renewable energy eia application mapping report version 1

Renewable Energy EIA Application Mapping Report Version 1

July 2013

Mr J Reinecke

Mr A Ntisana

Ms SNL Poni

Commissioned by CSIR on behalf of the Department of Environmental Affairs

R e n e w a b l e E n e r g y E I A A p p l i c a t i o n M a p p i n g R e p o r t V e r s i o n 1 M a y 2 0 1 3

Executive Summary

This project was undertaken by the Centre for Renewable and Sustainable Energy Studies (CRSES)

and commissioned by the Council for Scientific and Industrial Research (CSIR), acting on behalf of the

national Department of Environmental Affairs (DEA). The objective of the project is to produce a

Geographical Information Systems (GIS) layer containing all renewable energy Environmental Impact

Assessment (EIA) applications received by the DEA before December 2012. This project was

undertaken as a sub-project of the DEA National Wind and Solar PV Strategic Environmental

Assessments (SEAs) and produced the development of the first Renewable Energy EIA Applications

Map for South Africa.

A single shapefile containing 470 renewable energy EIA applications comprising 2 433 land portion

entries was developed. As of 15 March 2013, 86 land portion entries were outstanding; 19 of which

were placed on hold; 41 had incorrect or no environmental practitioners’ details; and 26 were awaiting

response form the relevant environmental practitioners (NOTE: these numbers refer to individual land

portions, not entire projects).

This report discusses the data conditioning, verification and joining processes and goes on to describe

the challenges experienced and how they were resolved. It also describes other measures taken to

decrease data uncertainty.

In conclusion, recommendations for future EIA data submission and capturing are provided in order to

simplify the maintenance and future updating of the Renewable Energy EIA Application Map of South

Africa.


Acknowledgements

This project would not have been possible without the support of all the relevant EIA practitioners assisting with

verifying and providing lacking or incomplete information. We would also like to extend our gratitude for the

cooperative spirit shown by the DEA’s GIS Department as well as our colleagues at the CSIR EMS Group,

assisting in making this project a success.

Data Summary

Data Title DEA_Dec2012_RE_EIA_Portions_V1_July2013 DEA_Dec2012_RE_EIA_Projects_V1_July2013

Data Custodian National Department of Environmental Affairs National Department of Environmental Affairs

Release Data July 2013 July 2013

Version Version 1 Version 1

Data Extent Republic of South Africa Republic of South Africa

Data Type Spatial extents of all land portions subject to any

renewable energy EIA application.

Spatial extents of all renewable energy EIA

applications.

Time Representation EIA applications received before December 2012 EIA applications received before December 2012

Coordinate System CGS_Hartebees_1994 CGS_Hartebees_1994

GIS Data Format Shapefile Shapefile


Table of Contents

Executive Summary .....................................................................................................................................ii

Acknowledgements .................................................................................................................................... iii

Data Summary ........................................................................................................................................... iii

Table of Contents ....................................................................................................................................... iv

List of Figures ............................................................................................................................................. v

1. Introduction ........................................................................................................................................ 1

2. Objectives and Scope of Work ............................................................................................................. 1

3. Methodology ...................................................................................................................................... 2

3.1. Data Conditioning and Verification ............................................................................................... 3

3.2. Joining Process .......................................................................................................................... 6

4. Findings........................................................................................................................................... 11

5. Conclusions and Recommendations................................................................................................... 17

Appendix A: Flagging colours .................................................................................................................... 19

Appendix B: Discrepancies in DEA reference numbers ................................................................................ 20

Appendix C: Joining process chart ............................................................................................................. 22

Appendix D: Challenges and problems experienced .................................................................................... 23

Appendix E: Chart indicating the number of mapped and unmapped projects ................................................. 25

Appendix F: Comparison between DEA R1 shapefile and CRSES R1 shapefile ............................................. 26


List of Figures

Figure 1: A multi-portioned farm with one portion identified for EIA...................................................................... 3

