning and remotely sensed time-series data are widely utilized to detect crop plant...
Multi-source remote sensing-derived information on crops contributes significantly to agricultural monitoring, assessment, and management. In Africa, some challenges (i.e., small-scale farming practices associated with diverse crop types and agricult...
Organic farming systems have become widespread in recent decades due to their popularity with consumers and their beneficial effects on the environment and biodiversity. Through the increasing number of available studies from farm surveys and compara...
Crop type classification with satellite imageries is widely applied in support of crop production management and food security strategy. The abundant supply of these satellite data is accelerating and blooming the application of crop classification a...
Field N2O emissions are a key point in the evaluation of the greenhouse gas benefits of bioenergy crops. The aim of this study was to investigate N2O fluxes from perennial (miscanthus and switchgrass), semi-perennial (fescue and alfalfa) and annual (...
Intensive agriculture, ecosystem degradation, and declining soil quality highlight the urgent need for sustainable land use strategies. The cultivation of short-rotation woody crops (SRC), combined with fertilization using sewage sludge digestate (SS...
Accurate global crop type mapping is essential to ensure food security. However, large-scale crop-type mapping still poses challenges to commonly used classification strategies. Specifically, variation within crop types downgrades classification perf...
The application of satellite single-pass interferometric data to crop-type mapping is demonstrated for the first time in this work. A set of nine TanDEM-X dual-pol pairs of images acquired during its science phase, from June to August 2015, is exploi...
Crop type information at the field level is vital for many types of research and applications. The United States Department of Agriculture (USDA) provides information on crop types for US cropland as a Cropland Data Layer (CDL). However, CDL is only...
Orthomosics and digital surface models (DSM) derived from aerial imagery, acquired by consumer-grade cameras, have the potential for crop type mapping. In this study, a novel method was proposed for extracting the crop height from DSM and for evaluat...
Monitoring and forecasting crop yields is a critical component of understanding and better addressing global food security challenges. Detailed spatial information on crop-type distribution is fundamental for in-season crop condition monitoring and y...
Northeast China (NEC) is one of the most important national agricultural production bases, and its agricultural water dynamics are essential for food security and sustainable agricultural development. However, the dynamics of long-term annual crop-sp...
Large-scale agricultural remote sensing monitoring is challenged by pronounced spatial heterogeneity arising from fragmented terrain, complex climatic backgrounds, and diverse cropping structures. However, existing agricultural zoning schemes general...
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