Relationship between TIR and NIR-SWIR as Indicator of Vegetation Water Availability

Holzman, Mauro; Rivas, Raúl Eduardo; Bayala, Martín Ignacio

doi:10.3390/rs13173371

Cited by 23 publications

(6 citation statements)

References 56 publications

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“…The chlorophyll content of the crops was well represented by the B5 to B7 bands [38,39]. B11 and B12 bands were connected to the water content of plants and crops [40,41]. It has been established that these bands can distinguish between different types of agricultural crops [42].…”

Section: Datasets 221 Satellite Images For Classificationmentioning

confidence: 99%

Mapping Small-Scale Willow Crops and Their Health Status Using Sentinel-2 Images in Complex Agricultural Areas

Beygi Heidarlou,

Oprea-Sorescu,

Marcu

et al. 2024

Remote Sensing

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The goal of this study was to estimate the areas under willow cultivation by farmers, as well as their growth and health status. Due to the extremely small patch size of land cover types in the study area, Sentinel-2 data were used to conduct supervised classification based on the random forest machine learning technique, and a large training dataset was produced from PlanetScope satellite imagery. The results of image classification using Google Earth Engine indicated that the Sentinel data were suitable for identifying willow-cultivated areas. It was found that these areas declined from 875.32 ha in 2017 to 288.41 ha in 2022. The analysis of the growth and health conditions of willow-cultivated plots also revealed that the temporal variations in the NDVI in these plots decreased significantly in 2022 as compared to previous years (p < 0.05). An in-depth analysis revealed a significant positive correlation between NDVI, precipitation, and temperature. It was found that the most efficient components explaining the process of browning the vegetation in the planted willow plots were the increasing temperature and decreasing precipitation. This research may be used to document the national and global monitoring efforts for climate change adaptation.

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Section: Datasets 221 Satellite Images For Classificationmentioning

confidence: 99%

Mapping Small-Scale Willow Crops and Their Health Status Using Sentinel-2 Images in Complex Agricultural Areas

Beygi Heidarlou,

Oprea-Sorescu,

Marcu

et al. 2024

Remote Sensing

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“…The 945 nm wavelength region had the highest covariance, i.e., the highest overall reflectance intensity, and this is the reason why the algorithm selected and sorted it in the first round. Regarding the spectral slices selected in the second and third rounds, with the range between 1,600 and 2,500 nm, i.e., in the shortwave infrared (SWIR) domain, it is well-known that the reflectance in this region of the spectrum is strongly correlated with vegetation water content (Jopia et al, 2020;Holzman et al, 2021). However, the second round (2,190 nm) showed a baseline additive-type trend profile that reveals, as the first round, possible effects derived from the remote sensing spectral measurement.…”

Section: Spectral Slicesmentioning

confidence: 99%

Potential of N-CovSel for Variable Selection: A Case Study on Time-Series of Multispectral Images

et al. 2022

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Multispectral image time-series have been promising for some years; yet, the substantial advance of the technology involved, with unprecedented combinations of spatial, temporal, and spectral capabilities for remote sensing applications, raises new challenges, in particular, the need for methodologies that can process the different dimensions of satellite information. Considering that the multi-collinearity problem is present in remote sensing time-series, regression models are widespread tools to model multi-way data. This paper presents the results of the analysis of a high order data of Sentinel-2-time series, conducted in the framework of extreme weather event. A feature extraction method for multi-way data, N-CovSel was used to identify the most relevant features explaining the loss of yield in Mediterranean vineyards during the 2019 heatwave. Different regression models (uni-way and multi-way) from features extracted from the N-CovSel algorithm were calibrated based on available heat wave impact data for 107 vineyard blocks in the Languedoc-Roussillon region and multispectral time-series predictor data for the period May to August. The performance of the models was evaluated by the r2 and the root mean square of error (RMSE) as follows: for the temporal N-PLS model (r2 = 0.62—RMSE = 11%), for the spatial N-PLS model (r2 = 0.61—RMSE = 12%) and the temporal-spectral PLS model (r2 = 0.63—RMSE = 11%). The results validated the effectiveness of the proposed N-CovSel algorithm in order to reduce the number of total variables and restricting it to the most significant ones. The N-CovSel algorithm seems to be a suitable choice to interpret complex multispectral imagery by temporally discriminating the most appropriate spectral information.

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“…The SWIR band has the characteristics of penetrating clouds, fog, and high sensitivity (Chen et al, 2019). Modified soil line and combination of SWIR, NIR, or Red bands can reduce VI sensitivity to soil background (Feng et al, 2011b;Holzman et al, 2021).…”

Section: Joining Of Swir Bandmentioning

confidence: 99%

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

Liu¹,

Yuanyuan²,

Zhou³

et al. 2022

Revista Brasileira De Ciência Do Solo

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Soil moisture (SM) plays an important role in regulating the global water cycle, especially in arid areas, and is one of the main indicators of ecological environmental health. Although traditional methods can accurately measure SM at a single sample site, they are limited in large-scale and dynamic SM monitoring. Therefore, we used the Landsat images as the data source and the soil adjusted vegetation index (SAVI) to build the adjusted SAVI (aSAVI) index by modifying the soil adjustment parameter L and introducing the short-wave infrared band. According to the theory of temperature vegetation dryness index (TVDI) and feature space, we introduced a model, combined the measured SM data (Minqin Basin, China) through a comparative analysis of four vegetation indices (NDVI, SAVI, MSAVI, aSAVI) determine the optimal model. Taking the Minqin Basin as the study area, the spatiotemporal variation characteristics of SM in three sub-regions (the entire study area, irrigated region, and periphery of the irrigated regions) were quantitatively analyzed and compared in four different periods: pre-Comprehensive Treatment Program of the Shiyang River Basin (pre-CTSRB) (2000)(2001)(2002)(2003)(2004)(2005), CTSRB I (2006-2010), CTSRB II (2011-2016), and CTSRB-end (2017-2021) to evaluate the ecological restoration effects of treatment programs from the SM perspective. The results showed that: 1) SM values derived from TVDI inversion and the aSAVI were more accurate, and the model sensitivity decreased with soil depth; 2) the mean value of SM fluctuated across the four periods but decreased slightly over the entire time series. The spatial variations of the SM were characterized by a "descending then ascending" trend. Soil moisture increased in 21.35 % of areas at 0.00-0.10 m in the past 22 years, and 59.66 % at 0.10-0.20 m. There was a negative correlation between the mean variation trend of SM and the percentage of area where SM fell in different periods; 3) the treatment program positively affected the ecological restoration of the Minqin Basin from the SM perspective. The area where SM increased was larger than that of decreasing SM, especially in 0.10-0.20 m soil layer. The increase can promote growth and confer resistance to desertification.

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Relationship between TIR and NIR-SWIR as Indicator of Vegetation Water Availability

Cited by 23 publications

References 56 publications

Mapping Small-Scale Willow Crops and Their Health Status Using Sentinel-2 Images in Complex Agricultural Areas

Mapping Small-Scale Willow Crops and Their Health Status Using Sentinel-2 Images in Complex Agricultural Areas

Potential of N-CovSel for Variable Selection: A Case Study on Time-Series of Multispectral Images

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

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