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ARF_sp_DataPreparation
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ARF_sp_DataPreparation
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###############
# Script for data preparation using GDAL tools and Linux terminal
#
# Author: Felipe Barros (f.barros@iis-rio.org)
#
# Institution: International Institute for Sustainability (IIS-Rio.org)
#
# this script was developed to ensure the documentation of all procedures and that all rasters has the same propreties:
# Origin:
# Pixel resolution: 1000, 1000 (in meters)
# Raster Extent: -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724
# SRC (Albers):
#
###############
## DATA PREPARATION
--## Using data from SDM as standart for a vector grid:
cd psql/modelagem_priorizacao/
# Modified the SDM to Albers QGIS
# Resampling the grid to 1000X1000 Km² due to Albers transofrmation the pixel size in bigger than 1000
gdalwarp -dstnodata 0 -tr 1000 -1000 -r "near" -of GTiff Alt_Albers.tif modelo_albers_100.tif -overwrite
--## Transofrming the raster to SQL raster then importing to PostGIS to use as reference raster.
raster2pgsql -c -C -s 102033 -b 1 -I -M modelo_albers_100.tif public.rast_modelo>rast.sql
sudo su
su postgres
--## Importing sql file to DB
psql -d modelagem -f rast.sql
--## After converted the raster to shp on GIS, saving it as SQL and importing to PostGIS
shp2pgsql -W LATIN1 -s 102033 grid_modelo_Albers.shp public.grid_priori_ma>grid.sql
sudo su
su postgres
--## Before, Albers projection must be implemented in DB:
INSERT into spatial_ref_sys (srid, auth_name, auth_srid, proj4text, srtext) values ( 102033, 'ESRI', 102033, '+proj=aea +lat_1=-5 +lat_2=-42 +lat_0=-32 +lon_0=-60 +x_0=0 +y_0=0 +ellps=aust_SA +units=m +no_defs ', 'PROJCS["South_America_Albers_Equal_Area_Conic",GEOGCS["GCS_South_American_1969",DATUM["South_American_Datum_1969",SPHEROID["GRS_1967_Truncated",6378160,298.25]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["False_Easting",0],PARAMETER["False_ ",0],PARAMETER["longitude_of_center",-60],PARAMETER["Standard_Parallel_1",-5],PARAMETER["Standard_Parallel_2",-42],PARAMETER["latitude_of_center",-32],UNIT["Meter",1],AUTHORITY["EPSG","102033"]]');
--## Importing sql file to DB
psql -d modelagem -f grid.sql
--## Removing the external grid (using R)
R
install.packages('RPostgreSQL')
library(RPostgreSQL)
con<-dbConnect(drv="PostgreSQL", host="localhost", port=5432, dbname="modelagem", user="postgres", password="postgres")
for (i in 1:500){
start=Sys.time()
print(i)
Dados_Disponíveis<-dbGetQuery(con, "DELETE from public.grid_priori_ma where gid in (select gid from public.grid_priori_ma where st_disjoint(geom, (select st_transform(b.geom, 102033) from biorregioes.ma_1148 as b)) limit 10000);")
print(Sys.time()-start)
}
quit()
# adding all columns that will be used
--area_ha
ALTER TABLE priorizacao_ma.grid_priori_ma add column area_ha numeric(10,2) NOT NULL DEFAULT(0);
--area
ALTER TABLE priorizacao_ma.grid_priori_ma add column area numeric(10,2) NOT NULL DEFAULT(0);
--perc_remnant
ALTER TABLE priorizacao_ma.grid_priori_ma add column perc_remnant numeric(10,2) NOT NULL DEFAULT(0);
