Differentiating Irrigation Treatments in Sorghum Using Planetscope Multispectral Imagery DOI
Kamila Dilmurat, Erin L. Hestir,

Benjamin J. Lewis

и другие.

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Год журнала: 2024, Номер unknown, С. 4245 - 4249

Опубликована: Июль 7, 2024

Язык: Английский

CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration DOI Creative Commons
Ling Zhang, Yanhua Xie, Xiufang Zhu

и другие.

Earth system science data, Год журнала: 2024, Номер 16(11), С. 5207 - 5226

Опубликована: Ноя. 12, 2024

Abstract. Accurate maps of irrigation extent and dynamics are crucial for studying food security its far-reaching impacts on Earth systems the environment. While several efforts have been made to map irrigated area in China, few provided multiyear maps, incorporated national land surveys, addressed data discrepancies, considered fractional coverage cropland within coarse-resolution pixels. Here, we these important gaps developed new annual China's from 2000 2020, named CIrrMap250 (China's with a 250 m resolution). We harmonized statistics surveys reconciled them remote sensing data. The refined estimates were then integrated multiple (i.e. vegetation indices, hybrid products, paddy field maps) an suitability by means semi-automatic training approach. evaluated our using ∼ 20 000 reference samples, high-resolution water withdrawal data, existing local nationwide maps. Our demonstrated overall accuracy 0.79–0.88 years 2000, 2010, 2020 outperformed currently available CIrrMap250-estimated explained 50 %–60 % variance across China. revealed that increased about 180 km2 (or 25 %) majority (61 occurring water-unsustainable regions facing severe extreme stress. Moreover, product unveiled noticeable northward shift area, attributed substantial expansions northeastern northwestern accurate representation will greatly support hydrologic, agricultural, climate studies aiding improved resources management. can be accessed at https://doi.org/10.6084/m9.figshare.24814293.v2 (Zhang et al., 2023a).

Язык: Английский

Процитировано

6

Applicability of three remote sensing based soil moisture variables for mapping soil organic matter in areas with different vegetation densities DOI

Chenconghai Yang,

Lin Yang, Lei Zhang

и другие.

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132980 - 132980

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Effects of Water Application Frequency and Water Use Efficiency Under Deficit Irrigation on Maize Yield in Xinjiang DOI Creative Commons
Ting Duan, Licun Zhang, Guodong Wang

и другие.

Agronomy, Год журнала: 2025, Номер 15(5), С. 1110 - 1110

Опубликована: Апрель 30, 2025

Water conservation is critical for global maize production, particularly in arid regions where water scarcity, exacerbated by climate change, threatens conventional irrigation sustainability. Optimizing strategies to reconcile productivity and yield remains a key scientific challenge water-limited agriculture. This four-year study (2018–2021) evaluated integrated management that combined frequency volume adjustments. A field experiment compared three strategies: high-frequency limited (HL: 2400 m3·hm−2), low-frequency (LC: (HC: 4800 m3·hm−2). The mean showed HL (10,793.78 kg·hm−2) had non-significant 18.2% numerical advantage over LC (9,129.11 kg·hm−2, p > 0.05). WUE reached 3.63 kg·m−3, representing an 18.6% increase (3.06 kg·m−3; Physiological parameters (plant height + 2.6%, leaf area 9.9%, SPAD 1.5%) marginal improvements HL, yet lacked both statistical significance (p 0.05) strong correlation. Multi-year analyses confirmed no statistically distinguishable differences between 0.05), demonstrating adjustments alone cannot reliably enhance drought resilience. These findings caution against advocating as superior practice, given the equivalence despite savings, gap HC. Future research must establish causality through models integrating real-time soil–crop–climate feedback prior recommending altered regimes.

Язык: Английский

Процитировано

0

Methodologies for Water Accounting at the Collective Irrigation System Scale Aiming at Optimizing Water Productivity DOI Creative Commons
Antónia Ferreira, João Rolim, Paula Paredes

и другие.