Figure 2: A farm name search in cadastral data layer returning several results in South Africa. ............................ 5

Figure 3: Farm portion that has multiple polygons but has the same SG code ..................................................... 8

Figure 4: Preferred bidders R2 layers of Amakhala Emoyeni WEF farms with (blue) and without (green) names. . 9

Figure 5: Preferred bidders R2 merged layers of Amakhala Emoyeni WEF ......................................................... 9

Figure 6: Completed EIA projects in South Africa ............................................................................................. 10

Figure 7: Renewable Energy EIA Application map. ........................................................................................... 13

Figure 8: Renewable energy EIA application map with the Eskom national transmission grid ............................. 14

Figure 9: Renewable energy map showing locations for proposed solar PV and onshore wind plants ................ 15

Figure 10: Proposed solar PV and onshore wind EIA applications .................................................................... 16

Figure B1: Difference in location between New Kalkbult and Van der Lindes Kraal farms in the NC ................... 20

Figure B2: Showing the distance between New Kalkbult and Van der Linde's Kraal ........................................... 21

Figure C1: Joining process chart ...................................................................................................................... 22

Figure E1: Chart showing mapped and unmapped projects .............................................................................. 25

Figure F1: SAHRA map of Herbert PV Power Station location .......................................................................... 26

Figure F2: Comparison of CRSES R1 (purple with light green border) and DEA R1 (light green) Herbert PV

Power Station polygons ................................................................................................................................... 27


List of abbreviations/acronyms

COM_POLY Completed projects for polygons

CRSES Centre for Renewable and Sustainable Energy Studies

CSIR Council for Scientific and Industrial Research

DEA Department of Environmental Affairs

EAPs Environmental Assessment Practitioner

EIA Environmental Impact Assessment

GIS Geographic Information Systems

IPP Independent Power Producer

NC Northern Cape

NEAS National Environmental Authorisation System

PREFR1 Preferred Bidders Round 1

PREFR2 Preferred Bidders Round 2

PV Photovoltaic

R1 Round 1

R2 Round 2

REIPPPP Renewable Energy Independent Power Producer Procurement Programme

RFP Request for Proposal

SEA Strategic Environmental Assessment

SG Surveyor General

WEF Wind Energy Facility

1 | P a g e R e n e w a b l e E n e r g y E I A A p p l i c a t i o n M a p p i n g R e p o r t

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1. Introduction

The rollout of the Renewable Energy Independent Power Producer Procurement Programme

(REIPPPP) has seen South Africa attract significant local and international interest in its renewable

energy sector. This resulted in the national Department of Environmental Affairs (DEA) receiving

numerous Environmental Impact Assessment (EIA) applications for renewable energy projects scattered

across the country. To the knowledge of the authors no map of renewable energy EIA applications has

been produced at national scale prior to this project.

The Council for Scientific and Industrial Research (CSIR), on behalf of the Department of Environmental

Affairs (DEA), hereafter referred to as the ‘client’, approached the Centre for Renewable and

Sustainable Energy Studies (CRSES), hereafter referred to as the ‘Centre’, to conduct a verification and

mapping exercise of land parcels of approximately five hundred renewable energy environmental impact

assessment (EIA) applications received by the DEA before December 2012.

2. Objectives and Scope of Work

This report describes the procedures followed in order to verify and plot site location information of

renewable energy EIA applications as provided by the client. It also describes the challenges that were

experienced, the reasons therefore, how they were resolved, and how similar challenges can be

avoided in future.

The approach was largely determined by the quality and type of site location information received from

the client.

The Centre had to adhere to the terms of reference provided by the client. These terms included the

following: plotting the EIA application locations on high resolution cadastral data and creating a clear

distinction between applications in process, already approved and those that were withdrawn/lapsed.

Furthermore, the data had to comply with the DEA’s metadata standards.

