Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk

Möller, Markus; Gerstmann, Henning; Gao, Feng; Dahms, Thorsten; Förster, Michael

doi:10.1016/j.catena.2016.11.016

Cited by 41 publications

(9 citation statements)

References 83 publications

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“…Remote sensing medium resolution imagery has shown a great capacity to quantify damages in crop lands. The satellites MODIS and Landsat have been widely used [12][13][14], but Sentinel-2, especially for its finer resolution, constitutes a major asset for this kind of application [15,16]. However, due to the types of damages that affect the majority of the crops, satellite resolutions are still too coarse.…”

Section: Introductionmentioning

confidence: 99%

Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Mediterranean Rice Crops Caused by Western Swamphen (Porphyrio porphyrio)

Pla

Bota

Duane

et al. 2019

Drones

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Making agricultural production compatible with the conservation of biological diversity is a priority in areas in which human–wildlife conflicts arise. The threatened Western Swamphen (Porphyrio porphyrio) feeds on rice, inducing crop damage and leading to decreases in rice production. Due to the Swamphen protection status, economic compensation policies have been put in place to compensate farmers for these damages, thus requiring an accurate, quantitative, and cost-effective evaluation of rice crop losses over large territories. We used information captured from a UAV (Unmanned Aerial Vehicle) equipped with a multispectral Parrot SEQUOIA camera as ground-truth information to calibrate Sentinel-2 imagery to quantify damages in the region of Ebro Delta, western Mediterranean. UAV vegetation index NDVI (Normalized Difference Vegetation Index) allowed estimation of damages in rice crops at 10 cm pixel resolution by discriminating no-green vegetation pixels. Once co-registered with Sentinel grid, we predicted the UAV damage proportion at a 10 m resolution as a function of Sentinel-2 NDVI, and then we extrapolated the fitted model to the whole Sentinel-2 Ebro Delta image. Finally, the damage predicted with Sentinel-2 data was quantified at the agricultural plot level and validated with field information compiled on the ground by Rangers Service. We found that Sentinel2-NDVI data explained up to 57% of damage reported with UAV. The final validation with Rangers Service data pointed out some limitations in our procedure that leads the way to improving future development. Sentinel2 imagery calibrated with UAV information proved to be a viable and cost-efficient alternative to quantify damages in rice crops at large scales.

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Section: Introductionmentioning

confidence: 99%

Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Mediterranean Rice Crops Caused by Western Swamphen (Porphyrio porphyrio)

Pla

Bota

Duane

et al. 2019

Drones

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“…To this end, the derivation of indicators based on the analysis of multi-(three or more images) or hyper-temporal imagery (e.g., images for one or many years; [105]) may be useful. Multior hyper-temporal image data can be obtained from satellite image archives [142] or be generated by applying data fusion algorithms [143]. Maynard and Levi [105] for example, were able to show that hyper-temporal time series of a vegetation index based on Landsat imagery enable typical and temporally stable spectral fingerprints to be derived, which significantly increased the prediction accuracy of soil texture.…”

Section: Pedologymentioning

confidence: 99%

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Lausch

Baade

Bannehr³

et al. 2019

Remote Sensing

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In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

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“…Remote sensing has the capacity to map and quantify plant productivity in different types of natural and anthropogenic influenced plant communities and land uses (Díaz‐Delgado et al, 2017 ). For several decades, various satellite platforms, as MODIS, Landsat, and other mid‐spatial‐resolution (tens of meters) satellites have been used to explore and map plant productivity and other vegetation characteristics at large scales (e.g., Möller et al, 2017 ). Recently, Sentinel‐2 (S2) has emerged as a major asset (Belgiu & Csillik, 2018 ; Inglada et al, 2015 ), basically for its medium spatial (10 m), high radiometric (13 spectral bands), and rapid temporal (revisit time of 5 days at the equator) resolutions, together with its free cost.…”

Section: Introductionmentioning

confidence: 99%

Comparative assessment of satellite‐ and drone‐based vegetation indices to predict arthropod biomass in shrub‐steppes

Traba

Gómez‐Catasús

Barrero

et al. 2022

Ecological Applications

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Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk

Cited by 41 publications

References 83 publications

Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Mediterranean Rice Crops Caused by Western Swamphen (Porphyrio porphyrio)

Calibrating Sentinel-2 Imagery with Multispectral UAV Derived Information to Quantify Damages in Mediterranean Rice Crops Caused by Western Swamphen (Porphyrio porphyrio)

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Comparative assessment of satellite‐ and drone‐based vegetation indices to predict arthropod biomass in shrub‐steppes

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