Accurate recognition and extraction of karst abandoned land features based on cultivated land parcels and time series NDVI
WANG Lingyu1(), CHEN Quan1, WU Yue1, ZHOU Zhongfa1,2(), DAN Yusheng1
1. School of Karst Science, Guizhou Normal University, Guiyang 550001, China 2. School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, China
The abandoned land has been spread all over the world and has become an important research direction for land use. Due to the lack of optical remote sensing images and serious mixed pixels in Karst rocky desertification land, it is difficult to accurately identify and extract the abandoned land. Based on short-term high precision image and long temporal resolution data features, taking Xifeng County in Guizhou Province as an example, using the high precision image accurately, and aided by maximum value composite (MVC) method, the authors calculated Landsat data for 2003—2018 time-series NDVI data, identified characteristics of abandoned land NDVI, and analyzed the relationship between the abandoned land and karst rocky desertification. The results are as follows: ①The combination of land parcels and time series NDVI can accurately identify and extract abandoned land, with an accuracy of 90.7% under the condition of 95.56% of cultivated land extraction. This method has a good application effect in cloudy and rainy mountains areas where optical remote sensing data are lacking and cultivated land is broken. ②The curve shape of the NDVI of the abandoned land is of “V” type, the continuous abandonment of arable land curve shape is of “U” type, and the cumulative NDVI curve shape is of asymmetric “W”, “M” or several combinations. ③The overall level of NDVI in non-karst abandoned lands is higher than that in rocky desertification abandoned lands. The level of rocky desertification is inversely proportional to the overall level of the curve and positively correlated with the degree of curve fluctuation. The number of abandoned lands is inversely proportional to the value of NDVI of the plot and positively correlated with the degree of dispersion of the NDVI curve. The results provide an efficient and feasible method for accurate identification and extraction of uninhabited land in karst cloudy and rainy mountain areas.
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WANG Lingyu, CHEN Quan, WU Yue, ZHOU Zhongfa, DAN Yusheng. Accurate recognition and extraction of karst abandoned land features based on cultivated land parcels and time series NDVI. Remote Sensing for Land & Resources, 2020, 32(3): 23-31.
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