The site location information that was received from the client was of poor quality; 20% of the site

locations were lacking and only 5% of the co-ordinate information was available. The rest of the site

location information was in terms of farm names, farm numbers and farm portions. Up-to-date South


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African cadastral data would thus be required to verify the data. For this purpose, the 2013 South

African AfriGIS cadastral data layer in shapefile format was provided by the client and used to verify the

data. However, in some cases, it was observed that farm names and numbers were absent or

interchangeable.

Approximately 470 EIA renewable energy applications were validated. Owing to the quality of the

information received from the client the worksheets had to be conditioned into a format compatible with

GIS software. More than 1000 single land portion entries needed to be processed.

Environmental assessment practitioners were contacted in cases where the information was either

lacking or could not be verified. They were requested to provide the correct co-ordinates or the Surveyor

General (SG) code for the proposed land portions. This process continued until, or close to, the final

submission date of this project. The delay in, or inability to obtain the necessary information from

environmental assessment practitioners was due to the fact that the information was regarded by some

practitioners to be highly sensitive and confidential. In such cases a formal letter of request for the

information from the DEA’s Director General’s Office was sent to the practitioner.

3. Methodology

The mapping methodology described in this report is based on preparing and importing a fully verified

and conditioned MS Excel spreadsheet into the ArcMap GIS software. The ArcGIS ‘Join’ tool was

subsequently used to combine the renewable energy EIA applications data with the South African

cadastral data.

The methodology was largely dependent on the accuracy and type (co-ordinates, farm names) of site

location information of the EIA applications that were in the MS Excel list received from the client. Some

of the land portion entries in the EIA application list only contained farm names, farm numbers and

portion numbers.

Data received from the client were firstly conditioned and verified before being imported into ArcMap.

During the verification process, when the raw site location information was verified against a cadastral

data layer in ArcMap, it was discovered that 18% of the data did not correspond with the latest cadastral

data.


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3.1. Data Conditioning and Verification

For the EIA applications data to be compatible with the ArcMap GIS software conditioning the data of

each application entry into an acceptable Excel spreadsheet format was necessary. The verification

process was carried out in parallel with the conditioning process. Data were validated against the 2013

South African AfriGIS cadastral data as well as by contacting environmental assessment practitioners

where necessary.

The conditioning of the site location information was initially based on three fields, namely: farm name;

farm number; and farm portion. These fields were common for both the cadastral data and the EIA

applications list. Based on this the two datasets could be combined into a single layer in ArcMap once

conditioning and validation was completed.

Solar and wind energy facilities usually span a number of farms or different farm portions. In order to

achieve accurate representation and positions of the site locations, it was opted to use portion numbers

in conjunction with the farm numbers and farm names, rather than only use farm names or farm

numbers. It may be possible for different portions of the same farm to be subject to different EIA

processes for different renewable energy projects. Figure 1 depicts a farm (outlined in blue) for which

only one portion (highlighted in yellow) was subject to an EIA for renewable energy.

Figure 1: A multi-portioned farm with one portion identified for EIA

For each EIA project with its individual DEA reference number, project name, etc., every farm portion

was recorded as an individual entry in an MS Excel spread sheet. The farm names, numbers and

portion numbers were then validated using the 2013 South African AfriGIS cadastral data layer in

ArcMap.


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A simple method called “flagging” was used to identify farm portions, numbers and names that

corresponded with, and those that did not correspond with, the cadastral data layer. All farm portions,

farm numbers and farm names were individually validated. This method was based on highlighting

(“flagging”) rows in MS Excel using different colours. Entries with location information corresponding

with the cadastral data layer were simply highlighted green, while those that did not correspond were

highlighted in various different colours. See Appendix A for further information.

Reasons for entries not corresponding with the cadastral data layer include:

Incorrect spelling of farm names;

Farm portions not represented in the cadastral data layer;

Farm name and number combinations not corresponding with cadastral data layer;

Site location information being vague. With a project location, for example, listed as in the

“Peddie area” as opposed to a specific land portion.

