For Official Use Only
Development of Methodology for Wasteland Mapping at Large scale
A Case Study of Selected Villages of Rampachodavaram Mandal,
East Godavari District, Andhra Pradesh
Project Report
Prepared for
Sakti, Hyderabad
&
Society for Promotion of Wastelands Development
New Delhi
Prepared by
Land Use Division
Land Resources Group
Remote Sensing and GIS Applications Area
National Remote Sensing Agency
Balanagar, HYDERABAD – 500 037
2007
National Remote Sensing Agency
Document Control Sheet
Document Number |
NRSA/RS&GIS/ |
Title |
Development of Methodology for Wasteland Mapping at Large scale: A Case Study of Selected Villages of Rampachodavaram Mandal, East Godavari District, Andhra Pradesh |
Type of document & Classification |
Project Report |
Number of pages |
1-116 |
Author(s) |
Dr. Manoj Raj Saxena |
Originating Unit |
Land Use Division/ Soils Division |
Reviewed by |
Dr. R S Dwivedi |
Approved by |
Group Director, Land Resources |
Abstract |
The report discusses the methodology for large scale waste land mapping at cadastral level. |
Distribution |
Project Team Members, NRSA |
EXECUTIVE SUMMARY
In order to ensure food security for ever growing population, additional lands which have otherwise been lying waste need to brought under plough. Information on nature, magnitude of the problem, spatial extent and distribution of wastelands is available at 1:50,000 scale for entire country for two cycles i.e. 2000 and 2003. In the exercise that was carried out in 2003, reclamative groupings of wastelands have been made that enables planning their reclamation programme. However, for implementation of reclamation programme on wastelands individual field-level (cadastral-level) information is a pre-requisite. With the availability of high spatial resolution satellite data and the advancement of object-based image classification techniques, it has now become feasible to generate the level of information required fro implementation of reclamation programmes on wastelands. The study reported here aims at developing an appropriate wastelands classification scheme (i) to map selected hilly villages of Rampachodavarm mandal, East Godavari district, Andhra Pradesh, southern India using Cartosat-1PAN digital images with 2.5m spatial resolution at 1:10,000 scale, and (ii) to develop a digital database at cadastral level that links each plot/holding to the data containing spatial distribution of wasteland categories.
Initially, Cartosat 1 PAN image was interpreted visually following onscreen visual interpretation method. The approach consists of delineation of wastelands from PAN data and verifying them on the ground and finalizing the map after incorporating the necessary changes. Viz., field observations. Similarly, for defining information on soils to begin with physiographic units were delineated with the help of SOI sheets and manifestations of various landforms on the PAN image. Further divisions in the physiographic units were made based on land cover, erosion status and drainage pattern. The soil composition of each physiographic unit was defined by excavating soil profile representative physiographic unit. After refining the physiographic unit, in the light of ground observations, subsequent soils were classified upto phase level (USDA) and soil map was finalized by incorporating the above observations.
The wastelands and soil maps generated were used to develop a digital database in a GIS environment. Attribute data on terrain and socio-economic conditions were linked to geodatabase
The Cartosat 1 image enabled deriving information on wastelands upto level 3 at 10000 scale. Land with/without scrub is the major category encountered in the area. At the mapping scale, further sub-divisions were defined. However, LWS degraded forest, sheet rock area are other wasteland categories encountered in the area.
Hills, pediplain and inter-montane valleys comprise the major physiographic units. While inter-montane valleys support the development of coarse loamy deep soils, while, hill side slopes with moderate dense vegetative cover have added advantage in the development of moderate, deep skeletal soils with loamy texture. In addition to information on soils, the parameter which contribute to plant growth namely (viz., calcareousness, stoniness and degree of erosion could also be mapped. Additionally, based on information on soil and terrain conditions, land capability classes were defined. Such information helps in preparation and implementation of optimum land use plan for reclamation programmes.
The digital data bases as mentioned earlier contain information on wastelands, soils and attribute data. This will help in prioritizing the reclamation efforts depending upon the availability of time and human resources.
The study has demonstrated the feasibility of generating individual information on wastelands and soils occurring in the area. The above information plays a vital role in implementation programmes on wastelands. Temporal Cartosat PAN images may help monitoring the progress and success of wasteland programmes. Cartosat 1 PAN data with better than 1 m spatial resolution may facilitate further refinement the level of information on data content on natural resources.
Land use/land cover maps of the area with special emphasis on wasteland categories are generated based on object-based image classification techniques in conjunction with the soil information. For creating land use including Level-III wasteland categories, the correspondence between image objects extractable from Cartosat-1 data and land use classes observable on the ground is taken into account based on the spectral, spatial, and contextual relationships besides soil information. The following wasteland type have been identified viz. degraded scrub with cashew, land with scrub along the streams, land with scrub within agricultural land, land without scrub, sheet rock, degraded plantations and degraded forest.
The methodology attempted here is on-screen interpretation of wastelands using IRS-P5 (Cartosat-1) PAN standard geo-corrected data of 23 November 2006. Also, thematic information on soils for the village were delineated using the satellite data that was used an additional input in wasteland categorization. Various primary input datasets were collected from the field and the attribute information is linked with each of the cadastre in a GIS environment.
