LAND COVER CHANGE ANALYSIS IN THE STATE OF CALIFORNIA USING NLCD DATA

Land cover change is critical to be monitored as land cover change has significant impacts on flooding, ground water recharge, and urban air temperature. In this paper, key findings from a land cover change analysis study performed in the State of California are presented. National Land Cover Database (NLCD) data from the Multi-Resolution Land Characteristics Consortium (MRLC) was used for this study. Time series of NLCD data during the time period of 2001 through 2016 was used for the analysis. NLCD data processing was done in ArcMap 10.6.1. This paper includes the methodology in detail, and the results of the analysis. Results of the study indicate a significant increase in impervious surfaces, and a significant decrease in forest land cover.


INTRODUCTION
Urbanization has been accompanied by abundant increase of built surfaces, and decrease in vegetated surfaces (Kondoh and Nishiyama, 2000). Abundance of built surfaces has led to an increase in runoff (Ando et al., 1984;DeWalle et al., 2000).
Land Cover change analysis serves as a great means to understand impacts of urbanization, and provides an estimate of the percent increase or decrease in the areal extent of built surfaces and vegetated areas. The impacts of land cover changes include the following: reduced evapotranspiration due to decrease in vegetation (Peterson et al., 1995;Dow and DeWalle, 2000), increased urban air temperatures due to increase in built surfaces and decrease in vegetation (Landsberg, 1981;Akbari et al., 2001), formation of the urban heat island (UHI) (Oke, 1987;Grimmond and Oke, 1995). Increase in urban air temperature leads to an increase in energy usage for air-conditioning in warm summer months (Akbari et al., 2001).
Remote Sensing data is being increasingly used for land cover change monitoring due to the availability of time series of data. Landsat data and other regionally available remote sensing data has been used for LULC change analysis (Singh and Dubey, 2012;Bijender and Joginder, 2014;Nguyen et al., 2016;Utomo and Kurniawan, 2016;Wan et al., 2019).
In this paper, timer series of National Land Cover Database (NLCD) land cover data was used for the land cover change analysis in the State of California during the time period of 2001 through 2016. The organization of the paper is as follows: Section 2 focuses on the study area and data used, Section 3 focuses on the methodology, Section 4 focuses on the results and discussion, and Section 5 is the conclusion section of the paper.

Study Area
State of California was used as the study area for the land cover change analysis. The area of State of California is 423,970 sq.km. There are 58 counties in the State of California. The case study area is shown in Figure 1.

Data Used
National Land Cover Database (NLCD) land cover data downloaded from the Multi-Resolution Land Characteristics Consortium Website was used for the land cover change analysis.

Time Period of Analysis
Land cover change analysis was performed for the time period of 2001 through 2016.

NLCD data for Contiguous United States (CONUS) was downloaded from the Multi-Resolution Land Characteristics
Consortium Website for the following years : 2001, 2004, 2006, 2008, 2011, 2013, 2016. This was the first step in the land cover change analysis.
NLCD data was processed in Esri ArcMap 10.6.1 for the land cover change analysis. A vital step in the land cover change analysis, was clipping the NLCD data to the extent of State of California. For the clipping process, Clip tool in ArcMap was used. State of California's boundary data was used as the clipping extent. To automate and batch process the time series of NLCD data (2001 through 2016), a model was created in Model Builder tool in ArcMap. The created model is shown in Figure 2.

Figure 2. Land Cover Data Clip Model
Once the NLCD data for the years 2001, 2004, 2006, 2008, 2011, 2013, and 2016 were clipped to the study area extent, the area of each land cover type was computed. As the first step, an attribute field for area was added in the attribute table of the clipped NLCD time series data. This step is shown in Figure 3. Once the attribute field for area was added, the field calculator tool in ArcMap 10.6.1 was used for the area computation. The field calculator tool for computation of area is shown in Figure  4. Area was computed by multiplying the number of pixels in each cover category by the area of each pixel (30 m x 30 m) as the resolution of the NLCD data is 30-m. The area of each land cover category was computed using Equation 1. (1) where Area = Area of each land cover type (in square meters) Count = Number of Pixels in each land cover type

RESULTS AND DISCUSSION
Results of the land cover change analysis during the time period of 2001 through 2016, show a significant increase in impervious surfaces through the increase in the following land cover categories: low-intensity developed, medium intensity developed, and high-intensity land cover categories. The overall increase in impervious surface from 2001 through 2016 is 33 %. The change in impervious surfaces from 2001 through 2016 is shown in Figure 6.

CONCLUSION
The results of the land cover change analysis indicate an increase of 33% in impervious surfaces, a decrease of 24% in forest land cover, and a decrease of 9% in pasture land cover. Land Cover Changes are vital to be analyzed to devise urban development plans conducive to creating a sustainable environment. Future research will focus on modeling land cover changes impact on water demand and urban air temperature.