In order to verify a farm portion, its farm name together with its farm number was searched on the

cadastral layer in ArcMap. The attribute table of the layer was opened and “select by attributes” was

invoked. This feature in ArcMap returned the exact farm number and farm name that was typed in the

“select by attributes” field. If an application’s farm number and farm name were not found or the search

returned empty, either the farm number or the farm name was known to be incorrect. In most cases it

was discovered that the farm names were misspelt.

To determine whether the farm number is the variable that was incorrect, the farm number would be

searched together with a field titled “AREA_TABLE”. The latter contains the area or province in which a

certain portion is situated. Since the area information was provided in the provided data it could be used

to narrow down the search to only the applicable area. The farm name closest to the name that was

listed in the applications list was then selected and highlighted. Since several farm portions usually form

part of the same EIA application it was assumed that if the selected farm portion is adjacent to other

portions falling under the same EIA application, it was the correct portion.

In the cadastral layer it was only possible to search for one area or province at a time in which the

‘unknown’ land parcels could be located. This created problems when applying the aforementioned

verification process for project applications situated near the borders of provinces as a project might be

situated on provincial borders, but have only one province listed. This was especially true for entries

with no farm name or where the farm name was provided as only a farm number. A search for the farm


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number in the “AREA_TABLE” for the province the application was listed in return empty. It is however

known that for wind EIA applications, if the above mentioned problem occurs, there are probably two

provincial borders near which a farm or portion could be located. These are the Eastern Cape/Western

Cape, and Northern Cape/Western Cape borders.

Some of the site locations for the farm portions received from the environmental consultants could not

be represented in the cadastral data. It was decided that the co-ordinates of those points would be

recorded and that the entry would be entered in as a point in ArcMap, rather than as a polygon

describing a land parcel/erf. Co-ordinates were also recorded in other cases, namely, where the EIA

was conducted in highly built-up areas (e.g. in industrial development zones).

In the case where the EIA application entries only had farm portions and farm numbers, or only farm

names, the validation of those farms was problematic. When these details were searched in the

cadastral data, there would be several farms in South Africa with exactly the same farm numbers and

farm portions, or the same farm names. In cases where it was impossible to identify the correct site

locations, these types of entries were “flagged”. Figure 2 illustrates this how a search for a single farm

name results returns with several farms in South Africa.

Figure 2: A farm name search in cadastral data layer returning several results in South Africa.

A few discrepancies were also found when it came to the allocation of the DEA reference numbers. For

instance in the case where amendments were made to the EIA application, or to the authorisation


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documentation, new reference numbers were assigned to the projects. See Appendix B for more

information.

A new field, “MAJOR_REGION”, was created in the EIA applications projects list. This field was used to

narrow down location of entries with missing information and also used to combine the information from

the 2013 South African AfriGIS cadastral layer and the conditioned and verified EIA application MS

spreadsheet.

For all entries that were flagged as ‘missing data’ the environmental consultants that undertook these

EIAs were contacted. The environmental consultants were provided with an MS Excel spreadsheet

containing the DEA reference number and project title and were asked to provide details or co-ordinates

to the exact location of each farm portion under that specific project title.

3.2. Joining Process

The joining process constituted the second phase of the project. Here the various EIA application land

parcels were fully integrated with the cadastral data information in ArcGIS. This meant that all the

recorded information in the Excel sheets needed to be joined to the correct land parcels as contained in

the cadastral GIS layer. One way of doing this was to export the validated and conditioned MS Excel

sheet into ArcGIS and thereafter use the “Join” tool to combine the two tables. The results of this

process however proved cumbersome and a new method of pre-joining the data in Excel and then

importing it into the cadastral layer in ArcGIS was selected.

The validated and conditioned MS Excel sheet and cadastral layer data were exported to Excel and

joined based on coincident labels (farm name, farm number, portion number and major region). Once

the data sheets were joined using this method the newly created joined Excel data was imported back

into the cadastral layer which now contained not only the cadastral layer data, but also the associated

EIA application data in the attributes.


