Landsat:FIA (Mask less) Map Accuracy

Map accuracy/agreement assessment following the Riemann et. al. framework.

Description

Map accuracy assessment for Landsat models trained directly on FIA plot data for the years 2013-2019. A less aggressive lcmap mask (also applied in LiDAR-AGB v0.0.4) was applied to the modeled surfaces before conducting this assessment.

Model Document

Riemann et. al.

Branch used to produce this document: lj_landsat-fia-0.0.4-mask

FIA plot inclusion criteria

• All subplots must be sampled.
• Annual assessment vs pooled assessment:
  • For an annual assessment: only FIA plots sampled in the designated year were considered, and compared to the modeled AGB surface for said year.
  • For a pooled assessment: FIA plots inventoried in all years (2013-2019) were aggregated within each hex. Modeled values were extracted from each annual surface to match the inventory year for a particular FIA plot, but aggregated within each hex just the same.

Masking

LCMAP Collection 1.1. primary classification layers were used to mask out water, developed, and barren areas i.e. “!class %in% c(1, 5, 8)” pixels from the modeled AGB surfaces. Annual AGB surfaces were matched to the LMCAP layer from the same year.

NOTE: Masked AGB pixels are set to 0, and included in the agreement assessment just as any other AGB pixel.

Masked classes:

• 1: Developed
• 5: Water
• 8: Barren

Agreement Statistics (SI corrected)

Table 1: Plot:Pixel Comparison

Group	n	PPH	Mean FIA	MBE	RMSE	MAE	R2	KS	AC	ACs	ACu
target_2013	680	NA	76.71	2.01	43.30	30.35	0.69	0.23	0.57	0.94	0.63
target_2014	661	NA	79.69	1.45	46.46	31.63	0.68	0.26	0.54	0.92	0.61
target_2015	651	NA	75.06	2.55	42.89	29.97	0.72	0.26	0.61	0.93	0.68
target_2016	627	NA	80.54	0.14	44.20	30.94	0.70	0.24	0.56	0.93	0.63
target_2017	608	NA	81.51	-1.79	47.56	32.66	0.71	0.26	0.57	0.91	0.66
target_2018	601	NA	77.51	0.91	43.60	30.16	0.70	0.28	0.57	0.94	0.64
target_2019	595	NA	80.97	-1.79	43.05	29.85	0.74	0.27	0.63	0.92	0.70
pooled	4423	NA	78.80	0.56	44.47	30.79	0.70	0.26	0.57	0.93	0.64

Table 2: 8660 Ha Hex

Group	n	PPH	Mean FIA	MBE	RMSE	MAE	R2	KS	AC	ACs	ACu
target_2013	645	1.05	76.51	2.13	43.47	30.44	0.68	0.22	0.56	0.94	0.62
target_2014	617	1.07	78.24	2.04	44.70	30.75	0.69	0.25	0.56	0.93	0.63
target_2015	574	1.13	74.87	3.14	41.36	28.96	0.72	0.25	0.62	0.94	0.68
target_2016	564	1.11	79.54	0.59	43.17	30.00	0.71	0.24	0.57	0.93	0.64
target_2017	568	1.07	82.36	-1.96	47.07	32.24	0.71	0.25	0.57	0.91	0.66
target_2018	551	1.09	77.10	1.05	42.33	29.57	0.71	0.29	0.59	0.94	0.65
target_2019	520	1.14	81.27	-2.43	42.07	29.47	0.75	0.25	0.63	0.92	0.71
pooled	1502	2.94	77.26	0.93	29.80	21.34	0.76	0.12	0.68	0.96	0.72

Table 3: 78100 Ha Hex

Group	n	PPH	Mean FIA	MBE	RMSE	MAE	R2	KS	AC	ACs	ACu
target_2013	190	3.58	71.43	2.33	25.06	18.60	0.76	0.08	0.72	0.98	0.74
target_2014	184	3.59	75.98	2.59	26.66	18.83	0.78	0.11	0.73	0.96	0.77
target_2015	184	3.54	70.38	3.44	26.22	19.39	0.75	0.10	0.70	0.96	0.74
target_2016	180	3.48	79.06	-0.37	29.73	20.53	0.77	0.09	0.65	0.92	0.73
target_2017	182	3.34	79.84	-2.84	30.30	22.19	0.79	0.12	0.71	0.94	0.77
target_2018	186	3.23	76.60	-0.07	29.88	20.85	0.73	0.10	0.61	0.94	0.67
target_2019	179	3.32	80.30	-1.77	29.81	21.09	0.75	0.10	0.68	0.96	0.72
pooled	205	21.58	72.37	2.37	16.08	10.66	0.86	0.06	0.85	0.99	0.86

Table 4: 216500 Ha Hex

Group	n	PPH	Mean FIA	MBE	RMSE	MAE	R2	KS	AC	ACs	ACu
target_2013	80	8.50	67.69	1.30	17.68	11.91	0.83	0.08	0.82	1.00	0.82
target_2014	75	8.81	74.61	1.77	18.96	14.30	0.84	0.09	0.80	0.97	0.83
target_2015	77	8.45	69.17	2.16	19.20	12.87	0.77	0.12	0.74	0.99	0.75
target_2016	77	8.14	75.22	1.02	15.77	11.54	0.90	0.10	0.87	0.97	0.90
target_2017	74	8.22	78.20	-2.00	15.71	12.42	0.90	0.11	0.88	0.97	0.90
target_2018	77	7.81	70.36	3.37	21.36	14.98	0.76	0.13	0.75	0.99	0.76
target_2019	76	7.83	78.07	-1.03	22.99	16.55	0.78	0.11	0.71	0.96	0.75
pooled	85	52.04	70.34	2.29	12.24	8.46	0.90	0.07	0.89	0.98	0.91

ECDF Comparisons Across Scales - FIA Plots vs Mapped (SI corrected)

1:1 and GMFR Lines Across Scales - FIA Plots vs Mapped (SI corrected)

Spatial/Distribution Patterns of Local Differences (SI Corrected)

Target 2013 Distribution

Target 2016 Distribution

Target 2019 Distribution

Pooled Distribution

Spatial Differences

Patterns of Local Variability (SI Corrected)