A Novel Spectral Index to Identify Cacti in the Sonoran Desert at Multiple Scales Using Multi-Sensor Hyperspectral Data Acquisitions

Abstract

Accurate identification of cacti, whether seen as an indicator of ecosystem health or an invasive menace, is important. Technological improvements in hyperspectral remote sensing systems with high spatial resolutions make it possible to now monitor cacti around the world. Cacti produce a unique spectral signature because of their morphological and anatomical characteristics. We demonstrate in this paper that we can leverage a reflectance dip around 972 nm, due to cacti’s morphological structure, to distinguish cacti vegetation from non-cacti vegetation in a desert landscape. We also show the ability to calculate two normalized vegetation indices that highlight cacti. Furthermore, we explore the impacts of spatial resolution by presenting spectral signatures from cacti samples taken with a handheld field spectroradiometer, drone-based hyperspectral sensor, and aerial hyperspectral sensor. These cacti indices will help measure baseline levels of cacti around the world and examine changes due to climate, disturbance, and management influences.

Multi-Temporal LiDAR and Hyperspectral Data Fusion for Classification of Semi-Arid Woody Cover Species

“…We used photochemical reflectance indices (PRI) 1 and 2 to assess short term changes in photosynthetic activity with their sensitivities to xanthophyll cycle pigment de-epoxidation state and photosynthetic efficiency [70][71][72][73]. CACTI 1 and 2 were indices developed to identify cacti vegetation using near-infrared signals and water absorption in larger landscapes using hyperspectral bands [74]. The MERIS Terrestrial Chlorophyll Index (MTCI) estimates chlorophyll content with a sensitivity to the red edge position by utilizing reflectance ratio within the wavelength range of 650-700 nm [75,76].…”

A Novel Algorithm for Classifying Vegetation and Non-Vegetation Using Red Edge Slope Coefficient with Hyperspectral LCTF Imaging

“…Hyperspectral imaging, a rapidly evolving technique, furnishes exhaustive information on Earth's surface reflectance over an extensive spectrum of wavelengths [6]. This imaging modality has already proven indispensable in botany and plant sciences for reliably detecting and identifying plant stress diseases and quantifying their severity [7][8][9][10], as well as facilitating the precise classification of plant species [7,[11][12][13][14] and charting their distribution [15][16][17][18]. The high spatial and spectral resolution of hyperspectral data is increasingly vital for advancing these fields.…”