--perct_restoration
ALTER TABLE priorizacao_ma.grid_priori_ma add column perct_restoration numeric(10,2) NOT NULL DEFAULT(0);
# Adding area information
update priorizacao_ma.grid_priori_ma set area_ha = st_area(geom)/10000;
update priorizacao_ma.grid_priori_ma set area = st_area(geom);
# Creating table with real Altlantic Rain forest area (Considering the area of bioma in the grid only):
--drop table priorizacao_ma.ma_real
CREATE table priorizacao_ma.ma_real AS
SELECT g.id as id,
row_number() over () as id2,
ST_Multi(st_intersection(g.geom,st_transform(ma.geom, 102033)))::geometry(MultiPolygon,102033) as real_geom,
st_area(st_intersection(g.geom,st_transform(ma.geom, 102033)))/10000 as realarea_ha
FROM priorizacao_ma.grid_priori_ma as g
JOIN biorregioes.ma_1148 as ma
on ((g.geom && st_transform(ma.geom, 102033)) and st_intersects(g.geom, st_transform(ma.geom, 102033)));
--limit 255964
# backuping
pg_dump modelagem --table=grid_priori_ma> grid_priori_ma.backup
pg_dump modelagem --table=rast_modelo> rast_modelo.backup
# restoring in other DB
psql -f grid_priori_ma.backup iis
psql -f rast_modelo.backup iis
#Changing the schema
psql iis
CREATE schema priorizacao_ma
ALTER TABLE public.grid_priori_ma SET SCHEMA priorizacao_ma;
ALTER TABLE public.rast_modelo SET SCHEMA priorizacao_ma;
#Creating spatial index
CREATE INDEX grid_priori_ma_geom_gist ON grids.grid_priori_ma USING GIST (geom);
CREATE INDEX rem_11_12_albers_gist ON sos_ma.remanescentes_2011_2012 USING GIST (geom_albers);
#####
--## 1) layer: raster with total forest area remnant.
#####
# The column perct_remnant will be used.
# 1.1) updating table setting perct_remnant with percent of forest in grid.
update priorizacao_ma.grid_priori_ma as g set perc_remnant = p.perc_veg from (
select
g.gid,
(round(st_area(st_union(st_intersection(g.geom, geom_albers)))::numeric/g.area,2))*100 as perc_veg
from priorizacao_ma.grid_priori_ma as g
join sos_ma.remanescentes_2011_2012 as f
on ((g.geom && f.geom_albers) and st_intersects(g.geom, f.geom_albers)) where f.legenda LIKE 'Mata%' Group by g.gid, g.geom) p
where g.gid=p.gid;
--## 1.2) Exporting from postgis to shp2
\q
exit
pgsql2shp -f /home/felipe/psql/forest_area.shp -h localhost -u postgres -P postgres iis priorizacao_ma.grid_priori_ma
--## 1.3) Rasterizing
gdal_rasterize -a PERC_REMNA -tr 1000 1000 -a_nodata 999 -l forest_area -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/forest_area.shp /home/felipe/psql/forest_area.tif
gzip /home/felipe/psql/forest_area.tif -9 -c >/home/felipe/psql/forest_area.tif.gz
#####
--## 2) layer: raster with oportunity cost
#####
--## Data was produced by Daniel Silva (d.silva@iis-rio.org)
--## 2.1) Rasterizing vector layer
gdal_rasterize -a Op_cost -tr 1000 1000 -a_nodata 999 -l Op_Cost_MA -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/modelagem_priorizacao/OportunityCost/uso_MA_shp/Op_Cost_MA.shp /home/felipe/psql/modelagem_priorizacao/OportunityCost/uso_MA_shp/Oportunity_cost_albers.tif
--# Falta inserir no banco de dados
#####
--## 3) layer: raster with area to be restored.