Agronomy, Год журнала: 2023, Номер 13(7), С. 1938 - 1938

Опубликована: Июль 22, 2023

To improve water use efficiency and productivity, particularly in irrigated areas, reliable accounting methodologies are essential, as they provide information on the status trends irrigation availability/supply consumption/demand. At collective system level, (IWA) relies quantification of fluxes from diversion point to plants, at both conveyance distribution network field level. Direct measurement is most accurate method for IWA, but cases, there limited metering despite increasing pressure groundwater surface resources, hindering procedures. However, various methodologies, tools, indicators have been developed estimate IWA components, depending scale level detail being considered. Another setback wide implementation vast terminology used literature different scales levels application. Thus, main objectives this review, which focuses services, (i) demonstrate importance by showing its relationship with productivity efficiency; (ii) clarify concepts related IWA; (iii) an overview approaches obtain data demand side, on-farm systems. From it can be concluded that a need provides common base all stakeholders. Future work could include development user-friendly tools reduce bridge between technology available collect process components effective

Язык: Английский

Процитировано

8

A new variant of the optical trapezoid model (OPTRAM) for remote sensing of soil moisture and water bodies DOI Creative Commons
Morteza Sadeghi,

Neda Mohamadzadeh,

Lan Liang

и другие.

Science of Remote Sensing, Год журнала: 2023, Номер 8, С. 100105 - 100105

Опубликована: Окт. 11, 2023

Over the past few years, Optical Trapezoid Model (OPTRAM) has been widely used as a means for high-resolution mapping of surface soil moisture using optical satellite data. In this paper, we propose new variant OPTRAM that can map not only moisture, but also water bodies such lakes and rivers. The proposed was tested laboratory experimental data well Landsat-8 reflectance observations. Results showed greater skill than original in separating land pixels. addition, less sensitivity to model parameters, hence, is user dependent. To quantitatively examine user-dependency model, analyzed based on images California, where varied parameters plausible range. correlations resulting maps terms R2 between two largely different sets were found range 0.47-0.52 0.67-0.76 variant. Because some be quite uncertain, particularly wet regions, reduced promises more consistent estimates across parameter choices.

Язык: Английский

Процитировано

8

Extraction of grassland irrigation information in arid regions based on multi-source remote sensing data DOI Creative Commons

Di Fu,

Xin Jin,

Yanxiang Jin

и другие.

Agricultural Water Management, Год журнала: 2024, Номер 302, С. 109010 - 109010

Опубликована: Авг. 16, 2024

Irrigation is a vital measure for maintaining grassland productivity in arid and semi-arid regions. Grasslands typically have characteristics such as unclear boundaries, complex vegetation types, relatively small irrigation amounts, making it challenging to extract information. Currently, research on extracting information scarce. This study proposes method using high spatiotemporal resolution (30 m, 1 day) downscaled surface soil moisture data, combined with Landsat 8/9 Sentinel 1/2 data. was applied the area, timing, frequency of grasslands Delingha Piedmont, northwestern China. The results showed that overall classification accuracy irrigated 93.43 %, kappa coefficient 0.91, indicating extraction accuracy. average values recall, precision, F-score timing were 82.54 72.25 77.03 respectively, most events accurately identified, commendable efficacy. use multi-source remote sensing data crucial Among these, by providing detailed dynamics, demonstrate potent capacity capturing events, thus effectively enhancing extraction.

Язык: Английский

Процитировано

2

CIrrMap250: Annual maps of China’s irrigated cropland from 2000 to 2020 developed through multisource data integration DOI Creative Commons
Ling Zhang, Yanhua Xie, Xiufang Zhu

и другие.

Опубликована: Янв. 29, 2024

Abstract. Accurate maps of irrigation extent and dynamics are important to study food security its far-reaching impacts on Earth systems the environment. While several efforts have been made map irrigated areas in China, few them provided multi-year maps, incorporated national land surveys, addressed data discrepancies, considered fraction coverage cropland (i.e., mixed pixel issue). In this study, we these gaps developed new annual China’s from 2000 2020, named as CIrrMap250. We harmonized area statistics surveys reconciled with remote sensing data. The refined estimates were then integrated multiple vegetation indices, hybrid product, paddy field maps) suitability through a semi-automatic training approach. evaluated our CIrrMap250 using independently interpreted 20,000 reference locations, high-resolution water withdrawal data, existing local nationwide maps. Our evaluation results showed that agreed well points, an overall accuracy 0.79–0.88 for years 2000, 2010, respectively. CIrrMap250-estimated can explain 50–60 % variance withdrawals across China. product superior performance than currently available ones IrriMap_CN, IAAA, GFSAD). revealed has increased by about 180,000 km2 (or 25 %) majority (61 being water-unsustainable occurring regions facing high severe stress. Moreover, unveiled noticeable northward shift area, attributed substantial expansion Northeast Northwest accurate representation will greatly support hydrologic, agricultural, climate studies China improved resources management.

