# _remote sensing_
## 2 Materials and Methods
### Crop Diseases Detection Methods
#### 2.2.1 Orchards Diseases Detection
Psa was detected in New Zealand for the first time in November 2010, in several kiwifruit orchards of the North Island, i.e., 92 orchards, mainly in the regions of Hawke's Bay and Bay of Plenty. Disease spread continued during the first semester of 2011 (170 orchards affected) across a wide area (Te Puke, Bay of Plenty, Matapiih) [46]. For our analysis, a total of 50 RapidEye satellite images (five spectral channels in the VNIR spectral range) were processed for the period March 2010-October 2012 and July-October 2019, to cover different validated outbreaks and phenology stages of the fields of interest. RapidEye Level 3A images (radiometrically and geometrically corrected) have the following characteristics: five bands (blue, green, red, red edge, near-infrared) with 5 m of spatial resolution. The following vegetation indices (VI) were applied to the RapidEye data set: Simple ratio (SR), the Normalized difference vegetative index (NDVI), Green NDVI (G-NDVI), Red-edge NDVI (ReNDVI), Modified red-edge NDVI (MRe-NDVI), Enhanced vegetative index (EVI), Enhanced vegetative index 2 (EVI2), Photosynthetic vigor ratio (PVR), Green chlorophyll index (GCI), Red-edge chlorophyll index (ReCI), Triangular vegetative index (TVI), and the MERIS terrestrial chlorophyll index (MTCI). Additional indexes were applied to Sentinel-2 images, taking advantage of the 13 spectral channels in the VSWIR spectral range. The new set of vegetation indices includes: Leaf Chlorophyll Index (LCI), Tasseled Cap-Green Vegetation Index (TCGVI), Green atmospherically resistant vegetation index (GARVI), Structure Intensive Pigment Index 1 (SIPI1), Structure Intensive Pigment Index 2 (SIPI2), Modified Chlorophyll Absorption in Reflectance Index (modCARI), Atmospheric Resistant Vegetation Index (ARVI), and the Optimized Soil Adjusted Vegetation Index (OSAVI). Finally, the use of PRISMA hyperspectral satellite data (having 30 m spatial resolution) allowed the definition of a larger set of indices peculiar to an hyperspectral imagery: NDRE, modNDRE, PSSR-1, PSSR-2, PSND-1, PSND-2, PSRI, CARI, CRI-1, CRI-2, NDLI, MDNI, RVSI, NDVI-750, mNDVI-750, VOG-1, VOG-2, GM-1, GM-2, LIC-1, and MTVI-2. The list and details of all indices can be found at [[https://www.indexdatabase.de/db/i.php?offset=1](https://www.indexdatabase.de/db/i.php?offset=1)]([https://www.indexdatabase.de/db/i.php?offset=1](https://www.indexdatabase.de/db/i.php?offset=1)) (accessed on 15 May 2020). Moreover, for this study, 400 fields were digitized through visual interpretation (Figure 3A) from the Te Puke area, setting randomly selected sub-samples of 60% of the fields for training, 20% for validation, and 20% for testing the network. The Levenberg-Marquardt back-propagation function was used for the training process, and the error estimation was computed by minimum squares. In the second phase of the study, an additional 250 blocks located in the Takaka region were included (Figure 3B), using the same subset percentages of blocks for training, validation, and testing as in the Te Puke region. As it was described in the statistics provided by KVH (Kiwifruit Vine Health Inc.) for December 2019, in the Te Puke region 99% of the orchards had been identified to be affected by Psa, while in the South Island (where the Takaka area is located), no cases of Psa were detected. Therefore, this dataset provided potentially good samples for training and validation of the NNs. The VIs extracted from RapidEye and Sentinel-2 images were fed into the NNs, taking into account the list of indices processed in the previous analysis for the period 2010-2012, i.e., SR, NDVI, G-NDVI, ReNDVI, MReNDVI, EVI, EVI2, PVR, GCI, ReCI, TVI, and MTCI, which can be summarized by their statistics (Minimum, Maximum, Mean, and Standard Deviation). To improve the performance, an additional set of VIs were added to the previous ones extracted from Sentinel-2 images. The new set of vegetation indices included in the input to the NN were: LCI, TCGVI, GARVI, SIPII, SIPI2, MCARI, ARVI and OSAVI.