#####
--## 3.1) A unique vector layer was created merging all areas that should'nt be restored (e.g.: Urban Areas):
--agua: bc250.hid_massa_dagua_a; bc250.hid_trecho_massa_dagua_a; bc250.hid_rocha_em_agua_a as rocha_agua
--extracao vegetal: bc250.eco_area_agropec_ext_vegetal_pesca_a
--industrias: bc250.eco_edif_industrial_a; bc250.eco_ext_mineral_a
--area edificada: bc250.loc_area_edificada_a
--UCs excluindo APAs: bc250.lim_unidade_protecao_integral_a; bc250.lim_unidade_uso_sustentavel_a as ucs2 where sigla = 'APA'
--area militar: bc250.lim_terra_publica_a
--DESCONSIDERADO: mineração em fase de mineracao: dnpm.dnpm where dnpm.fase in ('CONCESSÃO DE LAVRA','LAVRA GARIMPEIRA','LICENCIAMENTO','REGISTRO DE EXTRAÇÃO')
--Area urbana: ibge.setores_censitarios where urbana.tipo='URBANO'
--Area de floresta: sos_ma.remanescentes_2011_2012 where florestas.legenda like 'Decremento%' or florestas.legenda like 'NMata%' or florestas.legenda like 'Desmatamento%';
--#All data were merged and dissolved using GIS
#############
# 3.2) After GIS processing: rasterizing
gdal_rasterize -a restore -tr 1000 1000 -a_nodata 999 -l grid_ma_Albers -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/modelagem_priorizacao/grid_ma_Albers.shp /home/felipe/psql/modelagem_priorizacao/Area_ToRestore_albers.tif
#####
--## 4) layer: raster with area to be restored discounting Riparian area (From Britaldo).
#####
##-- Britaldo raster layer
# 4.1) cropping raster without changing pixel size
gdalwarp -multi -dstnodata 0 -q -cutline /home/felipe/Projetos/Analise_area_relevo/Vetores/MataAtlantica_1148_Albers.shp -crop_to_cutline -of GTiff /home/felipe/psql/modelagem_priorizacao/apps/apps_hierarchical.tif /home/felipe/psql/modelagem_priorizacao/apps_hierarchical.tif -overwrite
# 4.2) Converting to shp
gdal_polygonize.py /home/felipe/psql/modelagem_priorizacao/apps_hierarchical.tif -f "ESRI Shapefile" /home/felipe/psql/modelagem_priorizacao/apps_hierarchical_MA.shp apps_hierarchical_MA DN
# 4.3) After removing the RPA from grid using GIS: rasterizing
gdal_rasterize -a torestapp -tr 1000 1000 -a_nodata 999 -l grid_ma_Albers -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/modelagem_priorizacao/grid_ma_Albers.shp /home/felipe/psql/modelagem_priorizacao/Area_ToRestore_app_albers.tif
#####
--## 5) layer: Percent remnant considering Riparian area (From Britaldo).
#####
--# After GIS processing (merging riparian area with remnant from SOS_MA)
# 5.1) After considering the RPA using GIS:
gdal_rasterize -a ForARAPP -tr 1000 1000 -a_nodata 999 -l grid_ma_Albers -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/modelagem_priorizacao/grid_ma_Albers.shp /home/felipe/psql/modelagem_priorizacao/apps/ForestArea_app_albers.tif
#####
## 6) Layer: Carbon stock (From Robin Chazdon)
#####
--## 6.1) Resampling to the same grid structure
gdalwarp -dstnodata -9999 -s_srs EPSG:4326 -t_srs '+proj=aea +lat_1=-5 +lat_2=-42 +lat_0=-32 +lon_0=-60 +x_0=0 +y_0=0 +ellps=aust_SA +units=m +no_defs' -tr 1000 -1000 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -r "near" -cutline /home/felipe/Projetos/Analise_area_relevo/Vetores/MataAtlantica_1148_Albers.shp -of GTiff "/home/felipe/psql/modelagem_priorizacao/Carbon/Brazil Atlantic Forest IIS/AGB_20yr_IIS_v6.tif" "/home/felipe/psql/modelagem_priorizacao/Carbon/Brazil Atlantic Forest IIS/AGB_20yr_IIS_v6_Albers.tif" -overwrite
--##layer: SDMs
##FLORA
cd ~/Projetos/ARF_spatial_planning/ENM/FLORA_buffermax2/final
ls
