Landsat-TM slika je obrađena upotrebom SAGA GIS programa za testiranje indeksa vegetacije na osnovu udaljenosti u poljoprivrednim kartama: 4 pristupa indeksa vertikalne vegetacije (PVI) i 2 indeksa vegetacije TSAVI prilagođenog pristupa. PVI vegetacije sa linije zemljišta (podloge) ukazivao je na zdravstvenu ispravnost kao indeks lisne površine (LAI). Refleksija vegetacije ima linearni odnos sa linijom pozadine. Četiri PVI modela i dva TSAVI pokazala su koeficijente determinacije sa LAI. Podaci pokazuju varijacije u izračunatim koeficijentima. Način u histogramima PVI zasnovan na 4 različita algoritma pokazuje razliku: -7,1, -8,36, 2,78 i 7,0. Skup podataka za 2 pristupa TSAVI: prvi slučaj kreće se u rasponu od 4.4 do 80.6 sa histogramom u obliku zvona (od 8.09 do 23.29) za prvi algoritam i nepravilnim oblikom za drugi algoritam sa nekoliko načina (0,11 do 0,2) i opadajućim do 0,26. SAGA GIS program prikazuje vrednosti PVI i TSAVI izračunavanjem NDVI na osnovu preseka podataka vegetacije i pozadine podloge (zemljišta). Upotrebom podataka NIR i R, urađena je linearna regresija pomoću jednačine ugrađene u SAGA GIS. Prednosti PVI i TSAVI sastoje se u prilagođenom položaju piksela na liniji osvetljenja zemljišta što poboljšava u odnosu na VI na temelju nagiba. U radu je prikazana primjena SAGA GIS programa u poljoprivrednim studijama.
Landsat-TM of 2001 covering Iceland (15.5°W-21°W, 64.5°N-67°N) was processed using SAGA GIS for testing distance-based Vegetation Indices (VIs): four approaches of Perpendicular Vegetation Index (PVI) and two approaches of Transformed Soil Adjusted Vegetation Index TSAVI. The PVI of vegetation from the soil background line indicated healthiness as a leaf area index (LAI). The results showed that the reflectance for vegetation has a linear relation with soil background line. Four PVI models and two TSAVI shown coefficients of determination with LAI. The dataset demonstrate variations in the calculated coefficients. The mode in the histograms of the PVI based on four different algorithms show the difference: -7.1, -8.36, 2.78 and 7.0. The dataset for the two approaches of TSAVI: first case ranges in 4.4.-80.6 with a bell- shape mode of a histogram (8.09 to 23.29) for the first algorithm and an irregular shape for the second algorithm with several modes starting from 0.11 to 0.2 and decreasing to 0.26. SAGA GIS permits the calculation of PVI and TSAVI by computed NDVI based on the intersection of vegetation and soil background. Masking the NIR and R, a linear regression of grids was performed using an equation embedded in SAGA GIS. The advantages of the distance-based PVI and TSAVI consists in the adjusted position of pixels on the soil brightness line which refines it comparing to the slope-based VIs. The paper demonstrates SAGA GIS application in agricultural studies.
Lemenkova, P. (2021). Distance-based vegetation indices computed by SAGA GIS: A comparison of the perpendicular and transformed soil adjusted approaches for the LANDSAT TM image. POLJOPRIVREDNA TEHNIKA, 46(3), 49-60 [10.5937/poljteh2103049l].
Distance-based vegetation indices computed by SAGA GIS: A comparison of the perpendicular and transformed soil adjusted approaches for the LANDSAT TM image
Lemenkova, Polina
Primo
2021
Abstract
Landsat-TM of 2001 covering Iceland (15.5°W-21°W, 64.5°N-67°N) was processed using SAGA GIS for testing distance-based Vegetation Indices (VIs): four approaches of Perpendicular Vegetation Index (PVI) and two approaches of Transformed Soil Adjusted Vegetation Index TSAVI. The PVI of vegetation from the soil background line indicated healthiness as a leaf area index (LAI). The results showed that the reflectance for vegetation has a linear relation with soil background line. Four PVI models and two TSAVI shown coefficients of determination with LAI. The dataset demonstrate variations in the calculated coefficients. The mode in the histograms of the PVI based on four different algorithms show the difference: -7.1, -8.36, 2.78 and 7.0. The dataset for the two approaches of TSAVI: first case ranges in 4.4.-80.6 with a bell- shape mode of a histogram (8.09 to 23.29) for the first algorithm and an irregular shape for the second algorithm with several modes starting from 0.11 to 0.2 and decreasing to 0.26. SAGA GIS permits the calculation of PVI and TSAVI by computed NDVI based on the intersection of vegetation and soil background. Masking the NIR and R, a linear regression of grids was performed using an equation embedded in SAGA GIS. The advantages of the distance-based PVI and TSAVI consists in the adjusted position of pixels on the soil brightness line which refines it comparing to the slope-based VIs. The paper demonstrates SAGA GIS application in agricultural studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
