Data on identification of desertified regions in Anantapur district, Southern India by NDVI approach using remote sensing and GIS

Abstract

Present dataset aims at the inventory data on preparation of Desertification Status Maps (DSM) for the first time in semi-arid region of Anantapur district in the state of Andhra Pradesh, South India by applying Normalized Difference Vegetation Index (NDVI) with acquired Remote Sensing (RS) satellite imageries and processed in ERDAS Imagine and ArcGIS software's. The NDVI has been classified into five such as water body, vegetation, fallow land, degradation land, and desertified land. Further, degradation land has been decreased to 4.87% which lead to desertification in the study region. The current research data will be resourceful to the environmental scientists and planning agencies who can utilize optimum for sustainable development and good governance in land degradation, desertification, and conserve land resources.

Specifications Table

Subject	Environmental Geology
Specific subject area	Remote Sensing and GIS
Type of data	Tables and Figures
How data were acquired	Topographical sheets from SOI, ASTER DEM, Land sat 4–7 and Land sat 8 data from USGS website, Soil data from Irrigation department, Anantapur and GPS (Germinetrix 10) field surveys processed and analyzed
Data format	Raw and analyzed
Parameters for data collection	SOI maps are georeferenced, Geometric corrections were made in ArcGIS. NDVI and SAVI were carried out in ERDAS Imagine software and Geometric data procured by using ArcGIS 10.4 software
Description of data collection	DSM have been prepared for knowing the rate of migration of desertification for the past 29 years
Data source location	Bommanahal Mandal, Anantapur district, Southern India (Fig. 1)
Data accessibility	Data is available in the article

Value of the data

• •Data showed the first catalog on the DSM (Desertification Status Mapping) occurrences in the semi-arid region of Anantapur District, Southern India, during 1990, 2000, 2010, and 2019.
• •The analyzed data is useful to the stakeholders and decision makers for governance to implement the sustainable development for eco-friendly ecosystem in the desertified regions.
• •Can be utilized for future research in monitoring various studies and preparations of natural hazard zone maps to assess the desertification in future.
• •Taking the data into account, it can be realized that the majority of land degradation and desertification is happening on the eastern side of the Hagari/Vedavathi River.

1. Data

1.1. Study area

The study area, Bommanahal, is the southern-most point of Anantapur District in the Rayalaseema region of Southern India and lies in the SOI topographical maps 57A/16, 57B/13, 57 E/4, and 57 F/1 between 13° 40′ and 15° 15′ Northern latitude and 76° 50′ and 78° 30′ Eastern longitude (Fig. 1). It is geologically formed by older groups of metamorphic rocks that belong to the Archean and younger groups of Sedimentary rocks of Proterozoic age (Fig. 2) [7,8,11]. Geomorphologically, the study area has geomorphic changes due to wing action where alluvium is seen along the course of the Hagari/Vedavathi River [8,10]. A pattern of sand dunes sand sheets are also spread over the course of the Hagari River that are migrated by the action of wind in the study area (Fig. 3).

Fig. 1.

Location map: Bommanahal.

Fig. 2.

Geology.

Fig. 3.

Geomorphology.

A range of soils present in the study area are shown in Fig. 4. At the same time, Lithology, Geomorphology, and soil data has shown in Table 1. On the other hand, NDVI of the study area of four different years has been provided respectively in Fig. 5(A) (year 1990), (B) (year 2000), (C) (year 2010), and (D) (year 2019), that are the primary Desertification Status Maps (DSM) of the study region [1,2,4]. Statistical data of NDVI for the past 29 years i.e., from 1990 to 2019 has been given in the Table 2.

Fig. 4.

Soils.

Table 1.

Lithology, geomorphology, and soils data.

Thematic layers	Parameters	Area (km2)	Area (%)
Geology	Gray granite/pink granite	6.72	2.19
	Hornblende – biotite gneiss, Biotite gneiss, Migmatites	275.96	90.23
	Quartzite; BIF/BMQ/Ferruginous Quartzite	3.57	1.16
	River/Water body	19.61	6.42
Geomorphology	Denudational Origin-Pediment-Pedi Plain Complex	268.71	87.85
	Structural Origin-Moderately Dissected Hills and Valleys	5.47	1.78
	River/Water body	20.41	6.67
	Aeolian Origin/Sand/Sand dunes	11.28	3.68
Soils	Gravelly clayey moderately deep desert soils	239.88	78.42
	Loamy to clayey skeletal deep reddish brown soils	18.4	6.01
	Gravelly clayey moderately deep red soils	23.19	7.58
	Fine loamy gravelly clayey shallow reddish brown soils	11.82	3.86
	Water bodies	12.57	4.11

Fig. 5.

A, 5B, 5C and 5D: primary DSM's.

Table 2.

NDVI for past 29 years.

Year	Features	Area (Km2)	Area (%)
1990	Water body	19.37	6.33
	Vegetation	81.96	26.79
	Fallow land	59.78	19.54
	Degraded land	97.86	31.99
	Desertified land	46.89	15.33
2000	Water body	16.65	5.44
	Vegetation	75.09	24.55
	Fallow land	50.04	16.36
	Degraded land	92.96	30.39
	Desertified land	71.12	23.25
2010	Water body	12.96	4.23
	Vegetation	60.26	19.7
	Fallow land	35.72	11.67
	Degraded land	96.47	31.54
	Desertified land	100.45	32.84
2019	Water body	6.83	2.23
	Vegetation	53.49	17.48
	Fallow land	27.04	8.84
	Degraded land	82.94	27.11
	Desertified land	135.56	44.32

2. Experimental design, materials, and methods

As a part of the dataset design, four different Landsat data for the past 29 years i.e., 1990, 2000, 2010, and 2018 has been collected from USGS earth explorer (Landsat 4–5(1990), Landsat 7(2000 and 2010) with 30 m’ resolution, and Landsat 8 (2019) with 30 m’ resolution). SOI toposheets have been collected and georeferenced by using ArcGIS and extracted the boundary of the study area [3]. Further, attribute tables are prepared for geology, geomorphology, soil maps, and geometric calculations procured for these base maps in ArcGIS software.

Simultaneously, normalized Differential Vegetation Index (NDVI) enumerates vegetation by quantifying the variance between near-infrared (vegetation strongly reflects) and red light (which vegetation absorbs) where NDVI has calculated with the formula given below

$$\text{NDVI}=\left(\text{NIR}-\text{Red}\right)/\left(\text{NIR}+\text{Red}\right)$$

For the Landsat 4 – 7 the bands combination is, NDVI = (Band4 – Band3) / (Band4 + Band3),

For the Landsat 8 the bands combination is, NDVI = (Band5 – Band4) / (Band5 + Band4).

NDVI always ranges from −1 to +1. But there isn't distinct boundary for each type of land cover. Negative NDVI values are likely water, the NDVI value is close to +1, it will be green leaves or vegetation, and the value is close to zero will have degraded land or desertified land [5,6,9]. It is carried out for the study area through ArcGIS software where four signatures are collected such as water body, Vegetation land, degraded land (severely affected) and desertified land (very severely affected) (Fig. 6).

Fig. 6.

Final DSM.