Язык: Английский

Процитировано

1

Advancing in satellite-based models coupled with reanalysis agrometeorological data for improving the irrigation management under the European Water Framework Directive DOI Creative Commons
Giuseppe Longo-Minnolo, A. D’Emilio, Daniela Vanella

и другие.

Agricultural Water Management, Год журнала: 2024, Номер 301, С. 108955 - 108955

Опубликована: Июль 16, 2024

Soon, water scarcity is expected to worsen due several factors including the population growth and climate change. To address this, European Water Framework Directive (WFD) mandates an increase in use efficiency of agrosystems. In this context, aim study was provide a novel methodological approach, based on satellite-based classification algorithms (i.e., artificial neural networks, ANN, Optical Trapezoid Model, OPTRAM), agro-hydrological modelling ArcDualKc model versus traditional FAO-56 approach) combined with different sources agrometeorological data ground-based ERA5 Land data), for mapping irrigated crops determining their irrigation requirements (IWR) at district level. The carried out, during period 2019–20, district, named "Quota 102,50" (Eastern Sicily, Italy) managed by local reclamation consortium. ANN OPTRAM allowed obtain accurate detection crops, overall accuracy 82 % 88 %, respectively 2019–20. IWR retrieved standard approach were generally underestimated comparison volumes supplied farmers. best performance resulted when implemented data, average values coefficient determination, residual error slope 0.99, 975.31 m3 0.78, respectively, outputs scale compared declared consortium overestimations terms both areas IWR, absolute errors about 1539 ha 1431 ha, 9 106 12 m3, Finally, provided useful framework supporting management authorities better planning monitoring uses under current WFD.

Язык: Английский

Процитировано

1

rOPTRAM: Deriving Soil Moisture from Satellite Imagery in R DOI Creative Commons
Micha Silver,

Ron Beiden,

Zhe Dong

и другие.

The Journal of Open Source Software, Год журнала: 2024, Номер 9(100), С. 7086 - 7086

Опубликована: Авг. 22, 2024

Soil moisture at the Earth's surface is essential in many hydrological, pedological, and biological processes.Earth observations from satellites have been recognized as most efficient reliable means for assessing soil water content.The satellite-derived OPTRAM model has shown to determine over large areas accurately.Spectral data were obtained different spaceborne systems calculate several vegetation indices, was adjusted various SM conditions.The rOPTRAM package allows researchers practitioners monitor contents a regional scale long-time intervals.

Язык: Английский

Процитировано

1

Plot-Scale Irrigation Dates and Amount Detection Using Surface Soil Moisture Derived from Sentinel-1 SAR Data in the Optirrig Crop Model DOI Creative Commons
Mohamad Hamze,

Bruno Cheviron,

Nicolas Baghdadi

и другие.

Remote Sensing, Год журнала: 2023, Номер 15(16), С. 4081 - 4081

Опубликована: Авг. 19, 2023

This study aimed to develop an approach using Sentinel-1 synthetic aperture radar (SAR) data and the Optirrig crop growth irrigation model detect dates amounts for maize crops in Occitanie region, Southern France. The surface soil moisture (SSM) derived from SAR was analyzed changes indicating events at plot scale four reference plots located Montpellier (P1) Tarbes (P2, P3, P4). As rain most likely covers several square kilometers, while is decided scale, a difference between SSM signals grid (10 km × 10 km) clear indication of recent event. Its date amount are then sought by forcing Optirrig, selecting relevant (date, amount) combination appropriate criterion. observed values hold depth few centimeters, modeled exactly cm, best one that gives similar relative rather than values. were detected with overall accuracy (recall) 86.2% precision 85.7%, thus, relatively low numbers missed or false detections, respectively. performance method detecting seasonal varied climatic conditions. For P1 semi-arid climate Montpellier, mean absolute error percentage (MAE%) 16.4%, showing higher efficiency when compared humid P4 plots), where MAE% 50% recorded, larger discrepancy actual amounts. limitations proposed can be attributed characteristics constellation, including its 6-day revisit time signal penetration challenges dense cover, as well mismatch parameterization simulations practices followed farmers. Despite these weaknesses, results demonstrated relevance combining S1 SAR-derived field-scale detection and, potentially,

Язык: Английский

Процитировано

3