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3.2.1. The Joining Method and Discrepancies

The above mentioned method was the simplest available way of combining the cadastral data with the

DEA EIA applications data. A verification of the accuracy of the joining process was still needed. A

commercial Excel add-in ‘DigDB’ was used to join the two Excel data sets and also check the validity of

the join. This initially entailed working with small quantities of data to check and refine the add-in

algorithm before applying the method to the complete datasets.

For optimal accuracy of the tool, it was important to separate the farm portions into those that had farm

names, those that did not have farm names and those that had only co-ordinates. In the add-in tool, a

merge application was used to combine the Excel sheets and the merge was based on three fields. For

those entries that had a farm name these fields were: farm name; farm number; and farm portion. For

those entries that had a major region and no farm name these fields were farm number and farm

portion. The farm portions that had only co-ordinates were added into directly ArcMap as point data.

It was found that the order in which the merge fields were listed in DigDB affected the efficiency of the

tool in merging the two data sheets. The first entry would be the first condition that the merge would be

based on and the second entry the second condition, and so forth. The strategy was to use farm

number and farm portion as the first and second fields, respectively, as these were regarded as the

project ‘finger prints’.

It was observed that in the cadastral data a land parcel would have more than one polygon (all polygons

associated with that land parcel had the same “SG_CODE” but different “AG_CAD_ID”), meaning that a

single entry would be associated with more than one polygons in ArcGIS. This was observed in cases

where land portions have been subdivided for the registration of servitudes, and all resulting portions

retained the original portion number. In some instances more than one farm portion shared the same

farm name, farm number and farm portion number but had different geographical locations.

When the two tables were joined with the Excel add-in tool, DigDB, the tool listed the number of

matches for each entry. In cases where an entry had more than two matches, those were individually

assessed and validated.

Figure 3 illustrates three land potions with the same information due to servitudes subdividing its original

extent.


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Figure 3: Farm portion that has multiple polygons but has the same SG code

3.2.2. Results and Validation

For the purpose of presenting the mapping results, the Preferred Bidders from Round 2 dataset will be

discussed. The same process was also followed for the rest of the data (i.e. Preferred Bidders Round 1,

Pending, Completed, etc.).

As mentioned before, two merge processes, one based on farm name and the other on major region,

resulted in 2 Excel sheets with the combined information. These datasets were subsequently imported

into ArcGIS.

The new tables imported into ArcGIS were joined to the cadastral data layer, resulting in two new layers.

The join was based on the “AG_CAD_ID” common to both the exported tables and the cadastral layer.

In order to produce one shapefile from the Preferred Bidders R2 dataset, the two abovementioned

layers were merged. Figure 4 illustrates two layers for the Amakhala Emoyeni wind energy facility

(WEF) prior to being joined and Figure 5 shows the two layers after being joined in ArcGIS.


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Figure 4: Preferred bidders R2 layers of Amakhala Emoyeni WEF farms with (blue) and without (green) names.

Figure 5: Preferred bidders R2 merged layers of Amakhala Emoyeni WEF


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The joining procedure was used for all other category layers and successfully completed. Figure 6

shows the farm portions for the completed EIA project portions for the whole of South Africa.

Figure 6: Completed EIA projects in South Africa

It is important to note that some of the received and mapped Renewable Energy EIA applications

include land portions on which only power lines are proposed. In order to avoid adding columns or

irrelevant information to the data and to adhere to the DEA data standard, the amount of power that is

listed in the “MEGA_WATT” field when the “PROJECT_TYPE” is listed as a power line is treated not as

an output power in megawatts (MW) but as the voltage carried by the power lines in kilovolts (kV).

All listed EIA application project statuses were mapped, including the shape files for “Pending”,

“Completed”, “Preferred Bidders R1 and R2” and the “Withdrawn or Lapsed” statuses. Using the built in

‘Join’ tool in ArcGIS. A single layer was produced comprising all the EIA applications that could be

found in the AfriGIS cadastral data and those that were obtained from the respective environmental

consultants.


