Estimation of soil and crop residue parameters using AVIRIS-NG hyperspectral data. Issue 6 (19th March 2023)
- Record Type:
- Journal Article
- Title:
- Estimation of soil and crop residue parameters using AVIRIS-NG hyperspectral data. Issue 6 (19th March 2023)
- Main Title:
- Estimation of soil and crop residue parameters using AVIRIS-NG hyperspectral data
- Authors:
- Majeed, Israr
Purushothaman, Naveen K.
Chakraborty, Poulamee
Panigrahi, Niranjan
Vasava, Hitesh B.
Das, Bhabani S. - Abstract:
- ABSTRACT: Detailed ground cover information and efficient modelling approaches are needed for estimating soil properties from hyperspectral remote sensing (HRS) data. With the objective to estimate both soil and crop residue (CR) parameters using HRS data from the airborne visible-infrared imaging spectrometer-next generation (AVIRIS-NG) sensor, soil and CR samples were collected from 101 locations in the Western Catchment of Chilika lagoon, India. Nonlinear unmixing and two chemometric models were examined for estimating basic soil properties, nutrient contents, soil and CR wetness, and masses of fresh crop residue (FCR) and dry crop residue (DCR). Both soil and CR parameters showed wide variation with FCR and DCR masses varying from 0 to 13.33 Mg ha −1 and 0 to 10.16 Mg ha −1, respectively. Soils were relatively dry with an average gravimetric water content (θg ) of 14% whereas CR moisture content (θc ) ranged from 2.4 to 93%. Estimated coefficient of determination (R 2 ) values in the validation datasets varied from 0.51 for soil base saturation to 0.91 for exchangeable Mg +2 using soil spectra obtained through linear polynomial unmixing of AVIRIS-NG spectra. The R 2 values were more than 0.70 for clay content, soil organic carbon (SOC), cation exchange capacity (CEC), and several exchangeable cations although the CR parameters showed lower R 2 values than soil parameters. With the chemometric models calibrated, high spatial resolution maps for soil and CR parameters wereABSTRACT: Detailed ground cover information and efficient modelling approaches are needed for estimating soil properties from hyperspectral remote sensing (HRS) data. With the objective to estimate both soil and crop residue (CR) parameters using HRS data from the airborne visible-infrared imaging spectrometer-next generation (AVIRIS-NG) sensor, soil and CR samples were collected from 101 locations in the Western Catchment of Chilika lagoon, India. Nonlinear unmixing and two chemometric models were examined for estimating basic soil properties, nutrient contents, soil and CR wetness, and masses of fresh crop residue (FCR) and dry crop residue (DCR). Both soil and CR parameters showed wide variation with FCR and DCR masses varying from 0 to 13.33 Mg ha −1 and 0 to 10.16 Mg ha −1, respectively. Soils were relatively dry with an average gravimetric water content (θg ) of 14% whereas CR moisture content (θc ) ranged from 2.4 to 93%. Estimated coefficient of determination (R 2 ) values in the validation datasets varied from 0.51 for soil base saturation to 0.91 for exchangeable Mg +2 using soil spectra obtained through linear polynomial unmixing of AVIRIS-NG spectra. The R 2 values were more than 0.70 for clay content, soil organic carbon (SOC), cation exchange capacity (CEC), and several exchangeable cations although the CR parameters showed lower R 2 values than soil parameters. With the chemometric models calibrated, high spatial resolution maps for soil and CR parameters were generated, which offer a continuous mapping capability for such parameters. Extensive soil property data also allowed us to evaluate SOC sequestration capability of different land use systems. A critical value of 1/25 for the SOC/Clay content ratio was observed for most of our agricultural land uses and degraded landscapes showed lower SOC/Clay ratios. Thus, high spatial resolution soil and crop residue parameters may be accurately assessed for large areas with multiple land use and soil cover conditions. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 44:Issue 6(2023)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 44:Issue 6(2023)
- Issue Display:
- Volume 44, Issue 6 (2023)
- Year:
- 2023
- Volume:
- 44
- Issue:
- 6
- Issue Sort Value:
- 2023-0044-0006-0000
- Page Start:
- 2005
- Page End:
- 2038
- Publication Date:
- 2023-03-19
- Subjects:
- Hyperspectral imaging -- AVIRIS-NG -- linear polynomial unmixing -- soil and crop residues
Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2023.2195570 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 26788.xml