#Changinf the Coordinate Reference System CRS
SAVEIFS=$IFS
IFS=$(echo -en "\n\b")
for f in *.tif; do echo "Processing $f"; gdalwarp -s_srs EPSG:4326 -t_srs '+proj=aea +lat_1=-5 +lat_2=-42 +lat_0=-32 +lon_0=-60 +x_0=0 +y_0=0 +ellps=aust_SA +units=m +no_defs' -dstnodata 9999 -tr 1000 -1000 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -r "near" -of GTiff $f ${f%.*}_Albers.tif -overwrite
done
IFS=$SAVEIFS
# Changing datatype:
R
for (a in 1:length(list.files('./FLORA_buffermax2/final', pattern='_Albers.tif$'))){
print(a)
modelos.list <- list.files('./FLORA_buffermax2/final', pattern='_Albers.tif$', full.names = T)[a]
modelos.list2 <- list.files('./FLORA_buffermax2/final', pattern='_Albers.tif$', full.names = F)[a]
modelos.bin<-raster(modelos.list)
writeRaster(modelos.bin, filename = paste0("./FLORA_buffermax2/final/mod_",modelos.list2), datatype="INT1U", overwrite=TRUE)
}
quit()
#AVES
cd ~/Projetos/ARF_spatial_planning/ENM/AVES_buffermax2/final
ls
#Changinf the Coordinate Reference System CRS
SAVEIFS=$IFS
IFS=$(echo -en "\n\b")
for f in *.tif; do echo "Processing $f"; gdalwarp -s_srs EPSG:4326 -t_srs '+proj=aea +lat_1=-5 +lat_2=-42 +lat_0=-32 +lon_0=-60 +x_0=0 +y_0=0 +ellps=aust_SA +units=m +no_defs' -dstnodata 9999 -tr 1000 -1000 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -r "near" -of GTiff $f ${f%.*}_Albers.tif -overwrite
done
IFS=$SAVEIFS
cd ~/Projetos/ARF_spatial_planning/ENM/
# Changing datatype:
R
library(raster)
for (a in 1:length(list.files('./AVES_buffermax2/final', pattern='_Albers.tif$'))){
print(a)
modelos.list <- list.files('./AVES_buffermax2/final', pattern='_Albers.tif$', full.names = T)[a]
modelos.list2 <- list.files('./AVES_buffermax2/final', pattern='_Albers.tif$', full.names = F)[a]
modelos.bin<-raster(modelos.list)
writeRaster(modelos.bin, filename = paste0("./AVES_buffermax2/final/mod_",modelos.list2), datatype="INT1U", overwrite=TRUE)
}
quit()
#Anfibios
cd ~/Projetos/ARF_spatial_planning/ENM/ANFIBIOS_buffermax2/final
ls
#Changinf the Coordinate Reference System CRS
SAVEIFS=$IFS
IFS=$(echo -en "\n\b")
for f in *.tif; do echo "Processing $f"; gdalwarp -s_srs EPSG:4326 -t_srs '+proj=aea +lat_1=-5 +lat_2=-42 +lat_0=-32 +lon_0=-60 +x_0=0 +y_0=0 +ellps=aust_SA +units=m +no_defs' -dstnodata 9999 -tr 1000 -1000 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -r "near" -of GTiff $f ${f%.*}_Albers.tif -overwrite
done
IFS=$SAVEIFS
cd ~/Projetos/ARF_spatial_planning/ENM/
# Changing datatype:
R
library(raster)
for (a in 1:length(list.files('./ANFIBIOS_buffermax2/final', pattern='_Albers.tif$'))){
print(a)
modelos.list <- list.files('./ANFIBIOS_buffermax2/final', pattern='_Albers.tif$', full.names = T)[a]
modelos.list2 <- list.files('./ANFIBIOS_buffermax2/final', pattern='_Albers.tif$', full.names = F)[a]
modelos.bin<-raster(modelos.list)
writeRaster(modelos.bin, filename = paste0("./ANFIBIOS_buffermax2/final/mod_",modelos.list2), datatype="INT1U", overwrite=TRUE)
}
quit()
#Compressing
gzip -rv ~/Projetos/ARF_spatial_planning/ENM/FLORA_buffermax2/final -9 -c >/home/felipe/psql/Flora_sdm.gz
gzip -rv ~/Projetos/ARF_spatial_planning/ENM/AVES_buffermax2/final -9 -c >/home/felipe/psql/Aves_sdm.gz
gzip -rv ~/Projetos/ARF_spatial_planning/ENM/ANFIBIOS_buffermax2/final -9 -c >/home/felipe/psql/Anfibios_sdm.gz
#####
# Data from Britaldo
#####
#Hilltop
#NEW