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4. Findings

By unpacking and processing 705 project titles and their respective project reference numbers as

received from DEA, 1 789 individual farm portion entries were successfully verified. A resulting 2 344

polygons were mapped. The reason for so many more polygons being mapped than land portions

identified is a result of the split of land portions due to a river or servitude passing through. All split

polygons of the same farm portions have the same particulars except for the “AG_CAD_ID”, which is

used to identify an individual polygon.

Although 705 reference numbers were received from DEA (including projects that could not be

mapped), a single shapefile layer of 469 renewable energy projects was produced.

The difference between the quantity of reference numbers received and projects mapped is due to

various issues that were encountered throughout the EIA application mapping process and include:

Some of the projects were discontinued by their respective developers but were not listed as

such in the DEA EIA Applications List. This information was difficult to obtain and therefore not

mapped. These amounted to 19 projects;

It was impossible to verify some projects in time as information was still outstanding from the

relevant environmental practitioners. Other environmental practitioners could not be contacted

for verification of site location information. See Appendix D for further information; and

A major contributor to this difference (705 versus 470) was the number of projects for which the

authorisations were amended. Each time a project was amended it was allocated a new project

reference number; usually the original number would be appended with a forward slash and a

number indicating iteration of the amendment.

It was decided that amended projects be excluded from the application mapping process as they would

cause confusion and duplication. Only the latest project reference number (the one ending with a

forward slash and the highest number) was thus used. The overall number of amendments in the

applications list that was provided by the DEA was 160. See Appendices D and E for further information.

The foregoing paragraphs describe the care that was taken in order to provide an accurate Renewable

Energy EIA Applications Map of South Africa. It was very important to apply and establish a high degree

of certainty when it came to the input data (EIA Applications Project List) as any inaccuracy in it would

affect the resulting map, thus rendering some aspects of the map inaccurate.


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Although this was the first project of its kind to be concluded at a national scale, it was very important to

measure the accuracy of the newly developed map against some form of reference map.

A map showing the spatial locations of all Round 1 Preferred Bidders developed in-house by the DEA’s

GIS department was used to this end. It was found that there were some discrepancies between the

map produced by the Centre and map produced by DEA. Differences were mainly around the exclusion

of certain land portions but the locations of the projects were consistent (Please see Appendix F for

further information). Inaccuracies were also found between the two datasets in the field “MEGA_WATT”.

For some projects in the DEA dataset power outputs were not recorded and others were incorrectly

recorded.

A thorough analysis was undertaken in order to evaluate which farm portions were satisfactorily

accurate between the two layers. It was found that the layers developed by the Centre were sufficiently

accurate.

It is concluded that the project not only resulted in developing the first Renewable Energy EIA

Applications Map for South Africa, but also led to the development of fairly accurate and simple

methodologies for future implementation.

The newly developed Renewable Energy EIA Applications Map for South Africa and a map that is

integrated with the national grid are shown in Figures 8 through to 11.


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Figure 7: Renewable Energy EIA Application map.


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Figure 8: Renewable energy EIA application map with the Eskom national transmission grid


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Figure 9: Renewable energy map showing locations for proposed solar PV and onshore wind plants


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Figure 10: Proposed solar PV and onshore wind EIA applications


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5. Conclusions and Recommendations

A total of 1 789 farm portion entries was processed and a map resulting of 2 433 entries and 470 EIA

applications was developed. As of 15 March 2013, 86 entries of farm portions were outstanding, 19 of

which were placed on hold, 41 had incorrect or no environmental practitioners’ details and 26 were

awaiting response. (NOTE: the above numbers refer to individual farm portions, not individual projects.)

Only the latest versions of projects that were amended were mapped.

All renewable energy EIA application projects were mapped to one shapefile, where each of the

different renewable energy technologies can be isolated and analysed.

For this and future versions of the Renewable Energy EIA applications map of South Africa to be

satisfactorily accurate, it must be ensured that EIA application data is provided and captured accurately

and in terms of the latest available cadastral information. To this end the following recommendations are

made:

The same cadastral information used to capture, verify and map EIA applications has to be

available to developers and consultants when completing the EIA application form.

