OpenLand (version 1.0.5)

intensityAnalysis: Performs the intensity analysis based on cross-tabulation matrices of each time step

Description

This function implements an Intensity Analysis (IA) according to Aldwaik & Pontius (2012), a quantitative method to analyze time series of land use and cover (LUC) maps. For IA, a cross-tabulation matrix is composed for each LUC transition step in time.

Usage

intensityAnalysis(dataset, category_n, category_m, area_km2 = TRUE)

Value

Intensity object

Arguments

dataset

list. The result object from contingencyTable.

category_n

character. The gaining category in the transition of interest (n).

category_m

character. The losing category in the transition of interest (m).

area_km2

logical. If TRUE the change is computed in km2, if FALSE in pixel counts.

Details

IA includes three levels of analysis of LUC changes. Consecutive analysis levels detail hereby information given by the previous analysis level (Aldwaik and Pontius, 2012, 2013).

1. The interval level examines how the size and speed of change vary across time intervals.

2. The category level examines how the size and intensity of gross losses and gross gains in each category vary across categories for each time interval.

3. The transition level examines how the size and intensity of a category’s transitions vary across the other categories that are available for that transition.

At each analysis level, the method tests for stationarity of patterns across time intervals.

The function returns a list with 6 objects:

1. lulc_table: tibble. Contingency table of LUC transitions at all analysed time steps, containing 6 columns:

   1. Period: <fct>. Evaluated period of transition in the format year t - year t+1.

   2. From: <fct>. The category in year t.

   3. To: <fct>. The category in year t+1.

   4. km2: <dbl>. Area in square kilometers that transited from the category From. to the category To in the period.

   5. QtPixel: <int>. Number of pixels that transited from. the category From to the category To in the period.

   6. Interval: <int>. Interval in years of the evaluated period.

2. lv1_tbl: An Interval object containing the St and U values.

3. category_lvlGain: A Category object containing the gain of the LUC category in a period (Gtj).

4. category_lvlLoss: A Category object containing the loss of the LUC category in a period (Lti).

5. transition_lvlGain_n: A Transition object containing the annualized rate of gain in category n (Rtin) and the respective Uniform Intensity (Wtn).

6. transition_lvlLoss_m: A Transition object containing the annualized rate of loss in category m (Qtmj) and the respective Uniform Intensity (Vtm).

References

Aldwaik, S. Z. and Pontius, R. G. (2012) ‘Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition, Landscape and Urban Planning. Elsevier B.V., 106(1), pp. 103–114. tools:::Rd_expr_doi("10.1016/j.landurbplan.2012.02.010").

Aldwaik, S. Z. and Pontius, R. G. (2013) ‘Map errors that could account for deviations from a uniform intensity of land change, International Journal of Geographical Information Science. Taylor & Francis, 27(9), pp. 1717–1739. tools:::Rd_expr_doi("10.1080/13658816.2013.787618").

Examples

# editing the category name

SL_2002_2014$tb_legend$categoryName <- factor(
  c(
    "Ap", "FF", "SA", "SG", "aa", "SF",
    "Agua", "Iu", "Ac", "R", "Im"
  ),
  levels = c(
    "FF", "SF", "SA", "SG", "aa", "Ap",
    "Ac", "Im", "Iu", "Agua", "R"
  )
)

SL_2002_2014$tb_legend$color <- c(
  "#FFE4B5", "#228B22", "#00FF00", "#CAFF70",
  "#EE6363", "#00CD00", "#436EEE", "#FFAEB9",
  "#FFA54F", "#68228B", "#636363"
)

intensityAnalysis(dataset = SL_2002_2014, category_n = "Ap", category_m = "SG", area_km2 = TRUE)