LAND USE AND LAND COVER MAPPING IN DETAILED SCALE: A CASE STUDY IN SANTA ROSA DE LIMA-SC

Macedo, Rodrigo de Campos; Schmitt Filho, Abdon Luiz Schmitt; Farley, Joshua C.; Fantini, Alfredo Celso; Cazella, Ademir Antonio; Sinisgalli, Paulo Antonio de Almeida

doi:10.1590/S1982-21702018000200015

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ARTICLE • Bol. Ciênc. Geod. 24 (2) • June 2018 • https://doi.org/10.1590/S1982-21702018000200015 copy

LAND USE AND LAND COVER MAPPING IN DETAILED SCALE: A CASE STUDY IN SANTA ROSA DE LIMA-SC

Mapeamento da cobertura e uso da terra em escala detalhada: um estudo de caso em Santa Rosa de Lima-SC

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract:

It is challenging to reconcile large scale data with the dynamic characteristics present in land use. Such dynamism requires data with a high repetition of sampling. An alternative is the integration of data of high spatial resolution and low temporal resolution, with that of high temporal resolution and low spatial resolution. The aim addressed in this article is related to the integration of aerial photographs and temporal series for land use and land cover mapping in high detail scale. We conducted a case study in Santa Rosa de Lima-SC. The main data used was the aerial survey that overlaid the state of Santa Catarina, executed in 2010/2011. The interpretation key included typical elements of photointerpretation (color, texture, size, shape), aiming to classify the land use and land cover classes. The mapping evaluation resulted in 75.6% global accuracy, ranging from 54% (Grassland and Wetlands) to 96% (Water Bodies and Rocks). Such results are considered satisfactory. The integration of high-resolution images with high temporal resolution data has enabled the discrimination between classes that present great difficulties of separability. Such discrimination is essential in the territorial management processes of Encosta da Serra and the municipality of Santa Rosa de Lima.

Keywords:
change detection; image interpretation; temporal series

Land cover classes
Levels
I	II	III
Non-vegetated areas	Water bodies	Water bodies
	Urban area	Urban area
	Rocky outcrop	Rocky outcrop
	Bare land	Bare land
Vegetation	Non-forest vegetation	Native non-forest vegetation
	Non-forest vegetation	Exotic non-forest vegetation
	Forest vegetation	Native forest
	Forest vegetation	Exotic forest vegetation
Land use classes
Levels
I	II	III
Water bodies	Water bodies	Water bodies
Urban use	Urban use	Urban use
Areas without significant anthropism	Rocky outcrop	Rocky outcrop
Areas without significant anthropism	Non significantly anthropic vegetation	Non significantly anthropic vegetation
Bare land	Bare land	Bare land
Anthropic vegetation	Anthropic grassland	Anthropic grassland
	Planted pasture	Planted pasture
	Silviculture	Silviculture
	Crops	Seasonal crops
		Permanent crops
		Agroecological mosaics
Land use and cover classes (combined subtitles)
Not applicable	Not applicable	Water bodies
		Urban area
		Rocky outcrop
		Bare land
		Native forest
		Silviculture
		Grassland vegetation and wetland areas
		Pastures
		Seasonal crops
		Permanent crops
Agroecological mosaics

Universidade Federal do Paraná Centro Politécnico, Jardim das Américas, 81531-990 Curitiba - Paraná - Brasil, Tel./Fax: (55 41) 3361-3637 - Curitiba - PR - Brazil
E-mail: bcg_editor@ufpr.br

Acompanhe os números deste periódico no seu leitor de RSS

[TFN1] Source: Based on Level III of Table 1.

Class	Color/Hue (RGB/CIR)	Texture	Dimension	Shape	Brightness	Seasonality	Variation related to management
Rocky outcrop	Grayish/Greenish	-	It tends to be small	It tends to be irregular	-	No	No
Water bodies	Black / Dark	It tends to be flat	It tends to be small	It tends to be irregular	It tends to be dark	No	No
Grassland	Light green / Light red	It tends to be slightly rough	-	Irregular	It tends to be light	Yes	No
Urban area	Magenta / Cyano	Rough	It tends to be small	-	It tends to be light	No	No
Forest	Dark green / Dark red	Rough	-	Irregular	It tends to be dark	No	No
Seasonal crop	Light green or orange / Light red or orange	It tends to be flat	-	It tends to be regular	It tends to be light	Yes	Yes
Agroecological mosaic	-	-	It tends to be small	-	-	-	-
Pastures	Light green or orange / Light red or orange	It tends to be flat	-	It tends to be irregular	It tends to be light	A little	A little
Permanent crop	It tends to be dark green / dark red	Rough	It tends to be small	It tends to be regular	It tends to be dark	A little	A little
Silviculture	Green / Red	Intermediate	-	-	It tends to be light	No	No
Exposed soil (bare land)	Orange or brownish / Orange or purple	Flat	It tends to be small	If erosion (irregular) / if soil prepare (regular)	It tends to be light	No	No

	W¹	U²	R³	B⁴	N⁵	S⁶	G⁷	P⁸	CS⁹	CP¹⁰	M¹¹	Total
W	48	0	1	0	1	0	0	0	0	0	0	50
U	0	47	1	2	0	0	0	0	0	0	0	50
R	0	0	48	0	0	0	0	0	0	0	2	50
B	0	3	0	46	0	0	0	0	0	0	1	50
N	1	0	0	0	38	11	0	0	0	0	0	50
S	0	0	0	0	10	39	0	1	0	0	0	50
G	0	1	0	0	0	0	27	7	6	0	9	50
P	0	0	0	0	0	0	11	29	7	0	3	50
CS	0	0	0	5	0	0	8	3	28	0	6	50
CP	0	0	0	0	0	9	0	0	0	36	5	50
M	0	0	0	0	0	0	5	9	4	2	30	50
Total	49	51	50	53	49	59	51	49	45	38	56

	Producer Accuracy	Errors of omission	Consumer Accuracy	Commission Errors
W	0.96	0.04	0.98	0.02
U	0.94	0.06	0.92	0.08
R	0.96	0.04	0.96	0.04
B	0.92	0.08	0.88	0.13
N	0.76	0.24	0.78	0.22
S	0.78	0.22	0.66	0.34
G	0.54	0.46	0.53	0.47
P	0.58	0.42	0.59	0.41
CS	0.56	0.44	0.62	0.38
CP	0.72	0.28	0.95	0.05
M	0.60	0.40	0.54	0.46
Gobal Accuracy	0.756
Kappa Index	0.732