The following data fields should be requested in the EIA application form and captured by the

EIA case officers onto NEAS:

Project Name

Proponent (with contact details)

Environmental Assessment Practitioner (EAP) (with contact details)

Land Owner (with contact details)

DEA Case Officer (with contact details)

Project Reference Number (DEA Reference Number and NEAS Reference Number)

Technology (Preferred and Alternatives)

Installed Capacity

Province

District Municipality

Local Municipality

Town

Farm Name

Farm Number


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Portion Number

SG Code

An online platform from which a standard map including cadastral information should be

accessible to all EAPs on the internet. From this platform a map with a predefined resolution

should be exported by EAPs and submitted to the competent authority with the EIA application

form;

Data capturing by case officers should be based on the same cadastral data as mentioned

above and verified by an automatically generated map with detailed cadastral information of the

entered data compared to the map submitted with the EIA application;

It is recommended that the competent authority case officer undertakes to update the EIA

Applications List database as soon as any changes are reported or observed for a specific

application, especially when it involves project reference numbers, change in case officer,

change in project status, etc.

The simple and straightforward methodologies devised are recommended for any other type of

mapping application of this nature that may be conducted. The simplicity of these methods

makes it easy to amend or update the developed map whenever needed, without having to

carry out laborious tasks.


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Appendix A: Flagging colours

GREEN Good

ORANGE Does not correspond (farm name missing, number incorrect)

BLUE Able to find but portion not as indicated i.e. (the AfriGIS and SG layers differ in

farm number, but the location and polygon is the same)

RED No location data

YELLOW Change/condensing of portions only

LIGHT PURPLE Portion number changed

ITALICS Farm name spelling corrected

BOLD ITALICS Farm name not given / farm number not given

PINK Farm portions not associated with any polygon


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Appendix B: Discrepancies in DEA reference numbers

Figure B 1: Difference in location between New Kalkbult and Van der Lindes Kraal farms in the NC

A discrepancy was found between the two data sheets that were provided, one containing data for the

completed EIA projects and the other containing the list of PREFERRED BIDDERS R1. In the

completed EIA projects data sheet, the DEA number for the proposed PV solar farm near Phillipstown,

NC is listed as DEA/NEAS/0000227/2011 and is to be located on the farm New Kalkbult (shaded yellow

and with blue outline in the figure above). In the PREFERRED BIDDERS R1 list, the DEA number for

the proposed PV solar farm near De Aar, NC is also listed as DEA/NEAS/0000227/2011 but in the

completed EIA projects the DEA numbers is DEAT/EIA/0000744/2011 and the development is to be

located on the farm Van der Lindes Kraal near Hanover (shaded yellow in the figure above). Both of

these developments


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were proposed by Scatec Solar. The distance between the two farms portions where the developments

are proposed is about 114 km SSW from New Kalkbult (yellow) to Van der Lindes Kraal (red). It is wise

to believe that it is not possible for solar farm developments to have the same DEA number as they are

very far apart, as can be seen on the image above.

Figure B2: Showing the distance between New Kalkbult and Van der Linde's Kraal


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Appendix C: Joining process chart

Figure C1: Joining process chart


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Appendix D: Challenges and problems experienced

Challenges experienced while conducting the validation process for the EIA applications list

One of the major issues discovered in the early stages of the project was that some of the site

locations that were provided by the DEA had farm names that were misspelt. Farm names from

one province or project would be confused with others due to similarities in their names, for

example, a farm name of Riet Fontein would be confused with a farm name of Rietfontein, or

names would be outright incorrectly spelled, farm numbers were not as indicated and these

resulted in lack of proof that the information was correct, in which case the responsible

environmental practitioners were contacted;

Some of the farm portions, especially those that were part of projects that were situated near

the provincial borders of South Africa, were assigned to an incorrect province. A wind project

near Sutherland would have multiple portions even in the Western Cape but would be

designated “NC” not, say, NC and WC or NC/WC;

