Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2

Cheng, Yan; Vrieling, Anton; Fava, Francesco; Meroni, Michele; Marshall, Michael; Gachoki, Stella

doi:10.1016/j.rse.2020.112004

Cited by 112 publications

(67 citation statements)

References 95 publications

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“…During the early crop development, a small change of emergence may be complicated with the change of soil moisture, such as snow melting or rainfall. In addition, the availability of usable remote sensing observations is affected by clouds and thus affects phenology results [60]. For these reasons, near-real-time monitoring of crop emergence may be delayed.…”

Section: Discussionmentioning

confidence: 99%

Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities

2021

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Crop phenology is critical for agricultural management, crop yield estimation, and agroecosystem assessment. Traditionally, crop growth stages are observed from the ground, which is time-consuming and lacks spatial variability. Remote sensing Vegetation Index (VI) time series has been used to map land surface phenology (LSP) and relate to crop growth stages mostly after the growing season. In recent years, high temporal and spatial resolution remote sensing data have allowed near-real-time mapping of crop phenology within the growing season. This paper summarizes two classes of near-real-time mapping methods, i.e., curve-based and trend-based approaches. The curve-based approaches combine the time series VIs and crop growth stages from historical years with the current observations to estimate crop growth stages. The curve-based approaches are capable of a short-term prediction. The trend-based approaches detect upward or downward trends from time series and confirm the trends using the increasing or decreasing momentum and VI thresholds. The trend-based approaches only use current observations. Both curve-based and trend-based approaches are promising in mapping crop growth stages timely. Nevertheless, mapping crop phenology near real-time is challenging since remote sensing observations are not always sensitive to crop growth stages. The accuracy of crop phenology detection depends on the frequency and availability of cloud-free observations within the growing season. Recent satellite datasets such as the harmonized Landsat and Sentinel-2 (HLS) are promising for mapping crop phenology within the season over large areas. Operational applications in the near future are feasible.

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Section: Discussionmentioning

confidence: 99%

Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities

2021

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“…This interval is shorter towards the poles where overlap between orbits increases. However, despite S2's short revisit time, effective phenology retrieval may still be hampered by significant cloud cover reducing the actual availability of valid observations ( Cheng et al 2020 ; Jönsson et al 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

Meroni

d’Andrimont

Vrieling

et al. 2021

Remote Sensing of Environment

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105

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“…For analysis ii (remote sensing analysis ii), since a greater spatial resolution was necessary, the PlanetScope satellite constellation was used. This constellation is composed of more than 150 nanosatellites (CubeSats) 45 , most of which have a synchronous orbit with the sun 46 .…”

Section: Methodsmentioning

confidence: 99%

Impact of soil water regimes and partial root-zone drying in field-grown papaya in semi-arid conditions

Santos

Coelho

Oliveira

et al. 2021

Sci Rep

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This study aimed to evaluate in the papaya Tainung genotype, the effects of partial root-zone drying (PRD) technique on soil water regimes by using different frequencies of shifting irrigation-side of plant row and the effects of PRD technique on (1) crop agronomic performance, (2) titratable fruit acidity (TA), (3) total soluble solids (TSS), and TSS/TA ratio. Also, we analyze the spatial dynamic of papaya condition using normalized difference vegetation index (NDVI) from different satellite images. The study was conducted in the semi-arid region of Bahia (BA) and Minas Gerais (MG), Brazil. The combination of 100% (Full irrigation—FU), 50%, and 35% in the irrigation depth (WID) and frequencies of shifting plant-row side irrigation of 0 (Fixed Irrigation—FX), 7, 14, and 21 days were applied. Nine treatments were studied in BA and five in MG. The water available in the soil was reduced to 44% for frequencies of shifting plant-row side irrigation of 7 days, 50% for 14 days, and 85% for 21 days, compared to the soil water availability at field capacity. Partial water deficit in the soil through the PRD technique did not significantly reduce the total root length, effective root depth, and root effective horizontal distance of the papaya Tainung genotype. However, PRD treatments showed leaf abscission, which resulted in reduced leaf area and NDVI values, especially in the MG experiment. Papaya yield and fruit quality were not affected. However, except for PRD 21 35%, irrigation water depth reduced to 50 and 35% under PRD increased crop water productivity (CWP) in papaya plants. Thus, the PRD technique may save 35% of WID using the alternation of lateral shift irrigation of crop row every 7 days under water scarcity in semi-arid regions. The NDVI index was important to compare the papaya canopy vigor between the experimental areas studied. We also confirmed the potential of NDVI to monitor the vigor of papaya canopy, since we could notice the sensibility of NDVI to identify water stress in papaya in higher vapor pressure deficit (VPD) conditions occurred in October 2016 and January 2017 in Bom Jesus da Lapa-BA. Therefore, the PRD strategy can be a useful tool to save water in papaya cultivation under semi-arid conditions.

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Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2

Cited by 112 publications

References 95 publications

Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities

Mapping Crop Phenology in Near Real-Time Using Satellite Remote Sensing: Challenges and Opportunities

Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

Impact of soil water regimes and partial root-zone drying in field-grown papaya in semi-arid conditions

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