gdalwarp -dstnodata -9999 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -cutline /home/felipe/Projetos/Analise_area_relevo/Vetores/MataAtlantica_1148_Albers.shp -of GTiff "/media/felipe/Seagate Expansion Drive/Banco de dados Geograficos/BKP/Britaldo/codigo_florestal/ForestCodeBalance/Brazil_newFC_hilltops.tif" "/home/felipe/psql/modelagem_priorizacao/BritaldoNewHillTop_MA.tif" -overwrite
#OLD
gdalwarp -dstnodata -9999 -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 -cutline /home/felipe/Projetos/Analise_area_relevo/Vetores/MataAtlantica_1148_Albers.shp -of GTiff "/media/felipe/Seagate Expansion Drive/Banco de dados Geograficos/BKP/Britaldo/codigo_florestal/ForestCodeBalance/Brazil_oldFC_hilltops.tif" "/home/felipe/psql/modelagem_priorizacao/BritaldoOldHillTop_MA.tif" -overwrite
####
# current Forest area + potential app
####
# Estimando Area de app e Floresta atual no pixel.
pgsql2shp -f /home/felipe/psql/forest_area2.shp -h localhost -u postgres -P postgres iis "select * from sos_ma.remanescentes_2011_2012 as florestas where florestas.legenda LIKE 'Mata%'";
#EITO NO SIG
gdal_rasterize -a area_appFo -tr 1000 1000 -a_nodata 999 -l grid_ma_Albers -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/modelagem_priorizacao/grid_ma_Albers.shp /home/felipe/psql/modelagem_priorizacao/Area_appForest_albers.tif
#####
--## 7) layer: Area to be restored considering Riparian area (From Britaldo) as restored.
#####
##-- Britaldo raster layer
--# After britaldo's raster convertion to shp, submitted to modelagem
cd psql/modelagem_priorizacao/
--##Converting to sql
shp2pgsql -W LATIN1 -s 102033 apps_hierarchical_MA.shp public.apps_britaldo>apps_brit.sql
sudo su postgres
--#Importing to modelagem db
psql -f apps_brit.sql -d modelagem
#backuping
pg_dump modelagem --table=apps_britaldo> apps_brit.backup
#restoring in other DB
psql -f apps_brit.backup iis
#Changing the schema
psql iis
ALTER TABLE public.apps_britaldo SET SCHEMA priorizacao_ma;
#Adciionando coluna de perct_remnant_app
alter table priorizacao_ma.grid_priori_ma add column perct_remnant_app numeric(10,2) not null default (0);
#Adicionando percent area
update priorizacao_ma.grid_priori_ma as g set perct_remnant_app = p.perc_veg_app from (
select
g.gid,
(round(st_area(st_union(st_intersection(g.geom, geom_albers), st_intersection(g.geom, app.geom)))::numeric/g.area,2))*100 as perc_veg_app
from priorizacao_ma.grid_priori_ma as g
join sos_ma.remanescentes_2011_2012 as f
on ((g.geom && f.geom_albers) and st_intersects(g.geom, f.geom_albers))
join priorizacao_ma.apps_britaldo as app
on ((g.geom && app.geom) and st_intersects(g.geom, app.geom)) where f.legenda LIKE 'Mata%' Group by g.gid, g.geom, perc_veg_app) p
where g.gid=p.gid;
--## Exporting from postgis to shp2
\q
exit
pgsql2shp -f /home/felipe/psql/forest_area_app.shp -h localhost -u postgres -P postgres iis priorizacao_ma.grid_priori_ma
--##Rasterizing
gdal_rasterize -a perct_remnant_app -tr 1000 1000 -a_nodata 999 -l forest_area -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/psql/forest_area.shp /home/felipe/psql/forest_area.tif
gzip /home/felipe/psql/forest_area.tif -9 -c >/home/felipe/psql/forest_area.tif.gz
#####
#-- rasterizing Brazilian states using IBGE code
#####
gdal_rasterize -a CODIGOIB1 -tr 1000 1000 -a_nodata 999 -l Estados_Albers -te -1654726.4418294357601553 -470314.6068012891337276 3542273.5581705644726753 4210685.3931987108662724 /home/felipe/Projetos/Base_dados/IBGE/Estados/Estados_Albers.shp /home/felipe/psql/states.tif
#####
--## Data Base procedure (not working so far)
#####
--## layer: raster with total forest area remnant.