It was also discovered that after making amendments, projects were, in some cases, awarded

new project reference numbers. These new numbers were however not updated to the DEA

EIA Applications Database nor to their applications list dated 12/2012. The environmental

practitioners would concede that the DEA reference had changed or initially they would not

recognise it at all until they search their records;

In projects that underwent several amendments, only the records of the last amendment were

taken as definitive, in order to avoid duplication or capturing outdated information;

Sometimes a project title would be in conflict with the project. The project title of SOLAR PV

would have a project type for WIND;

There was no clear distinction what was meant by portion RE (remaining extent). This was

assumed to be the remaining extent of the farm, therefore taken to be portion zero, as all other

portions would be subdivisions of this;

In total, 1789 entries of farm portions were processed and nearly 40% (699) of these entries

were missing (site location was not accurate or not supplied); and

As of 15 March 2013, 86 entries of farm portions were outstanding, 19 of which were placed on

hold, 41 had incorrect or no environmental practitioners’ details and 26 were awaiting response.

(NOTE: the above numbers refer to individual farm portions, not individual projects.)

Problems encountered when information was sourced from the environmental practitioners

Some companies refused to verify or provide any information without an official verification

letter from the Department of Environmental Affairs validating the Centre’s involvement in the

project;

Contact details of some of the practitioners were not provided at all. It was therefore not

possible to verify the information provided or to request omitted information.


V e r s i o n 1 M a y 2 0 1 3

The contact details provided for some of the environmental assessment practitioners were

incorrect;

Some of the environmental assessment practitioners who were said to have conducted some of

the EIAs did not recognise the projects. In the case of Enviro Dynamics Environmental

Consultants, the environmental assessment practitioner indicated in the original spreadsheet

said that not only does he not recognise the project, but the company is based in the USA and

does not have any projects in South Africa;

In one case, the contact details provided were for a library software company and not for an

environmental assessment company. This again made it impossible to obtain the required

information;

It was found from the environmental practitioners that some of the projects were placed on hold

or withdrawn. These project have however not been accordingly updated in the DEA EIA

Applications Database; and

Further discrepancies were caused by selecting a completely wrong farm portion. A thorough

analysis was carried out at the Centre in order to determine whether the correct portion was

chosen.

There were a few discrepancies that were found between the DEA EIA applications for the first round

and the Centre’s Application Map for the first round. Some of the farms in the CRSES’ map were not

mapped yet as response from the environmental practitioners is still awaited. This might cause some of

the discrepancies, as the polygons do not overlay each other.


V e r s i o n 1 M a y 2 0 1 3

Appendix E: Chart indicating the number of mapped and unmapped

projects

Figure E1: Chart showing mapped and unmapped projects

70

5 R

efer

ence

d E

IA

Ap

plic

atio

ns

235 unmapped

160 ammendments

75 with discrepancies

11 - Consultant names not provided

19 - Projects cancelled / withdrawn

24 – Information requested. Awaiting

response

21 – Incorrect contact details provided

470 mapped


V e r s i o n 1 M a y 2 0 1 3

Appendix F: Comparison between DEA R1 shapefile and CRSES

R1 shapefile

Figure F1: SAHRA map of Herbert PV Power Station location

Figure F1 is taken from the SAHRA Paleontological Heritage Statement Report which shows the exact location of

the proposed Herbert PV Power Station near Douglas, in the Northern Cape. This map location was then

compared to the two layers developed by the Centre (purple) and the DEA (light green) as shown in Figure F1,

for the same project.

When the Figure F1 and Figure F2 were compared it was established that the purple (Centre) layer was more

accurate to determining the location of the Herbert PV Power Station which is indicated by a light blue outline in

Figure F2.


V e r s i o n 1 M a y 2 0 1 3

Figure F2: Comparison of CRSES R1 (purple with light green border) and DEA R1 (light green) Herbert PV Power Station polygons

renewable energy eia application mapping report version 1

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