calculate_temporal_trend

Internal function to calculate pixel-wise temporal trends.

internal

A comprehensive toolkit for geospatiotemporal analysis
featuring 60+ vegetation indices, advanced raster visualization,
universal spatial mapping, water quality analysis, CDL crop analysis,
spatial interpolation, temporal analysis, and terrain analysis.
Designed for agricultural research, environmental monitoring, remote
sensing applications, and publication-quality mapping with support for
any geographic region and robust error handling. Methods include
vegetation indices calculations (Rouse et al. 1974), NDVI and enhanced
vegetation indices (Huete et al. 1997)
<doi:10.1016/S0034-4257(97)00104-1>, (Akanbi et al. 2024)
<doi:10.1007/s41651-023-00164-y>, spatial interpolation techniques
(Cressie 1993, ISBN:9780471002556), water quality indices (McFeeters
1996) <doi:10.1080/01431169608948714>, and crop data layer analysis
(USDA NASS 2024)
<https://www.nass.usda.gov/Research_and_Science/Cropland/>. Funding:
This material is based upon financial support by the National Science
Foundation, EEC Division of Engineering Education and Centers, NSF
Engineering Research Center for Advancing Sustainable and Distributed
Fertilizer production (CASFER), NSF 20-553 Gen-4 Engineering Research
Centers award 2133576.

Olatunde Akanbi

geospatialsuite

Comprehensive Geospatiotemporal Analysis and Multimodal
Integration Toolkit

Olatunde D. Akanbi

Vibha Mandayam

Yinghui Wu

Jeffrey Yarus

Erika I. Barcelos

Roger H. French

calculate_temporal_trend function

<dl><dt>rasters</dt>
<dd>List of rasters</dd>
<dt>dates</dt>
<dd>Vector of dates</dd></dl>

Arguments

Calculate temporal trend using linear regression — calculate_temporal_trend

<dl>

<dt>rasters</dt>
<dd>List of rasters</dd>


<dt>dates</dt>
<dd>Vector of dates</dd>

</dl>

calculate_temporal_trend: Calculate temporal trend using linear regression

Description

Usage

Value

Arguments