The study also enabled development of updated digital database at cadastral level that links each plot/holding to the data containing spatial distribution of current land use and wasteland categories, besides indicating ownership, demography details for the village. These technological improvements are expected to enable the state governments to harness computerization of the databases for their instantaneous updating and retrieval for manifold uses.
PREFACE
The achievement of the goals set for 2015 by the Millennium Declaration – and especially, poverty reduction, food security, universal primary education and gender equity– will require special efforts in rural areas. This is of particular significance in India where it is crucial to develop policies and programmes designed specifically to target “the poor” and the “disadvantaged” and thus principally rural people. With rapidly increasing population, there is tremendous pressure on natural resources. Therefore, inventory of natural resources is essential for their management. With the improvement of technology of RS & GIS, it has become possible to generate and update the natural resource information, in spatial format, at frequent intervals, thus enabling proper monitoring of natural resources and environment. Latest and up to date information on natural resources at village level is essential for better planning towards sustainable development of agriculture. The Land use/land cover information system would contribute to the National Spatial data infrastructure (NSDI) as major content definition and would hopefully become the mainstay of the NNRMMS programme for the coming years. Such study will also help for modeling indicating future trend of sustainability.
By keeping the above points in view, a pilot project on large scale wasteland mapping and preparation of a methodology for land use information: A case study of Rampachodavaram Mandal, East Godavari District, and A.P. Three revenue villages district has been taken up to have a detailed inventory of various resources at 1:10,000 scale in the month of February 2007 and completed within a short period of 6 months. I am happy to note that the village resources could also 'identify natural resources that are areas of rapid and deteriorating changes calling for more detailed survey & investigation. I would like to appreciate the efforts made by scientists from Land use/ Soils division to complete the work in a record time in spite of their involvement in various other on going projects.
I hope the report along with the maps will be highly useful for the user community and also for the planners in various state/central government organizations and non governmental organizations.
R S Dwivedi
Group Director, Land Resources
Remote Sensing & GIS Applications Area
Acknowledgements
Members of the Project Team are grateful to SAKTI, Hyderabad and SPWD, New Delhi for the cooperation and interest during the course of the study. Our sincere thanks are due to:
Dr. Vijay K Sardana, Executive Director, SPWD, New Delhi
Dr. P Sivaramakrishna, Director, SAKTI, Hyderabad
Ms. P Sarada Devi, Programme Executive, SAKTI, Hyderabad
Mr. Hardeep Singh, Programme Director, SPWD, New Delhi
Ms. Amita Badhuri, Programme Executive, SPWD, New Delhi
Mr. G Syam Kumar, Project Manager, SAKTI, Rampachodavaram
We express our sincere gratitude to Dr. K Radhakrishnan, Director and Dr P S Roy, Deputy Director, RS & GIS – AA, National Remote Sensing Agency for their encouragement, constant guidance and for providing necessary facilities during the course of the project.
Our thanks are due to Dr.R.Nagaraja Group Head, NDC for extending valuable technical support in project execution. Thanks are also due to the Scientists of Land Use Davison and Mr. Milind Wadodker for providing necessary suggestions at various stages of the project
Contents
List of figures
List of plates
List of tables
1. Introduction
2. Scope
3. Objectives
4. Study area
4.1 Geology
4.2 Physiography
4.3 Climate
4.4 Natural vegetation
4.5 Soils
5.1 Non-spatial data collected
5.2 Spatial data generated using satellite data
6.3 Ground truth
9. Final outputs
10. Observations and assessment of land use/ land cover
10.1 Built-up land
10.2.1 Kharif (Paddy)
10.2.2 Kharif (other crop)
10.2.3 Plantations
10.2.4 Fallow land
10.3 Forest
10.3.1 Dense forest
10.3.2 Degraded forest
10.4 Waste land
10.4.1 Land with/ without scrub
10.4.2 Scrub along streams/ field bunds/ roads
10.4.3 Degraded plantations with scrub
10.4.4 Salt affected
10.4.5 Stony waste
10.5 Water bodies
10.6 Individual trees
11. Soils
11.1 Methodology
11.2 Physiography & Soils
11.2.1 Structural hill
11.2.2 Loddipalem series
11.2.3 Bandapalli series
11.2.4 Burugubanda series
11.2.5 Thativada series
11.2.6 Gogumilli series
11.2.7 Mulapadu series
12. Observations
13. Recommendations
14. References
15. Annexure
List of Figures
3.2.a. Spatial extent of various land use/ land cover
3.2.b. Area under land use/ land cover – T Burugubanda village
3.3. Waste land map – T Burugubanda village
3.4.a FCC map – T Burugubanda village
3.4.b Soil map - T Burugubanda village
4.2.a. Spatial extent of various land use/ land cover
4.2.b. Area under land use/ land cover – Bheemavaram village
4.3. Waste land map – Bheemavaram village
4.4.a FCC map – Bheemavaram village
4.4.b Soil map - Bheemavaram village
5.2.a. Spatial extent of various land use/ land cover
5.2.b. Area under land use/ land cover – Korumilli village
5.3. Waste land map – Korumilli village
5.4.a FCC map – Korumilli village
5.4.b Soil map - Korumilli village
List of Plates
List of Tables
Annexures