Abstract
In this study, the split window (SW) method was applied for land surface temperature (LST) retrieval using Landsat 8 in two apple orchards (Glindow, Altlandsberg). Four images were acquired during high demand of irrigation water from July to August 2018. After pre-processing images, the normalized difference vegetation index (NDVI) and LST were calculated by red, NIR, and thermal bands. The results were validated by interpolated infrared thermometer (IRT) measurements using the inverse distance weighting (IDW) method. In the next step, the temperature vegetation index (TVDI) was calculated based on the trapezoidal NDVI/LST space to determine the water status of apple trees in the case studies. Results show good agreement between interpolated LST using IRT measurements and remotely sensed LST calculation using SW in all satellite overpasses, where the absolute mean error was between 0.08 to 4.00 K and root mean square error (RMSE) values ranged between 0.71 and 4.23 K. The TVDI spatial distribution indicated that the trees suffered from water stress on 7 and 23 July and 8 August 2018 in Glindow apple orchard with the mean value of 0.69, 0.57, and 0.73, whereas in the Altlandsberg orchard on 17 August, the irrigation system compensated the water deficit as indicated by the TVDI value of 0.34. Moreover, a negative correlation between TVDI and vegetation water content (VWC) with correlation coefficient (r) of −0.81 was observed. The corresponding r for LST and VWC was equal to −0.89, which shows the inverse relation between water status and temperature-based indices. The results indicate that the LST and/or TVDI calculation using the proposed methods can be effectively applied for monitoring tree water status and support irrigation management in orchards using Landsat 8 satellite images without requiring ground measurements.
Highlights
Tree water status and the determination of appropriate irrigation measure can be supported by digital plant data as suggested in the context of precision horticulture [1,2]
Increased leaf temperature and decreased vegetation water content (VWC) are signs of water stress monitored with thermal imaging [16] that can be implemented in the orchard by crane, tractor, and unmanned aerial vehicle (UAV)
“surface” means whatever is seen from the atmosphere on the surface of the earth, e.g., in an apple orchard, the tree canopy is considered as a surface, ergo the land surface temperature (LST) equals predominantly to the leaf surface temperature
Summary
Tree water status and the determination of appropriate irrigation measure can be supported by digital plant data as suggested in the context of precision horticulture [1,2]. The scatter plot of these remotely sensed indices (NDVI and LST) resulted in a trapezoidal space, which has a physical concept i.e., the spatial relation (trapezoidal space) between LST and NDVI is applied to monitor the water status of crops and orchards using temperature vegetation dryness index (TVDI) [28,29]. Many further studies applying satellite imagery for water status estimation based on land surface temperature (LST) were carried out in field crops, the application in orchards is still in its infancy. The present study was aimed at proposing a method for TVDI estimation based on partly mixed pixels in orchard conditions by means of (i) selecting an interpolation method for gaining spatial distribution data of LST based on infrared thermometer (IRT) measurements and approaching the SW method using Landsat 8 images. (ii) validate the results with ground reference measurements, and (iii) estimating TVDI considering the VWC
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