--##Trying to rasterize in postgis --NOT WORKING
#SELECT ronw_number() over() as id, ST_AsRaster(geom, (select rast from priorizacao_ma.rast_modelo limit 1), '32BF', #perc_remnant, -9999))
#FROM priorizacao_ma.grid_priori_ma limit 10;
#SELECT ST_Union(ST_AsRaster(geom, rast, '32BF', height, -9999)) rast
#FROM forestcover, (SELECT rast FROM elevation LIMIT 1) rast;
##############
## Layer: area to be restored
##############
cd /home/felipe/psql/modelagem_priorizacao/
ls *.shp -1
shp2pgsql -W LATIN1 -s 102033 TeRestore_Albers.shp public.torestore>torestore.sql
sudo su postgres
--##Importing sql file to DB
psql -d modelagem -f torestore.sql
#backuping
pg_dump modelagem --table=torestore> torestore.backup
#restoring in other DB
psql -f torestore.backup iis
#Changing the schema
psql iis
ALTER TABLE public.torestore SET SCHEMA priorizacao_ma;
#Creating spatial index
CREATE INDEX torestore_geom_gist ON priorizacao_ma.torestore USING GIST (geom);
\q
exit
#Adicionando coluna de perct_restoration
--## NOTE percent retore is thje erase (difference) of grid with area not to restore!!!
ALTER TABLE priorizacao_ma.grid_priori_ma add column perct_restoration numeric(10,2) NOT NULL DEFAULT(0);
# Criando tabela com área real da MA:
--drop table priorizacao_ma.ma_real
CREATE table priorizacao_ma.ma_real AS
SELECT g.id as id,
row_number() over () as id2,
ST_Multi(st_intersection(g.geom,st_transform(ma.geom, 102033)))::geometry(MultiPolygon,102033) as real_geom,
st_area(st_intersection(g.geom,st_transform(ma.geom, 102033)))/10000 as realarea_ha
FROM priorizacao_ma.grid_priori_ma as g
JOIN biorregioes.ma_1148 as ma
on ((g.geom && st_transform(ma.geom, 102033)) and st_intersects(g.geom, st_transform(ma.geom, 102033)));
--limit 255964
#Adicionando percent restoration area
update priorizacao_ma.grid_priori_ma as g set perct_restoration = p.perc_rest from (
WITH grid_ma AS(
SELECT g.id as id,
st_intersection(g.geom,st_transform(ma.geom, 102033)) as real_geom,
st_area(st_intersection(g.geom,st_transform(ma.geom, 102033)))/10000 as realarea_ha
FROM priorizacao_ma.grid_priori_ma as g
JOIN biorregioes.ma_1148 as ma
on ((g.geom && st_transform(ma.geom, 102033)) and st_intersects(g.geom, st_transform(ma.geom, 102033)))
limit 255964)
select
greal.id,
round((sum((st_area(st_Difference(real_geom, f.geom))/10000)/realarea_ha)*100)::numeric,2)
as perc_rest
from grid_ma as greal
join priorizacao_ma.torestore as f
on ((greal.real_geom && f.geom)
and st_intersects(greal.real_geom, f.geom))
Group by greal.id
) p
where g.id=p.id;
select count(g.gid) FROM priorizacao_ma.grid_priori_ma as g
join priorizacao_ma.torestore as f
on ((g.geom && f.geom)
and st_intersects(g.geom, f.geom))
#######